Production of a bioflocculant from methanol wastewater and its application in arsenite removal

Chemosphere 141 (2015) 274–281

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Production of a bioflocculant from methanol wastewater and its application in arsenite removal Gang Cao a,1, Yanbo Zhang a,b,1, Li Chen c, Jie Liu a, Kewei Mao a, Kangju Li a, Jiangang Zhou a,⇑ a

School of Environmental Engineering, Wuhan Textile University, Wuhan 430073, China School of Chemical Engineering, Wuhan Textile University, Wuhan 430073, China c Central China Normal University Library, Wuhan 430079, China b

h i g h l i g h t s
The methanol wastewater was first time used as a medium for EPS production.
The bioflocculant-producing bacteria were isolated from methanol wastewater sludge.
The application of MBF83 in arsenite removal was investigated.
MBF83 was found to be safe in Zebrafish in toxicity studies.

a r t i c l e

i n f o

Article history: Received 20 May 2015 Received in revised form 6 August 2015 Accepted 6 August 2015 Available online 26 August 2015 Keywords: Bioflocculant Wastewater treatment Arsenite Turicibacter sanguinis

a b s t r a c t A novel bioflocculant (MBF83) prepared using methanol wastewater as nutrient resource was systematically investigated in the study. The optimal conditions for bioflocculant production were determined to be an inoculum size of 8.6%, initial pH of 7.5, and a methanol concentration of 100.8 mg L1. An MBF83 of 4.61 g L1 was achieved as the maximum yield. MBF83 primarily comprised polysaccharide (74.1%) and protein (24.2%). The biopolymer, which was found to be safe in zebrafish in toxicity studies, was characterized using Fourier-transform infrared spectroscopy and elemental analysis. Additionally, conditions for the removal of arsenite by MBF83 were found to be MBF83 at 500 mg L1, an initial pH of 7.0, and a contact time of 90 min. Under the optimal conditions, the removal efficiency of arsenite was 86.1%. Overall, these findings indicate bioflocculation offers an effective alternative method of decreasing arsenite during wastewater treatment. Ó 2015 Elsevier Ltd. All rights reserved.

1. Introduction Arsenic-contaminated wastewater represents a great threat to the environment and human health. Arsenic contamination caused by both natural processes and anthropogenic activities is a worldwide problem. In aquatic systems, the predominant forms of As are the inorganic species arsenate and arsenite, with the latter being more labile and 25–60 times more noxious than the former (Dax et al., 2014). Reducing conditions at low redox potential result in conversion of arsenate into arsenite. Conversely, under oxidizing conditions such as those found in surface water, arsenate is the major arsenic species (Amrose et al., 2013). Owing to the high virulence of arsenic, the World Health Organization (WHO) has lowered the permissible limit of arsenic in drinking water from 50 to ⇑ Corresponding author. 1

E-mail address: [email protected] (J. Zhou). Gang Cao and Yanbo Zhang contributed equally to this work.

http://dx.doi.org/10.1016/j.chemosphere.2015.08.009 0045-6535/Ó 2015 Elsevier Ltd. All rights reserved.

10 lg L1 (Xu et al., 2013); accordingly, it is necessary to develop feasible, efficient methods to diminish both arsenic species concentration from water, particularly arsenite. To date, a substantial number of methods have been developed to remove arsenite (Balasubramanian et al., 2009; Altun et al., 2014), among which flocculation is recognized as one of the best available options because of its low cost and high efficiency (Bolto and Gregory, 2007; Mishra et al., 2014). Some flocculants, like diatom silica shells and Arthrobacter sp. biomass, were used to remove arsenite from the wastewater (Prasad et al., 2013; Zhang et al., 2015). However, most of these flocculants preferentially flocculate arsenate instead of arsenite, and consequently a preliminary oxidation step for the transformation of arsenite to arsenate to achieve efficient arsenic removal is required (Luo et al., 2010). Undoubtedly, this will increase the operation cost and complexity. Accordingly, ‘‘green” bioflocculation has attracted increasingly scientific and technological attention in the wastewater treatment

