Simultaneous methanethiol and dimethyl sulfide removal in a single-stage biotrickling filter packed with polyurethane foam: Performance, parameters and microbial community analysis

Journal Pre-proof Simultaneous methanethiol and dimethyl sulfide removal in a single-stage biotrickling filter packed with polyurethane foam: Performance, parameters and microbial community analysis Tipei Jia, Shihao Sun, Kaiqi Chen, Liang Zhang, Yongzhen Peng PII:

S0045-6535(19)32700-6

DOI:

https://doi.org/10.1016/j.chemosphere.2019.125460

Reference:

CHEM 125460

To appear in:

ECSN

Received Date: 1 September 2019 Revised Date:

8 November 2019

Accepted Date: 22 November 2019

Please cite this article as: Jia, T., Sun, S., Chen, K., Zhang, L., Peng, Y., Simultaneous methanethiol and dimethyl sulfide removal in a single-stage biotrickling filter packed with polyurethane foam: Performance, parameters and microbial community analysis, Chemosphere (2019), doi: https:// doi.org/10.1016/j.chemosphere.2019.125460. 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.

Graphical Abstract:

1

Simultaneous methanethiol and dimethyl sulfide removal in a

2

single-stage biotrickling filter packed with polyurethane foam:

3

Performance, parameters and microbial community analysis

4

Tipei Jia, Shihao Sun, Kaiqi Chen, Liang Zhang, Yongzhen Peng*

5

National Engineering Laboratory for Advanced Municipal Wastewater Treatment and

6

Reuse Technology, Key Laboratory of Beijing Water Quality Science and Water

7

Environment Recovery Engineering, Beijing University of Technology, Beijing

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100124, China.

9

* Corresponding author: Yongzhen Peng, Beijing University of Technology, Beijing

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100124, China

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Tel/fax: +86-10-67392627; E-mail:[email protected]

12

Abstract

13

The bio-treatment of methanethiol (MT) and dimethyl sulfide (DMS), the most

14

common sulfur compounds in odorous gas, is difficult due to the inhibition of DMS

15

degradation by MT. This article investigated the treatment of MT and DMS odorous

16

gas using a single-stage biotrickling filter (BTF) packed with polyurethane foam

17

cubes that were inoculated with activated sludge from a sewage treatment plant

18

operating an anaerobic/aerobic/oxic (AAO) process. The BTF system lasted for 161

19

days (with 9 days to startup) under an empty gas residence time of 39 s. The

20

elimination capacities for MT and DMS were 85.2 g/m3/h (removal efficiency= 96.6%)

21

and 6.4 g/m3/h (removal efficiency= 95.0%), respectively, and the maximal

22

elimination capacities of MT and DMS were 119.7 g/m3/h and 7.3 g/m3/h,

1

23

respectively. The optimal parameters were as follows: empty bed retention time, 39 s;

24

pH, 6.1; recirculation medium flow rate,

25

SO42- concentration, < 2.0 g-SO42-/L. Microbial community analysis revealed that

26

spatial differentiation between MT-degrading bacteria and DMS-degrading bacteria

27

enable the single-stage BTF can simultaneously remove MT and DMS. The activated

28

sludge of AAO process can be used as the inoculation sludge to treating MT and DMS

29

gas, which provides an important reference for the industrial application of treating

30

odorous gas containing MT and DMS.

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Keywords: Odorous gas; Biotrickling filter; MT; DMS; Operating parameters;

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Microbial community analysis

33

1. Introduction

1.2 m3/m2/h; temperature, 29-36 °C; and

34

Methanethiol (MT) and dimethyl sulfide (DMS) are reduced sulfur compounds

35

(RSCs) that are the main organic sulfur compounds found in odorous gas from pulp

36

mills, landfill, refineries and sewage treatment plants (Muezzinoglu, 2003; Chan,

37

2006; van den Bosch et al., 2009; Giri et al., 2014; Kim et al., 2014). They can be

38

harmful because of their malodorous smell and low odor threshold (DMS 1.2 ppb,

39

MT 2.4 ppb). Additionally, they may threaten human health and corrode construction

40

and equipment.

41

Based on operating costs, purification efficiency and secondary pollution,

42

biological technologies are believed to be the most suitable option to treat odorous gas

43

(Barbusinski et al., 2017; Rybarczyk et al., 2019). The most common biological

44

reactors for treating odorous gas are biofilters, biotrickling filters (BTFs) and

2

45

bioscrubbers. These systems differ in the existence or nonexistence of a carrier; the

46

carrier material property (organic and inorganic); the phase state of the biomass

47

(suspended or fixed); and the state of the liquid medium (circulatory or stationary).

48

BTFs were adopted in this experiment because they allow better control of

49

environmental conditions, easy elimination of metabolites and durability of a packing

50

material.

