Bioresource Technology 102 (2011) 10305–10311

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Bioresource Technology

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Effects of metal oxide nanoparticles (TiO2, Al2O3, SiO2 and ZnO) on wasteactivated sludge anaerobic digestion

Hui Mu, Yinguang Chen ⇑, Naidong XiaoState Key Laboratory of Pollution Control and Resources Reuse, School of Environmental Science and Engineering, Tongji University, 1239 Siping Road, Shanghai 200092, China

a r t i c l e i n f o

Article history:Received 1 June 2011Received in revised form 28 July 2011Accepted 22 August 2011Available online 27 August 2011

Keywords:Metal oxide nanoparticlesWaste activated sludgeAnaerobic digestionMethane

0960-8524/$ - see front matter � 2011 Elsevier Ltd. Adoi:10.1016/j.biortech.2011.08.100

⇑ Corresponding author. Tel.: +86 21 65981263; faxE-mail address: yg2chen@yahoo.com (Y. Chen).

a b s t r a c t

The effect of metal oxide nanoparticles (nano-TiO2, nano-Al2O3, nano-SiO2 and nano-ZnO) on anaerobicdigestion was investigated by fermentation experiments using waste activated sludge as the substrates.Nano-TiO2, nano-Al2O3 and nano-SiO2 in doses up to 150 milligram per gram total suspended solids (mg/g-TSS) showed no inhibitory effect, whereas nano-ZnO showed inhibitory effect with its dosagesincreased. The methane generation was the same as that in the control when in the presence of 6 mg/g-TSS of nano-ZnO, however, which decreased respectively to 77.2% and 18.9% of the control at 30 and150 mg/g-TSS. The released Zn2+ from nano-ZnO was an important reason for its inhibitory effect onmethane generation. It was found that higher dosages of nano-ZnO inhibited the steps of sludge hydro-lysis, acidification and methanation. Also, the activities of protease, acetate kinase (AK) and coenzymeF420 were inhibited by higher dosages of nano-ZnO during WAS anaerobic digestion.

� 2011 Elsevier Ltd. All rights reserved.

1. Introduction discharged to the environment. WAS anaerobic digestion for meth-

Researches about nanotechnology have drawn much attentiondue to the unique physicochemical properties of nanoparticles,such as enhanced magnetism, electricity, and optics (Maynardet al., 2006; Roco, 2005). Metal oxide nanoparticles, such as tita-nium dioxide (TiO2), aluminum oxide (Al2O3), silicon dioxide(SiO2) and zinc oxide (ZnO), have received increasing interestsdue to their widespread industrial, medical and military applica-tions (Ellsworth et al., 2000; Miziolek, 2002; Serda et al., 2009).With the world wide utilization of these metal oxide nanoparticles,their potential effects on environment have been investigated, butmost studies focused on the toxicity to human health, and soil andaquatic organisms (Franklin et al., 2007; Ge et al., 2011; Limbachet al., 2007).

The increasing use of nanoparticles introduces them intention-ally or unintentionally into wastewater treatment plants (WWTPs),which are the last barriers prior to nanoparticles waste (causedmainly by both daily activities and industrial use) environmentalrelease. The existence of nanomaterials in WWTPs has been re-ported (Gottschalk et al., 2009; Kiser et al., 2009), and the adsorp-tion of activated sludge was reported to be the main mechanismfor nanoparticles removal in WWTPs (Ganesh et al., 2010; Kiseret al., 2009, 2010; Limbach et al., 2008). Therefore, nanoparticleswould eventually end up in sludge. Large amounts of WAS are pro-duced in municipal WWTPs, which need to be treated before being

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ane generation is a sustainable sludge treatment practice in whichboth pollution control and energy (methane) recovery can beachieved. Nevertheless the influences of metal oxide nanoparticleson sludge anaerobic digestion have seldom been investigated.

There are some publications discussing the toxicity of metaloxide nanoparticles to pure microbes. For example, nano-Al2O3,nano-SiO2 and nano-ZnO were observed to be harmful to Bacillussubtilis, Escherichia coli and Pseudomonas fluorescens (Jiang et al.,2009). Adams et al. (2006) found that the antibacterial effects ofnanoparticles on B. subtilis and E. coli increased from SiO2 to TiO2

to ZnO. Nano-ZnO was observed to cause significant toxicity tothe viability of gram negative bacterial cells (Sinha et al., 2011).It is well known that large numbers of different microorganismsparticipate in sludge anaerobic digestion due to several stages (sol-ubilization, hydrolysis, acidification and methanation) involved.Thus, it is impossible to deduce the negative effect of these metaloxide nanoparticles on sludge anaerobic digestion microorganismsaccording to the current knowledge of pure microbial species.

