Landfill leachate treatment with microbial fuel cells

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Jun 25, 2009 - c Bristol Robotics Laboratory, Environment and Technology Faculty, University of the West of England, Frenchay Campus, Coldharbour Lane, ...
Bioresource Technology 100 (2009) 5085–5091

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Landfill leachate treatment with microbial fuel cells; scale-up through plurality Antonia Gálvez a, John Greenman b, Ioannis Ieropoulos b,c,* a b c

Department of Civil Engineering, University of Granada, Campus Fuentenueva, 18071 Granada, Spain Microbiology Research Laboratory, Faculty of Health and Life Sciences, University of the West of England, Frenchay Campus, Coldharbour Lane, Bristol BS16 1QY, UK Bristol Robotics Laboratory, Environment and Technology Faculty, University of the West of England, Frenchay Campus, Coldharbour Lane, Bristol BS16 1QD, UK

a r t i c l e

i n f o

Article history: Received 30 April 2009 Received in revised form 22 May 2009 Accepted 25 May 2009 Available online 25 June 2009 Keywords: Microbial fuel cells Landfill leachate treatment System scale-up Multiple columns

a b s t r a c t Three Microbial Fuel Cells (MFCs) were fluidically connected in series, with a single feed-line going into the 1st column through the 2nd column and finally as a single outflow coming from the 3rd column. Provision was also made for re-circulation in a loop (the outflow from the 3rd column becoming the feed-line into the 1st column) in order to extend the hydraulic retention time (HRT) on treatment of landfill leachate. The effect of increasing the electrode surface area was also studied whilst the columns were (fluidically) connected in series. An increase in the electrode surface area from 360 to 1080 cm2 increased the power output by 118% for C2, 151% for C3 and 264% for C1. COD and BOD5 removal efficiencies also increased by 137% for C1, 279% for C2 and 182% for C3 and 63% for C1, 161% for C2 and 159% for C3, respectively. The system when configured into a loop was able to remove 79% of COD and 82% of BOD5 after 4 days. These high levels of removal efficiency demonstrate the MFC system’s ability to treat leachate with the added benefit of generating energy. Ó 2009 Elsevier Ltd. All rights reserved.

1. Introduction A microbial fuel cell (MFC) is a device that converts biochemical energy into electricity through the catalytic activities of microorganisms (Bennetto et al., 1983). The MFC has received increased attention as a novel process for alternative energy generation and energy-efficient treatment of wastewater (Habermann and Pommer, 1991; Rabaey et al., 2005a). Various wastewaters have been used as fuel in MFCs such as domestic wastewater (Ghangrekar and Shinde, 2007; Habermann and Pommer, 1991; Liu et al., 2004; Min and Logan, 2004; Rodrigo et al., 2007), swine wastewater (Min et al., 2005), manure (Scott and Murano, 2007), dairy-cow waste slurry (Yokoyama et al., 2006) or food-processing wastewater (Oh and Logan, 2005). The application of MFCs in wastewater treatment has several advantages over existing processes including energy recovery as electricity from waste and generation of less excess sludge in a more stable manner than the aerobic treatment process (Kim et al., 2007). Among all the existing types of wastewaters, landfill leachate is one of the most difficult effluents to deal with due to its high strength and complex composition, including refractory and toxic components such as heavy metals or xenobiotic organic compounds (Alkalay et al., 1998). Landfill leachate is an increasing

problem for landfill operators and the environment as it is a highly polluting effluent. Hence, economically and environmentally sustainable solutions for this effluent are in growing demand. Several workers have previously demonstrated the feasibility of using the MFC technology for simultaneous leachate treatment and energy generation (Greenman et al., 2009; Habermann and Pommer, 1991; You et al., 2006; Zhang et al., 2008). One common feature of the previous studies was that all experiments described single un-stacked units of microbial fuel cells (MFCs). Other workers have used multiple stacked MFCs electrically connected by a wire in series or in parallel to enhance the current output (Aelterman et al., 2006; Ieropoulos et al., 2003, 2005, 2008; Melhuish et al., 2006; Oh and Logan, 2007; Wilkinson, 2000). However, it is also possible to fluidically connect multiple MFCs in order to improve their performance and enhance the pollutant removal efficiencies (Ieropoulos et al., 2008). The primary objective of the present work was to study the ability of the microbial fuel cell technology to remove pollutants from landfill leachate, through a plurality of units fluidically connected in series and with re-circulation of fluid to increase hydraulic retention time. The effect of increasing electrode surface area in this system was also investigated. 2. Methods