51

The most commonly used carriers in BTFs include propylene rings (Jin et al.,

52

2005), ceramics (Ruokojärvi et al., 2011), pall rings (Montebello et al., 2013),

53

granular activated carbon and peat mixture (Shu and Chen, 2009). However, some

54

research has been carried out with polyurethane foam (PUF) (Ramírez et al., 2009)

55

because of its large specific surface area, good water holding capacity and high void

56

fraction.

57

A number of microorganisms have shown degradation activity on RSCs, such as

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Thiobacillus thioparus (Park et al., 1993), Bacillus sphaericus (Giri et al., 2010),

59

Hyphomicrobium VS (Sercu et al., 2005) and Xanthomonas sp. (Cho et al., 1992),

60

Microbacterium sp. (Shu and Chen, 2009) and Pseudomonas sp. (Ho et al., 2008).

61

Studies have demonstrated the biodegradation process of MT and DMS is carried

62

out as follows (Bentley and Chasteen, 2004; Schäfer et al., 2010; Cáceres et al.,

63

2012):

64


CH  S + O + 2H  → CH SH + HCHO + H O

(1)

CH SH + O + H O → H S + HCHO + H O

(2)

H S + 2O → H SO

(3)

The presence of MT was found to notably inhibit the removal of DMS due to MT is

3

65

an intermediate in the biodegradation process of DMS (Li et al., 2003; Cáceres et al.,

66

2012), while the presence of DMS do not affect the removal of MT (Zhang et al.,

67

1991; Cáceres et al., 2012). Therefore, the treatment of odorous gas containing both

68

MT and DMS was difficult. However, few of studies have explored the feasibility of

69

the long-term treatment of odorous gas containing DMS and MT using a single-stage

70

BTF.

71

Therefore, the main objective of this study was to investigate the feasibility of

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long-term treatment of MT and DMS odorous gas using a single-stage BTF packed

73

with cubes of PUF inoculated with activated sludge from a sewage treatment plant

74

operating an anaerobic/aerobic/oxic (AAO) process. The maximal elimination

75

capacity (ECmax) of MT and DMS was determined and the optimal parameters of the

76

BTF system were investigated. Finally, the removal mechanism of MT and DMS by

77

the biotrickling filter was analyzed.

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2. Materials and Methods

79

2.1 Cultivation and immobilization of microorganisms

80

The MT and DMS degrading culture was inoculated with activated sludge from

81

an AAO process sewage treatment plant. The composition of the mineral medium

82

used was KH2PO4, 2 g/L; K2HPO4, 2 g/L; NH4Cl, 0.4 g/L; MgCl2∙6H2O, 0.2 g/L;

83

FeSO4∙7H2O, 0.01 g/L; and trace elements solution S8 (Ruokojärvi et al., 2011), 1

84

mL/L.

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Excess AAO process activated sludge was poured into an aerated incubation

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bottle which contain PUF cubes (3 L) to immobilize enough microorganisms to PUF,

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87

ensuring attached growth of microorganisms (Cohen, 2001). After 7 days, the

88

colonized PUF was then transferred into the BTF.

89

2.2 Characteristics of the carrier material

90

PUF cubes (8 cm3 each) were used as the carrier material. It is an inert material

91

with good scale-up possibility and a very low commercial cost. The main beneficial

92

properties of this material are its density (21 kg/m3), specific surface area (2500

93

m2/m3) and porosity (95%).

94

2.3 Experimental configuration

95

The BTF used in this study was a cylindrical packed bed reactor of 60 mm

96

diameter and 640 mm height (Fig. S1). The active height of the packed column, filled

97

with PUF cubes, was 580 mm. Five sampling ports were distributed along the height

98

of the BTF at 0, 90, 295, 495 and 580 mm. The BTF and all fittings were made of

99

polymethyl methacrylate (PMMA).

100

The gas of MT and DMS were soured from a compressed gas cylinder (4 L,

101

Praxair, China) filled with MT (30 mg/L), DMS (15 mg/L) and N2. The gas flow of

102

MT and DMS was regulated by a reduction valve (HPR43, HaiXuan, China) and a

103

mass flow rate controller (MT-52, XiTai, China). The air flow was supplied by an air

104

compressor (FCY5015, QIHAI, China) and regulated by a flow meter (LZB-4,

105

AIDEKESI, China). The air flow and the gas flow of MT and DMS were introduced

106

into an expansion tank (2.5 L) to dilute MT and DMS concentration, then the diluted

107

gas of MT and DMS was introduced to the bottom of the BTF. Gaseous samples from

108

both the inlet and outlet of the system were collected in 3 L gas sampling bags

5

109

(LB-202-3, HedeTech, China). Mineral medium (5 L) as the circulating fluid was

110

continuously recirculated over the packed bed by a peristaltic pump (BT100-2J,

111

Shenchen, China) from a water tank. The mineral medium was refreshed about every

112

10 days and pH was controlled at above 4 by adding HCl or NaOH solutions (1.0 M).