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field because it is not dangerous to humans, uses easily biodegraded materials, and is free of secondary pollution by degradation intermediates. Moreover, bioflocculants have been widely employed in a variety of processes including wastewater clarification, purification of carbohydrates from plant biomass, paper production, chemical operations, dredging, dewatering and thickening in mineral operations (Aljuboori et al., 2013; Zhao et al., 2013). Nevertheless, there has been no published research regarding the removal of arsenite using microbially produced bioflocculants. High-costs are the major bottleneck in bioflocculants development for commercial use (Fujita et al., 2000; Zhang et al., 2013). Hence, industrial-scale production and application of bioflocculants as potential alternatives to synthetic ones has yet to be achieved. Although several investigations using inexpensive substrates for bioflocculant production have been conducted (Zhang et al., 2007; Gong et al., 2008), there have been no studies of the production of bioflocculants from methanol wastewater. Methanol, which is colorless and has a characteristic distinctive irritating odor, is especially useful for HPLC, UV/VIS spectroscopy, and LCMS due to its low UV cutoff. It is also an alternative fuel for internal combustion and other engines, either in combination with gasoline. Although methanol wastewater is very harmful to ecological systems and human health, it is a potentially inexpensive medium and a rich source of carbon and other nutrients that have the potential for use as bioflocculants. Hence, microorganisms that use wastes as substrates for the production of interesting materials not only contribute to the production of these value added compounds, but also focus on the minimization of waste disposal. Therefore, the present study was conducted to: (1) isolate and identify bioflocculant-producing strains from methanol wastewater sludge; (2) produce bioflocculant using strains isolated from methanol wastewater; (3) evaluate the performance of this bioflocculant and its application to arsenite removal. 2. Materials and methods 2.1. Isolation and identification of bioflocculant-producing microorganisms Bioflocculant-producing strains were isolated from activated sludge samples (pH 7.6–7.8) taken from a methanol wastewater treatment plant located in Jiangsu, China. The procedure was the same as previously described (Bala Subramanian et al., 2010). Each isolated strain was cultivated in screening medium (50 mL) containing 2% methanol, 0.05% (NH4)2SO4, 0.5% K2HPO4, 0.2% KH2PO4, 0.05% MgSO4, and 0.01% NaCl at 30 °C for 3 d. Next, 1 mL of fermentation broth was added into 100 mL kaolin suspension (4 g L1) in a 250-mL beaker and the flocculating activities of the suspensions were measured. Culture broths propitious to flocculating rate were further explored. Five strains were found to produce flocculants, among which ZCY83 exhibited the excellent flocculating activity in kaolin suspension. Therefore, ZCY83 was inoculated onto an isolation slant culture-medium and cultivated at 30 °C for 8 d, after which it was preserved at 4 °C for further study. PCR amplification of the 16S rDNA was conducted by Takara Biotechnology Co., Ltd. (Bala Subramanian et al., 2010). 2.2. Bioflocculant production and flocculating activity tests Methanol wastewater (CODCr 1,060 mg L1, pH 7.7, methanol 350 mg L1) was collected from the primary sedimentation tank of the JiHua Chemical Plant in Jiangsu, China. The concentrations of methanol, formaldehyde and methanoic acid were determined by GC-FID techniques. The culture medium consisted of 1 L diluted

