Synergistic effects of bioremediation and electrokinetics in the remediation of petroleum-contaminated soil

Abstract

The present study evaluated the coupling interactions between bioremediation (BIO) and electrokinetics (EK) in the remediation of total petroleum hydrocarbons (TPH) by using bio-electrokinetics (BIO-EK) with a rotatory 2-D electric field. The results demonstrated an obvious positive correlation between the degradation extents of TPH and electric intensity both in the EK and BIO-EK tests. The use of BIO-EK showed a significant improvement in degradation of TPH as compared to BIO or EK alone. The actual degradation curve in BIO-EK tests fitted well with the simulated curve obtained by combining the degradation curves in BIO- and EK-only tests during the first 60d, indicating a superimposed effect of biological degradation and electrochemical stimulation. The synergistic effect was particularly expressed during the later phase of the experiment, concurrent with changes in the microbial community structure. The community composition changed mainly according to the duration of the electric field, leading to a reduction in diversity. No significant spatial shifts in microbial community composition and bacterial numbers were detected among different sampling positions. Soil pH was uniform during the experimental process, soil temperature showed no variations between the soil chambers with and without an electric field.

Full text

Technical Note
Synergistic effects of bioremediation and electrokinetics
in the remediation of petroleum-contaminated soil
Shuhai Guo
a,
⇑
,1
, Ruijuan Fan
a,b,1
, Tingting Li
a
, Niels Hartog
c
, Fengmei Li
a
, Xuelian Yang
d
a
Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China
b
Graduate School of Chinese Academy of Sciences, Beijing 100049, China
c
KWR Watercycle Research Institute, 3433 PE Nieuwegein, The Netherlands
d
Shenyang University, Shenyang 110014, China
highlights

The coupling interactions between BIO and EK were studied under a 2-D electric field.

The decay of TPH was attributed to a synergistic effect between BIO and EK.

The synergistic effect was attributed to concurrent changes in microbial community.