* Corresponding author. Address: Bristol Robotics Laboratory, Environment and Technology Faculty, University of the West of England, Frenchay Campus, Coldharbour Lane, Bristol BS16 1QD, UK. Tel.: +44 1173286318; fax: +44 1173283960. E-mail address: [email protected] (I. Ieropoulos). 0960-8524/$ - see front matter Ó 2009 Elsevier Ltd. All rights reserved. doi:10.1016/j.biortech.2009.05.061

2.1. Landfill leachate Leachate samples were taken from Harnhill landfill site, South Gloucestershire, UK. The majority of the disposed waste was


A. Gálvez et al. / Bioresource Technology 100 (2009) 5085–5091

domestic. Only the leachate produced in the last phase (filled between 1997 and 2003) was obtained. For the experiments, samples were collected from tower 3 (located within phase 4 of the landfill) in the winter of 2006. These leachate samples had COD and BOD5 concentrations of 12,900 and 6300 mg/L, respectively. The measured pH was 7.74, the Eh 31.7 mV and the conductivity 33.3 mS/cm. 2.2. Laboratory scale plant description The plant consisted of 3 1L column-type microbial fuel cells fluidically connected as shown in Fig. 1. 2.3. Experimental conditions The MFC column setup was as previously described in Greenman et al. (2009). In the first phase of this study, the three columns were fluidically connected in series. Leachate was fed in at the top of column 1 (see Fig. 1), outflowing from the bottom into column 2, the outflow of which was fed into column 3 and finally from there into the outlet waste bottle. In the second phase of this investigation, the anode electrode surface area was increased in a step manner whilst the three columns were fluidically connected in series. The increase of the electrode surface area was achieved by connecting (using a platinum wire) additional carbon veil below the existing electrodes. Firstly, a 360 cm2 piece of carbon veil was added only to column 1 (total surface area of 720 cm2). The same was then done for columns 2 and 3. As a final step, a third piece of carbon veil was added to each column resulting in a surface area of 1080 cm2/column (total surface area 3240 cm2). The influent was 1:8 dilute leachate supplemented with 1% Na2SO4, at a flow rate of 96 ml/h for when the first stages of the electrode surface area increase (surface areas of 360 and 720 cm2/column) and 24 ml/h for 1080 cm2/column. The change of flow rate for the last electrode surface area was done

in order to avoid overflow spillages. Based on published reports from various workers, sodium sulfate (1% w/v) was added due to its reported beneficial effects in terms of power output (Cooney et al., 1996; Habermann and Pommer, 1991; Ieropoulos et al., 2005). In the third and final phase, the columns were disconnected from the input bottle and were fluidically joined in a loop. The effluent from column 1 was fed into column 2 the effluent of which was fed into column 3 the output of which was fed back into column 1 (dotted line in Fig. 1). The flow rate was kept at 24 ml/min and the electrode surface area in each column was 1080 cm2. This part of the investigation lasted for 96 h. The system was stopped after the power output had decreased below the baseline, which was set at 390 lW/cm2. One sample of the input bottle was taken at the beginning and also samples from each column outlet were taken at the end of the experiment runs. COD and BOD5 of the final samples were compared with COD and BOD5 of the input bottle. The experimental conditions are summarized in Table 1. 2.4. Analytical methods In order to perform COD and BOD5 analyses, the samples were centrifuged for 5 min (560g). COD was determined according to the closed reflux method (colorimetric), while BOD5 followed the dilution method (iodometric, azide modification) (APHA, AWWA and WPCF, 1989). Ion concentration (pH) and redox potential (Eh) were measured with a pH and redox meter (Sartorius PT-10) whilst conductivity was measured with a multi range conductivity meter (HANNA Instruments HI 9033). 2.5. Data capture and statistical analyses All MFCs were linked to the serial communications port of a desktop pc via a multi-channel interface as previously described

Fig. 1. Schematic diagram of the experimental setup with the 3 columns fluidically connected. Inflow is at the top of column 1 and the outflow is at the bottom feeding into the top of column 2 of which similarly the outflow from the bottom feeds into the top of column 3. The dotted arrow line illustrates the connection of the outflow from column 3 straight into column 1 to have the system in a loop (Phase 3).