methanol wastewater containing 0.05% (NH4)2SO4 and 0.5 g yeast extract. Prior to cultivation, the methanol wastewater was diluted to the desired methanol concentration, after which the initial pH of methanol wastewater medium was adjusted to the determined value. Batch anaerobic fermentations were conducted in a 5-L stirred tank reactor (14 cm ID  45 cm height) at 30 °C for 8 d with agitation at 120 rpm. Samples were drawn and monitored for flocculation properties. After 144 h of fermentation, the pH of the culture broth was adjusted to 12 and the culture broth was stirred for 30 min to extract the bioflocculant from the cells. After the alkali extraction, viscous culture broth was centrifuged at 8000g for 30 min. Two volumes of cold ethanol were added to the supernatant and left overnight at 4 °C. The precipitate was collected by centrifugation at 14,000g for 10 min and dissolved in ultrapure water. Cetyltrimethyl ammonium bromide (2%) was added to the solution with stirring. The mixture was set aside for 6 h at room temperature. Then two volumes of ethanol were added to recover the precipitate, which was lyophilized for further experiments (Tang et al., 2014). 2.3. Statistical analyses Statistical analyses were conducted using Design Expert Version 8.0. In this design, the central composite design and response surface methodology were applied to optimize the three most important operating variables: methanol concentration, inoculum size and initial pH. Experiments were initiated as a preliminary study for determining a narrower range of methanol concentration, inoculum size and initial pH prior to designing the experimental runs. Accordingly, methanol concentration from 25 mg L1 were tried and the increments continued until appreciable reductions were observed in the process responses. Likewise, the wide pH range of 4–10 and inoculum size range of 4.5–20% were examined to search for a narrower and more effective range. As a result the study ranges were chosen as methanol concentration 50–150 mg L1, inoculum size 6.5–10.5% and pH 6–8 for bioflocculant production (Table 1). Each of these three significant variables was assessed at five different levels (1.682, 1, 0, +1, +1.682). The average yield which obtained in these experiments was used as the response variable (Y) and all the experiments were conducted in triplicate. The second-order model for the three quantitative factors can be described as follows:

Y ¼ b0 þ Rbi X i þ Rbii X 2i þ Rbij X i X j ; . . . i;

j ¼ 1; 2; 3; . . . ; k

ð1Þ

where Y is the predicted response, b0 is the offset term, bi is the linear effect, bii is the quadratic effect and bij is the interaction effect, Xi and Xj are input variables which influence the response variable Y. 2.4. Characteristics of the bioflocculant The purified bioflocculant was analyzed using a Fourier transform infrared (FTIR) spectrophotometer (Made in Germany Model EQUINOX55). The spectrum of the sample was recorded on the spectrophotometer over a wave length range of 400–4000 cm1 under ambient conditions. The polysaccharide concentration of the purified biopolymer was determined by the phenol–sulfuric method (Aljuboori et al., 2015). The protein concentration of the purified bioflocculant was determined by the Coomassie brilliant blue G-250 dye binding method using bovine serum albumin as the protein standard (Ugbenyen et al., 2014). Neutral sugar, amino sugar, and uronic acid content were determined using the standard methods (Ghosh et al., 2009). The monosaccharide composition of the purified biopolymer was analyzed after hydrolysis with 3 M TFA at 100 °C for 4 h using

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zebrafish in each group were conducted using GraphPad Prism5.0 (Lawrence, 2007).

Table 1 Independent variables for the MBF83 production. Factors

Coded levels

Methanol concentration (mg L1) Initial pH Inoculum size (%)