The TPH degradation extent showed a positive correlation with electric intensity.
article info
Article history:
Received 8 October 2013
Received in revised form 4 February 2014
Accepted 5 February 2014
Available online 4 March 2014
Keywords:
Bioremediation
Electrokinetics
Electrochemical stimulation
Microbial community
Total petroleum hydrocarbons
abstract
The present study evaluated the coupling interactions between bioremediation (BIO) and electrokinetics
(EK) in the remediation of total petroleum hydrocarbons (TPH) by using bio-electrokinetics (BIO–EK)
with a rotatory 2-D electric field. The results demonstrated an obvious positive correlation between
the degradation extents of TPH and electric intensity both in the EK and BIO–EK tests. The use of BIO–
EK showed a significant improvement in degradation of TPH as compared to BIO or EK alone. The actual
degradation curve in BIO–EK tests fitted well with the simulated curve obtained by combining the deg-
radation curves in BIO- and EK-only tests during the first 60 d, indicating a superimposed effect of bio-
logical degradation and electrochemical stimulation. The synergistic effect was particularly expressed
during the later phase of the experiment, concurrent with changes in the microbial community structure.
The community composition changed mainly according to the duration of the electric field, leading to a
reduction in diversity. No significant spatial shifts in microbial community composition and bacterial
numbers were detected among different sampling positions. Soil pH was uniform during the experimen-
tal process, soil temperature showed no variations between the soil chambers with and without an elec-
tric field.
Ó2014 Elsevier Ltd. All rights reserved.
1. Introduction
A wealth of studies have reported on the bioremediation (BIO)
technology involved in the removal of organic contaminants from
soils (Guerin, 1999; Lima et al., 2009; Moliterni et al., 2012; Lladó
et al., 2013). The efficiency of BIO strongly depends on the type of
contaminant, the availability of nutrients and contaminants, as
well as soil conditions, such as soil pH, temperature, and moisture
content (Boopathy, 2000). The catabolic potential of a homoge-
neously dispersed microbial community, however, is the driving
force of an efficient BIO (Wick, 2009). The insufficient bioavailabil-
ity of some hydrophobic organic compounds can hinder the reme-
diation efficiency of a microbial community (Sarkar et al., 2005). In
recent years, the coupled use of electrokinetics (EK) in bio-electro-
kinetics (BIO–EK) technology has been employed to accelerate the
BIO of organic contaminants from soils, particularly those more re-
calcitrant (Gomes et al., 2012).
The EK technology for the remediation of soils relies on a num-
ber of electrochemical processes, including electromigration, elec-
troosmosis, electrophoresis, and electrochemically induced
reactions within the soil matrix (Acar, 1993; Probstein and Hicks,
1993; Torres et al., 2003). During the EK treatment, the transport
http://dx.doi.org/10.1016/j.chemosphere.2014.02.007
0045-6535/Ó2014 Elsevier Ltd. All rights reserved.
⇑
Corresponding author. Tel.: +86 024 83970449; fax: +86 024 83970448.
E-mail address: shuhaiguo@iae.ac.cn (S. Guo).
1
These authors contributed equally to this work.
Chemosphere 109 (2014) 226–233
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of nutrients and terminal electron acceptors is improved (Wick
et al., 2007), and the bioavailability of contaminants can be in-
creased due to the increased mobility of both xenobiotics – which
is difficult for total petroleum hydrocarbons (TPH) since they are
uncharged and microorganisms (Jackman et al., 2001; Wick et al.,
2004). Also, electrochemically induced reactions within the soil
matrix can result in the destruction of the immobile organic sub-
stances (Röhrs et al., 2002; Rahner et al., 2002). Major factors influ-
encing the efficiency of electrochemical processes are the electric
current, and its intensity (Jin and Fallgren, 2010; Haidar et al.,
2013), as well as other physical factors, such as soil moisture con-
tent and pH (Acar et al., 1995). However, direct current-induced
water electrolysis and electroosmotic effects lead to pH and mois-
ture changes adjacent to the electrodes, having negative impacts
on microbial community and concomitant biodegradation of con-
taminants (Lear et al., 2007; Kim et al., 2010). In recent years, the
application of polarity-reversal mode electric field has effectively
prevented the occurrence of wide changes in pH and moisture con-
tent (Luo et al., 2005b; Harbottle et al., 2009).
In BIO–EK remediation technology, the removal of the contam-
inant likely depends not only on the effect of biodegradation, but
also on that of electrochemically induced stimulation. At present,
there have been some preliminary reports demonstrating the
superimposed effects between BIO and EK in the remediation of
polycyclic aromatic hydrocarbons-contaminated soil (Li et al.,
2012; Huang et al., 2013). However, the above mentioned studies
were all conducted under a 1-D electric field, making the data
not sufficient enough to systematically and rigorously illustrate
the interactions between BIO and EK.
This experimental investigation aimed to evaluate the coupling
interactions between BIO and EK in the remediation of TPH based
on a comprehensive analysis of TPH degradation kinetics and spa-
