Chemosphere 141 (2015) 62–70

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Sand amendment enhances bioelectrochemical remediation ofpetroleum hydrocarbon contaminated soil

http://dx.doi.org/10.1016/j.chemosphere.2015.06.0250045-6535/� 2015 Elsevier Ltd. All rights reserved.

⇑ Corresponding authors.E-mail addresses: xinwang1@nankai.edu.cn (X. Wang), zhouqx@nankai.edu.cn

(Q. Zhou).

Xiaojing Li a, Xin Wang a,⇑, Zhiyong Jason Ren b, Yueyong Zhang a, Nan Li c, Qixing Zhou a,⇑a MOE Key Laboratory of Pollution Processes and Environmental Criteria, Tianjin Key Laboratory of Environmental Remediation and Pollution Control, College of EnvironmentalScience and Engineering, Nankai University, Tianjin 300071, Chinab Department of Civil, Environmental, and Architectural Engineering, University of Colorado Boulder, Boulder, CO 80309, USAc Tianjin Key Lab of Indoor Air Environmental Quality Control, School of Environmental Science and Engineering, Tianjin University, Tianjin 300072, China

h i g h l i g h t s

� Addition of sand can effectivelyenhance mass transport in soil MFCs.� Addition of sand increased soil

porosity and decreased Ohmicresistance.� Both hydrocarbon degradation and

charge output were enhanced by sandaddition.� The degradation of hydrocarbons

with high molecular weight wereobviously enhanced.� Bioelectrochemical stimulation

imposed a selective pressure onanodic community.

g r a p h i c a l a b s t r a c t

a r t i c l e i n f o

Article history:Received 5 May 2015Received in revised form 4 June 2015Accepted 6 June 2015

Keywords:Bioelectrochemical remediationHydrocarbon contaminated soilsMass transportInternal resistanceMicrobial community

a b s t r a c t

Bioelectrochemical system is an emerging technology for the remediation of soils contaminated by pet-roleum hydrocarbons. However, performance of such systems can be limited by the inefficient masstransport in soil. Here we report a new method of sand amendment, which significantly increases bothoxygen and proton transports, resulting to increased soil porosity (from 44.5% to 51.3%), decreasedOhmic resistance (by 46%), and increased charge output (from 2.5 to 3.5 C g�1 soil). The degradation ratesof petroleum hydrocarbons increased by up to 268% in 135 d. The degradation of n-alkanes and polycyclicaromatic hydrocarbons with high molecular weight was accelerated, and denaturing gradient gel elec-trophoresis showed that the microbial community close to the air-cathode was substantially stimulatedby the induced current, especially the hydrocarbon degrading bacteria Alcanivorax. The bioelectrochem-ical stimulation imposed a selective pressure on the microbial community of anodes, including that farfrom the cathode. These results suggested that sand amendment can be an effective approach for soilconditioning that will enhances the bioelectrochemical removal of hydrocarbons in contaminated soils.

� 2015 Elsevier Ltd. All rights reserved.

1. Introduction

The concern of soil contaminated by petroleum hydrocarbonshas increased since such polluted area was enlarged in the pastdecades all over the world (Hall et al., 2003). The pollution containstoxic components, alters soil microbial community and inhibits

X. Li et al. / Chemosphere 141 (2015) 62–70 63

plant growth (Tang et al., 2011). Compared to physical and chem-ical technologies, the biological technology is considered as agreen, efficient and low-cost remediation approach (Zhou andHua, 2004; Haritash and Kaushik, 2009). In recent years, as anemerging technology based on biostimulation, microbial fuel cells(MFCs) has been demonstrated to remove hydrocarbons from soilsand sediments (Huang et al., 2011; Morris and Jin, 2012; Wanget al., 2012; Lu et al., 2014b).

The removal of hydrocarbons in soil is correlated withbio-current generated by exoelectrogenes (Li et al., 2014b; Luet al., 2014a; Zhang et al., 2014). Using MFCs to remediate sedimentcontaminated by hydrocarbons, the degradation rate increased byup to 12 times from 2% to 24% in 66 d. However, according to thelow power density reported previously (an average of37 mW m�3), the system heavily suffered from very high internalresistance of�4 kX, mainly attributed to the high Ohmic resistanceas a result of low conductivity in soil (Morris and Jin, 2012). Thepower density in sediment MFCs was limited more by internal resis-tance than by substrate degradation kinetics at the same power den-sity (ca. 37 mW m�2) using soluble substrate (glucose) compared toinsoluble substrate (chitin or cellulose powder) (Rezaei et al., 2007).As an evidence, Lu et al. found that the current densities increasedfrom 35.2 to 70.4 mA m�2 when the internal resistance decreasedfrom 25.6 (biochar anode) to 11.1 X (graphite anode) (Lu et al.,2014b). Furthermore, the high internal resistance even reducedCoulombic efficiency in sediment MFCs (Huang et al., 2011).