A. Gálvez et al. / Bioresource Technology 100 (2009) 5085–5091 Table 1 Experimental operating conditions. Phase

Leachate strength

Flow rate (ml/h)

Electrode surface area (cm2/column)

(I) Three columns connected fluidically in series

(a) Dil 1:8 (b) Dil 1:8 (1%Na2SO4) Dil 1:8 (1%Na2SO4)



(a) 96 (b) 24 Re-circulation mode (C1 into C2 into C3, re-circulated 24 ml/h)

(a) 360, 720 (b) 1080 1080

(II) Electrode surface area increase (C1, C2, C3 in series) (III) Three columns connected in a loop

Full strength

(Greenman et al., 2009). Statistical analyses for means and errors were performed using SPSS for Windows, whereas analysis of variance (ANOVA) was performed again as previously described in Greenman et al. (2009) using GraphPadÒ Prism. 3. Results and discussion 3.1. Three MFC columns fluidically connected in series (Phase 1) Fig. 2 illustrates the results (first 50 h) from the experiments with the three MFC columns fluidically connected in series. As can be seen, column 3 produced higher current levels than columns 1 and 2. After the addition of sodium sulfate (1%) to the inlet bottle, the current output from column 1 increased above the output of both columns 2 and 3; however column 3 reinstated its superior performance once the sulfate percolated in the looped system. Although the highest output was expected to be produced from the column closest to the input (C1) due to higher BOD concentrations (Greenman et al., 2009), the result showed the opposite. A possible explanation for the higher current produced by column 3 could be the outflow of bacteria and also the accumulation of other beneficial microbial metabolites from columns 1 and 2 into column 3. In addition, it may also be due to the fact that certain long-chain polymers would have been broken down into more easily degradable shorter-chain sugars inside columns 1 and 2, and made available to the microbial community inside column 3. The raw leachate could also contain different types of compounds in high concentrations that could inhibit the growth of the bacteria in column 1. This requires further investigation.

3.2. Step increase in the electrode surface area (Phase 2) The effect of increasing the electrode surface area on the performance of the system was studied whilst the three microbial fuel cells were still fluidically connected in series and it was shown that power density increased as a function of electrode surface area (Fig. 3). The addition of the first unit of carbon veil (increasing the electrode surface area from 360 to 720 cm2) resulted in percentage increases of the order of 39.7% (from 500.7 to 699.5 lW/m2), 5.7% (from 443.2

Fig. 3. Power density as a function of the electrode surface area.

Fig. 2. Current vs. time for columns 1, 2 and 3 fluidically connected in series.


A. Gálvez et al. / Bioresource Technology 100 (2009) 5085–5091

to 468.5 lW/m2) and 28.2% (from 683.5 to 876.6 lW/m2) for columns 1, 2 and 3, respectively. The addition of a second (and final) unit of carbon veil, giving a total area of 1080 cm2, produced the highest power density output (1822.6 lW/m2). Expressed as a percentage, the increase in power density from the addition of the second unit of electrode was of the order of 160% (from 699.5 to 1822.6 lW/cm2), 106% (from 468.5 to 964.5 lW/cm2) and 96% (from 876.6 to 1714.3 lW/cm2) for columns 1, 2 and 3, respectively. The highest percentage increase in power density from the overall increase in electrode surface area (i.e. from 360 to 1080 cm2) was produced from column 1 and was 264% (from 500.7 to 1822.6 lW/cm2), whereas the lowest was produced from column 2, but which was still of the order of 118% (from 443.2 to 964.5 lW/cm2). The corresponding percentage increase for column 3 was 151% (from 683.5 to 1714.3 lW/cm2). The big error bars for the last surface area increase in Fig. 3 were attributed to power density fluctuations caused by ferricyanide depletion and replenishment. Further increases in electrode surface area had adverse effects (data not shown). These data suggest that the control electrode (360 cm2) in the anodic volume was sub-optimal for all three columns. Furthermore, the column closer to the influent was shown to have produced the biggest improvement with increases in electrode area, whereas the ones furthest away were affected to a lesser extent. The improvement in column 1, was probably due to more electrode surface becoming available for colonization and electron transfer but this may have given rise to less ‘fuel’ for utilization in column 2, hence a lower percentage increase with increase of electrode area. The same explanation can also be given for the even lower percentage increase (after the addition of the second electrode unit) of column 3. These findings highlight the usefulness of a cascade system in a wastewater treatment plant where maximum treatment efficiency would be achieved by the nth column. The statistical analysis (ANOVA) performed showed differences among the different surface areas tested (p < 0.05) for current and power density for column 1. For columns 2 and 3 the increase in power density was only statistically significant after adding the third unit of carbon veil but not for the second unit. COD and