tiotemporal changes in the microbial community. A 2-D electric
field with multiple electrodes was applied, for which it was possi-
ble to switch the polarity of the electrodes rotationally by each row
and column in turn. The study was conducted on a loamy soil, arti-
ficially contaminated with petroleum, and inoculated with petro-
leum-degrading bacteria. Soil samples were collected from
multiple positions with varying treatment durations.
2. Materials and methods
2.1. Soil, contaminant and bacteria
A loamy soil was taken from the Institute of Applied Ecology
experimental station at Shenyang, China, from the topsoil layer
(0–30 cm), and the properties were as described by Li et al.
(2010). Soil was air-dried and passed through a 2-mm sieve prior
to use.
The soil was artificially contaminated with crude oil at a final
concentration of approximately 45 g kg
1
. The crude oil was ob-
tained from Daqing Oilfield, China. The density of the petroleum
was 0.882 g cm
3
at 20 °C, the solidifying point was 25.8 °C, and
the viscosity was 18.9 mPa s
1
at 50 °C. The major constituents of
the petroleum were alkanes (69.5%), aromatics (23.4%) and resin
asphaltene non-hydrocarbons and ozokerites (7.1%).
A mixed culture of petroleum-degrading bacteria was used as
the experimental bacteria. The bacteria were isolated from oil-con-
taminated soil sampled from Daqing Oilfield by using a basic min-
eral medium with petroleum as the sole carbon source. The
mineral media consisted of (in g L
1
) NaNO
3
(1.5), (NH
4
)
2
SO
4
(1.5), K
2
HPO
4
(1.0), MgSO
4
7H
2
O (0.5), KCl (0.5), FeSO
4
7H
2
O
(0.01), CaCl
2
(0.002), and petroleum (0.5). The pH was adjusted
to 7.0. The bacterial cells were incubated in mineral media in a fer-
mentor under conditions of 30 °C and 150 rpm. They were then
harvested in the exponential growth phase by centrifugation, and
resuspended in mineral media to obtain a bacterial suspension.
2.2. Experimental system and protocol
A schematic diagram of the testing system is shown in Fig. 1.
The setup consisted of a perspex soil chamber (100 100
25 cm), 25 cylindrical graphite electrodes (20 1 cm) distrib-
uted into a matrix in a soil reactor, a DC power supply, a control
system, a soil thermometer, and a real-time monitoring system.
The control apparatus was capable of reversing the polarity of
the electric field rotationally by each row and column in turn at
an optional interval, thus generating a 2-D electric field. The mon-
itoring system can carry out real-time monitoring of the soil tem-
perature adjacent to the electrode.
The soil was rehydrated to a moisture content of 16–19% (w:w).
100 kg Of the moist soil was then placed into the soil cell in layers,
and each layer was tamped so as to minimize void space. The soil
samples were removed every 10 d from positions of different elec-
tric intensity (Fig. 2a and b), the total duration of the tests was
100 d. Samples were also taken prior to power connection to deter-
mine the initial target indexes. During the study, deionized water
was periodically added to soil matrix to maintain the moisture
content. Soil pH was measured using a pH probe under a soil to
water ratio of 1:2.5 (Lu, 2000).
Four experiments were conducted in this study: BIO–EK, EK
only, BIO only, and a control test. In the BIO–EK and EK tests, a con-
stant electric field gradient of 1 V cm
1
was applied. The polarity of
the electric field was reversed rotationally by each row and column
every 5 min. In the BIO–EK and BIO tests, the degrading-bacteria
suspension was mixed into the petroleum-contaminated soil to ob-
tain a final enumeration of approximately 6.5 10
8
16S rRNA gene
copies g
1
soil (the cell numbers were 3.8 10
8
colony-forming
units g
1
soil). In the control test, neither an electric field nor bac-
terial suspension was applied.
2.3. TPH analysis
TPH was extracted using methylene dichloride. 10 g Soil
samples were mixed with 30 mL of methylene dichloride in a
100-mL centrifugal tube, extracted by ultrasonics for 30 min, and
centrifuged for about 10 min at a speed of 5000 rpm. The superna-
tant was then filtered and dehydrated with anhydrous sodium sul-
fate. Each soil sample was extracted four times, and the filtrate was
combined; no visible colour was observed in the fourth extraction
solvent. The extracted TPH content was then isolated and quanti-
fied by gravimetric methods (Mana Capelli et al., 2001).
2.4. Microbial community analysis
Microbial communities were examined by denaturing gradient
gel electrophoresis (DGGE) analysis of PCR-amplified 16S rRNA
gene fragments from soil samples, as described by Muyzer et al.
(1993). Total soil microbial genomic DNA was extracted from
0.5 g of soil using a FastDNA SPIN Kit for Soil (MP Biomedicals,
Ohio, USA). The 16S rRNA genes for DGGE were amplified using
universal bacterial primers GC-341F (5
0
-CGCCCGCCGCGCGCGGC
GGGCGGGGCGGGGGCACGGGGGGCCTACGGGAGGCAGCAG-3
0
) and
907R (5
0
-CCGTCAATTCCTTTRAGTTT-3
0
). The presence of amplifica-
tion products was verified by electrophoresis in 1% agarose gels
stained with Gold viewna I (TaKaRa, China). The PCR products were
separated as follows: 6% polyacrylamide gels with a 40–60% dena-
turing gradient used; gels were electrophoresed in 1 Tris acetate
EDTA (TAE) buffer using a Bio-Rad D-Code Universal Detection
Mutation system (Bio-Rad, Hercules, CA, USA) for 16 h at a temper-
ature of 60 °C and a constant voltage of 70 V. The gel was subse-
S. Guo et al. / Chemosphere 109 (2014) 226–233 227

quently stained for 45 min in a 1 TAE buffer containing 0.01%
Genefinder (Viction, China).
Similarities between PCR–DGGE fingerprints were calculated
using the Dice coefficient; the unweighted pair-group method with
arithmetic means was used for cluster analysis. Prominent bands
in the DGGE lanes were excised under UV illumination and washed
with sterile deionized water. The bands were then placed in 30
l
L
of Tris–EDTA buffer and incubated at 4 °C overnight. Using 3
l
Lof
the supernatant as the template, the extracted DNA was amplified
with primers 341F (5
0
-CCTACGGGAGGCAGCAG-3
0
) and 907R. After
purification, PCR products were sequenced by the company BGI
(Tianjin, China). The 16S rRNA partial sequences were identified
Fig. 1. Schematic diagram of the experimental setup.
Fig. 2. Contour plots signifying the distribution of sampling positions (a), electric field intensity (V cm
1
) (b), and TPH degradation extent (%) within the EK (c) and BIO–EK (d)
chambers (delectrode; a, adjacent to electrodes; b, 5 cm from the nearest electrode; c, center position between two electrodes; d, 7 cm from nearest electrode in the diagonal
direction; e, diagonal center).
228 S. Guo et al. / Chemosphere 109 (2014) 226–233

through a BLAST search in GenBank. The Shannon–Weaver index
was used to analyse the soil microbial diversity (Simpson, 1949),
which was calculated according to the following equation:
Shannon—Weaver index ðH
0
Þ¼
X
s
i¼1
P
i
ðln P
i
Þ
where sis the number of species in the sample and P
i
is (intensity of
band i)/(total band intensity).
2.5. Microbial enumeration analysis
Total bacteria numbers were measured by real-time PCR of 16S
rRNA gene. Real-time PCR was performed using an ABI Prism 7000
Real-Time PCR Detection System (Applied Biosystems, USA), SYBR
Premix Ex Taq II (2) and ROX Reference Dye (50) (TaKaRa, Chi-
na). The standard curve was made with genomic DNA extracted
from Escherichia coli. 16S rRNA genes were amplified with primers
8F (5
0
-GAGAGTTTGATCCTGGCTCAG-3
0
) and 518R (5
0
-ATTACCGC
GGCTGCTGG-3
0
). The real-time PCR conditions were as follows:
95 °C for 30 s, 40 cycles of 95 °C for 15 s, 55 °C for 30 s, 72 °C for
45 s and 72 °C for 5 min. Total bacteria counts were measured as
copies g
1
oven-dried soil.
2.6. Statistical analysis
SigmaPlot 10.0 (Systat Software, USA) was used for schematics
plotting; SPSS 17.0 (SPSS Software, USA) was used for variance
analysis; Quantity One 4.4.0 (Bio-Rad, USA) was used for construct-
ing the phylogenetic tree of the DGGE profiles with simple cluster
analysis.
3. Results
3.1. TPH degradation
The spatial distribution characteristics of TPH degradation
extent as a function of electric field intensity at the end of the EK
and BIO–EK remediation tests are shown in Fig. 2. The degradation
extents of TPH both in the EK (Fig. 2c) and BIO–EK (Fig. 2d) tests
were positively related to electric intensity, with Pearson correla-
tion coefficient reaching 0.970 and 0.967 respectively (significant
at the 0.01 level). The maximum degradation extents for EK and
BIO–EK were achieved around the electrodes with the strongest
field intensity, and the TPH degradation extent was reduced with
the weakening of the electric field. The minimum degradation ex-
tents were observed at the diagonal center with the weakest elec-
tric intensity (positions e in Fig. 2a).
Fig. 3 shows the concentration changes of TPH during 100 d of
remediation. TPH decreased from an initial concentration of
45 g kg
1
to 42, 35, 33 and 23 g kg
1
in the control, BIO, EK and
BIO–EK tests respectively by the end of the experiments. There
was a significant decrease in TPH content during the first 20 d.
The maximum decay of TPH was achieved in the BIO–EK test
throughout the remediation process, and the removal efficiency
was positively related to the electric intensity.
Fig. 4 shows the average TPH degradation extent for BIO, EK and
BIO–EK during the 100 d of remediation, as well as the TPH degra-
dation extent at different sampling positions (a, c and e). A simu-
lated curve was obtained by the sum of the curves for TPH
degradation extent in the BIO and EK systems. In addition to the
natural degradation extent (8%), an average of 14%, 19% and 42%
of the TPH was degraded in the BIO, EK and BIO–EK tests respec-
tively after 100 d. 22%, 19% and 15% of the TPH was degraded at
positions a, c and e respectively in the EK test, and 45%, 42% and
38% of the TPH was reduced at positions a, c and e respectively
in the BIO–EK test. The experimental results obtained from the
BIO–EK test agreed well with the simulated curve during the first
60 d, with Pearson correlation coefficient reaching 0.998 (signifi-
cant at the 0.01 level). As for positions a, c and e, the Pearson cor-
relation coefficient reached 0.996, 0.998 and 0.990 (significant at
the 0.01 level) respectively. However, the degradation extent in
the BIO–EK test was significantly higher than that in the simulated
curve after 60 d, concurrent with changes in the microbial commu-
nity structure as will be described in the following section.
3.2. Microbial community changes
The samples on 0, 20, 50, 70 and 100 d in the BIO–EK and BIO
chambers were removed to measure microbial community
Fig. 3. TPH content in soil samples from the BIO, EK and BIO–EK tests, as compared
with the control test. Error bars represent 1 SE.
S. Guo et al. / Chemosphere 109 (2014) 226–233 229

changes as determined by DGGE analysis (Fig. 5a). The banding
patterns of 16S rRNA revealed that the samples clustered mainly
according to the duration of the test (Fig. 5b). Band 1 was found
in the initial soil and each sampling position on 20 and 50 d. Band
2 was mainly prominent on 0 and 20 d. Bands 3, 7, 8, 9, 11, 12 and
13 existed in all soil samples, while the intensity of band 3 reduced
after 70 d, and bands 12 and 13 gradually became prominent over
time. Band 4 was prominent on day 0, while its intensity declined
with the duration of the experiment, disappearing on day 100.
Band 6 was detected after applying the electric field, and was
prominent in the samples after 70 d, especially at position e on
day 100. Bands 5 and 10 were found only in soil samples on day
0. The largest shift in microbial community structure occurred on
20 and 70 d in the BIO–EK test. A smaller variation in community
structure was observed among sampling positions a, c and e.
The diversity of soil microbes was calculated using the H
0
. The
maximum diversity was observed in soil samples on day 0 (2.06
and 2.09 in BIO–EK and BIO tests respectively), with the duration
of exposure to the electric field in the BIO–EK test causing the
diversity to be reduced at each position, and to reach a minimum
on day 100 (H
0
a;c;e
¼1:56, 1.61 and 1.56 respectively). Meanwhile,
the diversity rebounded on day 70, especially at position e (1.99).
The difference in the BIO test was that the minimum diversity
was observed on day 20 (1.64) (Fig. 5a).
Bacterial populations observed during the BIO–EK treatment are
reported in Table 1. Thirteen DGGE bands were excised and se-
quenced in all, and every clone sequence exhibited high levels of
similarity (ranging from 97% to 99%) to GenBank bacterial se-
quences. The 13 bacterial strains were characterised with a high
diversity belonging to ten genera, comprising Gram-negative and
Gram-positive bacteria. Gram-negative bacteria were dominant
and belonged mainly to Beta-proteobacteria (bands 2, 5, 6 and 8)
and, to a lesser extent, to Alpha-proteobacteria (bands 3, 7 and 10).
In the Beta-proteobacteria group, strains were identified as belong-
ing mainly to Massilia (bands 2 and 5), Burkholderia (band 6), and
Hydrogenophaga (band 8). In the Alpha-proteobacteria group, strains
were identified as belonging to Sphingobium (band 3), Devosia (band
7) and Phenylobacterium (band 10). Gram-positive bacteria be-
longed mainly to Actinobacteria (bands 11, 12 and 13), Firmicutes
(bands 1 and 4) and Acidobacteria (band 9). In the Actinobacteria
group, strains were identified as belonging to Arthrobacter (bands
11 and 13) and Flexivirga (band 12). In the Firmicutes group, strains
were identified as belonging to Bacillus (bands 1 and 4).
3.3. Microbe numbers
Fig. 6 shows the changes in microbial numbers in the BIO–EK
and BIO chambers. From the results of real-time PCR, the total bac-
terial numbers expressed by 16S rRNA gene copy numbers fluctu-
ated by the same order of magnitude (10
8
) during the whole
process both in the BIO–EK and BIO tests. The 16S rRNA gene copy
numbers decreased during the first 20 d relative to day 0. In the
BIO–EK test, the 16S rRNA gene copy numbers among sampling
locations a, c and e never showed an obvious difference
(P> 0.05). The average gene copy numbers in the BIO–EK test were
a little higher than those in the BIO test. During the experimental
process, the 16S rRNA gene copy numbers in the BIO–EK chamber
were approximately 1.5 times those in the BIO.
3.4. Soil pH and temperature
Soil pH remained broadly constant during the period of the four
experiments (ranged from 6.3 to 6.5). Also, no significant spatial
changes (P> 0.05) in soil pH were observed among different sam-
pling positions in the BIO–EK and EK tests. No variations of the soil
temperature in the BIO–EK and EK chambers as compared with the
BIO and control tests in the absence of electric field were observed
(data not shown).
Fig. 4. Average degradation extent of TPH for the BIO, EK and BIO–EK tests, as well as the degradation extent of TPH at different positions (a, c and e). The simulated curve
calculated by the sum of the degradation extent in the BIO and EK tests to compare with that in the BIO–EK test. Error bars represent 1 SE.
230 S. Guo et al. / Chemosphere 109 (2014) 226–233

4. Discussion
The decrease of TPH could be attributed to a synergistic effect of
the combination of biological degradation and electrochemical
stimulation during the BIO–EK treatment. The experimental results
obtained from the BIO–EK test agreed well with the simulated
curve during the first 60 d, indicating that the decrease of TPH
was attributed to the superimposed effect of both biological degra-
dation and electrochemical stimulation. The degradation extent in
the BIO–EK test was significantly higher than that in the simulated
curve after 60 d, concurrent with changes in the microbial commu-
nity structure, indicating that the biological degradation was stim-
ulated by electric field, and signifying a synergistic effect between
biological degradation and electrochemical stimulation.
The greatest decrease in TPH was achieved adjacent to the elec-
trodes, and the minimum was obtained at the diagonal center,
implying a positive correlation between the removal efficiency
and electric intensity. Some previous studies have suggested that
the electric intensity is a driving force for mass transfer in the elec-
tric field: the stronger the electric field intensity, the more interac-
tion opportunities there are between the contaminant and the
degrading bacteria, thus generating more degradation of the con-
taminant (Luo et al., 2005b, 2006; Fan et al., 2007). This is con-
firmed by the positive correlation between degradation efficiency
Fig. 5. Microbial community shifts (a) and cluster analysis (b), sampled from positions a, c and e for different sampling times (0, 20, 50, 70 and 100 d). Some prominent bands
indicated by numbers 1–13 were cut off and sequenced (Table 1). H
0
refers to the Shannon–Weaver index value for the microbial diversity.
Table 1
Sequences of prominent bands in DGGE gels.
Strain Accession no. Homologous bacterial sequence Similarity (%)
1 KC505593 Bacillus cereus strain JCM 2152 98
2 KC505594 Massilia haematophila strain CCUG 38318 99
3 KC505595 Sphingobium fuliginis strain DSM 14926 97
4 KC505596 Bacillus cereus strain ATCC 14579 99
5 KC505597 Massilia aerilata strain 5516S-11 97
6 KC505598 Burkholderia fungorum strain LMG 16225 97
7 KC505599 Devosia insulae strain DS-56 98
8 KC505600 Hydrogenophaga atypica strain BSB 41.8 98
9 KC505601 Uncultured Acidobacteria bacterium clone GASP-WC1S2-C07 16S rRNA gene 97
10 KC505602 Phenylobacterium muchangponense strain A8 98
11 KC505603 Arthrobacter sulfonivorans strain ALL 99
12 KC505604 Flexivirga alba strain ST13 97
13 KC505605 Arthrobacter oxydans strain DSM 20119 99
S. Guo et al. / Chemosphere 109 (2014) 226–233 231