1.682

1.000

0

1.000

1.682

16.9 5.3 4.1

50 6.0 6.5

100 7.0 8.5

150 8.0 10.5

184.1 8.7 11.9

cellulose TLC with ethyl acetate, pyridine, acetic acid, and water (5:5:1:3, v/v) as a solvent. Monosaccharide was detected by spraying with aniline phthalic acid reagent and heating at 110 °C for 300 s (Peng et al., 2014). Gel filtration chromatography (Sepharose gel column, Pharmacia) was conducted in a glass column (900  10 mm) to determine the molecular weight of the bioflocculant. A sample solution (20 lL) was injected, and the column was eluted with 0.05 M NaCl solution at a flow activity of 0.7 mL min1. Characterization of the chromatographic system was achieved using a mixture containing protein urease (480 kDa), ovalbumin (45 kDa), cytochrome C (12.3 kDa), and blue dextran (2000 kDa). 2.5. Jar testing for arsenic removal A standard Jar Tester was used for the flocculation tests in arsenite solution. Sodium arsenite stock solution (NaAsO2, 1.0 ppm) was prepared by dissolving 0.174 g of NaAsO2 in 100 mL of ultrapure water. MBF83 (prepared as a solution of 1.0 g L1 using the fermentation broth) were added into 1.0 L of arsenite solution at room temperature (20 ± 1 °C). The jar testing procedure involved a 2-min rapid mixing stage at 200 rpm followed by a slow stir phase at 40 rpm for 30 min to promote the collision of particles and hence floc growth, which resulted in a 60-min settlement period. Sodium hydroxide and sulfuric acid were employed to adjust the pH of the solutions to the predetermined level before the jar test and keep the pH constant during the flocculation process. ALL experiments were performed in triplicate. After each test, the supernatant was separated by filtration with a 0.22-lm pore size membrane filter, and arsenic in the solution was analyzed by inductively coupled plasmaatomic emission spectroscopy (ICP-AES). The removal efficiency (%) was obtained using the following equation:

Removal efficiency ð%Þ ¼

Ci  Ce  100 Ci

ð2Þ

where Ci and Ce (mg L1) are the initial and equilibrium concentrations of the arsenite, respectively. 2.6. Zebrafish-farming and determination of lifespan and embryos Male and female adult zebrafish (Danio rerio) of AB wild type were purchased from the Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, China. Fish were kept at a maximum density of 100 individuals in a glass recirculation aquarium (length 80 cm; height 50 cm, width 46 cm) on a 14-h light:10-h dark cycle. Water and air were temperature controlled (25 ± 0.5 °C and 23 °C, respectively). The fish were fed twice daily with Artemia salina, after which their lifespans were determined according to a previously described method (Desai et al., 2015). Zebrafish were allowed to lay eggs at 25 °C, and all embryos were observed daily for 72 h and counted with a Zeiss Axiovert 25 microscope (Carl Zeiss, Inc). The numbers of embryos (±standard deviation) were calculated from 10 pairs of zebrafish during 72 h of exposition. Statistical analyses (t tests) of the lifespan and the embryos for

3. Results and discussion 3.1. Isolation and identification of bioflocculant-producing strain ZCY83 Five anaerobic bacteria were isolated from methanol wastewater sludge for bioflocculant production. Strain ZCY83, which demonstrated the highest flocculating efficiency of 95.7% in 4 g L1 kaolin suspensions, was selected for further studies. This strain was nonspore-forming, irregular rod-shaped, facultatively anaerobic, and Gram-positive. Nitrate reduction, citrate utilization, and hydrolysis of starch were observed, while H2S and indole were not produced. Glucose, maltose, ribose, 5-ketogluconate, and sucrose were used, but mannitol growth was not observed. The 16S rDNA of strain ZCY83 was sequenced and deposited in the GenBank database under the accession number KR422351. According to its biochemical, morphological, and physiological properties, and 16S rDNA BLAST result, the isolated strain ZCY83 was identified as a bacterium of Turicibacter sanguinis. The bioflocculant produced by this bacterium was named MBF83.

3.2. Optimization of culture conditions for fermentation 3.2.1. Effect of methanol concentrations on MBF83 yield As methanol was used as the carbon source in the production medium, its concentration would affect MBF83 production. Therefore, the effects of methanol concentrations on MBF83 yield were investigated (Fig. 1A). When the concentration of methanol in the production medium was 100 mg L1, the flocculating activity of MBF83 reached a peak. The production medium with lower levels of methanol wastewater could not meet the nutrient demands of the microorganism, whereas those with higher levels of methanol may have inhibited microbial growth. Hence, the concentration of methanol used for all subsequent cultures was 100 mg L1.

3.2.2. Effect of the inoculum size on MBF83 yield Inoculum size is known to play a key role in the production of MBF83. As shown in Fig. 1B, MBF83 yield was obviously affected by inoculum size. The initial MBF83 yield increased with increasing inoculum size, with the maximum MBF83 yield being obtained at an inoculum size of 8.5%. However, any further increases in inoculum size progressively decreased MBF83 yield. Similar results were observed in the production of bioflocculant in Klebsiella mobilis KLE-1 (Wang et al., 2007). Thus, an inoculum size of 8.5% was selected as the initial inoculum size in the following experiments.