The purpose of this study was to investigate the influences offour metal oxide nanoparticles (TiO2, Al2O3, SiO2 and ZnO) onmethane generation during sludge anaerobic digestion and to digout the mechanisms. Firstly, the effects of three dosages (6, 30and 150 mg/g-TSS) of these four nanoparticles on methane gener-ation were studied when WAS was anaerobically digested in batchtests. Then, the mechanisms for nanoparticles affecting methanegeneration were investigated from the role of dissolved metal ionsand the changes of products and key enzymes involved each stage(solubilization, hydrolysis, acidification and methanation) ofsludge anaerobic digestion.

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2. Methods

2.1. Waste activated sludge: origin and chemical properties

The WAS used in this study was withdrawn from the secondarysedimentation tank of a municipal WWTP in Shanghai, China. Thesludge was concentrated by settling at 4 �C for 24 h, and its maincharacteristics (average data and standard deviations of three tests)are as follows: pH 6.7 ± 0.2, total suspended solids (TSS)10,070 ± 780 mg/L, volatile suspended solids (VSS) 7700 ± 450 mg/L, soluble chemical oxygen demand (SCOD) 90 ± 14 mg/L, totalchemical oxygen demand (TCOD) 10,700 ± 200 mg/L, total carbohy-drate 900 ± 530 mg-COD/L, and total protein 5685 ± 150 mg-COD/L.The natural concentrations of titanium, aluminum, silicon and zincin the WAS used in this study were 3.4 ± 0.2, 14.7 ± 0.9, 52.5 ± 3.5and 0.8 ± 0.2 mg/g-TSS, respectively.

2.2. Metal oxide nanoparticles and their dissolved metal ions

Nano-TiO2 (<25 nm, anatase), nano-Al2O3 (<50 nm), nano-SiO2

(10–20 nm, amorphous) and nano-ZnO (<100 nm) were purchasedfrom Sigma Aldrich (St. Louis, MO). The suspensions of nanoparticlesstock (2000 mg/L) were prepared by adding 2000 mg nanoparticlesto 1.0 L distilled water (pH 7.0) containing 0.1 mM sodium dodecyl-benzene sulfonate (SDBS) to enhance the stability of nano-suspen-sion, followed by 1 h of ultrasonication (40 kHz, 250 W). Theanalyses of these suspensions by dynamic light scattering (DLS)using a Malvern Autosizer 4700 (Malvern Instruments, UK) (Frank-lin et al., 2007) indicated that the average particle sizes of nano-TiO2, nano-Al2O3, nano-SiO2 and nano-ZnO were 185 ± 40,130 ± 30, 110 ± 40 and 140 ± 20 nm, respectively. The specific sur-face area (SSA) of nano-TiO2, nano-Al2O3, nano-SiO2 and nano-ZnOanalyzed by Micromeritics Tristar 3000 analyzer at 77 K using theBrunauer–Emmett–Teller (BET) method was 110.0 ± 8.5, 138.0 ±7.0, 52.5 ± 4.0 and 42.5 ± 2.5 m2/g, respectively. The X-ray diffrac-tion (XRD) analysis using a Rigaku D/Max-RB diffractometerequipped with a rotating anode and a Cu Ka radiation source isshown in Fig. S1 (Supplementary material).

It has been reported that sometimes the toxicity of nanoparti-cles comes from the dissolution of nanoparticles (Brunner et al.,2006; Franklin et al., 2007; Wong et al., 2010; Xia et al., 2008).Thus, in this study, three concentrations of nanoparticles in0.1 mM SDBS water solution were prepared with the stock disper-sion, and the mixtures were maintained in an air-batch shaker(150 rpm) at 35 ± 1 �C for 48 h. At different times, the sampleswere withdrawn and centrifuged at 12,000 rpm for 30 min. Thesupernatant was collected, filtered through 0.22 lm mixed cellu-lose ester membrane, and determined by inductively coupled plas-ma optical emission spectrometry (ICP-OES, PerkinElmer Optima2100 DV, USA) after acidified with 4% ultrahigh purity HNO3

(Franklin et al., 2007; Jiang et al., 2009). In this study among fournanoparticles only nano-ZnO showed significant amount of metalion (Zn2+) release, and the released metal ions were negligible inthe suspensions of nano-TiO2, nano-Al2O3 and nano-SiO2. The re-leased Zn2+ was respectively 4.4, 11.6 and 17.6 mg/L at nano-ZnOdosage of 6, 30 and 150 mg/g-TSS.