BOD5 results obtained for the different electrode surface areas are shown in Fig. 4. BOD5 and COD removal efficiencies followed a similar trend for the three columns. Initial COD loading rate for column 1 was 4.17 kg COD/m3d. This value subsequently decreased for columns 2 and 3 as COD was being utilized by microorganisms. Thereafter as the surface area was increased the effective volume of the columns slightly decreased and consequently the COD loading rate slightly increased. COD removal efficiencies remained around the same values (10%) after adding the second unit. The addition of a third electrode unit improved the COD removal efficiency by 20% (from 10% to 31.0%). BOD5 removal efficiencies increased with the increase in the electrode surface area and reached values of up to 84.4%. For COD, the increase in removal efficiencies achieved after increasing the electrode surface area was statistically significant for the third unit, but not for the second unit, while for BOD5 it was the other way around (i.e. significant for the second unit but not for the third unit). The BOD5/COD ratio also decreased at the outlet of the columns which reflects the higher rate of removal of BOD5 as compared to the COD. This was attributed to the degradation of most of the biodegradable organic matter, leaving the remaining recalcitrant or hardly biodegradable fraction which is detected by the COD method but not by the BOD5. The effects of the different electrode surface areas on pH, Eh and conductivity are shown in Table 2. Increases in electrode surface area were carried out in chronological order and it was noticed that the influent pH shifted slightly downwards with time. This was also substantiated by the Eh drift, which became less positive with time due to the relationship between pH and Eh (where proton pressure opposes redox). Conductivity depends on the numbers of ionic species and for the influent it was shown to increase with time, possibly due to fermentation by-products such as acetate and fatty acids. The influent pH for the 360 cm2 electrode area is shown to be progressively decreasing as the wastewater flows through the columns. Similarly, Eh – apart from the smallest electrode area –, became more negative by the time it reached the third column. A possible explanation for this may be the fact that the small surface

Fig. 4. COD and BOD5 removal efficiencies as a function of the electrode surface area.


A. Gálvez et al. / Bioresource Technology 100 (2009) 5085–5091 Table 2 pH, Eh and conductivity measured in the effluent of columns 1, 2 and 3 at different electrode surface area. Electrode surface area (cm2)

pH influent

360 720 1080

8.00 7.86 7.53

pH effluent C1



7.99 8.05 7.87

7.97 8.16 7.95

7.80 8.21 8.11

Eh influent (mV)

Eh effluent (mV) C1

40.50 33.25 32.20

area electrode was sub-optimal with concomitant sub-optimal rate of acid anion removal. Higher surface areas gave pH and redox increases probably due to increased utilization of acid anion, but possibly also due to higher production of ammonia or amines by the biofilm microorganisms. The pH of the leachate fed to the columns was slightly alkaline with values between 7.53 and 8.00. With an electrode surface area of 360 cm2, the pH of the effluent of the columns remained around the same values as the inlet leachate. However with higher electrode surface areas (720 and 1080 cm2), the pH increased slightly. Eh increased by small amounts or remained approximately the same at the outlet of the columns with an electrode surface area of 360 cm2. With higher electrode surface areas however, a slight decrease in the Eh values was noted. Conductivity values increased for columns 1 and 2 and decreased slightly for column 3 after increasing the electrode surface area. Increasing the surface area of the electrodes should increase power output per volume of reactor, and should decrease retention times needed for wastewater treatment (Logan, 2005). Several other workers showed that power output levels were significantly improved by decreasing the distance between the anode and cathode electrodes (Ghangrekar and Shinde, 2007; Jang et al., 2004; Liu et al., 2005) and recently a report investigating the effects of volume and electrode surface area showed improved energy density levels from smaller units (Ieropoulos et al., 2008). We also noted an increase in power output as a result of placing the anode and cathode electrodes closer together (results not presented).