For MFCs filled by liquid media, the Ohmic loss can be alleviatedby the increase of ionic strength (Liu et al., 2005), decrease of elec-trode spacing (Cheng et al., 2006) and removal of the membrane(Liu and Logan, 2004). All these methods can be partly applied tosoil/sediment MFCs to improve performance. For example, addingNaCl (Hong et al., 2009), silica colloid (Domínguez-Garay et al.,2013) and domestic sewage (Mohan and Chandrasekhar, 2011) tosoil/sediments were reported to decrease internal resistance bymaintaining a high conductivity. However, in soil, the addition ofexogenous salt is expensive and will lead to the salinization of soil,making such methods not applicable. The primary Ohmic resis-tance is mainly from the dense packing of inorganic compoundsand clay complex of different particle sizes in soil, which acts asthe barrier for ion and substrate migrating toward electrodes andwaste products migrate out of the electrodes, which result in lowcurrent and degradation rate (Wang et al., 2012). This transportproblem can be aggravated when the soil is contaminated by stickyand hydrophobic oils. In order to facilitate ion transport in soil, wefound that the increase of soil moisture (from 23% to 33%)decreased the internal resistance (from 42.6 to 7.4 X), and thusimproved the current output and the removal rate of petroleumhydrocarbons (Wang et al., 2012). It is believed that minimizingof soil resistivity is a key to achieve a better power and remediationperformance.

In this study, sand, a common component in soil, was mixedwith the soil contaminated by petroleum hydrocarbons to acceler-ate the transport of ions and substrates as an exploration for prac-tical application based on laboratorial effects. Sand particlesenlarge pores of soil and provide more channels for ion and sub-strate transport. Microelectrodes were utilized to investigate thepH and dissolved oxygen (DO) profiles. The electrochemical perfor-mance, the degradation of petroleum hydrocarbons as well as themicrobial community were tested before and after the experiment.

2. Materials and methods

2.1. Aged soil preparation and sand addition

The aged soil was collected from topsoil (0–10 cm) contami-nated by petroleum hydrocarbons in Dagang Oilfield, Tianjin,

China. After air-dried, the soil was grinded, passed sieve (2 mm),marked as original soil, OS (conventional properties see TablesSM-1–SM-3). Fresh sand (0.3–0.4 mm, 40–70 meshes, YuanhengMaterials Factory, Henan, China) was mixed with soil at two differ-ent contents, marked as low sand soil (LS) and high sand soil (HS),with mass ratios (soil to sand) of 5:1 (LS) and 2:1 (HS) (w/w). OS(without addition of sand) was filled in two reactors with andwithout the connection to external circuit as controls (marked asCK and OC). All reactors were filled with total 340 g (the sameweight) of soil or mixture of sand/soil.

2.2. MFC configuration and operation

Each soil MFC was assembled with three layers of carbon meshanodes and an activated carbon (AC) air-cathode as shown inFig. SM-1. The carbon meshes (6 cm � 6 cm, Jilin Carbon Factory,Jilin, China) were cleaned by acetone overnight followed by rinsingwith distilled water for three times (Wang et al., 2009). The ACair-cathode (6 cm � 6 cm) was made by rolling-press methodaccording to previous descriptions (Dong et al., 2013; Li et al.,2014c). The catalyst layer of the cathode contacted the soil, whilethe gas diffusion layer faced to the air. The cathode was fixed atthe bottom of soil MFC, supported by a porous Plexiglas plate (porediameter of 0.5 cm, with a spacing of 1 cm between two pores,Fig. SM-1). Anodes were parallelly inserted in soils with 1, 3 and5 cm to the cathode. Three layers of anodes were connectedtogether by titanium sheets (width of 1 cm and thickness of1 mm) to the cathode across a 1000 X of resistance. All soil MFCswere operated in a 30 �C constant temperature incubator andsealed with distilled water (Lu et al., 2014a). The soil samples inMFCs were collected and marked as Layer 1 to Layer 4 from topto bottom at the end of experiments (Fig. SM-1b). Duplicate reac-tors were parallelly operated for each treatment.