2.3. Effects of nanoparticles on methane generation during WASanaerobic digestion

In this study the environmental relevant concentration of nano-particles was chosen to be 6 mg/g-TSS as it was reported that thetitanium, aluminum and zinc content in WWTPs (84 in total)biosolids ranged from 0.02 to 7.02, 1.4 to 57.3 and 0.22 to8.55 mg/g-TSS in USA, respectively (USEPA, 2009). Also, someresearchers suggested that a much higher nanomaterial dosage

should be investigated if one wants to get the final conclusionregarding the toxicity of nanomaterial (Nyberg et al., 2008). Thus,the impacts of 30 and 150 mg/g-TSS of nanoparticles were alsoinvestigated. The experiments of nanoparticles exposure affectingsludge anaerobic digestion for methane generation were carriedout in series of serum bottles (500 mL), with a sludge volume of300 mL each. The nanoparticles (TiO2, Al2O3, SiO2 and ZnO) wereadded to the serum bottles with the dosage of 0.006, 0.03 and0.15 g/g-TSS, respectively. Also, two controls, one with only sludge,and another one with sludge plus 4 mg/g-TSS of SDBS (dispersingreagent), were used to investigate whether the SDBS addition in-duced a negative effect on methane generation during WAS anaer-obic digestion. After being flushed with nitrogen gas for 5 min toremove oxygen, all bottles were capped with rubber stoppers,sealed and placed in an air-bath shaker (150 rpm) at 35 ± 1 �C.The total gas volume was measured by releasing the pressure inthe bottles using a syringe (100 mL) to equilibrate with the roompressure according to the Owen method (1979), and the syringewas empty with the excess gas at ambient pressure when thegas component was analyzed. The cumulative methane gas volumewas calculated by the following equation modified according to Ohet al. (2003):

VH;i ¼ VH;i�1 þ CH;iðVG;iÞ � CH;i�1ðVG;i�1Þ ð1Þ

where VH,i and VH,i�1 are respectively the cumulative methane gasvolumes in the current (i) and previous (i � 1) time intervals, VG,i

is the total biogas volumes (including the total volume of headspacein the reactor and the syringe) in the current time, VG,i�1 is the totalvolume of biogas after the gas component analysis in the previoustime, CH,i and CH,i�1 are respectively the fractions of methane gasin the syringe or the headspace of the bottle measured using gaschromatography in the current and previous time intervals. By ana-lyzing the changes of methane generation, the effect of nanoparti-cles on WAS fermentative methane generation was obtained. Theinfluences of released metal ions from nanoparticles on WAS anaer-obic digestion were conducted with the same method describedabove except that the corresponding dissolved ions were used to re-place the nanoparticles.

2.4. Effects of nanoparticles on each stage involved in WAS anaerobicdigestion

The methane generation during WAS anaerobic digestion usuallyincludes the solubilization of sludge particular organic compounds,hydrolysis, acidification and methanation (Fig. S2 (Supplementarymaterial). The batch experiments of influences of four nanoparticleson the solubilization of sludge particulate organic maters were thesame as that described in the section of ‘‘Effects of nanoparticleson methane generation during WAS anaerobic digestion’’ exceptthat the fermentation time was 2 d. Based on the analyses of solubleprotein and carbohydrate in fermentation liquor, the impact ofnanoparticles on sludge solubilization was obtained. The influencesof nanoparticles on the other three stages (hydrolysis, acidificationand methanation) were conducted in synthetic wastewater consist-ing of (mg/L of distilled water) 1000 KH2PO4, 400 CaCl2, 600MgCl2�6H2O, 100 FeCl3, 0.5 ZnSO4�7H2O, 0.5 CuSO4�5H2O, 0.5CoCl2�6H2O, 0.5 MnCl2�4H2O, 1 NiCl2�6H2O and 34.8 SDBS. WAS of30 mL, which was heat-pretreated at 102 �C for 30 min to kill meth-anogens (Oh et al., 2003), was used as the inocula of each bottle un-less otherwise stated.