3.2.3. Effect of pH on MBF83 yield during fermentation The initial pH of culture medium could determine the electrification state of microbial cells, oxidation–reduction potential, microbial nutriment assimilation, and enzyme reaction (Nie et al., 2011; Patil et al., 2011); therefore, the production of the MBF83 at pH 4.0–10.0 in the methanol wastewater was investigated (Fig. 1C). The results demonstrated that the initial pH of the culture medium influenced the MBF83 production. The highest MBF83 yield of 4.61 g L1 was achieved when the pH for the MBF83 production was 7.0, which is in accordance with the results of previous studies (Tang et al., 2014; Zhong et al., 2014). As a result, an initial pH of 7.0 was used for all subsequent cultures.

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277

Fig. 1. Effect of methanol concentrations, inoculum size, pH of the wastewater on MBF83 yield. Data are means of three replicates and error bars show standard deviations.

3.3. Production of MBF83 Since methanol concentration, inoculum size, and initial pH had obviously influenced the MBF83 yield. It was desirable to investigate the interaction between the three most significant factors for maximum MBF83 yield. The results from the optimization experiments were analyzed by standard ANOVA and the central composite design was represented with the polynomial equations:

Y MBF83 production ¼ 4:48 þ 0:18  A  0:012  B  0:039  C þ 0:08  A  B þ 0:06  A  C þ 0:034  B  C  0:43  A2  0:26  B2  0:18  C 2

ð3Þ

where A, B and C are the methanol concentration, inoculum size, and initial pH (all for coded factors), respectively. As the p value for the model was 0.008 (<0.05), the statistical relation between the response and selected factors at 95% confidence level shows that the regression analysis is statistically significant. The value of the determination coefficient R2 = 94.14% indicates that the model cannot explain only 5.86% of the total variations, thus the model fits quite well. In this study, the validation of RSM model was performed at optimal conditions. Experiments were performed in triplicates under optimum conditions (inoculum size 8.6%, pH 7.5, methanol 100.8 mg L1). Under these optimized conditions, the actual production of 4.61 g L1 was obtained, which was in close agreement with predicted maximum values (4.56 g L1). The results denote the efficiency of RSM with proper design to provide significant information about combinations of the three independent variables which can be applied to enhance the MBF83 productivity in T. sanguinis KR422351. 3.4. Time course and economic assay of MBF83 production The growth curve of the strain was obtained in methanol wastewater medium (ethanol, acetate, propionate and methanol of 29.4, 16.7, 9.1, and 100.8 mg L1, respectively) at 30 °C. Fig. 2

Fig. 2. Change of flocculation activity, and biomass during the fermentation process. Data are means of three replicates and error bars show standard deviations.

depicts the exponential growth of MBF83 production during the first 3 d. At the initial point of fermentation, no cell growth was observed within the first 24 h of cultivation (lag phase). However, a steady increase in cell growth accompanied by a corresponding increase in flocculating activity was observed after this period. The stationary growth phase was attained after 120 h of cultivation. Moreover, the flocculating activity ran parallel to cell growth, indicating a concomitant increase in MBF83 production with cell growth. The flocculating activity of the MBF83 peaked at 93.1% during the late stationary phase of 144 h, after which both flocculating activity and cell growth decreased. In the recession phase, the production of MBF83 started to decrease, suggesting the excreted bioflocculants could be consumed by the microbes as a substitute for food (Li et al., 2009). At the end of the fermentation test, the concentrations of ethanol, acetate, propionate and methanol were 1.2, 1.3, 2.4, and 0.9 mg L1, respectively. As a result, the strain consumed more than 99.1% of the methanol, ethanol (95.9%), acetate (92.2%), and part of the propionate (73.6%) to produce MBF83.