2.3. Chemical and Electrochemical Analysis

The conductivity and pH of soil were measured in a mixture ofsoil and distilled water (1:5 (w/v)). In situ DO and pH measure-ments were obtained using respective microsensors (1 mm indiameter, steplength of 1 mm, waiting 10 s and measuring 10 sfor each point) connected to a micromanipulator and a multimeter(MM-Meter, Unisense, Aarhus N, Denmark). Prior to the measure-ments, two microsensors were polarized overnight to achieve thestable signal before calibration. DO and pH profiles were measuredwhen stable voltages were generated in all soil MFCs (day 8).Available N, available P, available K, organic matter, soil bulk den-sity and soil porosity were evaluated according to methodsreported previously (Liu, 1996). Soil digestion liquid was measuredfor Zn, Cu, Ni, Mn, Fe, Pb, Cr, Cd using ICP-OES (Vista MPX Varian,US) (Sun et al., 2010). Soil particle size distribution was obtainedby using Mastersizer 2000 particle size analyzer (MalvernInstruments Ltd., US) (Wang et al., 2012). Total petroleum hydro-carbons (TPH), n-alkanes and 16 priority PAHs were measuredaccording to previous report (Wang et al., 2012). 2 g soil or mixtureof sand/soil was sampled to analyze concentrations of hydrocar-bons, which was normalized to the unit weight of contaminatedsoil.

Electrochemical impedance spectrum (EIS) was performed overa frequency range from 100 kHz to 1 Hz with an amplitude of10 mV using a potentiostat (Autolab PGSTAT 302N, Metrohm,Switzerland) at the open circuit potential (stabilized for at least1 h). All layers of anodes were connected together as the workingelectrode, while the cathode was connected to the counter and ref-erence electrodes (two electrodes system). The Nyquist plots wereused to interpret the spectra. A fitting program (ZsimpWin 3.10)was employed to simulate plots according to an equivalent circuit

Fig. 1. The cell voltages during initial 30 d (a) and the charge output of different soilMFCs in 135 d, (b). The insert figure of (a) is the cell voltage over whole 135 d. CK,the no sand connected control; LS and HS, sand to soil as 1:5 and 1:2 (w/w). Externalresistance was 1 kX. The data was the mean value of duplicate soil MFCs. Individualdata of duplicate reactors were shown in Fig. SM-3.

64 X. Li et al. / Chemosphere 141 (2015) 62–70

(Fig. SM-2) (Li et al., 2014c). Cell voltages (U in mV, 1000 X ofexternal loading) were recorded using a data acquisition system(PISO-813, ICP DAS Co., Ltd, Shanghai, China) every 1800 s (t).

2.4. Biological analysis

Soil samples extracted from the same layer of duplicates weremixed for microbial community characterization. The bacterialgenomic DNA was extracted using DNA Gel Extraction Kit(OMEGA, US). Universal primer set GC-338F (50-CGC CCG GGGCGC GCC CCG GGG CGG GGC GGG GGC GCG GGG GG CCT ACGGGA GGC AGC AG-30) and 518R (50-ATT ACC GCG GCT GCT GG-30)were used. The procedure of PCR amplification was as follow: ini-tial denaturation at 94 �C for 5 min, denaturation at 94 �C for1 min, renaturation at 55 �C for 45 s, extension at 72 �C for 1 min,followed by 30 cycles and finally at 72 �C for 10 min. 10 lL ofPCR products were loaded onto 8% polyacrylamide gels (35–55%)and denaturing gradient gel electrophoresis (DGGE) was run in1 � TAE buffer at 150 V for 5 h (60 �C) using the Gel-Doc 2000(Bio-Rad, US). After being stained for 15 min, the gels werephotographed.

The DNA sequences (Table SM-4) were sent to analyze (GeniaBiological Technology Co., Ltd., Beijing, China). Results were com-pared with those of the NCBI BLAST GenBank (http://www.ncbi.nlm.nih.gov/BLAST/). The Shannon-Wiener Index (H), UniformityIndex (EH) and Richness (S) were calculated as the analysis ofDGGE pattern using Quantity One. H = �

P(Ni/N ln(Ni/N)), where

Ni is the optical density of the band i and N is the sum of opticaldensity of all bands. EH = H/lnS, where S is the number of the band(Jin, 1999).