113

2.4 Parameters of the biotrickling experiments

114

Operating parameters for the BTF are summarized in Table 1. Experiments were

115

divided into five stages according to the state of BTF, namely startup, increase load

116

rate, shut down, re-startup and increase load rate.

117

Table 1

118

The target concentrations were selected according to the field investigations

119

reported according to previous studies (Muezzinoglu, 2003; van den Bosch et al.,

120

2009). In Phase I, a relatively low concentration was selected to facilitate the quick

121

startup of the BTF system. In Phase II, the increase of MT and DMS concentration to

122

investigate the performance of the system on lifting load shock. In Phase III and

123

Phase IV, shutting down the system to examine recovery performance of the BTF

124

system. Phase V have the same purpose as Phase II.

125

2.5 Analysis and calculation methods

126

Gaseous MT and DMS concentrations were measured using a gas chromatograph

127

(GC; 7890B, Agilent, USA) equipped with an enhanced flame photometric detector

128

(FPD+) with a 113-4332 column (30 m, 320 µm). Nitrogen (1 mL/min) was used as

129

the carrier gas. The temperatures of the oven, injector and detector were 80, 150 and

130

200°C, respectively. Gaseous samples (200 µL) were manually injected into the front

6

131

inlet of the GC. The SO42- concentrations were measured by ion chromatography (861,

132

Metrohm, Switzerland) equipped with a Metrosep A Supp 5-150 column (150 mm, 4

133

mm, 5.0 µm). Pressure drop (∆P) through the beds was monitored daily with U-type

134

water manometers (0-3000PA, HongPeng, China) connected to the top and bottom

135

sections of the BTF. The pH and temperature were monitored using 172 pH/Oxi 340i

136

analyzers (WTW, Germany).

137

The formulas used to determine of the removal efficiency (RE), load rate (LR),

138

elimination capacity (EC), empty bed residence time (EBRT) and ∆P are as follows: C − C × 100 C C Q LR
g/m /h = V
C − C Q EC
g/m /h = V V EBRT
s = Q P* ΔP
Pa/m = H RE
% =

139

4 5 6 7 8

where, Cin and Cout are the inlet and outlet concentrations (g/m3), respectively; Q

140

is the gas flow rate (m3/h); V is the bed volume of the carrier material (m3); P0 is the

141

pressure difference between the top and bottom sections of the BTF (Pa); H is the

142

height of the carrier (m).

143

2.6 High-throughput sequencing and date analysis

144

Three biofilm samples were collected for bacterial community analysis. One

145

sample was obtained from the bottom of the BTF (90 mm height from the subface of

146

the packing) on day 1 and two samples were obtained on day 160 from the bottom and

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top of the BTF (495 mm height from the subface of the packing). DNA was extracted

7

148

from the dried sludge (0.10-0.20 g) using the Fast DNA Kit (MP bio, USA).

149

Polymerase chain reaction (PCR) was conducted to amplify the bacterial 16S rRNA

150

gene with the forward primer 338F (5’-ACTCCTACGGGAGGCAGCA-3’) and

151

reverse primer 806R (5’-GGACTACHVGGGTWTCTAAT-3’). The PCR mixture (20

152

µL) contained 4 µL 5×FastPfu buffer, 2 µL dNTPs (2.5 mM), 0.8 µL of each

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forward/reverse primer (5 mM), 0.4 µL FastPfu Polymerase, 10 ng of template DNA

154

and complementary Milli-Q water. PCR amplification was performed on an ABI

155

GeneAmp®9700 PCR System using the following thermal-cycling parameters: an

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initial temperature of 95 °C for 3 min; followed by 27 cycles of 95 °C for 30 s, 55 °C

157

for 30 s and 72 °C for 45 s; and a final extension at 72 °C for 10 min. PCR products

158

were imaged by agarose gel electrophoresis (2%) to confirm successful amplification

159

and then quantified and normalized using a TBS-380 fluorometer (QuantiFluor-ST

160

System, Promega, USA) on the Illumina Miseq PE300 platform by Shanghai

161

Majorbio Biopharm Biotechnology Co., Ltd. (Shanghai, China). By comparing to the

162

16S rRNA gene sequences to the MiSeq PE database, the optimized sequences were

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assigned into operational taxonomic units (OTUs) at a confidence threshold of 97%

164

using MOTHUR software. Taxonomy was assigned via the RDP classifier using the

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SILVA database. These data were analyzed online using the Majorbio I-Sanger Cloud

166

Platform (www.i-sanger.com). Based on the community abundance data, hypothesis

167

tests were performed by the Fisher’s exact test between the genera on day 160 at the

168

bottom and the top of the biotrickling filter.