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The cultivation of bioflocculant-producing microorganisms using methanol wastewater had both environmental and economic benefits. The COD concentration of methanol wastewater after cultivation was 57.3 mg L1 with a removal activity of 81.11%. Following treatment by the anaerobic method, the water could be used to irrigate plant field without any other treatment. Additionally, the MBF83 production cost decreased significantly when the microorganism was cultivated in methanol wastewater, but the flocculating efficiency did not decrease (Table 2). Thus, this procedure can reduce the cost of bioflocculant production. 3.5. Characterization of purified MBF83 3.5.1. Chemical composition analysis of MBF83 MBF83 was found to be a proteoglycan comprised of 74.1% (w/ w) carbohydrate and 24.2% (w/w) protein. Further analysis of the hydrolyzed MBF83 revealed that the mass proportion of neutral sugar, amino sugar, and uronic acid was 3:4:3. MBF83 had an appropriate content of uronic acid, which can provide a certain amount of carboxyl. The carboxyl groups presented on the molecular chain provide more effective sites for particles attachment; thus, many particles can be adsorbed to the long molecular chain (Fujita et al., 2000; Cosa et al., 2012). Elemental analysis of the purified MBF83 revealed that the mass proportion of C, H, O, N, and S was 38.75:6.81:33.92:8.16:0.94 (w/w), respectively. The molecular weight of the biopolymer determined by size exclusion chromatography was found to be approximately 1.9  106 Da. Glycoproteins (Bala Subramanian et al., 2010), polysaccharides (Tang et al., 2014; Zhong et al., 2014) and proteoglycan (Aljuboori et al., 2013), have been found to be the key constituents of bioflocculants. For instance, Enterobacter gergoviae (Tang et al., 2014), Aspergillus flavus (Aljuboori et al., 2015), and Klebsiella pneumoniae (Zhao et al., 2013) produced polysaccharides based bioflocculant, while Bacillus mojavensis (Elkady et al., 2011) and Pseudomonas sp. CYGS1 (Zhang et al., 2007) produced protein based bioflocculant. Proteoglycan bioflocculants composed of glucose, fucose, mannose, galacturonic acid, and cysteine are the key constituents in this study. 3.5.2. MBF83 functional groups analysis The FTIR spectrum of purified MBF83 exhibited many peaks from 3490 to 450 cm1. The intense absorption peaks at 3490 cm1 and 2950 cm1could be attributed to the vibration of hydroxyl groups and amino groups in the sugar ring of polysaccharides. The spectrum also displayed an asymmetrical stretching band at 1647 cm1 and a weak absorbance near 1400 cm1, which were consistent with the presence of the carboxylate ion, indicating the presence of uronate in this polysaccharide (Zaki et al., 2013). The band at 1046 cm1 corresponding to the CO single bond and CN single bond stretching vibration suggested the presence of an OH group and CN bond in the MBF83. The strong absorption peaks presented in the region of 1100–1250 cm1 were characteristic of carbohydrates and could be attributed to coupled CO and CC stretching and COH bending vibrations in polysaccharides (Zhao et al., 2013). The weak band at 1009 cm1 was also the characteristic absorption peak of other sugar derivatives, while 622 and 478 cm1 showed the presence of disulfides and aryl disulfide (S–S) stretch respectively.

