Anaerobic treatment of glutamate-rich wastewater in a continuous UASB reactor: Effect of hydraulic retention time and methanogenic degradation pathway

Journal Pre-proof Anaerobic treatment of glutamate-rich wastewater in a continuous UASB reactor: Effect of hydraulic retention time and methanogenic degradation pathway Hong Chen, Yanxiao Wei, Chenglei Xie, Hong Wang, Sheng Chang, Ying Xiong, Chunyan Du, Benyi Xiao, Guanlong Yu PII:

S0045-6535(19)32912-1

DOI:

https://doi.org/10.1016/j.chemosphere.2019.125672

Reference:

CHEM 125672

To appear in:

ECSN

Received Date: 25 September 2019 Revised Date:

27 November 2019

Accepted Date: 14 December 2019

Please cite this article as: Chen, H., Wei, Y., Xie, C., Wang, H., Chang, S., Xiong, Y., Du, C., Xiao, B., Yu, G., Anaerobic treatment of glutamate-rich wastewater in a continuous UASB reactor: Effect of hydraulic retention time and methanogenic degradation pathway, Chemosphere (2020), doi: https:// doi.org/10.1016/j.chemosphere.2019.125672. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier Ltd.

Anaerobic treatment of glutamate-rich wastewater in a continuous UASB reactor: Effect of hydraulic retention time and methanogenic degradation pathway

Hong Chen a,b,c, Yanxiao Wei a, Chenglei Xie c, Hong Wang a, Sheng Chang d, Ying Xiong a, Chunyan Du a, Benyi Xiao b,*, Guanlong Yu a

a.

Key Laboratory of Dongting Lake Aquatic Eco-Environmental Control and

Restoration of Hunan Province, School of Hydraulic Engineering, Changsha University of Science & Technology, Changsha 410004, China; b

Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences,

Beijing 100085, China c

Department of Civil and Environmental Engineering, Graduate School of

Engineering, Tohoku University, Sendai 980-8579, Japan d

School of Engineering, University of Guelph, Guelph N1G 2W1, Ontario, Canada

* Corresponding author. E-mail: [email protected]

Euryarchaeota

Archaea

(S)-Glutamate acid

Methanosaeta

Clostridium pascui

Methanobacterium

(s)-Citramalate Acidaminococcus

others

sp.

Firmicutes Clostridium Anaeromusa Syntrophomonas Acetoanaerobium Acidaminococcus

Bacteria

UASB reactor

Syntrophobacter Klebsiella

Syntrophobacter sp.

Butyrate

Lentimicrobium DQ677001_g

Proteobacteria

Propionate

Pyruvate

Bacteroidetes

Firmicutes Synergistetes Proteobacteria Bacteroidetes Saccharibacteria TM7 others

Glutamate feeding

Anaeroarcus burkinensis

Methanosarcina

Syntrophomonas sp.

Synergistetes

Acetate

Acetoanaerobium sp.

AF280863_g

Saccharibacteria_TM7 Saccharimonas others

80 70 60 50 40 30 20 10 0

Methanosaeta concilii

CH4

H2/CO2

Methanobacterium beijingense Methanobacterium subterraneum Methanobacterium formicicum

Percentage (%)

Microbial Communities (Phase Ⅶ)

Proposed methanogenic degradation pathways

1

Anaerobic treatment of glutamate-rich wastewater in a continuous UASB reactor:

2

Effect of hydraulic retention time and methanogenic degradation pathway

3 4

Abstract

5

To investigate the anaerobic treatment efficiency and degradation pathways of

6

glutamate-rich wastewater under various hydraulic retention times (HRTs), a lab-scale

7

upflow anaerobic sludge blanket (UASB) reactor was operated continuously for 180

8

days. Results showed that high chemical oxygen demand (COD) removal efficiencies

9

of 95.5%–96.5% were achieved at HRTs of 4.5 h to 6 h with a maximum methane

10

yield of 0.31 L-CH4/g-COD. When the HRT was shortened to less than 3 h, the

11

removal performance of the reactor declined. There also was an excessive

12

accumulation of volatile fatty acids, which implies that an appropriately small HRT is

13

applicable to the UASB reactor treating glutamate-rich wastewater. Methanogenic

14

degradation of glutamate in the UASB reactor depended on the HRT applied, and the

15

typical methane-producing capability of the sludge at an HRT of 3 h, in descending

16

order, was acetate > glutamate > butyrate > H2/CO2 > valerate > propionate.

17

Clostridium and Methanosaeta were predominant in the glutamate-degrading sludge.

18

At least three degradation pathways most likely existed in the UASB reactor, and the

19

pathway via 3-methlaspartate by Clostridium pascui was expected to be dominant.

20 21

Keywords: 3-methylaspartate pathway; Biodegradation; Glutamate fermentation;

22

Methanogenesis; Upflow anaerobic sludge blanket

1

23

1. Introduction

24

Since it was first commercially produced as a flavor-enhancing additive in Japan in 1909,

25

monosodium glutamate (MSG) has been widely used in the food industry (Ault, 2004).

26

As the largest MSG producing country worldwide, China produces 2.2 million tons of

27

MSG per year, accounting for approximately 80% of the total global production (Dong et

28

al., 2018). Meanwhile, a large amount of wastewater is produced during MSG production,

29

with high concentrations of chemical oxygen demand (COD) (10,000–40,000 mg/L),

30

NH4+-N (15,000–25,000 mg/L), and sulfate (15,000–30,000 mg/L), and a very low pH

31

(approximately 2.0) (Xue et al., 2008). Sulfate reduction by sulfate reducing bacteria that

32

competes with methane producing archaea occur with the exist of sulfate, which

33

influences on the bioenergy recovery efficiency and even the overall performance by the

34

produced hydrogen sulfide (Lu et al., 2016). To avoid serious environmental pollution by

35

MSG wastewater, the development of cost-effective and environmental-friendly treatment

36

technologies has attracted researchers’ interest (Jiang et al., 2015; Singh et al., 2009;

37

Tseng & Lin, 1990; Yao et al., 2010). Of these studies, anaerobic treatment is considered

38

among the most promising technologies, given its superiority in energy recovery, less

39

secondary pollution, and its wide application (Fang & Zhang, 2015; Feng et al., 2018;

40

Han et al., 2017).

41 42

Since it was developed in the 1970s, upflow anaerobic sludge blanket (UASB) reactors

43

have been widely utilized for the treatment of various types of wastewater, particularly

44

high strength food processing and beverage wastewater (Li et al., 2015; Chen et al.,

45

2019a; Olivares et al., 2016). Several studies have investigated the feasibility of using a

46

UASB reactor for the treatment of MSG wastewater; these studies examined the startup

2

47

performance of the reactor, as well as its biological degradation activity and kinetic

48

parameters (Cao et al., 1992). Tseng & Lin (1990) obtained a maximal COD removal

49

efficiency of 65% for treating the MSG wastewater using an anaerobic biological

50

fluidized bed reactor. Nevertheless, in these studies, the washout of granules was

51

observed, and the obtained kinetic constants could not be used to describe the UASB

52

process (Cao et al., 1992; Tseng & Lin, 1990). In practice, hydraulic retention time (HRT)

53

is one of the most important design and operational parameters of UASB reactors (Chen

54

et al., 2018a; Kim et al., 2014). To scale down wastewater treatment projects, a relatively

55

small HRT is commonly proposed, which corresponds with a high upflow velocity for the

56

UASB reactor. However, few studies have investigated the effect of HRT for the

57

long-term anaerobic treatment of MSG wastewater in UASB reactors. It remains

58

necessary to evaluate the effect of HRT on MSG wastewater treatment in a UASB reactor

59

for continuous long-term operation.

60 61

On the other hand, to better understand the inherent removal mechanisms of anaerobic

62

wastewater treatment, many studies have focused on changes in the microbial community

63

as well as pollutant degradation pathways under anaerobic conditions (Chen et al., 2019b;

64

Lu et al., 2017; Sudmalis et al., 2018; Tian et al., 2015). Investigations on microbial

65

responses and metabolic pathways can reveal the process mechanism of the bioreactor

66

system such as changes in the microbial community structure in long-term competition

67

(Wu et al., 2018) and recovery mechanisms of biogas production under ammonia

68

inhibitions (Chen et al., 2018b). Generally, anaerobic degradation of amino-containing

69

pollutants occurs via Stickland fermentation (Batstone et al., 2003; Fang & Zhang, 2015).

70

For glutamate fermentation, at least five different pathways have been verified thus far,

3

71

including two coenzyme B12-dependent 3-methylaspartate pathways, a

72

2-hydroxyglutarate pathway, and pathways via 4-aminobutyrate – radical formation by

73

one-electron oxidation and via 5-aminovalerate – transient two-electron oxidation of

74

5-hydroxyvaleryl-CoA (Buckel, 2001; Buckel & Thauer, 2013). Bacterial orders,

75

including Clostridiales and Fusobacteriales, were identified in soil, sewage sludge, both

76

marine and freshwater sediments, and in the gastrointestinal tract of animals. Some

77

closely related anaerobic bacteria (Clostridium tetani, Clostridium tetanomorphum, and

78

Clostridium pascui) are involved in the fermentation of glutamate to acetate, butyrate,

79

carbon dioxide, and ammonia (Buckel, 2001), but those species have never been reported

80

in a UASB reactor for glutamate degradation. Hence, it is necessary to investigate

81

microbial community changes and degradation pathways to understand the process

82

mechanisms of MSG wastewater treatment by UASB reactors.

83 84

The aim of this study was to discover the effect of one of the key operational parameters,

85

HRT, on anaerobic treatment performance and removal mechanisms of glutamate-rich

86

wastewater. A UASB reactor operated continuously for 180 days under various HRTs

87

ranging from 24 h to 2 h. The changes in microbial community structures between startup

88

and later operational periods were characterized by 16S rDNA gene sequencing. within

89

addition to specific methanogenic activity (SMA) tests of granular sludge with different

90

substrates, methanogenic pathways for degrading glutamate in glutamate-rich wastewater

91

were also explored.

92 93

2. Materials and Methods

94

2.1 Experimental apparatus

4

95

A schematic diagram of the experimental set-up is illustrated in Fig. 1. A lab-scale UASB

96

was utilized and consisted of a substrate tank, peristaltic pump, water bath system, UASB

97

main body, gas buffer bottle, and wet gas flow meter. The UASB main body consisted of

98

a gas-liquid-solid separator and a cylindrical reaction zone, which was enclosed by a

99

plexiglass cylinder with an internal diameter of 100 mm, a reaction zone height of 800

100

mm, and an effective working volume of 6 L.

101

Fig. 1.

102 103

2.2 Inoculum and synthetic wastewater

104

The reactor was inoculated with 2 L of fresh sludge from the anaerobic unit of a

105

wastewater treatment plant in Changsha City, China, and 2 L of granular sludge from a

106

UASB reactor treating practical starch wastewater in Inner Mongolia, China. The

107

granular sludge had a mixed liquor suspended solids concentration of 80 g/L and a mixed

108

liquor volatile suspended solids concentration of 48 g/L (Supplementary data). Synthetic

109

wastewater was prepared by analytical (S)-glutamate and the following minerals: COD

110

2000 mg/L, K2HPO4 250 mg/L, KH2PO4 100 mg/L, KCl 300 mg/L, MgCl·6H2O 50 mg/L,

111

CoCl2·6H2O 0.4 mg/L, CaCl2 15 mg/L, FeCl2·4H2O 3.56 mg/L, (NH4)6Mo7O24·4H2O

112

0.65 mg/L, NiCl2·6H2O 0.81 mg/L, ZnC12 0.60 mg/L, and CuC12·2H2O 0.3 mg/L.

113 114

2.3 Experimental procedure

115

The operational conditions of the reactor are shown in Table 1. The UASB reactor

116

operated continuously for 180 days under various HRTs that were categorized into seven

117

phases (I–VII). These phases corresponded with the HRTs of 48 h, 24 h, 12 h, 6 h, 4.5 h,

118

3 h, and 2 h, respectively. The influent COD concentration was set at 2000 mg/L. Both

5

119

the operational temperature and the influent pH value remained constant throughout the

120

different HRT phases.

121 122

Table 1

123 124

2.4 Analytical methods

125

The total COD, NH4+-N, and alkalinity in the influent and the effluent and total

126

suspended solid (TSS), volatile suspended solid (VSS), and extracellular polymeric

127

substances (EPS) of anaerobic granules were determined according to references (Lu et

128

al., 2015; Xiao et al., 2018). The pH value was measured with a pH meter (PHSJ-3F,

129

Shanghai). The daily biogas production was measured with a laboratory biogas wet gas

130

flow meter (JH-LMF-1, Jinzhiye). Biogas composition and volatile fatty acids (VFAs)

131

were analyzed using gas chromatography with a flame ionization detector and a thermal

132

conductivity detector (GC9790II, Fuli). Proteins (PN) and polysaccharides (PS) in the

133

granules were measured with the Lowry method and the phenol/H2SO4 method,

134

respectively (Lu et al., 2015; Wu et al., 2018). The particle size of the granular sludge

135

was evaluated with a standardized sieve series, while the mean settling velocity was

136

evaluated with settling column tests (Lu et al., 2017). Both the morphology and the

137

microstructure of the granules were analyzed with scanning electron microscopy

138

(S-3000N, Hitachi).

139 140

2.5 Specific methanogenic activity tests

141

Granular sludge was taken from the UASB reactor for the specific methanogenic activity

142

(SMA) test; 120 mL serum bottles were also required and contained methanol, acetate,

6

143

propionate, n-butyrate, n-valerate, (S)-glutamate, and H2/CO2 as a substrate, respectively.

144

The SMA analysis involved filling each serum bottle with 10 mL of granular sludge and

145

50 mL of anaerobic sludge (inoculum), adding the various substrates, and adjusting the

146

pH values of each to 7. Each serum bottle was topped off with the trace element nutrient

147

solution to make a total solution volume of 80 mL, and then the serum bottles were sealed

148

with rubber stoppers and secured by aluminum crimps. The nutrient solution was boiled

149

for 2 h prior to use to remove any dissolved oxygen present and then cooled to room

150

temperature under a nitrogen atmosphere. The initial concentration for the serum bottles

151

was maintained at 2000 mg-COD/L. Oxygen in the headspace of the bottles was purged

152

with nitrogen gas for 5 min. However, the bottle containing the additional H2/CO2

153

substrate required H2/CO2 (80:20, v/v) gas to remove oxygen in the headspace, and an

154

ultimate gas pressure of 1.4 atm was maintained by injecting an additional 30 mL of

155

H2/CO2. Then, 0.25 mL of 2000 mg/L Na2S·9H2O solution was injected into each bottle

156

to maintain an absolute anaerobic condition. Finally, all serum bottles were placed in an

157

incubator (100±5 rpm, 35±1 °C). After waiting 5 min for the temperature of each bottle to

158

increase to the set value, the headspace was vented using a syringe to release the pressure

159

caused by the thermal expansion. Biogas production and composition were measured for

160

standard conditions at intervals of 2 h to 6 h. Each experiment was replicated to ensure

161

reliability.

162 163

2.6 Microbial community analyses

164

Biomass samples from the reactor were collected during phases I (Day 35) and VII (Day

165

180) to analyze the microbial communities by 16s rRNA high-throughput sequencing.

166

7

167

Microbial DNA was extracted from samples with an E.Z.N.A.® soil DNA Kit (Omega

168

Bio-tek, USA) according to the protocols of the manufacturer. The final DNA

169

concentration and purification were determined with a NanoDrop 2000 UV-vis

170

spectrophotometer (Thermo Scientific, USA). The quality of the DNA was checked using

171

1% agarose gel electrophoresis. The V3-V4 hypervariable regions of the bacterial and the

172

archaeal 16S rRNA gene were individually amplified with the primers (Supplementary

173

data) using a polymerase chain reaction (PCR) thermal cycler system (GeneAmp 9700,

174

ABI, USA). The PCR reactions were conducted in the following manner: 3 min of

175

denaturation at 95 °C, 27 cycles of 30 s at 95 °C, 30 s for annealing at 55 °C, 45 s for

176

elongation at 72 °C, and a final extension at 72 °C for 10 min. The PCR reactions were

177

performed in triplicate with a 20 µL mixture containing 4 µL of 5 × FastPfu Buffer, 2 µL

178

of 2.5 mM dNTPs, 0.8 µL of each primer (5 µM), 0.4 µL of FastPfu polymerase, and 10

179

ng of template DNA. The resulting PCR products were extracted from a 2% agarose gel,

180

further purified using the AxyPrep DNA Gel Extraction Kit (Axygen Biosciences, USA),

181

and quantified using the QuantiFluor™-ST (Promega, USA) according to the protocols of

182

the manufacturer.

183 184

Purified amplicons were pooled in equimolar and paired-end sequenced (2 × 300) on an

185

Illumina MiSeq platform (Illumina, San Diego, USA) according to standard protocols

186

(Majorbio, Shanghai, China). Raw fastq files were demultiplexed, quality-filtered by

187

Trimmomatic, and merged using FLASH with the following criteria: (i) the reads were

188

truncated at any site receiving an average quality score <20 over a 50 bp sliding window;

189

(ii) primers were exactly matched allowing for two nucleotide mismatches, and reads

190

containing ambiguous bases were removed; (iii) sequences with an overlap longer than

8

191

10 bp were merged according to their overlap sequence.

192 193

Operational taxonomic units (OTU) were clustered with a 97% similarity cutoff using

194

UPARSE (version 7.1, http://drive5.com/uparse/), and chimeric sequences were identified

195

and removed using UCHIME. After generating an OTU table with the phylogenetic

196

information of each OTU and its abundance in each sample, OTU analysis and the alpha

197

diversity calculation were both completed using the free online platform, Majorbio

198

I-Sanger Cloud Platform (www.i-sanger.com). Similarity searches for the obtained

199

sequences were performed via the EzBioCloud server (http://www.ezbiocloud.net) (Yoon

200

et al., 2017). Raw sequencing reads were deposited in the Sequence Read Archive at the

201

NCBI under accession number PRJNA566074.

202 203

2.7 Calculations

204

The methane and the biogas production, in terms of standard temperature and pressure

205

(STP), were used for the calculations of biogas production rate (BPR), methane yield, and

206

methane production rate (MPR).

207 208

A modified Gompertz equation was employed to estimate the maximum hydrogen

209

production rate in Eq. (1).

210

(1)

211

where P is the cumulative methane production, mL-CH4; Rmax is the maximum MPR,

212

mL-CH4/d; Pm is the methane production potential, mL-CH4; e = 2.71828; λ is lag-phase

213

time, d; and t is the time, d.

214 9

215

The maximum SMA was determined as maximum rate of methane production, expressed

216

as grams COD of methane per gram sludge VSS per day in Eq. (2).

217

(2)

218

where Sm is the maximum SMA, g-COD CH4/g VSS/d; C’o is the conversion coefficient

219

of the volume of methane containing saturated steam to COD mass, 394 mL-CH4/g-COD

220

CH4 (25 °C); VR is the volume of the reaction liquid in the SMA tests, mL; and VSS is the

221

sludge concentration, g VSS/L.

222 223

The total VFA (VFAs) was calculated based on the total molar concentration of all the

224

acids tested, and the total VFA mass concentration was calculated using the following

225

equation (Cheng et al., 2018):

226

(3)

227

Here, MAcetic acid is the molecular weight of acetic acid, and C is the molar concentration

228

of the acid, mmol/L.

229 230

3. Results and Discussion

231

3.1 Overall performance under different HRTs

232

The overall performance of the UASB reactor from phases I to VII, in terms of pH,

233

alkalinity, COD, NH4+-N, VFA, biogas production, and methane content, are presented in

234

Fig. 2.

235 236

Fig. 2

237 238

During the start-up stage (phase I), the operational conditions (including the pH, effluent 10

239

NH4+-N, and alkalinity) gradually stabilized after 35 days of operation. The COD

240

removal efficiency increased to greater than 90%, and the methane percentage of the total

241

biogas increased to 70% at the end of phase I. However, the concentrations of the VFAs

242

drastically decreased to less than 200 mg/L in the first 10 days and continued to decline,

243

which indicated that methanogens in the granular sludge gradually grew and actively

244

functioned to decompose the VFAs under the current operational condition. Therefore,

245

the UASB reactor performed satisfactorily during the start-up stage for treating the

246

synthetic MSG wastewater.

247 248

During phases II–VII, the HRT was reduced from 24 h to 2 h, while all the other

249

parameters remained unchanged. As shown in Fig. 2a, the effluent pH stabilized at

250

approximately 7.1 to 7.3, with a slight increase in NH4+-N acclimation during the

251

anaerobic digestion process using glutamate as the sole carbon and nitrogen source. Fig.

252

2b shows that the effluent NH4+-N concentration slowly increased over time, and during

253

phase VII it finally reached a maximum value of 195±15 mg/L, which was still below the

254

minimum inhibitory concentration of ammonia (Chen et al., 2018b). The effluent total

255

alkalinity stabilized at 1107.7–1455.8 mg-CaCO3/L until the HRT was reduced to 4.5 h,

256

while a marked increase in alkalinity was observed at an HRT of 3 h and eventually

257

reached 2055.3–2453.5 mg-CaCO3/L with a bicarbonate alkalinity of 956.8–1426.1 mg/L

258

at an HRT of 2 h (Fig. 2c). The elevated alkalinity in the effluent reflected the dynamic

259

equilibrium between consumption and re-generation of inorganic carbon (HCO3-) and

260

ammonium (NH4+), which was enough to maintain pH stability (Lu et al., 2015).

261 262

A stable COD removal efficiency of approximately 95% was obtained during phases II–V

11

263

(Fig. 2d) but decreased to approximately 78% during phase VI (HRT = 3 h) and

264

approximately 67% in phase VII. In comparison, more than 93% of COD of dimethyl

265

phthalate was removed (Kong et al., 2018, Jia et al., 2007); and the highest COD removal

266

was 76.6% in biodegradation of MSG wastewater, which was lower than the removal

267

efficiency (97.9%) in the previous study (Chen et al., 2020). Moreover, only a small

268

amount of VFAs emerged during phase V (below 200 mg/L) and a relatively greater

269

percentage during phase VI, but a massive amount of VFAs accumulated during phase

270

VII (400–1000 mg/L) (Fig. 2e). During phase V, the COD removal efficiency initially

271

decreased to 78.2%, then gradually increased and stabilized at 95.5%, which

272

corresponded to a decrease in the VFA concentration in the effluent from 179.3 mg/L to

273

52.1 mg/L. Generally, low VFA concentrations (less than 200 mg/L) have minor impact

274

on the performance of bioreactors (Fang & Zhang, 2015). However, the performance of

275

the reactor severely deteriorated during phase VII at an HRT of 2 h when excessive VFAs

276

accumulated (greater than 500 mg/L), thereby depressing the activity of the functional

277

bacteria in the reactor.

278 279

As shown in Fig. 2f, both the methane content and the BPR were substantially affected by

280

the changes in the HRTs. During the entire operational period, the BPR increased with a

281

decrease in the HRT, which was similar to the increase in the organic loading rate while

282

maintaining the unchanged influent COD concentration. However, the methane content in

283

the biogas stabilized at approximately 73% under HRTs from 48 h to 4.5 h, followed by a

284

small decrease at an HRT of 3 h and a drastic decrease to 57% at an HRT of 2 h. Methane

285

production in a UASB or an EGSB at a very short HRT was easily inhibited by the

286

accumulation of VFAs (Fig. 2e), ammonia, and other inhibitors or by other process

12

287

problems. For instance, a large amount of foam produced could block the gas-liquid-solid

288

separator, which could result in the escape of biogas from the outlet and subsequent

289

attenuation of the collection efficiency of the biogas (Lu et al., 2015; Rajagopal et al.,

290

2013).

291 292

From the overall performance of the UASB reactor, we concluded that an operational

293

HRT of less than 3 h is not suitable for treating synthetic MSG wastewater that is

294

equivalent to a maximum organic loading rate of 16 g-COD/L/d, which was similar to the

295

organic loading rates proposed by other researchers for a stable process (Li et al., 2015;

296

Lu et al., 2017).

297 298

3.2 Effect of HRT

299

The effect of different HRTs on the performance of the UASB, in terms of COD removal

300

efficiency, organic removal rate (ORR), NH4+-N and VFA production, methane yield, and

301

MPR, were evaluated when the UASB reactor reached a relatively steady performance

302

during each phase (Fig. 3). An increase in NH4+-N production corresponded with a

303

decrease in the HRT (Fig. 3a). Ammonium generated during the glutamate degradation

304

process formed NH4HCO3 with carbon dioxide, which helped to neutralize the acids and

305

maintain the pH within a stable range (Figs. 2a and 2c) (Fang & Zhang, 2015; Rajagopal

306

et al., 2013). Few VFAs emerged in the reactor during phases II–IV, but an excessive

307

amount of VFAs accumulated during phase VII (Fig. 3b). When the total VFAs reached

308

approximately 600 mg-HAc/L during phase VII, the methanogenesis was easily

309

overwhelmed, and then the glutamate fermentation process was greatly inhibited (Cheng

310

et al., 2018). Under a short operational HRT (< 3 h), the conversion of VFAs became a

13

311

rate-limiting step in the UASB reactor for MSG wastewater treatment.

312 313

Fig. 3

314 315

Throughout the entire operational period, with changing HRTs from 48 h to 2 h, the ORR

316

correspondingly increased from 1.0±0.1 g-COD/L/d to 16.6±2.1 g-COD/L/d (Fig. 3c).

317

The mean COD removal efficiency were 91.7±3.4%, 94.6±5.7%, 94.5±2.8%, 95.0±4.2%,

318

and 96.3±3.4% under the HRTs of 48, 24, 12, 6, and 4.5 h, respectively. However, the

319

mean COD removal efficiency decreased to 78.8% and 67.0% during phases VI and VII,

320

respectively. The HRT had a significant effect on the MPR (it increased from 0.25±0.06

321

L-CH4/L/d to 4.34±0.41 L-CH4/L/d) and the methane yield (first it increased from

322

0.26±0.09 L/g-COD to 0.31±0.02 L/g-COD and then decreased to 0.18±0.03 L/g-COD)

323

(Fig. 3d). The deteriorated methane production under low HRTs indicated that the

324

performance of the UASB system was greatly dependent upon the HRT applied during

325

the MSG wastewater treatment.

326 327

3.3 COD mass balance analyses

328

The COD mass balance was calculated for phases II–VII (Fig. 4), which accounted for

329

the COD flowing in and out of the system and the COD converted into methane, but it

330

neglected the COD that was converted into biomass (Lu et al., 2015). The distribution of

331

COD mass flows varied with HRT. The minimum percentage of COD mass flow through

332

the effluent was 7.5%±3.7% (phase III) with a corresponding mass flow percentage of

333

80.1%±4.6% through the methane production. The maximum percentage of COD mass

334

flow through methane production was 83.3%±3.2% (HRT = 6 h) and 82.7%±9.0% (HRT

14

335

= 4 h), which indicated that the best energy recovery from the MSG wastewater was

336

under these HRT conditions (Kim et al., 2014). However, during phases VI and VII (with

337

HRTs of 3 h and 2 h, respectively), the COD mass flow through the effluent increased to

338

24.5%±4.1% and 34.7%±4.0%, respectively. In terms of energy recovery here, the

339

maximum percentage of COD converted into methane was 83.3%±3.2%, which was

340

similar to that of 81.7% for the treatment of starch wastewater (Lu et al., 2015). From the

341

COD mass balance analysis, it was apparent that operating a UASB reactor at an HRT

342

less than 4.5 h is unfavorable for energy recovery from MSG wastewater.

343 344

Fig. 4

345 346

3.4 Characteristics of granular sludge

347

For a UASB applied to wastewater treatment, the formation of granular microbial

348

aggregates played a crucial role in maintaining a stable process performance (Lu et al.,

349

2017; Sudmalis et al., 2018; Tan et al., 2018). In this study, granular sludge was collected

350

from the UASB reactor during each phase to characterize its properties in terms of VSS,

351

VSS/TSS, particle size distribution, settling velocity, EPS content, PN/PS ratio, and

352

microstructure. The results are shown in Fig. 5 and Fig. S1 in Supplementary data. Under

353

various HRTs from 48 h to 2 h, the VSS of the granular sludge first increased from 34

354

g-VSS/L (phase I), to a maximum value of 46 g-VSS/L (phase V), and then decreased to

355

38 g-VSS/L (phase VII) (Fig. 5a). The VSS/TSS ratio also showed a stepwise increase

356

during the first operational days (phases I–VI) with a slight decrease at the end of the

357

operational period (phase VII). Both the particulate organic matter and the total

358

particulate solids in the UASB reactor were relatively high during phases III–VI, which

15

359

implied that the biomass concentration of the granular sludge in the UASB reactor was

360

very high during these days. The increase in VSS from phase I to phase IV indicated a

361

high bioactivity and reproductive capacity of biomass during these operational phases

362

(Liang et al., 2007).

363 364

Fig. 5

365 366

Both the particle size distribution and the settling velocity of the granular sludge varied

367

with different HRTs (Fig. 5b). The percentage of small particles (≤ 1 mm) increased from

368

63% (phase I) to 72% (phase II), then decreased to a minimum value of 46% (phase IV)

369

before it finally reached 78% (phase VII). The percentages of large particles (≥ 1 mm) at

370

various HRTs from 12 h to 4.5 h (phases III–V) were greater than during the start-up

371

stage (phase I). Fig. 5b shows the average settling velocities of the granular sludge during

372

phases II–V were also faster than during phase I. The superior properties in particle size

373

distribution and settling velocity with the granular sludge obtained during phases III–V

374

aligned with the stable overall performance of the UASB reactor (Fig. 2). Additionally, a

375

large percentage of small particles with very slow settling velocities occurred in the

376

reactor during phases VI–VII, which implied poor granulation or collapse of the granular

377

structure under those HRT conditions. The collapse of the granular structure in a UASB

378

reactor could result in deterioration of the effluent quality due to biomass washout and

379

poor dewatering of the sludge (Kim et al., 2014; Pol et al., 2004). Although a short HRT

380

could help promote granulation in UASB reactors (Lu et al., 2017; Sudmalis et al., 2018),

381

this study demonstrated that extremely short HRTs would be detrimental to the formation

382

of granules in the UASB reactor.

16

383 384

The EPS contents and PN and PS portions of the tightly bound EPS (TB-EPS) extracted

385

from the granular sludge under various HRTs are shown in Fig. 5c. The EPS content

386

increased from 120 mg/L (phase I) to the maximum value of 210 mg/g (phase III),

387

maintained at 205 mg/g (phase IV) and 195 mg/g (phase V), but decreased to 160 mg/g

388

(phase VII). The EPS can help to promote adhesion of microorganisms through chemical

389

bonds or physical entanglement, and granules with a higher TB-EPS content usually

390

possess better mechanical strength and physical stability (Basuvaraj et al., 2015; Pol et al.,

391

2004). In this regard, the granular sludge during phases III–V was superior to that

392

obtained during the other phases. The PN/PS ratio also varied with the HRTs. In phase I,

393

the PN/PS ratio of the extracted EPS was 1.5, which then reached a minimum value of

394

1.3 in phase IV and increased to a maximum value of 2.2 in phase VII. Both the PN

395

portion in the EPS content and the PN/PS ratio had peak values during phase IV. The

396

PN/PS of EPS could play a role in the formation and stabilization of granular sludge. Pol

397

et al. (2004) suggested a high proportion of PN favors sludge granulation because of its

398

high content of negatively charged amino acids, and Basuvaraj et al. (2015) reported the

399

PN/PS ratio should be approximately 1.4 for good settling granular sludge, which

400

supported the observation of the high average settling velocities of granular sludge during

401

phases III–V in this study. The highest PN/PS ratio (2.2) for phase VII, which

402

corresponded to the lowest average velocity and the greatest portion of small particles (≤

403

1 mm), was caused by the decrease in the PS portion of the EPS. As PN predominantly

404

localized in the core region of the granules (Lu et al., 2017; Pol et al., 2004), the PS were

405

easily loosened from the EPS under a high hydraulic upflow velocity (HRT = 2 h), which

406

had a negative effect on sludge granulation (Basuvaraj et al., 2015; Kim et al., 2014).

17

407

Thus, based on overall performance and granular properties, an HRT within the range of

408

12 h to 4.5 h is proposed for MSG wastewater treatment using a UASB reactor.

409 410

3.5 Microbial community analyses

411

3.5.1 Alpha diversity analysis of microbial communities

412

Based on the analysis by 16S rDNA gene sequencing for the sludge samples collected

413

from the UASB reactor during phases I and VII, the Chao1 and ACE estimators, as well

414

as the Simpson and Shannon indices, were calculated and are listed in Table 2 and the

415

Supplementary data. Both the Chao1 and ACE estimators for archaea and bacteria

416

showed a decrease in species richness (Feranchuk et al., 2018) after 141 days of operation.

417

From the decreased Shannon and Simpson indices of both the archaea and bacteria, it was

418

apparent that the diversity of species in the microbial communities in the UASB reactor

419

decreased over time. The results suggested that the operational HRT had a substantial

420

effect on the microbial diversity in the UASB reactor, which is similar to the previous

421

study (Chen et al., 2020).

422 423

Table 2

424 425

3.5.2 Changes in the archaeal community

426

The relative abundance of dominant archaeal populations in the granular sludge samples

427

collected during phases I and VII are shown in Fig. 6 and the Supplementary data. During

428

phase I, the largest genus group in the granular sludge that was also examined in the

429

previous study (Chen et al., 2020) was Methanobacterium, which accounted for a total

430

relative abundance of 59.8% and included the species Methanobacterium beijingense,

18

431

Methanobacterium subterraneum, and Methanobacterium formicicum; these are

432

considered hydrogenotrophic methanogens (Yashiro et al., 2011). The second largest

433

genus group was Methanosaeta, which accounted for a total relative abundance of 34.4%

434

and included Methanosaeta concilii and Methanosaeta harundinacea; these are

435

considered acetoclastic methanogens (Chen et al., 2018b; Fang & Zhang, 2015; Tian et

436

al., 2015). The Methanosarcina genus showed a relative abundance of 4.92% and

437

included Methanosarcina mazei, which is of great ecological importance as it is the only

438

known organism capable of fermenting acetate, methylamines, and methanol to CH4, CO2,

439

and NH3 (in the case of methylamines) (Chen et al., 2018b; Deppenmeier et al., 2002). In

440

contrast, Methanosaeta, which mainly contained the species Methanosaeta concilii,

441

showed a dominant abundance of 77.01% during phase VII. Meanwhile, the relative

442

abundance of Methanobacterium, which included Methanobacterium beijingense,

443

Methanobacterium formocicum, and Methanobacterium subterraneum, decreased to

444

21.87%. Moreover, the relative abundance of Methanosarcina (containing

445

Methanosarcina mazei and Methanosaeta harundinacea) decreased to 0.88%.

446 447

Fig. 6

448 449

Unlike the archaeal community during phase I (where both acetoclastic and

450

hydrogenotrophic methanogens were the primary microbial sequences), the acetoclastic

451

methanogen (Methanosaeta containing Methanosaeta concilii) was dominant and mainly

452

responsible for methane production. The greatly increased population of Methanosaeta

453

and the decrease in hydrogenotrophic methanogens reflected the changes in the

454

intermediate products (Chen et al., 2018b; Lu et al., 2017) during the glutamate

19

455

fermentation process, which supported the excessive accumulation of acetate during

456

phase VII (Fig. 3d). From the dynamic changes in the archaeal community in the UASB

457

reactor, it was apparent that the operational HRT greatly influenced the archaeal

458

community during the long operational period.

459 460

3.5.3 Changes in the bacterial community

461

The relative abundance of dominant bacterial populations in the granular sludge samples

462

collected from phases I and VII are shown in Fig. 6 and the Supplementary data. Eight

463

known bacteria phyla (Firmicutes, Actinobacteria, Synergistetes, Thermotogae,

464

Proteobacteria, Chloroflexi, and Nitrospirae) were identified in the granular sludge

465

sampled during phase I. The dominant genera were determined in ascending relative

466

abundance as follows: Pseudomonas (2.05%), Romboutsia (5.52%), Mesotoga (5.74%),

467

Aminivibrio (8.52%), Clostridium (10.23%), and Actinomyces (22.56%). In contrast, only

468

five known bacterial phyla (Fimicutes, Synergistetes, Proteobacteria, Bacteroidetes, and

469

Saccharibacteria TM7) were identified from the sludge samples collected during phase

470

VII. Within the Firmicutes phylum, Clostridium was the largest genus with a relative

471

abundance of 30.33%, and it included Clostridium pascui, which was found as a

472

glutamate-fermenting spore formerly isolated from the soil samples (Buckel, 2001; Chen

473

et al., 2018b; Wilde et al., 1997). The other genera were ranked in ascending relative

474

abundance (>1%) as follows: Acidaminococcus (1.06%), Klebsiella (1.22%),

475

Saccharimonas (1.24%), Acetoanaerobium (1.91%), Syntrophobacter sp. (4.77%),

476

Syntrophomonas (5.02%), Lentimicrobium (6.94%), and Anaeromusa (9.85%).

477 478

As the largest bacterial phylum in the sludge sample from phase I, Actinobacteria

20

479

disappeared during phase VII and were replaced by Firmicutes (relative abundance of

480

48.17%). The anaerobic environment in the UASB reactor was quite inferior for

481

Actinobacteria (Gupta et al., 2014). Under continuous feeding with glutamate,

482

Clostridium easily adapted to the selective pressure in the UASB reactor under an

483

operational HRT of 2 h, as well as Anaeromusa, which can utilize glutamate to ferment

484

acetate and propionate (Buckel & Thauer, 2013; Strompl et al., 1999). Several diversified

485

VFA degraders were also reserved in the reactor, including Syntrophobacter and

486

Syntrophomonas that degrades propionate or butyrate only in coculture with a H2-using

487

organism; for example, Syntrophobacter wolinii, Syntrophobacter pfennigii, and

488

Syntrophobacter fumaroxidans are involved in the degradation of propionate (Fang &

489

Zhang, 2015; Hatamoto et al., 2007). The substrate (glutamate) and its intermediates

490

(acetate, propionate, butyrate, and valerate) provided a strong selective pressure that

491

drove bacterial evolution in the UASB reactor (Figs. 3 and 6). Therefore, the results of

492

the bacterial community analysis agree well with the experimental data.

493 494

3.6 Biodegradation pathways of glutamate in the UASB reactor

495

To investigate the biodegradation pathways of glutamate (Liang et al., 2007; Lu et al.,

496

2017), SMA tests were conducted on samples taken during each operational phase (I–VI)

497

by feeding them methanol, acetate, propionate, butyrate, valerate, glutamate, and H2/CO2,

498

respectively. The corresponding Rmax and SMA values, which reflected the utilization

499

ability of biomass for a specific substrate, are shown in Table 3. Both Rmax and the SMA

500

changed with the operational phases. For the substrates used, both acetate and glutamate

501

caused obvious increases in the SMA values, whereas the methanol and H2/CO2 reflected

502

inflexible values. It is remarkable that a large amount of VFAs accumulated in phase VII,

21

503

which could attributed to the HRT decrease or the doubled organic loading rate. Under a

504

short HRT of 3 h (phase VI), the methane-producing capacity (Fang & Zhang, 2015; Kim

505

et al., 2014) of the granular sludge, with the tested substrates in descending order, was as

506

follows: acetate > glutamate > butyrate > H2/CO2 > valerate > propionate.

507 508

Table 3

509 510

A sharp increase in the SMA for the sludge fed with acetate (Table 3) could be related to

511

the increase in the number of Methanosaeta (Supplementary data). An abundance of

512

hydrogenotrophic methanogens, such as Methanobacterium bei

513

jingense, Methanobacterium subterraneum, and Methanobacterium formicicum,

514

remained during phase VII and maintained a steady value in the SMA fed with H2/CO2.

515

Bacterial degraders for glutamate fermentation, including Clostridium pascui and

516

Anaeroarcus burkinensis (Supplementary data), increased in population with the

517

operational HRTs. Thus, compared to phase II, the methane-producing capacity of the

518

granular sludge for glutamate increased more than seven times during phase VI (Table 3).

519

The high utilization ability of butyrate in the SMA test during phase VI can likely be

520

attributed to the large population of Syntrophomonas sp. that appeared in the UASB

521

reactor after a long operational period.

522 523

The most common species in the bacterial domain during phase VII was Clostridium

524

pascui (Supplementary data), which is classified in Clostridium cluster I (Wilde et al.,

525

1997) and can utilize (S)-glutamate via the 3-methylaspartate pathway with fermentation

526

products of ammonium, acetate, butyrate, hydrogen, and carbon dioxide according to Eq.

22

527

(4) (Buckel, 2001; Buckel & Thauer, 2013).

528 529

(4)

530

The main biodegradation pathway via butyrate production is favorable over propionate

531

oxidization, as the latter pathway via propionate oxidization has higher activation energy

532

barriers (Stams & Plugge, 2009). In addition, glutamate can be converted to acetate and

533

propionate (and traces of H2/CO2) by Anaeroarcus burkinensis (Strompl et al., 1999),

534

which was identified as the second most common species with a relative abundance of

535

9.85% (one-third times that of Clostridium pascui) during phase VII (Supplementary

536

data). Acidaminococcus sp., with a small relative abundance (1.06%), can also

537

decompose glutamate via the 2-hydroxyglutarate pathway into butyrate, propionate,

538

acetate, and H2/CO2 (Buckel, 2001; Kim et al., 2004).

539 540

Based on the SMA tests and the analysis of dynamic evolution of a microbial community,

541

probable pathways of glutamate degradation and methanogenesis for the glutamate-rich

542

wastewater treatment in the UASB reactor are summarized in Fig. 7.

543 544

Fig. 7

545 546

Although at least three pathways for glutamate degradation occurred in the anaerobic

547

reactor, the pathway via 3-methlaspartate by Clostridium pascui was dominant in the

548

UASB reactor (HRT = 2 h). From there, VFAs were converted into acetate and H2 by

549

Syntrophomonas sp., Acidaminococcus sp., and Syntrophobacter sp. Finally, acetoclastic

550

and hydrogenotrophic methanogens were responsible for methane production, among 23

551

which Methanosaeta was dominant under a short operational HRT. Overall, in the UASB

552

reactor for glutamate-rich wastewater treatment during the long operational period, the

553

anaerobes converted glutamate into butyrate or propionate, then to acetate and H2/CO2,

554

and then again for methane production. Additional research seeking new evidence to

555

support these pathways is necessary for future wastewater treatment.

556 557

4. Conclusions

558

The UASB reactor showed good potential for glutamate-rich wastewater treatment. At

559

HRTs of 4.5 h to 6 h, a high and stable COD removal efficiency of more than 95% with a

560

methane yield of 0.31 L-CH4/g-COD was obtained, as well as advantageous properties of

561

granular sludge, including granular sludge diameter, settling velocity, and EPS content.

562

At a short HRT of 2 h, excessive VFAs accumulated, which led to a deterioration in

563

reactor performance. At least three degradation pathways occurred for glutamate

564

fermentation in the UASB reactor, and the pathway via 3-methlaspartate by Clostridium

565

pascui was likely dominant for glutamate-rich wastewater treatment at an HRT of 2 h.

566 567 568

Acknowledgements

569

This work was supported by the National Natural Science Foundation of China (Grant No.

570

51308068) and the China Hunan Provincial Science & Technology Department (Grant

571

No. 2017SK2361). The authors gratefully acknowledge the support from Professor

572

Yu-You Li (Tohoku University, Japan), the Japan Society for the Promotion of Science,

573

and the Majorbio Bio-Pharm Technology Co. Ltd. (Shanghai, China). We would like to

574

thank Editage (www.editage.cn) for English language editing.

24

575 576

Supplementary data

577

E-supplementary data for this article can be found online.

578 579

25

580

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750

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751

Figure Captions

752

Fig. 1 Schematic diagram of the experimental apparatus

753

Fig. 2 Overall performance of the UASB reactor in treating synthetic MSG wastewater

754

under various HRTs: (a) pH; (b) NH4+-N; (c) alkalinity; (d) COD; (e) volatile fatty acids

755

(VFAs); (f) biogas production and methane content

756

Fig. 3 Effects of HRT on MSG wastewater removal: (a) NH4+-N production; (b) VFA

757

concentration; (c) organic removal rate (ORR) and COD removal efficiency; (d) methane

758

yield and methane production rate (MPR)

759

Fig. 4 COD mass balance in the UASB system

760

Fig. 5 Characteristics of granular sludge

761

Fig. 6 Microbial community structure during phases I and VII

762

Fig. 7 Proposed pathways of methanogenic degradation of glutamate in the UASB

763

reactor

34

Table 1 Operational conditions of the UASB reactor. Phase I

Phase II

Phase III

Phase IV

Phase V

Phase VI

Phase VII

Days

Days

Days

Days

Days

Days

Days

1-35

36-63

64-82

83-106

107-127

128-149

150-180

1916.52

2109.05

2032.52

2060.72

2054.25

2043.45

2032.38

± 251.50

± 114.20

± 121.48

± 129.23

±100.16

± 109.45

± 131.02

HRT (h)

48

24

12

6

4.5

3

2

OLR (g-COD/L/d)

0.95±0.13 2.08±0.11 3.98±0.24 8.26±0.52 10.82±0.50 16.20±0.88 24.66±1.57

Influent flow (L/d)

3

Parameter

COD (mg/L)

Temperature ( ) pH of influent

6

12

24

32 35±1 7.0±0.5

48

72

Table 2 Richness and diversity estimation for the microbial community in the UASB reactor during each phase. Community richness estimators

Community diversity estimators

ACE

Chao1

Shannon

Simpson

Phase I

19

19

1.49

0.29

Phase VII

15

16

0.81

0.61

Phase I

382

380

3.72

0.07

Phase VII

346

352

3.42

0.11

Samples

Archaea

Bacteria

Table 3 The SMA and maximum methane production rate (Rmax) of the granular sludges with different substrates. Parameters

Rmax (mL-CH4/h)

SMA (g-COD CH4/g VSS/d)

Operational phase/HRT

I/48 h

II/24 h

III/12 h IV/6 h

VI/3 h

I/48 h

II/24 h

III/12 h IV/6 h

VI/3 h

Methanol

2.02

1.89

2.04

1.67

N.D.*

0.044

0.040

0.041

0.028

0.003

Acetate

0.38

0.90

1.42

2.07

3.55

0.008

0.019

0.028

0.034

0.101

Propionate

0.53

0.36

0.20

0.16

0.15

0.012

0.008

0.004

0.003

0.004

n-Butyrate

N.D.*

N.D.*

N.D.*

N.D.* 2.23

N.D.*

N.D.*

N.D.*

N.D.* 0.064

n-Valerate

N.D.*

N.D.*

N.D.*

N.D.* 0.23

N.D.*

N.D.*

N.D.*

N.D.* 0.007

(S)-glutamate

N.D.*

0.56

0.87

1.75

2.90

N.D.*

0.011

0.017

0.029

0.083

H2/CO2**

0.74

1.93

1.56

1.59

1.45

0.016

0.041

0.031

0.026

0.041

*

N.D.: not determined.

**

H2/CO2: the mixed gas consisted of H2 and CO2 (80:20, v/v).

Effluent Gas Meter Dryer / Desulfurizer

Buffer Bottle Thermometer

Water Bath

Biogas Collector Pump M

Thermostat Sampling Port

Influent

Up-flow Anaerobic Sludge Blanket (UASB)

Substrate Tank

9 4 b a 3 8 2 7 1 6 0 100 d c 3 80 60 2 40 1 20 0 0 1 0 0 12 0 e f 1 80 8 9 60 6 6 40 4 3 20 2 0020406080100120140160180 00204060801001201401601800 Ⅱ

Ⅰ

Ⅲ

Ⅳ

Ⅴ

Ⅶ

P h a se s

Ⅱ

Ⅰ

Ⅲ

Ⅳ

Ⅴ

Ⅵ

Ⅶ

In f. E ff.

O p e r a tio n D a y s (d )

0

In f. E ff. R e m o v a l e f f ic ie n c y

M e th a n e p e rc e n ta g e B io g a s p r o d u c tio n r a te

O p e r a tio n D a y s (d )

R e m o v a l E ffic ie n c y (% )

1 0 3 m g /L

1

2

B io g a s p r o d u c tio n r a te (L /L /d )

a c id a c id ic a c id c id

( )

3

1 0 A lk a lin ity

1 0

2

m g /L

( ) V F A

V a le r ic B u ty r ic P r o p io n A c e tic a

3

C O D

to ta l a lk a lin ity b io c a r b o n a te a lk a lin ity to ta l a lk a lin ity b io c a r b o n a te a lk a lin ity

M e th a n e p e r c e n ta g e in b io g a s (% )

In f. In f. E ff. E ff.

(

m g -C a C O 3 /L

)

A m m o n iu m

p H

1 0

2

m g /L

In f. E ff.

Ⅴ I

( )

P h a se s

100

a

VSS VSS/TSS

80

40

VSS/TSS (%)

VSS (g/L)

60

60 40

20 20

>3 mm 0.5~1 mm

150

2~3 mm <0.5 mm

1~2 mm

b

Average settling velocity

90

100 60 50

30

0

0 5

250

EPS content (mg/g)

120

PN PS PN/PS

200

c 4 3

150 100

2

50

1

0

0

Phases

I

II

Average settling velocity (m/h)

0

III

IV

V

VI

VII

PN/PS ratio

Particle size portion (%)

0

Archaea

Euryarchaeota Methanosaeta

Methanosaeta

Methanobacterium

Methanosarcina

Methanosarcina

others

others

Actinobacteria Actinomyces

Firmicutes Synergistetes Aminivibrio AQRZ_g

Thermotogae Mesotoga

Chloroflexi AF423186_g

Nitrospirae AB262729_g

Proteobacteria

Pseudomonas others

Phase Ⅰ

Actinobacteria Firmicutes Synergistetes Proteobacteria Thermotogae Chloroflexi Nitrospirae others

Firmicutes Synergistetes Proteobacteria Bacteroidetes Saccharibacteria TM7 others

0 10 20 30 40 50 60 70 80 70 60 50 40 30 20 10 0

Percentage (%)

Percentage (%)

Phase Ⅶ

Bacteria

Bacteria

Clostridium Romboutsia

Firmicutes Clostridium Anaeromusa Syntrophomonas Acetoanaerobium Acidaminococcus Bacteroidetes Lentimicrobium DQ677001_g Proteobacteria Syntrophobacter Klebsiella Synergistetes AF280863_g Saccharibacteria_TM7 Saccharimonas others

Archaea

Euryarchaeota Methanobacterium

(S)-Glutamate acid Clostridium pascui

(s)-Citramalate

Anaeroarcus burkinensis Acidaminococcus sp.

Propionate

Pyruvate

Syntrophobacter sp.

Butyrate Syntrophomonas sp.

Acetoanaerobium sp.

H2/CO2

Acetate Methanobacterium beijingense Methanobacterium subterraneum Methanobacterium formicicum

Methanosaeta concilii

CH4

Highlights •

Methanogenic degradation of glutamate in UASB reactor depended on HRT applied

•

High MSG removal and energy recovery obtained at HRTs of 4.5–6 h

•

Clostridium and Methanosaeta were predominant in glutamate-degrading granules

•

HRT had substantial impact on SMA and microbial community of granules

•

The pathway via 3-methlaspartate was dominant for methanogenic degradation

Author Contribution Statement of “Anaerobic treatment of glutamate-rich wastewater in a continuous UASB reactor: Effect of hydraulic retention time and methanogenic degradation pathway” (Reference No.: CHEM66161) by H. Chen, et al.

Hong Chen: Conceptualization, Methodology, Project administration, Funding acquisition Yanxiao Wei: Methodology, Data curation, Writing- Original draft preparation, Validation Chenglei Xie: Investigation, Writing - original draft Hong Wang: Methodology, Writing- Original draft preparation Sheng Chang: Resources, Writing- Original draft preparation Ying Xiong: Resources, Validation, Writing- Reviewing and Editing Chunyan Du: Resources, Funding acquisition, Validation Benyi Xiao: Funding acquisition, Validation, Supervision Guanlong Yu: Resources, Funding acquisition, Formal analysis

Declaration of Interest Statement

Article Title: Anaerobic treatment of glutamate-rich wastewater in a continuous UASB reactor: Effect of hydraulic retention time and methanogenic degradation pathway

Authors: Hong Chen, Yanxiao Wei, Chenglei Xie, Hong Wang, Sheng Chang, Ying Xiong, Chunyan Du, Benyi Xiao*, Guanlong Yu

All authors declare that we have no financial and personal relationships with other people or organizations that can inappropriately influence our work. We confirm that this manuscript has not been published elsewhere and was not previously submitted to Chemosphere. All authors have approved the manuscript and agree with its submission to Chemosphere. All authors of this manuscript have directly participated in the planning, execution, and analyses of this study.

Signature: Benyi Xiao (on behalf of all co-authors of this manuscript) Date: September 25, 2019 Institution: Research Center for Eco-Environmental Sciences, Chinese Academy of

Sciences (Corresponding author: B.Y. Xiao*)