39.50 44.95 34.10

38.00 51.25 38.20

C3 37.50 53.95 48.00

Conduct influent (mS/cm)

Conduct effluent (mS/cm) C1



8.58 12.75 13.00

9.34 11.95 12.10

9.89 11.10 11.40

12.02 11.10 10.90

Considering that the working volume of the columns was approximately 0.9 l, the specific surface area for 1, 2 and 3 units of carbon veil would be 40, 80 and 120 m2/m3 of reactor volume, respectively. The increase in specific surface area was probably contributing to the higher power density achieved. Although the area of anode was doubled and tripled, power production did not increase proportionately. These results are in line with the findings of other workers (Ghangrekar and Shinde, 2007; Logan et al., 2005) and indicate that power generation was limited by some factor other than anode surface area. Ghangrekar and Shinde (2007) observed a decrease in the power density as the anode surface area was increased. The probable limitation could be electron transfer from the microbial cell to the anode surface, in the absence of an exogenous mediator. In the current study the total effective area of electrodes was not optimized, which is probably why power output increase was not proportional to the area of added electrode. The rate of COD removal in a fixed film bioreactor is a function of the total biofilm surface area (Logan et al., 1987). Hence the rate of wastewater degradation can be accelerated by increasing the surface area of the electrodes per volume of wastewater. This helps explain the higher removal efficiencies obtained after increasing the electrode surface area. At this stage, the best results were produced from when the leachate was diluted 8 times. Clearly, this is a luxury that cannot be part of a system in a real treatment application; however, it highlights the potential of the MFC technology (even in this early

Fig. 5. Power density vs. time for column 2, for the time period the columns were connected in a loop. Straight line illustrates the linear regression fit with ±95% confidence interval (CI). The power output decrease depicted by the linear regression fit, reflects the BOD5 and COD depletion.


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stage) and in particular the employment of multiple MFC units as a stack for a proposed multi-stage treatment system. 3.3. Three MFC columns connected in a loop (Phase 3) In the final phase of the experiments, the columns were disconnected from the input bottle and were fluidically joined in a loop. The aim of this system configuration was to monitor the treatment of the same leachate as it was re-circulated. The power density measured for column 2, for the time period the columns were connected in a loop is shown in Fig. 5. Similar results were obtained for columns 1 and 3. The substantial power fluctuations were due to the rapid depletion of the hexacyanoferrate-based cathodic electrolyte as observed by Rabaey et al. (2006). Straight line illustrates the linear regression fit with ±95% confidence interval (CI). The power output decrease depicted by the linear regression fit, reflects the BOD5 and COD depletion. The initial COD and BOD5 concentrations were 7050 and 2962 mg/L, respectively. After 4 days of re-circulation, the system was able to remove 79.4% of the COD and 81.6% of the BOD5. These high removal efficiencies obtained demonstrate the applicability of the MFC system at treating leachate. It could therefore compete with other conventional biological systems such as a biological aerated filter in the treatment of landfill leachate with the advantage of electricity being generated in the process, hence reducing the treatment costs. The un-treated COD (1451 mg/L) or BOD5 (545 mg/L) was probably the part of wastewater consisting of slowly biodegradable or non biodegradable (recalcitrant) material. Anaerobic degradation of these components is considerably slower than the aerobic, oxygen-driven degradation (Rabaey et al., 2005b). Non biodegradable compounds can be found in leachate such as humic and fulvic like substances that cannot be removed by biological systems and need the aid of other physical or chemical methods (Alkalay et al., 1998; Kjeldsen et al., 2002). The percentage of non biodegradable compounds in the leachate is specific for each landfill leachate and may be ranging between 20% and 30% (Bae et al., 1999; Smith, 1995). Considering that the MFCs in this study removed nearly 80% of COD, it may therefore be assumed that the remaining 20% was the recalcitrant part, which would be the same for any other biological system. A physicochemical post-treatment is thus recommended for a full treatment of the leachate. 4. Conclusions Three Microbial Fuel Cells fluidically connected in series and in a re-circulation loop were employed for simultaneous leachate treatment and electricity generation. The addition of a second and a third unit of carbon veil electrode material, with an increase on the electrode surface area from 360 to 1080 cm2, increased the power output and the removal efficiencies achieved. The three column system connected in a loop removed 79.41% of the COD and 81.6% of the BOD5 after 4 days. This demonstrates that the system can compete with other conventional biological systems in the treatment of landfill leachate. A physicochemical post-treatment is recommended for the removal of recalcitrant compounds. Acknowledgements We are grateful to the Harnhill landfill site managers (Mark Garrett and Phil Adams) for allowing the collection of leachate samples, to Dr. Colin Mckenzie for his valuable aid on the plant construction and to Andy Taylor for performing the COD and BOD5 analyses of the final samples.