3.6. Factors impacting removal efficiency of arsenite A number of interfering molecules, such as mercaptoethanol, carbamide, glycine, and ethanol, exist in the wastewater. To investigate the effect of the above interfering molecules on arsenite removal, arsenite solutions were spiked with interfering molecules (0.05 M) and the removal of arsenite was determined. The experimental conditions for arsenite concentration were kept constant at 1.0 mg L1. As illustrated in Fig. 3A, MBF83 flocculation efficiency was not significantly impacted by carbamide, glycine and ethanol, but dramatically influenced by mercaptoethanol. The significant reduction in arsenite removal efficiency in the presence of mercaptoethanol was due to the competition of the interfering molecule with MBF83 for arsenite adsorption sites. Therefore, arsenite has a strong affinity toward mercaptan (thiol) groups existing in biomolecules, such as amino acids, peptides and proteins including some enzymes, which leads to severe toxicity to humans (Altun et al., 2014). For both MBF83 and PAM, the removal efficiency of arsenite increased gradually with increasing flocculants dose due to the increase in available sites (Fig. 3B). It revealed that the removal efficiencies of arsenite by MBF83 were 12.4–35.7% higher than those of arsenite by PAM at pH 7.0 over the flocculants dosage range examined in this study. Therefore, compared to PAM, much less MBF83 was necessary to achieve a certain concentration of arsenite in purified water. As shown in Fig. 3B, the maximum arsenite removal efficiency reached 86.1% at the optimal MBF83 dosage of 500 mg L1. Exceeding the optimal dose of MBF83 resulted in decreased removal efficiency. It may be due to the formation of agglomeration of the MBF83 at higher dosages. These results indicate that MBF83 is more effective for arsenite removal due to high flocculation capacity. Hence, 500 mg L1 was taken as optimum dose or the saturation limit of the biomaterial. pH was a key factor influencing the flocculation of arsenite based on both the chemical speciation of arsenite and surface charge of MBF83. It can also strongly modify the redox potential of arsenite and MBF83, as well as induce dissolution of MBF83 (Daus et al., 2004). As a result, the arsenite removal was strongly pH dependent in most natural waters. As shown in Fig. 3C, the influence of pH on arsenite removal was investigated by adding the optimal dose of flocculants into arsenic solution (1.0 mg L1 arsenite). The removal efficiency by PAM was lowest at pH 2.0, then increased with increasing pH to nearly 7.0, at which point a maximum uptake of 50% was achieved for arsenite. However, when pH further increased to 10.0, the removal efficiency of arsenite decreased to 24.5%. Compared to PAM, MBF83 exhibited much better performance on arsenite removal over the pH range of 4.0–9.0. The removal efficiencies by MBF83 at pH 4.0–9.0 were greater than those by PAM by 25.9–40.3%. These results demonstrated that MBF83 had higher removal efficiency for arsenite under neutral pH, which is consistent with the results of a previously conducted study (Al Rmalli et al., 2005). Furthermore, MBF83 exhibited much better removal capacity for arsenite than some other flocculants that have been reported to date (Da Sacco and Masotti, 2010; Luo et al., 2010). The influence of contact time on arsenite removal was determined at the optimum dosages, as illustrated in Fig. 3D. The arsenite removal efficiency increased obviously during the initial

Table 2 Comparison of the strain ZCY83 cultivated in conventional medium and methanol wastewater medium. Culture medium

Bioflocculant yield (g L1)

Cost (RMB/g bioflocculant)

Optimal dosage (mg L1)

Flocculating activity (%)

Conventional medium Methanol wastewater medium

14.53 8.99

0.874 0.005

8 10

95.7 93.1

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279

Fig. 3. Effects of organic molecules (A), dosage (B), initial pH (C) and reaction time (D) on removal efficiency of arsenite. Data are means of three replicates and error bars show standard deviations.

flocculation stage, then continued to increase at a relatively slow speed with contact time until flocculation equilibrium was reached. Interesting, the equilibrium time was 90 min for MBF83 and 30 min for PAM; thus, 1.5 h was selected as the optimum contact time for arsenite flocculation from the aqueous solution by MBF83. This is similar to the contact time reported for earlier studies investigating the flocculation of metal ions on various biomasses (Dax et al., 2014). In conclusion, the optimal flocculation conditions were pH 7.0, MBF83 at 500 mg L1 and a reaction time of 1.5 h. Under these conditions, the highest removal of arsenite of 86.1% was reached, It has been reported that the removal efficiency of arsenite using conventional water treatment processes was 70% (Lim et al., 2014). Overall, these findings indicate that MBF83 has the potential for the removal of arsenite from aqueous solution. Fig. 4. Stability and storage of MBF83 at 25 °C.