169

3. Results and Discussion 8

170

3.1 Startup and long-term running of the BTF system Fig. 1

171 172

This experiment lasted for 161 days. The operating conditions for the BTF

173

system are shown in the Table 1 and the Cin, Cout, RE and pH values throughout the

174

experiment are shown in Fig. 1 (a).

175

During period I, the pH was maintained in the range of 5-8, and the Cin of MT

176

and DMS were 15.0± 1.0 mg/m3 and 7.0± 1.0 mg/m3, respectively. The RE of MT and

177

DMS increased stepwise from 15.5% and 22.0%, respectively, to 96.0% and 97.1%,

178

respectively. This indicates that the startup time for the BTF to remove MT and DMS

179

was approximately 9 days. During period II, the Cin of MT and DMS gradually

180

increased to 136.2 g/m3 and 68.4 g/m3, respectively, and the RE was stable at above

181

90% for MT and 80% for DMS after day 28. During period III, the BTF stopped

182

running for 27 days (until day 101) and no recirculation medium or gas was

183

introduced. During period IV, the Cin of MT and DMS were set at 17.0 mg/m3 (RE=

184

61.8%) and 6.6 mg/m3 (RE= 26.2%), respectively, on day 101. The Cin of MT and

185

DMS then gradually increased to 42.0± 5.0 mg/m3 and 17.0± 3.0 mg/m3, respectively,

186

and the pH was maintained in the range of 5-7. The RE of MT and DMS were above

187

90% after day 123, indicating that the re-startup time for the BTF after 27 days of

188

being shut down was approximately 22 days. The RE of MT and DMS were both

189

stable over 90% throughout the period V, while the Cin of the MT and DMS increased

190

from 37.0 mg/m3 and 15.3 mg/m3, respectively, to 178.1 mg/m3 and 109.7 mg/m3,

191

respectively.

9

192

Overall, the above test showed that the BTF system has a stable and efficient

193

ability to simultaneously remove MT and DMS. The activated sludge from the AAO

194

process sewage treatment plant can be used as inoculum treat MT and DMS.

195

3.2 Maximum elimination capacity of MT and DMS

196

To predict the performance of a BTF under different LRs, many studies have

197

focused on models that explore the relationship between substrate concentration and

198

elimination capacity. Among them, the most famous is the Michaelis-Menten model

199

(Eqn. 9) (Chung et al., 2001; Romero Hernandez et al., 2013): EC =

200

where,

ECmax

is

the

EC+,- C. K 0 + C.

maximal

9 elimination

capacity

(g/m3/h);

201

CIn=[Cin-Cout)/ln(Cin/Cout)] is the logarithmic average of the inlet and outlet

202

concentrations of pollutants in the gas phase (g/m3); and Ks is the saturation constant

203

(g/m3).

204

ECmax and Ks are calculated from the regression of Eqn. 9, rearranged as follows: 1 K0 1 = + EC EC+,- C. EC+,-

10

205

The Haldane model, which includes an inhibition constant, can be used in the

206

case of biomass inhibition as a result of high substrate concentrations (Gallastegui et

207

al., 2011; Romero Hernandez et al., 2013). Eqn. 11 was used to calculate the

208

elimination capacity: EC∗ C. EC = 2  K 0 + C. +
C. /K . 

209 210

11

where, EC* is the maximal elimination capacity without inhibition (g/m3/h); Ks' is the saturation constant (g/m3); and KI is the inhibition constant (g/m3).

10

211 212

EC*, Ks' and KI were calculated by rearranging Eqn. 11, using the following Lineweaver-Burk equation (Eqn. 12):  C. K 20 C. C. = ∗+ ∗+ ∗ EC EC EC EC K .

213 214

12

Under this circumstances, the mathematical analysis reported by Sologar et al. (Eqn. 13) was used to calculate the value of ECmax (Sologar et al., 2003), as follows: EC+,- =

EC∗

13

1 + 23
K 20 /K . 

215

Both models were developed for a single compound. The relationship between

216

EC and CIn is showed in Fig. 1 (b) and 1 (c). The EBRT was maintained at 39 s and

217

the pH was in the range of 5-6. The single-stage BTF system obtained the

218

experimental ECMT of 85.2 g/m3/h (RE= 96.6%) and ECDMS of 6.4 g/m3/h (RE=

219

95.0%), and the ECmax of MT and DMS were 119.65 g/m3/h (RE= 49.7 %) and 7.25

220

g/m3/h (RE= 83.7%), respectively. However, under the presence of MT (LRMT= 24.75

221

g/m3/h), the experimental ECmax-DMS value was only 6.27 g/m3/h (RE= 70.7%) (Fig. 1

222

(c)), which proves that the presence of MT has an inhibitory effect on DMS removal.