References Aelterman, P., Rabaey, K., Pham, T.H., Boon, N., Verstraete, W., 2006. Continuous electricity generation at high voltages and currents using stacked microbial fuel cells. Environ. Sci. Technol. 40 (10), 3388–3394. Alkalay, D., Guerrero, L., Lema, J.M., Mendez, R., Chamy, R., 1998. Review: anaerobic treatment of municipal sanitary landfill leachates: the problem of refractory and toxic components. World J. Microbiol. Biotechnol. 14, 309–320. APHA, AWWA, WPCF, 1989. Standard Methods for the Examination of Water and Wastewater, 17th ed. American Public Health Association, Washington DC. Bae, B.-U., Jung, E.-S., Kim, Y.-R., Shin, H.-S., 1999. Treatment of landfill leachate using activated sludge process and electron-beam radiation. Water Res. 33 (11), 2669–2673. Bennetto, H.P., Stirling, J.L., Tanaka, K., Vega, C.A., 1983. Anodic reactions in microbial fuel-cells. Biotechnol. Bioeng. 25 (2), 559–568. Cooney, M.J., Roschi, E., Marison, I.W., Comninellis, Ch., von Stockar, U., 1996. Physiologic studies with the sulfate-reducing bacterium Desulfovibrio desulfuricans: evaluation for use in a biofuel cell. J. Enzyme Microb. Technol. 18, 358–365. Ghangrekar, M.M., Shinde, V.B., 2007. Performance of membrane-less microbial fuel cell treating wastewater and effect of electrode distance and area on electricity production. Bioresour. Technol. 98, 2879–2885. Greenman, J., Gálvez, A., Giusti, L., Ieropoulos, I., 2009. Electricity from landfill leachate using microbial fuel cells; comparison with a biological aerated filter. J. Enzyme Microb. Technol. 44, 112–119. Habermann, W., Pommer, E.H., 1991. Biological fuel cells with sulfide storage capacity. Appl. Microbiol. Biotechnol. 35 (1), 128–133. Ieropoulos, I., Melhuish, C., Greenman, J., 2003. Artificial metabolism: towards true energetic autonomy in artificial life. Lect. Notes Comput. Sci. 2801, 792– 799. Ieropoulos, I., Greenman, J., Melhuish, C., Hart, J., 2005. Energy accumulation and improved performance in microbial fuel cells. J. Power Sources 145 (2), 253– 256. Ieropoulos, I., Greenman, J., Melhuish, C., 2008. Microbial fuel cells based on carbon veil electrodes: stack configuration and scalability. Int. J. Energy Res. 32 (13), 1228–1240. Jang, J.K., Pham, T.H., Chang, I.S., Kang, K.H., Moon, H., Cho, K.S., Kim, B.H., 2004. Construction and operation of a novel mediator- and membrane-less microbial fuel cell. Process Biochem. 39, 1007–1012. Kim, B.H., Chang, I.S., Gadd, G.M., 2007. Challenges in microbial fuel cell development and operation. Mini review. Appl. Microbiol. Biotechnol. 76, 485–494. Kjeldsen, P., Barlaz, M.A., Rooker, A.P., Baun, A., Ledin, A., Christensen, TH., 2002. Present and long-term composition of MSW landfill leachate: a review. Crit. Rev. Environ. Sci. Technol. 32 (4), 297–336. Liu, H., Ramnarayanan, R., Logan, B.E., 2004. Production of electricity during wastewater treatment using a single chamber microbial fuel cell. Environ. Sci. Technol. 38, 2281–2285. Liu, H., Cheng, S., Logan, B.E., 2005. Power generation in fed-batch microbial fuel cells as a function of ionic strength, temperature, and reactor configuration. Environ. Sci. Technol. 