3.7. Stability of MBF83 The stability of MBF83 was tested both in the form of a supernatant and as a powder. As shown in Fig. 4, the stability of MBF83 stored as a supernatant decreased significantly after 30 d and decreased to 11.6% after 60 d. In contrast, the flocculating activity of the powder form decreased slightly by 10.9% and was above 75% after 60 d. MBF83 as a powder showed much better stability than that as a supernatant. 3.8. Bioassessment with Danio rerio In addition to the flocculation performance, a toxicity test was conducted to investigate, from a biological point of view, the effectiveness of the proposed process in reducing the overall toxic

potential in a synthetic wastewater. To this end we employed zebrafish (Danio rerio) as the test organism according to a previously described standard method (Desai et al., 2015) to comprehensively evaluate the efficacy of MBF83 at diminishing the overall toxic potential in arsenite-containing solution. In control experiments, fish were monitored by breeding in aeration culture water containing 1 g L1 MBF83. When zebrafish lived in the untreated arsenitecontaining solution, a conspicuous decrease in survival was observed, with about 15% of the individuals remaining alive after 48 h. A noticeable increase in the survival rate was achieved when the zebrafish lived in the purified solution. Fig. 5 also shows that approximately 60% of population in the treated arsenitecontaining solution was alive after 72 h.

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Fig. 5. Mean survivors of zebrafish breeded in the arsenite-containing solution (0.5 mg L1 arsenite) at 25 °C.

The capacity to reproduce and the aberration rate can be used to evaluate genotoxicity. Their size, husbandry, and early morphology make zebrafish a highly suitable toxicological model. Untreated arsenite-containing solution diminished the capacity of the zebrafish to reproduce; with each individual being able to only produce less than 20% of the embryos (50 ± 15) relative to the control population (262 ± 16). After the flocculation treatment, the zebrafish exposed to the treated arsenite-containing solution were able to produce embryos (240 ± 12), with an aberration rate (2.9%) very similar to that of the unexposed control embryos (2.2%), indicating a drastic reduction in genotoxicity in response to the bioflocculation process. Moreover, the reproductive capacity of the survival was highly similar to that of unexposed zebrafish, confirming that the removal of arsenite was very effective. These findings demonstrated that the main risk associated with arsenite had been substantially eliminated. 4. Conclusions This research revealed the potential for use of methanol wastewater for the production of MBF83. The optimized production conditions were an inoculum size of 8.6%, initial pH of 7.5, and a methanol concentration of 100.8 mg L1. A maximum yield of 4.61 g L1 MBF83 was achieved in the optimized medium. FTIR spectra demonstrated that amino and hydroxyl groups were present in the MBF83 molecules. In addition, the maximum removal efficiency of arsenite was 86.1%. Based on these findings, MBF83 has the potential for application to arsenite removal from aqueous solution. Acknowledgement The study was supported by Educational Commission of Hubei Province of China (No. Q20141602). References Al Rmalli, S.W., Harrington, C.F., Ayub, M., Haris, P.I., 2005. A biomaterial based approach for arsenic removal from water. J. Environ. Monit. 7, 279–282. Aljuboori, A.H., Idris, A., Abdullah, N., Mohamad, R., 2013. Production and characterization of a bioflocculant produced by Aspergillus flavus. Bioresour. Technol. 127, 489–493. Aljuboori, A.H., Idris, A., Al-Joubory, H.H., Uemura, Y., Ibn Abubakar, B.S., 2015. Flocculation behavior and mechanism of bioflocculant produced by Aspergillus flavus. J. Environ. Manage. 150, 466–471. Altun, M., Sahinkaya, E., Durukan, I., Bektas, S., Komnitsas, K., 2014. Arsenic removal in a sulfidogenic fixed-bed column bioreactor. J. Hazard Mater. 269, 31–37. Amrose, S., Gadgil, A., Srinivasan, V., Kowolik, K., Muller, M., Huang, J., Kostecki, R., 2013. Arsenic removal from groundwater using iron electrocoagulation: effect

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