The impacts of nanoparticles on sludge hydrolysis wereconducted in the following batch tests with 3510 mL syntheticwastewater (described above) containing 15.6 g bovine serumalbumin (BSA, average molecular weight Mw 67,000, model proteincompound used in this study) and 3.9 g dextran (model polysac-charide compound) (the mass ratio of protein to carbohydrate

H. Mu et al. / Bioresource Technology 102 (2011) 10305–10311 10307

was almost the same as that in WAS). Then the mixed liquid wasdivided into 13 bottles, and the heat-pretreated WAS of 30 mLwas added to each bottle with a final sludge concentration of1000 mg/L. According to the above described nanoparticles addi-tion dosages, the suitable dosages of nano-TiO2, nano-Al2O3,nano-SiO2 and nano-ZnO were respectively added to each bottlewith a final dosage of 6, 30 and 150 mg/L before the pH of mixedliquid was adjusted to 7.0 by adding 4 M NaOH or 4 M HCl. Afterbeing flushed with nitrogen gas to remove oxygen, all bottles werecapped with rubber stoppers, sealed and placed in an air-bathshaker (150 rpm) at 35 ± 1 �C. By analyzing the degradationefficiencies of BSA and dextran, the impact of nanoparticles onsludge hydrolysis was achieved.

The same operation was conducted when the effect of nanopar-ticles on the acidification of hydrolyzed products was investigatedexcept that the 3510 mL synthetic wastewater containing 15.6 g L-glutamate (model amino acid compound) and 3.9 g glucose (modelmonosaccharide compound). The influence of nanoparticles onacidification was obtained by measuring the concentration of gen-erated short-chain fatty acid (SCFA). The operation of nanoparticlesaffecting the methanation of acidification products was conductedwith the same method as described above except that the syntheticwastewater (3510 mL) containing 9.36 g sodium acetate (modelSCFA compound in this study) and the inocula was 30 mL rawWAS. By the analysis of methane generation, the effect of nanopar-ticles on methanation was obtained.

2.5. Scanning electron microscopy

The surface morphology of WAS exposed to nanoparticles wascharacterized by scanning electron microscopy (SEM) with en-ergy-dispersive X-ray (EDX) elemental analysis fitted with an Ox-ford Inca 300 EDS system. Fermentation mixture of 20 mL waswithdrawn from the reactors after WAS was exposed to nanoparti-cles for 18 d, and then centrifuged at 3000 rpm for 10 min. Afterbeing washed three times with 0.1 M phosphate buffer (pH 7.4),the centrifuged pellets were fixed in 0.1 M phosphate buffer (pH7.4) containing 2.5% glutaraldehyde at 4 �C for 4 h. The pelletsagain were washed three times with 0.1 M phosphate buffer, andthen dehydrated in the ethanol serials (50%, 70%, 90% and 100%,15 min per step), followed by air drying.

2.6. Key enzyme activity analysis

The activity of protease was assayed by the folin–phenol method(Ledoux and Lamy, 1986). Acetate kinase (AK) was the most impor-tant enzyme in acid-forming step (Fig. S2 Supplementary material).For determining its activity, fermentation mixture of 25 mL was ta-ken out of the reactors at different fermentation times and thenwashed and resuspended in 100 mM sodium phosphate buffer (pH7.4). The resuspended mixture was sonicated at 20 kHz and 4 �Cfor 10 min to break down the cells structure of bacteria and thencentrifuged at 10,000 rpm and 4 �C for 15 min to remove the wastedebris (Allen et al., 1964). The extracts were kept cold on ice beforethey were used for enzyme activity assay. Coenzyme F420 wasassayed by spectrophotometric study (Delafontaine et al., 1979).The specific enzyme activities of protease and coenzyme F420 weredefined as the unit of enzyme activity per milligram of VSS (units/mg-VSS), whereas AK was defined as the unit of enzyme activityper milligram of protein (units/mg-protein).