223

The ECMT versus CIn-MT fitted the Michaelis-Menten model (R2= 0.985) better,

224

proving that MT has no substrate inhibition effect. The ECDMS versus CIn-DMS was

225

better fitted by the Haldane model (R2= 0.953), indicating that DMS is a substrate

226

inhibitor. ECmax estimated by the Michaelis-Menten and Haldane models were 134.18

227

and 115.51 g/m3/h, respectively, for MT and 7.64 and 7.21 g/m3/h, respectively, for

228

DMS.

229

Ramírez et al. (2011) reported that the ECMT and ECDMS were 14.7 g/m3/h (RE=

11

230

78%) and 3.4 g/m3/h (RE= 97%), respectively, when using PUF as carrier in a BTF

231

that was inoculated with Thiobacillus thioparus. Sercu et al. (2005) obtained an

232

ECDMS of 58 g/m3/h (RE= 88%) when using polyethylene carrier rings as the carrier

233

in a two-stage BTF that was inoculated with Hyphomicrobium VS and

234

Acidithiobacillus thiooxidans. Arellano-García et al. (2009) reported that the ECMT

235

and ECDMS were 5.34-6.87 g/m3/h (RE= 71-91%) and 22.96 g/m3/h (RE= 98%),

236

respectively, when inoculated with Thiobacillus thioparus grown on PUF cubes as the

237

carrier material. Compared with the above reports, this experiment obtained a much

238

higher ECMT (119.65 g/m3/h); however, the ECDMS (7.25 g/m3/h) needs to be

239

increased.

240

3.3 ∆P versus superficial gas velocity (vg) during different periods Fig. 2

241 242

The ∆P is directly proportional to the increased number of microorganisms (or

243

other impurities) (Andreasen et al., 2013). High ∆P increases the energy consumption

244

of the blower, which contributes the most to the operation costs (Jin et al., 2007).

245 246

The relationship between ∆P and vg is in accordance with the Ergun equation (Ergun and Orning, 1949): ΔP = β56  + α56 56 =

247 248 249

Q A9

14 15

where, α (Pa/h/m2) and β (Pa/h2/m3) are the linear regression parameters; and Ac is the cross-sectional area of the filter perpendicular to the flow direction (m2). When the vg increased from 35.4 to 212.2 m/h, ∆P increased from 8.3± 1.9 Pa/m

12

250

to 49.8± 3.1 Pa/m on day 1 (Fig. 2). Under the same vg, the ∆P on day 1 was greater

251

than those on days 50 and 150, with day 150 greater than day 50. This is because

252

when the reactor started operating, the LR of MT and DMS was too lower so that

253

microorganisms cannot get enough energy and part of the biofilm was washed away

254

by the circulating liquid, making the ∆P on day 50 lower than day 1. After day 50, as

255

the LR of MT and DMS increased, the microorganisms obtained more carbon source

256

to produce more biomass, resulting in ∆P on day 150 being larger than day 50.

257

Overall, ∆P was always below 55 Pa/m (vg

258

operation. Overall, the low carbon source prevents microorganisms from

259

multiplication, therefore, ∆P was always below 55 Pa/m (vg

260

the 150 day operation.

212 m/h) throughout the 150 day

212 m/h) throughout

261

Different periods had different values of alpha (α) and beta (β) for the Ergun

262

equation. The β value, when compared with α value, had the greatest influence on the

263

higher ∆P since it determines the slope of the line (Ramírez et al., 2009). The β values

264

were 0.000295, 0.000232 and 0.000146 Pa/h2/m3 for the BTF system on days 1, 50

265

and 150, respectively. The β values of this experiment were comparatively much

266

lower than those obtained with other carrier materials. For example, Ramıŕ ez-López

267

et al. (2003) reported values of 0.128, 1.642, 2.271, 4.167 and 4.931 Pa/h2/m3 for

268

peanut shells, coconut husks, rice husks, maize stubble and bagasse, respectively.

269

Additionally, Ramírez et al. (2009) reported a β of 0.012 Pa/h2/m3 using PUF as the

270

carrier material in a BTF.

271

Jin et al. (2007) used polypropylene Pall rings as a carrier and ∆P was in the

13

272

range of 98-558 Pa/m (vg= 95 m/h). Ben Jaber et al. (2016) used expanded schist and

273

UP20 as a mixed carrier in a BTF and reported a ∆P of 3-94 Pa/m (vg= 56-565 m/h).

274

Dumont et al. (2008) started a BTF using pine bark as carrier and the ∆P was 15-370

275

Pa/m (vg= 72-504 m/h). It can be seen that PUF as carriers with large porosity had

276

lower ∆P than that of other materials in long-term operation.