39, 5488–5493. Logan, B.E., Hermanowicz, S.W., Parker, D.S., 1987. A fundamental model for trickling filter process design. J. Water Pollut. Control Fed. 59 (12), 1029–1042. Logan, B.E., 2005. Simultaneous wastewater treatment and biological electricity generation. Water Sci. Technol. 52 (1–2), 31–37. Logan, B.E., Murano, C., Scott, K., Gray, N.D., Head, I.M., 2005. Electricity generation from cysteine in a microbial fuel cell. Water Res. 39, 942–952. Melhuish, C., Ieropoulos, I., Greenman, J., Horsfield, I., 2006. Energetically autonomous robots: food for thought. Autonomous Robots 21 (3), 187–198. Min, B., Logan, B.E., 2004. Continuous electricity generation from domestic wastewater and organic substrates in a flat plate microbial fuel cell. Environ. Sci. Technol. 38, 5809–5814. Min, B., Kim, J., Oh, S., Regan, J.M., Logan, B.E., 2005. Electricity generation from swine wastewater using microbial fuel cells. Water Res. 39, 4961–4968. Oh, S., Logan, B.E., 2005. Hydrogen and electricity production from a food processing wastewater using fermentation and microbial fuel cell technologies. Water Res. 39, 4673–4682. Oh, S.-E., Logan, B.E., 2007. Voltage reversal during microbial fuel cell stack operation. J. Power Sources 167, 11–17. Rabaey, K., Lissens, G., Verstraete, W., 2005a. Microbial fuel cells: performances and perspectives. In: Lens, P.N., Westermann, P., Haberbauer, M., Moreno, A. (Eds.), Biofuels for Fuel Cells: Biomass Fermentation Towards Usage in Fuel Cells. IWA Publishing, London. Rabaey, K., Clauwaert, P., Aelterman, P., Verstraete, W., 2005b. Tubular microbial fuel cells for efficient electricity generation. Environ. Sci. Technol. 39, 8077– 8082. Rabaey, K., Sompel, K.V., Maignien, L., Boon, N., Aelterman, P., Clauwaert, P., Schamphelaire, L., Pham, H.D., Vermeulen, J., Verhaege, M., Lens, P., Verstraete, W., 2006. Microbial fuel cells for sulfide removal. Environ. Sci. Technol. 40, 5218–5224. Rodrigo, M.A., Cañizares, P., Lobato, J., Paz, R., Sáez, C., Linares, J.J., 2007. Production of electricity from the treatment of urban waste water using a microbial fuel cell. J. Power Sources 169, 198–204. Scott, K., Murano, C., 2007. Microbial fuel cells utilizing carbohydrates. J. Chem. Technol. Biotechnol. 82, 92–100.

A. Gálvez et al. / Bioresource Technology 100 (2009) 5085–5091 Smith, D.P., 1995. Oxygen flux limitation in aerobic fixed-film biotreatment of a hazardous landfill leachate. J. Hazard. Mater. 44, 77–91. Wilkinson, S., 2000. ‘‘Gastrobots” – benefits and challenges of microbial fuel cells in food powered robot applications. Autonomous Robot 9, 99–111. Yokoyama, H., Ohmori, H., Ishida, M., Waki, M., Tanaka, Y., 2006. Treatment of cowwaste slurry by a microbial fuel cell and the properties of the treated slurry as a liquid manure. Rapid communication. J. Anim. Sci. 77, 634–638.


You, S.J., Zhao, Q.L., Jiang, J.Q., Zhang, J.N., Zhao, S.Q., 2006. Sustainable approach for leachate treatment: electricity generation in microbial fuel cell. J. Environ. Sci. Health A 41, 2721–2734. Zhang, J.N., Zhao, Q.L., You, S.J., Jiang, J.Q., Ren, N.Q., 2008. Continuous electricity production from leachate in a novel up flow air-cathode membrane-free microbial fuel cell. Water Sci. Technol. 57 (7), 1017– 1021.

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