2.5. Calculations

The charge output of the unit weight of contaminated soil(C g�1 soil) was calculated as follow:

Q ¼R T

0UR dt

mð1Þ

where T (s) is the cycle time, U is the cell voltage, R is the externalresistance (X), and m is the weight of contaminated soil. The cur-rent density (A m�2 g�1 soil, I0 = U/(R�A�m)) and power density(mW m�2 g�1 soil, P0 = U2/(R�A�m)) were normalized to the projectedarea of cathode (A = 0.0036 m2) and the weight of contaminatedsoil.

Taking TPH as an example, the degradation rate of TPH was cal-culated as g = (COS � C)/COS, where COS is the TPH concentration inoriginal soil and C is the TPH concentration in treated soil (or soilwith sand). The average degradation rate of TPH was calculatedaccording to the TPH concentration obtained from the mixture ofall four layer soils (mixed soil). The overall degradation rate of 16PAHs (or 33 n-alkanes) was obtained by adding the concentrationsof 16 PAHs (or 33 n-alkanes) up.

The oxygen transport behaviors in different samples were ana-lyzed according to Fick’s law. The flux of DO through the waterlayer to the soil was as follow:

JwDO ¼ �Dw

DOdCw

DO

dxw

� �ð2Þ

JsDO ¼ �Ds

DOdCs

DO

dxs

� �ð3Þ

where J is the DO flux driven by the concentration gradient, dC/dx isthe measured concentration gradient of DO, and the D is the diffu-sion coefficient in the water or soil. Subscript w indicates waterlayer, and subscript s indicates soil (or soil with sand). Flux

continuity must be preserved at the interface of water and soil,where Jw and Js were assumed to be equal.

�DwDO

dCwDO

dxw

� �¼ �Ds

DOdCs

DO

dxs

� �ð4Þ

The derivative dC/dx can be calculated from the slope of the DOconcentration-distance profiles of linearity region in two layers.Dw

DO is 1.8 � 10�9 m2 s�1 according to a previous study (Bennettand Myers, 1967). Ds

DO can be calculated from Eq. (4).

3. Results

3.1. Performance of Soil MFCs

Voltages of soil MFCs reached maximum values in three days(Fig. 1a). Since then the voltages dropped sharply on day 4, fol-lowed by a slow decrease until the end of test (day 135). Duringdays 5–40, voltages of connected control (HS) were higher thanthose of CK and LS, and around 0.39 ± 0.05 mV g�1 soil for CK,0.42 ± 0.04 mV g�1 soil for LS and 0.52 ± 0.05 mV g�1 soil for HSwere observed. As showed in Fig. 1b, the charge outputs per unitweight of contaminated soil for CK, LS, and HS were 2.5, 2.9 and3.5 C g�1 soil, showing that the addition of sand had a positiveeffect on electricity generation (Fig. SM-4). The maximum currentdensities (averaged 10 h of peak current) for CK, LS, and HS were

X. Li et al. / Chemosphere 141 (2015) 62–70 65

0.20 ± 0.00 mA m�2 g�1 soil (1.40 ± 0.03 10�4 mW m�2 g�1 soil),0.27 ± 0.01 mA m�2 g�1 soil (2.56 ± 0.13 10�4 mW m�2 g�1 soil),and 0.28 ± 0.00 mA m�2 g�1 soil (2.76 ± 0.0710�4 mW m�2 g�1 soil) respectively, with the correspondingvoltages of 0.71 ± 0.01 mV g�1 soil (CK), 0.96 ± 0.02 mV g�1 soil(LS) and 1.00 ± 0.01 mV g�1 soil (HS) across 1000 X.

According to the Nyquist plots in Fig. 2, the Ohmic resistance(Rs) and the charge transfer resistance (Rct) reduced gradually withthe amount of added sand. HS exhibited a lowest Rs of 7.6 X, whichwas decreased by 32% and 46% compared to 11.2 X of LS and14.2 X of the no sand CK (Table SM-5). A similar trend was alsoobserved on the Rct, namely HS (13.4 X) < LS (17.4 X) < CK(18.2 X).

3.2. Changes in characteristics of soils

The concentration of DO decreased in all samples along with theincrease in depth (Fig. 3a). The DO of the surface soil (depth of 0–1 cm) exhibited a faster decline than that in the water layer (depthof �0.8 to 0 cm), which was demonstrated by a larger slope (abso-lute value) of DO concentration in soil than in water (Fig. 3b and c).The diffusion coefficient (Ds) of DO increased with the amount ofsand added. The highest Ds of 7.4 � 10�10 m2 s�1 was observed inHS, which was 164% and 42% higher than those of CK (2.8 � 10�10 -m2 s�1) and LS (5.2 � 10�10 m2 s�1) respectively.

Compared to the soil pH of open circuit control, the pH (averagevalue) of all active MFCs (CK, LS and HS) decreased by 1.1–1.4 units(Fig. 3d). pH profiles in soil were positively correlated with sandaddition, as larger pH shifts were observed with more sand addi-tion. At 0–2 cm and 3.7–5.5 cm of soil, the concave profile ofpH-distance faced right, indicating the net production of H+. At2–3.7 cm of soil layer, the profile of pH-distance was almoststraight line, showing the pure diffusion of H+. It was noted thatthe concave profile of pH-distance faced left at 5.5–6 cm, suggest-ing the net consumption of H+ (Xiao et al., 2013; Yuan et al., 2013).

The measured conductivity of soil, representing a soluble salinitygradient, was negatively correlated with the amount of sand(R2 = 0.69, Fig. SM-5). Compared to the conductivity of original soil(1.99 ± 0.09 mS cm�1), the conductivities of CK(1.52 ± 0.03 mS cm�1), LS (1.40 ± 0.19 mS cm�1) and HS(1.10 ± 0.19 mS cm�1) decreased by 24%, 30% and 45% respectively(Fig. SM-5). Addition of sand maybe dilute the clay content becausesand has lower conductivity than clay.

Fig. 2. Nyquist plots of different soil MFCs at open circuit potential. The insertfigure is the resistances analysis of different soil MFCs based on electrochemicalimpedance spectrum.

3.3. Degradation of petroleum hydrocarbons

The soil samples with bioelectrochemical stimulation exhibitedhigher degradation rates of total petroleum hydrocarbon (TPH) andn-alkanes over those of open circuit (OC) without sand addition(Fig. SM-6). Degradation rates increased with the amount of sandaddition. The average degradation rates of TPH reached 22 ± 0.5%in HS, which was enhanced by 52%, 84% and 268% than those inLS (15 ± 0.1%), CK (12 ± 0.4%) and OC (6 ± 0.3%) respectively. Thedegradation rates of different layers in all groups decreased as fol-low: Layer 4 > Layer 1 > Layer 2 > Layer 3.

Among the 16 priority PAHs, the phenanthrene (PHE), fluoran-thene (FLU), pyrene (PYR) and chrysene (CHR) were the primarycomponents in the soil samples, accounting for 71 ± 1% of totalPAHs (Fig. 4). Although the compounds with higher ring numberswere less biodegradable due to their stability, water insolubilityand complex nature, in mixed soil, dibenz(ah)anthracene (DahA)and benzo(ghi)perylene (BghiP) were degraded by 16.5 ± 0.5% inLS and 22.5 ± 1.5% in HS, compared to 3 ± 2% in CK (Fig. SM-7).The acenaphthylene (ACE) declined by 91% and 82% in LS and HS,exhibited the highest degradation rate among the 16 priorityPAHs in mixed soil. The overall degradation rates of PAHs in mixedsoil were 50% (LS) and 48% (HS), with values higher than 42% and40% in CK and OC respectively (Fig. SM-7b).

n-Alkanes (C8–C40) were mainly composed of C17–C40 in theoriginal soil (OS) (Fig. 5), and 34 lg g�1 of pristane and 201 lg g�1

of phytane were detected. Pristane/phytane ratio is an environ-mental indicator and assesses the redox conditions within thedepositional environment (Powell, 1988; Hughes et al., 1995).The pristane/phytane ratio for common petroleum is 1–1.5, herethe ratio for OS was only 0.17 showing that the petroleum hydro-carbons in OS were well aged (Powell and McKirdy, 1973). In soilMFCs with a connected circuit, the average degradation rates ofCK, LS and HS were 37%, 45% and 53% for C17–C40 (Fig. SM-8),enhanced by 23%, 50% and 77% than that of OC (30%). It is veryinteresting that the addition of sand obviously enhanced the degra-dation of n-alkanes (C24–C40) and PAHs (C20–C22) with highmolecular weight (Figs. 4 and 5), and these hydrocarbons were lessbiodegradable in traditional anaerobic process. The n-alkane frac-tion calculated by adding the concentrations of C8–C40 up alsovisualized an effective overall degradation in HS (54 ± 7.5%) andLS (46 ± 8.5%) compared to OC (30 ± 14%) in supporting informa-tion (Fig. SM-8b).

3.4. Microbial communities

According to the DO profile, oxygen diffused from water layercan affect the anaerobic environment and therefore the microbialcommunity of Layer 1. Therefore, we select Layer 2 (far from thecathode) and Layer 4 (close to the cathode) as the representativesamples to investigate the microbial population of different reac-tors. As showed in Fig. 6a, the microbial communities were differ-ent between Layer 2 and Layer 4. Bands 2, 7, 18, 19, 24 and 27 weredetected in Layer 2 of all samples, but poorly visible in Layer 4. Inparticularly, the bands 7, 24 and 27 were obviously enhanced bythe bio-generated current. For connected groups, the electrochem-ical stimulation made a distinction between the clusters of Layer 2and Layer 4 in terms of the Phylogenetic Tree analysis (Fig. 6b). TheShannon-Wiener Index (H) and Uniformity Index (EH) of Layer 4were higher than those of Layer 2 (Fig. 6c and d), suggesting themicrobial community was substantially stimulated by the inducedcurrent when DO was consumed. The changes of Richness (S)between Layer 2 and Layer 4 were more insignificant than H andEH (Fig. 6e). The H and S of LS and HS were lower than those ofCK, while the EH had no obvious trend.

Fig. 3. In situ dissolved oxygen (a), the fitting of linearity region in water layer (b) and in soil (or mixture of sand/soil) layer (c), and in situ pH (d) as a function of the depth insoil MFCs. DO, dissolved oxygen; OC, open circuit control without sand.

66 X. Li et al. / Chemosphere 141 (2015) 62–70

Alcanivorax (Cui et al., 2008) detected in band 35 was signifi-cantly intensified in Layer 4 of LS and HS, which was the possiblebiological reason for the high degradation rate of petroleum hydro-carbons in this layer. The popular exoelectrogen, unculturedGeobacteraceae sp. (Holmes et al., 2007), was also detected in band11. Moreover, an iron or sulfur cycling bacteria (Korehi et al., 2013)was found in band 14. Among 24 clone sequencing bands, the pre-dominant species (16 bands) were Proteobacteria, 88% of whichwere Gammaproteobacteria. Interestingly, 10 bands were identifiedas Escherichia sp. (Table 1).

4. Discussion

The voltage generation rose to the highest value in a short time,which was attributed to absorption by the anodes or abiotic elec-trochemistry (Lu et al., 2014b). Subsequently the voltage droppedsharply due to the heterogeneous nature of petroleum hydrocar-bons (e.g. the depletion of degradable substrate) (Lu et al.,2014b). The charge output rate of CK during 135 d (6 C d�1) wasequivalent to that of LS, and yet 20% higher than that of HS(5 C d�1) which was similar with previous results (Wang et al.,2012). However, if calculated based on the unit weight of contam-inated soil, HS has the highest charge output rate of0.026 C d�1 g�1 soil, with a value 4% and 33% higher than those ofLS (0.021 C d�1 g�1 soil) and CK (0.018 C d�1 g�1 soil). Theincreased electrochemical performance was firstly attributed tothe reduced internal resistance. With the increased addition of

sand, the volume proportion of large particle (sand, 1–0.05 mm)increased from 30% to 47% and 63% (Table SM-2), for CK, LS, andHS soils, respectively, and the porosity was also enhanced from44.5% to 49.8% and 51.3% (Table SM-3). The increased porositywas from the enlarged cracks among soil particles by the addedsand, so that the ion mobility was enhanced as indicated by the46% reduction in Ohmic resistance (Rs). Besides, the decrease incharge transfer resistance (Rct) indicated that the improved porousstructure has positive effects on electrochemical activity ofbio-anode since the cathodes of all reactors were the same.

The concentration of DO decreased with the depth due to thelimited oxygen diffusion in soil (Fig. 3a). The Ds of oxygen in CKwas similar to that of OC, but 86% and 164% lower than those ofLS and HS. However, the addition of sand may have negative effectson anode biofilm due to the resulted higher O2 mass transfer. Forthe connected soil MFCs, the average pH of the no sand control(CK) was 1.0 unit lower than that of the original soil, leading to60 mV of potential loss in anodic potential (Freguia et al., 2007)or 20% loss in maximum voltage, indicated the anode reactionwas inhibited by proton accumulation. Inflexions of pH profilesat 2, 3.7 and 5.5 cm were positively correlated with the positionof three anodes, confirming that the pH variation was due to theproton accumulation near anodes. As indicated by the reducedpH slope, a higher initial and final pH over the entire depth profilefrom 0 to 5.5 cm in Fig. 3d were found, showing that sand of addi-tion enhanced the anodic proton transport. Furthermore, the slowtransport of anodic proton incurred the accumulation of hydroxyl

Fig. 4. Concentrations of the 16 priority PAHs in mixed soils (a mixture of all layers, the left) and in Layer 1 to Layer 4 (the right) of different soil MFCs. OS, original soil; OC,open circuit no sand control; CK, the no sand connected control; LS and HS, sand to soil as 1:5 and 1:2 (w/w); NP, naphthalene; ACY, acenaphthylene; ACE, acenaphthylene;FLN, fluorine; PHE, phenanthrene; ANT, anthracene; FLU, fluoranthene; PYR, pyrene; BaA, benzo(a)anthracene; CHR, chrysene; BbF, benzo(b)fluoranthene; BkF,benzo(k)fluoranthene; BaP, benzo(a)pyrene; IcdP, indeno(1,2,3-cd)pyrene; DBah, dibenzo(a,h)anthracene; BghiP, benzo(ghi)perylene.

Fig. 5. Concentrations of n-alkane (C8–C40) in mixed soils (a mixture of all layers, the left) and in Layer 1 to Layer 4 (the right) of different soil MFCs.

X. Li et al. / Chemosphere 141 (2015) 62–70 67

near the cathode. As a result, a significant increase of pH in soilclose to the air-cathode (depth >5.5 cm) was observed in all threereactors (Fig. 3d).

The addition of sand introduced more oxygen in soil <2 cm fromthe soil surface (Fig. 3a), so the increase in degradation rate ofLayer 1 and Layer 2 was partly due to the aerobic process. In tested

soil MFCs, the fraction of TPH degradation at 0–1 (Layer 1) and 5–6 cm soil (Layer 4) accounted for �40% of total TPH degradation(Fig. SM-9). The petroleum hydrocarbon concentration exhibitedan increasing trend from Layer 1 to Layer 4 at the end of experi-ments (Figs. 4 and 5), especially in LS and HS (Table SM-3), indicat-ing that the enlarged soil porosity also enhanced the transport of

Fig. 6. DGGE fingerprint (a), cluster analysis (b) and Shannon-Wiener Index (c), Uniformity Index (d) and Richness (e) of different soil samples.

Table 1Overview of the sequencing results of the bands stabbed from the DGGE profiles in Fig. 6. Sequences were shown in Table SM-4.

Band Accession Name Organism Similarity Reference

1 KF870457 Escherichia sp. Proteobacteria, Gammaproteobacteria, Enterobacteriales, Enterobacteriaceae,Escherichia

100% Young et al. (2013)

2 KF767965 Escherichia albertii Proteobacteria, Gammaproteobacteria, Enterobacteriales, Enterobacteriaceae,Escherichia

100% Wei et al. (2014)

6 CP007391 Escherichia coli Proteobacteria, Gammaproteobacteria, Enterobacteriales, Enterobacteriaceae 100% Xavier et al. (2014)7 DQ825234 UGM-1 Uncultured bacterium (gut microbes in the mucosa and feces) 92% Ley et al. (2006)8 HQ218569 UBN-1 Uncultured bacterium (bacterial response to naphthalene exposure) 94% Guazzaroni et al. (2012)9 JQ427689 UBA-1 Uncultured bacterium (bacterial in an alkaline saline soil spiked with anthracene) 98% Betancur Galvis et al.

(2006)10 AB721131 Azospirillum sp. Proteobacteria, Alphaproteobacteria, Rhodospirillales, Rhodospirillaceae, Azospirillum 100% Yamamoto et al. (2014)11 EF668606 Geobacteraceae sp. Proteobacteria, Deltaproteobacteria, Desulfuromonadales 98% Holmes et al. (2007)12 FJ440032 Firmicutes sp. Uncultured bacterium (Firmicutes, environmental samples) 98% Scupham et al. (2010)13 KF914394 Escherichia coli Proteobacteria, Gammaproteobacteria, Enterobacteriales, Enterobacteriaceae,

Escherichia100% Murugan et al. (2012)

14 HF558574 UIS-1 Uncultured bacterium (iron- and sulfur-cycling bacteria) 98% Korehi et al. (2013)16 HQ697781 UPD-1 Uncultured bacterium (bioremediation of Petroleum-Contaminated Saline-Alkali

Soils)97% Wang et al. (2011b)