277

3.4 Effect of pH and SO42- concentration on removal Fig. 3

278 279

The final degradation product of MT and DMS by microorganisms is H2SO4. If

280

SO42- and H+ continuously accumulate in the system, the pH of the circulating liquid

281

will decrease and the high concentration of sulfate will become toxic to the

282

microorganisms (Jin et al., 2005).

283

In order to examine the effect of pH on the removal of MT and DMS, pH of the

284

recirculation medium was evaluated in the range from 3.1 to 8.9 (each value tested for

285

24 h) by adding HCl or NaOH. Meanwhile, the Cin of MT and DMS were 140± 2

286

mg/m3 and 75± 2 mg/m3, respectively, keeping EBRT at 39 s and the SO42-

287

concentration below 0.5 g/L. The results are shown in Fig. 3 (a). The maximum RE of

288

MT and DMS occurred at a pH of 6.1 (99.9% and 93.5± 4.6%, respectively). When

289

the pH was above 6.1, the RE of MT did not show a significant change, while RE of

290

DMS notably decreased. For instance, when the pH was 8.9, the DMS RE was 33.1±

291

2.4%; however, when the pH dropped from 6.1 to 3.1, the RE of MT and DMS

292

decreased to 88.8± 2.4% and 68.8± 3.4%, respectively. Therefore, the optimal pH for

293

microorganisms to degrade MT and DMS is 6.1. The RE of DMS can be significantly

14

294

inhibited under alkaline conditions, when compared with acidic conditions, while the

295

RE of MT is less affected by pH change.

296

To explore the effect of SO42- on removal, SO42- concentrations were adjusted by

297

adding Na2SO4 while maintaining the pH in the range of 5-6. When the SO42-

298

concentration increased from 0.2 to 5.2 g/L, the RE of MT and DMS decreased from

299

99.9% to 78± 4.9% and 99.9% to 54± 2.8%, respectively. The drop was marked when

300

increasing SO42- concentration from 2.0 g/L. With 2.0 g/L, the RE of MT and DMS

301

was maintained above 90%. As a result, it was decided to use 2.0 g/L as the SO42-

302

concentration limit for the subsequent experiments. Therefore, it was necessary to

303

regularly refreshing the mineral medium to assure an SO42- concentration lower than

304

2.0 g/L.

305

3.5 Effect of EBRT on removal

306

The EBRT is related to the time that the pollutants dissolve into the liquid phase

307

on the surface of the biofilm. The EBRT was varied in the range of 9-70 s (with 24 h

308

for each EBRT) by adjusting the flow rate of the air compressor, while maintaining

309

the LR of MT and DMS at 13.2± 0.1 g/m3/h and 6.8± 0.1 g/m3/h, respectively. The

310

SO42- concentration was below 0.5 g/L and pH was in the range of 5-6.

311

The optimal EBRT for removing MT and DMS was 39 s, where the maximum

312

RE of MT and DMS were 98.0± 2.0% and 96.5± 0.2%, respectively (Fig. 3 (b)).

313

When the EBRT went down to 9 s, the RE of MT and DMS decreased to 88.9± 3.1%

314

and 73.7± 9.0%, respectively. It is worth noting that when the EBRT was increased to

315

70 s, the RE of MT and DMS slightly decreased to 97.5± 1.8% and 95.6± 2.0%,

15

316

respectively. The reason for this phenomenon is possibly that DMS is an inhibitory

317

substrate, thus the activity of the microorganism was inhibited by the high

318

concentration of DMS because under a constant load rate, the higher EBRT resulted in

319

higher concentrations of MT and DMS (e.g., EBRT= 70 s, Cin-DMS= 140 mg/m3). The

320

results indicate that the optimal EBRT of the BTF was 39 s. The REDMS, when

321

compared with the REMT, is more susceptible to EBRT fluctuations and that high

322

DMS concentrations have an inhibitory effect on microbial activity.

323

3.6 Effect of the flow rate of circulating liquid on removal

324

The flow rate of circulating fluid affected the thickness of the liquid film on the

325

surface of the biofilm and the oxygen mass transfer in the liquid phase (San-Valero et

326

al., 2012). The flow rate of circulating fluid are calculated from the Eqn. 16 as follow: flow rate of circulating fluid =

QF A9

16

327

where, QL is the flow rate of the peristaltic pump (m3/h).

328

The BTF was operated under constant recirculation medium flow rates of 0.3,

329

0.6, 1.2, 1.8, 2.4 and 3.0 m3/m2/h (24 h for each flow rate), while maintaining the Cin

330

of MT and DMS at 140± 2 mg/m3 and 75± 2 mg/m3, respectively. The EBRT was 39 s

331

and the pH was in the range of 5-6.