2.7. Other analytical methods

Gas component was measured using a gastight syringe (0.2 mLinjection volume) and a gas chromatograph (Agilent 6890N, USA)equipped with a thermal conductivity detector using nitrogen as

the carrier gas. The titanium, aluminum, silicon and zinc concen-trations in sludge were analyzed by ICP-OES (PerkinElmer Optima2100 DV, USA), and the samples were digested according to EPAMethod 3052 prior to ICP analyses. The determinations of SCFA,protein, carbohydrate, TSS and VSS were the same as describedin the previous publication (Yuan et al., 2006). The pH value wasmeasured by a pH meter. The total SCFA was calculated as thesum of measured acetic, propionic, n-butyric, iso-butyric, n-valericand iso-valeric acids. The COD (chemical oxygen demand) conver-sion factors of protein, carbohydrate and SCFA were performedaccording to Grady et al. (1999).

2.8. Statistical analysis

All assays were conducted in triplicate and the results were ex-pressed as mean ± standard deviation. An analysis of variance (AN-OVA) was used to test the significance of results, and p < 0.05 wasconsidered to be statistically significant.

3. Results and discussion

3.1. Effects of nanoparticles exposure on methane generation duringWAS anaerobic digestion

A higher concentration of SDBS was observed to influencemethane generation during WAS digestion (Jiang et al., 2007).However, the presence of 4 mg/g-TSS of SDBS (dispersing reagent)in sludge digestion experiments or 0.1 mM SDBS in syntheticwastewater tests showed no influence on methane generation inthis study, which is consistent with Garcia et al. (2006). In the com-ing text, the control represented the reactor without nanoparticlesaddition but with a SDBS dosage of 4 mg/g-TSS (or 0.1 mM). Asshown in Fig. 1A–C, the presence of 6, 30 and 150 mg/g-TSS ofnano-TiO2, nano-Al2O3 and nano-SiO2 did not significantly affectmethane generation at any fermentation time investigated in thisstudy (p > 0.05). However, when nano-ZnO was in sludge fermen-tation system, its influence on methane generation was relevantto the dosage (Fig. 1D). No significant difference of methane gener-ation between the control and 6 mg/g-TSS of nano-ZnO reactorswas observed at any fermentation time (p > 0.05). However, theinhibitory effects of 30 and 150 mg/g-TSS of nano-ZnO on methanegeneration were significant at fermentation time being more than10 and 5 d, respectively (p < 0.05). The methane generation at fer-mentation time of 18 d in the presence of 30 and 150 mg/g-TSS ofnano-ZnO was respectively 99.5 and 24.5 mL/g-VSS, whereas in thecontrol test the methane generation was 129.1 mL/g-VSS, whichsuggested the methane inhibition rates were 22.8% and 81.1%. Inthe literature Luna-delRisco et al. (2011) studied the influence ofparticle size of ZnO and CuO on methane generation during anaer-obic digestion of cattle manure, and found that the inhibitory ef-fects of nano-ZnO and nano-CuO were much greater than thebulk ZnO and CuO.

3.2. Influence of dissolved metal ions from nanoparticles on methanegeneration during WAS anaerobic digestion

The toxicity of metal oxide nanoparticles is sometimes believedto be relevant to the released metal ions (Brunner et al., 2006;Franklin et al., 2007; Wong et al., 2010; Xia et al., 2008). However,the toxicity of nano-ZnO to some microorganisms (such as E. coliand P. fluorescens) was found not to be caused by the releasedZn2+ but nano-ZnO (Jiang et al., 2009). Therefore, the experimentsof comparisons of nano-ZnO and the corresponding released metalion (Zn2+) affecting methane generation were conducted to inves-tigate the influence of nano-ZnO dissolution on WAS anaerobic

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Fig. 1. Effects of different dosages (0, 6, 30 and 150 mg/g-TSS) of nano-TiO2 (A), nano-Al2O3 (B), nano-SiO2 (D) and nano-ZnO (D) exposure on methane generation during WASdigestion at different fermentation time. Asterisks indicate statistical differences (p < 0.05) from the control. Error bars represent standard deviations of triplicate tests.