17 JN221495 Escherichia sp. Proteobacteria, Gammaproteobacteria, Enterobacteriales, Enterobacteriaceae 100% Wilhelm et al. (2012)19 CP001383 Shigella Proteobacteria, Gammaproteobacteria, Enterobacteriales, Enterobacteriaceae 99% Ye et al. (2010)20 KF870457 Escherichia sp. Proteobacteria, Gammaproteobacteria, Enterobacteriales, Enterobacteriaceae,

Escherichia99% Young et al. (2013)

21 JF344166 UPG-1 Proteobacteria, Gammaproteobacteria 96% Acosta-González et al.(2013)

22 KF767890 Escherichia sp. Proteobacteria, Gammaproteobacteria, Enterobacteriales, Enterobacteriaceae 99% Wei et al. (2014)23 KF830694 Escherichia coli Proteobacteria, Gammaproteobacteria, Enterobacteriales, Enterobacteriaceae,

Escherichia99% Li et al. (2014a)

24 GU477928 URD-1 Uncultured bacterium (RDX degrading Microorganism) 94% Mitchell, (2010)27 KF851241 Escherichia sp. Proteobacteria, Gammaproteobacteria, Enterobacteriales, Enterobacteriaceae 100% Liu et al. (2014)32 HQ857728 Salinimicrobium Bacteroidetes, Flavobacteriia, Flavobacteriales, Flavobacteriaceae 92% Wang et al. (2011a)33 KF891381 Escherichia albertii Proteobacteria, Gammaproteobacteria, Enterobacteriales, Enterobacteriaceae 100% Sedlácek et al. (2013)34 EU085037 Halomonas

korlensisProteobacteria, Gammaproteobacteria, Oceanospirillales, Halomonadaceae,Halomonas

100% Li et al. (2008)

35 DQ768632 Alcanivorax Proteobacteria, Gammaproteobacteria, Oceanospirillales, Alcanivoracaceae 100% Cui et al. (2008)

68 X. Li et al. / Chemosphere 141 (2015) 62–70

hydrocarbons. Thus it is likely that natural attenuation is acceler-ated too that led to faster TPH degradation even without BESelectrodes.

The obvious variance of microbial communities between Layer2 and Layer 4 was believed due to the difference in soil character-istics such as DO and pH. It was noted that the band 35

(Alcanivorax, a strain of typical hydrocarbon degradation bacteria(Cui et al., 2008)) was distinctly stimulated in Layer 4 of LS andHS, indicating that the improved mass transport by sand promotedthe population of hydrocarbon degradation bacteria (Li et al.,2015). The H and S of LS and HS were lower than those of CK, show-ing a selective enrichment of functional communities (Li et al.,

X. Li et al. / Chemosphere 141 (2015) 62–70 69

2014b; Lu et al., 2014b). For OC, the microbial communitiesshowed a considerable difference between Layer 2 and Layer 4.Such difference was alleviated due to the bioelectrochemical stim-ulation in connected groups (CK, LS and HS), demonstrating thatbioelectrochemical stimulation imposed a selective pressure onthe microbial community although the anode was distant fromthe cathode.

For the application of sand amendment in bioelectrochemicalremediation of contaminated soil, it is possible and exercisable tomix sand when the soils are dug out and transferred to a remedi-ation site where electrodes are in place. It is also showed thatthe bioelectrochemical remediation system is more suitable to beapplied in a sandy soil, especially for most the coastal oil field withenough sand and conductive salt in soil.

5. Conclusions

This work demonstrates that addition of sand reduces inherentresistance and promotes ion and substrate transport in soil MFCsand hence improves electricity generation and remediation perfor-mance. Sand can be used as a effective amendment to increase MFCpower output for sensors and accelerate pollutant (especially therefractory compounds) removal from soils. Furthermore, we foundthat the local pH near electrodes in the soil bioelectrochemical sys-tem varied due to this amendment, which may alter heavy metalforms in soil, which will need further investigations in terms ofheavy metal transport in soil.

Acknowledgments

The authors thank Dr. Yuan Lu for help with the GC-MS analysis.This research work was financially supported by the MOEInnovative Research Team in University (IRT13024), the Ministryof Science and Technology as an 863 major project (grant No.2013AA06A205), the National Natural Science Foundation ofChina as a young scholar project (No. 21107053) and as a generalproject (No. 31170473) and the Ph.D. Candidate ResearchInnovation Fund of Nankai University (No. 68140001).

Appendix A. Supplementary material

Supplementary data associated with this article can be found, inthe online version, at http://dx.doi.org/10.1016/j.chemosphere.2015.06.025.

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