332

When the circulating fluid flow rate increased from 0.3 m3/m2/h to 1.2 m3/m2/h,

333

the RE of MT and DMS rose from 94.9± 4.2% and 32.7± .4%, respectively, to 98.6±

334

0.2% and 92.2± 5.1%, respectively, with the RE of DMS increasing more sharply than

335

that of MT (Fig. 3 (c)). This is probably because a higher flow rate increases both the

336

absorption capacity and liquid turbulence, thus diminishing mass transfer limitations

16

337

(Arellano-García et al., 2009). No apparent effect was observed on the RE of MT and

338

DMS when the liquid flow rates were greater than 1.2 m3/m2/h. The above results

339

show that the optimal circulating fluid flow rate of this experiment should be no less

340

than 1.2 m3/m2/h.

341

3.7 Effect of temperature on removal

342

The temperature can affect the activity of microbial enzymes, pollutant solubility

343

and the mass transfer efficiency in the liquid phase. The effect of temperature on MT

344

and DMS removal was studied by varying the temperature of the circulating fluid

345

from 10.0 to 45.5 °C (with each value maintained for 24 h), while the Cin of MT and

346

DMS were both 25.0± 1.0 mg/m3. The EBRT was 39 s and the pH was in the range of

347

5-6.

348

When the temperature was 29-36 °C, the RE of MT and DMS were above 99%;

349

however, it dropped rapidly when the temperature was lower than 29 °C or higher

350

than 36 °C (Fig. 3 (d)). As the temperature decreased from 29 °C to 10 °C, the RE of

351

MT and DMS were 74.2± 2.6% and 42.6± 10.8%, respectively, with the RE of DMS

352

exhibiting a larger decline than that of MT. The results show that the optimum

353

temperature range for removing MT and DMS is 29-36 °C. Poor performance of BTF

354

at lower temperatures may limit their application in colder climates, especially during

355

the winter.

356

3.8 Microbial community analysis of the biofilm

357

The bacterial composition and differences between the biofilms on days 1 and

358

160 were evaluated at the genus level via 16S rRNA gene sequencing using the

17

359

Illumina MiSeq platform (Fig. 4). Fig. 4

360 361

The bacterial community structure underwent tremendous changes after 160 days

362

of operation (Fig. 4 (a)). Dominant biofilm bacteria on day 1, such as Fusibacter,

363

Acidaminobacter and Acinetobacter, accounted for more than 34% of the community,

364

but declined to less than 1% on day 160. Fig. 4 (b) showed that the difference in the

365

bacteria community structure between the bottom and the top of the BTF on day 160

366

was extremely significant at p<0.05, indicating the removal of MT and DMS can lead

367

to extremely significant difference in the bacterial community structure inside the

368

BTF.

369

On day 60, the three most abundant bacterial genera in the bottom of the BTF

370

were Pseudoxanthomonas (18.3%), Pseudomonas (9.0%) and Rhodanobacter (7.4%),

371

while the three most abundant bacterial genera in the top of the BTF were

372

Pseudoxanthomonas (16.6%), Hyphomicrobium (12.5%) and Bacillus (10.9%) (Fig. 4

373

(a)). Thiobacillus and Stenotrophomonas were also found in both the bottom and top

374

of the BTF. According to previous reports, Bacillus and Hyphomicrobium possess the

375

ability to degrade DMS, whereas Pseudomonas and Thiobacillus have the ability to

376

degrade MT (Park et al., 1993; Sercu et al., 2005; Ho et al., 2008; Giri et al., 2010). It

377

is worth noting that the proportions of Bacillus (>0.1%) and Hyphomicrobium (3.7%)

378

in the bottom were lower than in the top (10.9% and 12.5%, respectively), while the

379

proportions of Pseudomonas (9.0%) and Thiobacillus (4.9%) in the bottom were

380

higher than in the top (8.1% and 3.1%, respectively). Fig. 4 (b) show that difference

18

381

of Bacillus, Hyphomicrobium, Pseudomonas and Thiobacillus between top and

382

bottom of the BTF was extremely significant, which indicated there was distinct

383

spatial differentiation between MT-degrading bacteria and DMS-degrading bacteria

384

along the BTF. As shown in Fig. S2, in the segment of 0-90 mm, 69.2± 2.4% (Mean±

385

Standard Deviation) of MT was removed, only 11.0± 0.8% of DMS was removed.

386

However, in the segment of 295-495 mm, 2.5± 0.7% of MT was removed and 34.5±

387

2.7% of DMS was removed. This is because the higher MT concentration in the

388

bottom inhibited the development of DMS-degrading bacteria while promoting the

389

growth of MT-degrading bacteria. Overall, the obtained result demonstrated that the

390

inhibition of DMS degradation by MT led to the spatial differentiation of

391

DMS-degrading bacteria along the BTF, which enables the single-stage biotrickling

392

filter to simultaneously treat MT and DMS.