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digestion. The experimental results showed that the presence of4.4 mg/L of Zn2+ did not induce significant influence on methanegeneration (p > 0.05) at fermentation time of 18 d. However, themethane generation in the presence of 11.6 and 17.6 mg/L ofZn2+ was respectively 84.4% and 22.1% of the control, and themethane generation was respectively 77.2% and 18.9% of the con-trol at nano-ZnO dosage of 30 and 150 mg/g-TSS. It seems that thereleased Zn2+ was an important reason for the inhibitory effect ofnano-ZnO on WAS digestion for methane generation, which mightbe one reason for only nano-ZnO among four nanoparticles show-ing the negative influence on WAS anaerobic digestion.

3.3. Morphology of WAS after nanoparticles addition

SEM analysis was usually applied to characterize the sludge sur-face structure after nanoparticles were added (Kiser et al., 2009).As seen in Fig. S3A1-D1 (Supplementary material), there were largenumbers of nanoparticles adsorbed on the surface of sludge whennano-TiO2, nano-Al2O3, nano-SiO2 and nano-ZnO appeared insludge digestion system. The same observations were reportedby other researchers when the behavior of nanoparticles in waste-water treatment system was studied (Kiser et al., 2010; Limbachet al., 2008). The EDX spectra further confirmed that the granulesobserved on sludge surface were nano-TiO2 (Fig. S3A2 Supplemen-tary material), nano-Al2O3 (Fig. S3B2), nano-SiO2 (Fig. S3C2) andnano-ZnO (Fig. S3D2).

3.4. Effects of nanoparticles exposure on each stage involved in theprocess of WAS anaerobic digestion

Methane generation during WAS anaerobic digestion usuallyincludes sludge solubilization, hydrolysis, acidification and metha-nation (Fig. S2 Supplementary material). In the following text, theimpacts of nanoparticles on each stage of sludge anaerobic diges-tion were discussed in detail.

Protein and carbohydrate are the main constituents of WAS(accounting for 61.5% of sludge TCOD). They are usually in partic-ulate state and cannot be hydrolyzed until solubilization. As seenfrom Fig. S4 (Supplementary material) the addition of nanoparti-cles did not induce significant changes of soluble protein andcarbohydrate production (p > 0.05). The possible reason was thatthe solubilization of sludge particulate organic matters was not amicrobial process, and thus insensitive to some toxicants, such asnanoparticles and their dissolved metal ions.

Fig. 2 shows the effects of nanoparticles on the hydrolysis of sol-ubilized products (soluble protein and carbohydrate). No signifi-cant differences in the degradation efficiency of either BSA ordextran were observed among the reactors of nano-TiO2, nano-Al2O3, nano-SiO2, 6 and 30 mg/L of nano-ZnO (p > 0.05). In the150 mg/L of nano-ZnO reactor, however, the degradation efficien-cies of BSA and dextran were 62.5% and 87.7% of the control,respectively (p < 0.05). It seems that one reason for the decreasedmethane generation in the presence of higher dosage of

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Fig. 2. Effects of nanoparticles exposure on the degradations of BSA (A) and dextran (B) in hydrolysis tests at fermentation time of 3 d. Asterisks indicate statistical differences(p < 0.05) from the control. Error bars represent standard deviations of triplicate tests.

H. Mu et al. / Bioresource Technology 102 (2011) 10305–10311 10309

nano-ZnO was due to its inhibitory effect on the hydrolysis ofprotein and carbohydrate.

The hydrolyzed products, such as amino acid and monosaccha-ride, are converted to SCFA in the acidification step. Fig. 3 illustratesthe effect of four nanoparticles exposure on the acidification of syn-thetic wastewater containing L-glutamic acid and glucose. It can beseen that only higher dosages of nano-ZnO induced negative effect

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Fig. 3. Effects of nanoparticles exposure on acetic acid (A), propionic acid (B), butyric acidiso-valeric acid) (D) production during acidification of L-glutamic acid and glucose at fecontrol. Error bars represent standard deviations of triplicate tests.

on SCFA production during sludge acidification step. At nano-ZnOdosage of 150 mg/L the acetic and propionic acids were 39.3% and20.4% of the control (Fig. 3A and B). As to the butyric and valericacids, their production concentrations were 87.4% and 78.2% ofthe control at 30 mg/L of nano-ZnO, and then decreased to 59.3%and 18.5% of the control when nano-ZnO dosage increased to150 mg/L (Fig. 3C and D). At nanoparticles dosage of 6 mg/L all

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(the sum of n-butyric and iso-butyric) (C) and valeric acid (the sum of n-valeric andrmentation time of 4 d. Asterisks indicate statistical differences (p < 0.05) from the

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Fig. 4. Effects of nanoparticles exposure on methanation of acetic acid syntheticwastewater. Asterisks indicate statistical differences (p < 0.05) from the control.Error bars represent standard deviations of triplicate tests.

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Fig. 5. Comparisons of the activities of protease (A), AK (B), and coenzyme F420 (C) in thdeviations of triplicate tests.

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reactors including the control had almost the same total SCFA con-centrations (around 2770 ± 65 mg-COD/L). However, the presenceof 30 and 150 mg/L of nano-ZnO caused the decrease of total SCFAconcentration to 2600 ± 70 and 1160 ± 50 mg-COD/L, respectively.Obviously, the acidification step involved in sludge anaerobic diges-tion was affected by higher dosages of nano-ZnO, which might beanother reason for the decreased methane generation in the pres-ence of 30 and 150 mg/L of nano-ZnO.

Acetic acid is a favorable substrate for methane generation dur-ing the sludge methanation step (Fig. S2 Supplementary material).The batch tests of methane generation from acetic acid syntheticwastewater indicated that the presence of nano-TiO2, nano-Al2O3

and nano-SiO2 did not significantly affect the methane generationat all three dosages investigated (p > 0.05) (Fig. 4). The methanegeneration, however, was respectively 79.9% and 20.8% of the con-trol when exposed to 30 and 150 mg/L of nano-ZnO. Apparently,higher concentrations of nano-ZnO significantly inhibited thebio-conversion of acetic acid to methane, i.e. the methanation stepof sludge anaerobic digestion. By comparing the data in Supple-mentary Fig. S4 and Figs. 2–4, it seems that the negative influenceof nano-ZnO on the methanation step was the most serious oneamong the four steps. It has been reported in the literature that

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e reactors of 0, 6, 30 and 150 mg/g-TSS of nano-ZnO. Error bars represent standard

H. Mu et al. / Bioresource Technology 102 (2011) 10305–10311 10311

methanogens were more sensitive to some metal ions, such as Zn2+

(Zayed and Winter, 2000).Several enzymes, such as protease, AK and coenzyme F420, take

part in sludge hydrolysis, acidification and methanation stepsduring sludge anaerobic digestion. The influences of nano-TiO2,nano-Al2O3 and nano-SiO2 at three dosages (6, 30 and 150 mg/g-TSS) on the activities of protease, AK and F420 were not observedin this study (data not shown), but these enzymes activities wereaffected by higher dosage of nano-ZnO (Fig. 5). The time curvesof protease, AK and coenzyme F420 activities at 6 mg/g-TSS ofnano-ZnO were almost the same as those in the control reactor(p > 0.05). When the nano-ZnO dosage increased to 30 mg/g-TSS,the coenzyme F420 activity was inhibited by 12.9% at fermentationtime of 18 d. At nano-ZnO dosage of 150 mg/g-TSS, the activities ofprotease, AK and coenzyme F420 were respectively inhibited by25.3%, 22.9% and 40.9% with fermentation time of 18 d. All theseobservations consisted well with the above observed methanegeneration affected by nano-ZnO.

4. Conclusions

Among four metal oxide nanoparticles (nano-TiO2, nano-Al2O3,nano-SiO2 and nano-ZnO) investigated it was found that onlynano-ZnO showed inhibitory effect on methane generation, andthe influence of nano-ZnO was dosage dependent. Lower nano-ZnO (6 mg/g-TSS) gave no impact on methane generation. Never-theless, with the increase of nano-ZnO to 30 and 150 mg/g-TSSthe methane was decreased by 22.8% and 81.1% compared withthe control. The mechanisms investigation showed that the re-leased Zn2+ from nano-ZnO was an important reason for its inhibi-tion, and the metabolic intermediates and key enzyme activityinvolved in sludge hydrolysis, acidification and methanation wereinhibited by nano-ZnO.

Acknowledgements

This work was financially supported by the Foundation of StateKey Laboratory of Pollution Control and Resource Reuse(PCRRK09002).

Appendix A. Supplementary data

Supplementary data associated with this article can be found, inthe online version, at doi:10.1016/j.biortech.2011.08.100.

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