and electric intensity in the BIO–EK test. In addition, electrochem-
ically induced reactions may also account for the higher degrada-
tion rate of TPH around the electrode (Torres et al., 2003; Jin and
Fallgren, 2010).
The microbial community changes occurred mainly according
to the duration of the experimental treatment. Soil pH is the most
crucial among the various parameters, affecting microbial growth,
activity, biomass, membrane integrity, and the bioavailability of
contaminants (Aciego Pietri and Brookes, 2009). Several studies
have provided evidence that microbial community composition
changes in soil samples of extreme pH due to electrolysis reactions
adjacent to the electrodes (Lear et al., 2004; Wick et al., 2010). In
the present research, a 2-D electric field was applied, eliminating
the pH gradient across the soil chamber. Therefore, no distinct spa-
tial shift in microbial community composition was detected among
different positions. The consumption of TPH was associated with
the dynamics of the microbial community. A distinct microbial
community change was detected on day 70, which may contribute
to the enhanced TPH degradation during the later stage of treat-
ment, and comitant the synergistic effect between BIO and EK.
Bacteria with the ability to tolerate environmental stress are
crucial in BIO–EK. Massilia aerilata and Phenylobacterium muchang-
ponense were only detected in the initial soil, while Massilia hae-
matophila largely disappeared 20 d after the treatment, indicating
a weak competitive power and adaptability of these bacteria, and
thus indicating that they are inappropriate to be used as inoculated
degrading strains for BIO–EK applications. With an ability to toler-
ate environmental stresses (such as desiccation and starvation),
the viable cells of the Arthrobacter strain are frequently recovered
from extreme environments and historic sediments (Vorobyova
et al., 1997). In the present study, Arthrobacter sulfonivorans and
Arthrobacter oxydans were found in all soil samples, among which
the intensity of A. oxydans was the highest among all of the de-
tected strains and its intensity increased gradually with the dura-
tion of exposure to the electric field, fully demonstrating its
survivability. Burkholderia fungorum contains homologues of al-
kane-hydroxylase genes, and it has been shown for this species
that the proteins encoded are functional alkane hydroxylases
(Head et al., 2006). B. fungorum emerged 20 d after treatment,
and its abundance increased with time, especially in the region
where the electric intensity was weaker. This may have been a
consequence of the need for the degradation of TPH in the
contaminated soil. A relatively high percentage of Sphingobium
fuliginis,Bacillus cereus and Flexivirga alba were also detected in
the soil, indicating the important role of these strains in the
degradation of the pollutant. Meanwhile, the abundance of S. fulig-
inis declined 70 d after treatment, and the abundance of B. cereus
declined gradually with time and even disappeared by the end of
the experiment. In contrast, the intensity of F. alba increased with
treatment duration. S. fuliginis and B. cereus may be better at con-
suming light fractions of oil, and F. alba may be more inclined to
heavy fractions. With the exception of the above bacteria, few sig-
nificant changes in the other genera in the composition or commu-
nity structure of the bacterial community were detected.
The bacterial numbers fluctuated by the same order of magni-
tude (10
8
) during the whole experimental process, and no signifi-
cant spatial shifts in bacterial numbers were detected. It has
been reported that stress from growth conditions can reduce bac-
terial numbers, but a weak electric field has no negative effect on
microbial viability (Shi et al., 2008; Tiehm et al., 2009). The bacte-
rial numbers fluctuated by the same order of magnitude during the
remediation process, suggesting that the use of 2-D electric field
was favorable to the bacterial growth. There is a positive correla-
tion between bacterial numbers and microbial respiration, and
when an electric field is applied to soil the bacterial cell respiration
rate would be promoted due to the generation of anodic oxygen via
water electrolysis, and bacterial numbers would thus be enhanced
(Lear et al., 2004). This may account for the reason why bacterial
numbers in the BIO–EK test were a little higher than those in the
BIO test. The decrease in bacterial numbers during the first 20 d
could be interpreted as an adaptation to the growth conditions.
Reversing the polarity of the electric field could impel bacteria to
traverse in the soil, and a small change interval could cause the
bacteria to move back and forth locally (Luo et al., 2005a). No dis-
tinct spatial changes in bacterial numbers were detected in this
study, this is thought to be due to the uniform pH value across
the soil chamber, as well as the traverse of bacteria within the soil
matrix.
5. Conclusion
The results of the present study show that the consumption of
TPH in the BIO–EK treatment could be attributed to the superim-
posed effect of both biological degradation and electrochemical
stimulation, and the superimposed effect was expressed in a spe-
cific synergistic effect during the later remediation phase, which
could be attributed to concurrent changes in microbial community
composition.
The greatest decay in TPH was achieved around the electrodes,
and the minimum was obtained at the diagonal center of four elec-
trodes, implying a positive correlation between the degradation
efficiency and electric intensity.
The microbial community changed mainly according to the
duration of the experimental treatment. No significant spatial
shifts in microbial community composition and bacterial numbers
were detected among different sampling positions.
Acknowledgments
This work was funded through Water Pollution Control and
Management Key Project of Science and Technology of China (No.
2013ZX07202-007), the National Natural Science Foundation of
China (Nos. 21107119, and 21207138) and the Knowledge Innova-
tion Project Key-Direction Project Sub-project of Chinese Academy
of Sciences (No. KZCX2-EW-407).
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