393

4. Conclusions

394

The single-stage BTF system obtained EC for MT and DMS of 85.2 g/m3/h

395

(RE=9 6.6%) and 6.4 g/m3/h (RE= 95.0%). The optimal conditions of the BTF system

396

used for the treatment of MT and DMS odorous gas are: pH 3.1; EBRT, 39 s;

397

temperature, 29 to 36 °C; flow rate of recirculation medium,

398

SO42- concentration, <2.0 g/L. Microbial community analysis revealed that spatial

399

differentiation between MT-degrading bacteria and DMS-degrading bacteria enable

400

the single-stage BTF can simultaneously remove MT and DMS. PUF has been

401

demonstrated as a suitable carrier for low resistance to airflow and activated sludge

402

from a sewage treatment plant operating AAO process can be acclimated to treat MT

19

1.2 m3/m2/h; and

403

and DMS, which provides an important reference for the industrial application of

404

treating odorous gas containing MT and DMS.

405

Acknowledgements

406

This study was financially supported by Beijing Municipal Science

407

&Technology Project (Z181100005518006), supported by National Natural Science

408

Foundation of China (21777005) and the Funding Projects of Beijing Municipal

409

Commission of Education

410

411

References

412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437

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23

569

List of Figures and Table

570

Fig. 1 (a) Startup and long-term operation of MT and DMS removal; (b) ECMT versus

571

Cln-MT fitted the Michaelis-Menten and Haldane model; (c) ECDMS versus Cln-DMS

572

fitted the Michaelis-Menten and Haldane model, and ECDMS versus Cln-DMS affected

573

by MT

574

Fig. 2 ∆P versus vg fitted the Ergun equation during different periods

575

Fig. 3 Effect of pH (a), EBRT (b), flow rate of circulating liquid (c) and temperature

576

(d) on removal of MT and DMS

577

Fig. 4 (a) Microbial community structure and relative abundance at the genus level

578

(Others: genera less than 3% of total composition in all samples); (b) differences in

579

the bacterial abundances at the genus level between days 1 and 160 using

580

high-throughput sequencing targeting the 16S rRNA gene (P < 0.001 (***)).

581

Table 1 Operating conditions for the BTF system

24

Table 1 Operating conditions for the BTF system

Period

pH

Flow rate

Inlet concentration (mg/m3)

Day

EBRT

(d)

(s)

I

1-8

39

II

9-74

39

III

75-101

IV

101-123

39

5-7

1.82

16.0-61.7

6.7-25.3

V

124-161

39

5-7

1.82

37.0-178.1

15.3-109.7

(m3/m2/h)

MT

DMS

5-8

1.82

14.0-16.0

6.0-7.9

4-7

1.82

14.0-136.2

6.5-68.4

Stop running

29

Fig. 1 (a) Startup and long-term operation of MT and DMS removal; (b) ECMT versus Cln-MT fitted the Michaelis-Menten and Haldane model; (c) ECDMS versus Cln-DMS fitted the Michaelis-Menten and Haldane model, and ECDMS versus Cln-DMS affected by MT

25

Fig. 2 ∆P versus vg fitted the Ergun equation during different periods

26

Fig. 3 Effect of pH (a), EBRT (b), flow rate of circulating liquid (c) and temperature (d) on removal of MT and DMS

27

Fig. 4 (a) Microbial community structure and relative abundance at the genus level (Others: genera less than 3% of total composition in all samples); (b) differences in the bacterial abundances between the bottom and the top of the BTF on day 160 using high-throughput sequencing targeting the 16S rRNA gene (P < 0.001 (***)).

28

Highlights:


The single-stage BTF system obtained the ECMT of 85.2 g/m3/h (RE=96.6%) and the ECDMS of 6.4 g/m3/h (RE=95.0%), and the ECmax of MT and DMS were 119.7 g/m3/h and 7.3 g/m3/h, respectively.




The optimal value of the key parameters of the BTF system were as follows: EBRT=39 s; pH=6.1.




The startup time of the BTF system can be as short as 9 days.




MT-degrading bacteria (Pseudomonas and Thiobacillus) are mainly distributed in the bottom of BTF, while DMS-degrading bacteria (Bacillus and Hyphomicrobium) are mainly distributed in the top of BTF.

Author Contribution Statement

Tipei Jia: Conceptualization, Methodology, Software, Data curation, Writing- Original draft preparation. Shihao Sun: Visualization. Kaiqi Chen: Writing- Reviewing and Editing. Liang Zhang: Software, Validation. Yongzhen Peng: Supervision, Investigation.

Declaration of interests ☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. ☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: