Accepted Manuscript System Evaluation and Microbial Analysis of a Sulfur Cycle-based Wastewater Treatment Process for Co-treatment of Simple Wet Flue Gas Desulfurization Wastes with Freshwater Sewage Jin Qian, Rulong Liu, Li Wei, Hui Lu, Guang-Hao Chen PII:

S0043-1354(15)00284-5

DOI:

10.1016/j.watres.2015.05.005

Reference:

WR 11276

To appear in:

Water Research

Received Date: 28 November 2014 Revised Date:

24 March 2015

Accepted Date: 1 May 2015

Please cite this article as: Qian, J., Liu, R., Wei, L., Lu, H., Chen, G.-H., System Evaluation and Microbial Analysis of a Sulfur Cycle-based Wastewater Treatment Process for Co-treatment of Simple Wet Flue Gas Desulfurization Wastes with Freshwater Sewage, Water Research (2015), doi: 10.1016/ j.watres.2015.05.005. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. 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.

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System Evaluation and Microbial Analysis of a Sulfur Cycle-based

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Wastewater Treatment Process for Co-treatment of Simple Wet Flue

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Gas Desulfurization Wastes with Freshwater Sewage

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Jin Qiana, Rulong Liua, Li Weia, Hui Lub*, Guang-Hao Chena*

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Clear Water Bay, Kowloon, Hong Kong, China

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b

Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology,

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School of Environmental Science and Engineering, Sun Yat-sen University, Guangzhou, China

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*Corresponding authors (E-mail: [email protected]; [email protected])

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Abstract: A sulfur cycle-based wastewater treatment process, namely the Sulfate

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reduction, Autotrophic denitrification and Nitrification Integrated process (SANI®

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process) has been recently developed for organics and nitrogen removal with 90%

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sludge minimization and 35% energy reduction in the biological treatment of saline

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sewage from seawater toilet flushing practice in Hong Kong. In this study, sulfate-

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and sulfite-rich wastes from simple wet flue gas desulfurization (WFGD) were

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considered as a potential low-cost sulfur source to achieve beneficial co-treatment

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with non-saline (freshwater) sewage in continental areas, through a Mixed

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Denitrification (MD)–SANI process trialed with synthetic mixture of simple WFGD

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wastes and freshwater sewage. The system showed 80% COD removal efficiency

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(specific COD removal rate of 0.26 kg COD/kg VSS/d) at an optimal pH of 7.5 and

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complete denitrification through MD (specific nitrogen removal rate of 0.33 kg N/kg

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VSS/d). Among the electron donors in MD, organics and thiosulfate could induce a

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much higher denitrifying activity than sulfide in terms of both NO3- reduction and

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NO2- reduction, suggesting a much higher nitrogen removal rate in organics-,

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ACCEPTED MANUSCRIPT thiosulfate- and sulfide-based MD in MD–SANI compared to sulfide alone-based

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autotrophic denitrification in conventional SANI®. Diverse sulfate/sulfite-reducing

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bacteria (SRB) genera dominated in the bacterial community of sulfate/sulfite-

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reducing up-flow sludge bed (SRUSB) sludge without methane producing bacteria

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detected. Desulfomicrobium-like species possibly for sulfite reduction and

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Desulfobulbus-like species possibly for sulfate reduction are the two dominant groups

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with respective abundance of 24.03 and 14.91% in the SRB genera. Diverse

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denitrifying genera were identified in the bacterial community of anoxic up-flow

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sludge bed (AnUSB) sludge and the Thauera- and Thiobacillus-like species were the

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major taxa. These results well explained the successful operation of the lab-scale

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MD–SANI process.

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Keywords MD–SANI process; Organics and nitrogen removal; Microbial structure analysis;

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Sulfate/sulfite-reducing bacteria (SRB); Autotrophic and heterotrophic denitrifiers

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1. Introduction

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Water scarcity and lacking of sanitation continue to be challenging issues worldwide.

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As a well-urbanized coastal city, Hong Kong has adopted a dual water supply system

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including seawater supply for toilet flush since 1958 (Leung et al., 2009). This system

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serves 80% of the city’s 7 million inhabitants and saves 20% of freshwater demand or

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740,000 m3/day (WSD, 2010). Seawater toilet flushing also brings in sufficient

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amount of sulfate into sewage allowing us to introduce a Sulfur cycle-based

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Biological Nitrogen Removal (ScBNR) concept into sewage treatment. And the

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Sulfate reduction–Autotrophic denitrification–Nitrification

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process (see Fig. 1a) has been developed (Lau et al., 2006; Wang et al., 2009; Lu et al.,

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Integrated

(SANI®)

ACCEPTED MANUSCRIPT 2012). In this novel process, sulfate acts as an electron shuttle for: i) anaerobic

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organics removal by sulfate-reducing bacteria in the anaerobic reactor and ii) nitrogen

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removal through autotrophic denitrification (AD) by sulfide-oxidizing bacteria (SOB)

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in the anoxic reactor (see Fig. 1a). Limited amount of biological sludge is produced in

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SANI® process because sulfate-reducing bacteria, SOB and nitrifying bacteria have

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very low sludge yields (Lu et al., 2011). Hence 35% of energy demand and 36% of

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greenhouse gas emission can be reduced by this novel process compared with

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conventional biological nitrogen removal processes (Lu et al., 2011, 2012).

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For freshwater sewage which does not contain sufficient sulfate, the SANI®

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process can be potentially applied by adding low-cost sulfur wastes. For example, the

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wet flue gas desulfurization (WFGD) system applied in coal-burning heaters, boilers

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and power plants can be simplified to flue gas alkaline-sorption (simple WFGD),

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generating sulfate/sulfite-rich liquid wastes (Weijma et al., 2000a). After removing of

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suspended solids and heavy metal, such wastes can be beneficially co-treated with

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sewage mainstream by SANI® (Qian et al., 2013). Such process simultaneously treats

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industrial wastes and sewage, meanwhile shares all advantages of the conventional

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SANI® such as low energy consumption, less greenhouse gas emission and also low

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sludge generation (Jiang et al., 2013). However, different from conventional SANI®

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which utilizing sulfate as the sole electron acceptor, the simple WFGD wastes contain

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mixed sulfur compounds (SO42-+SO32-), inducing the generation of thiosulfate and

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sulfide as well as certain amount of acetate-like volatile fatty acids (VFA) in the

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anaerobic effluent (Qian et al., 2015a). Such effluent subsequently allowed the mixed

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denitrification (MD, i.e., autotrophic and heterotrophic denitrification) in the anoxic

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reactor. Therefore, the new process was named MD–SANI as distinguished from

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SANI® (Fig. 1b) (Qian et al., 2015a).

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ACCEPTED MANUSCRIPT In the MD–SANI process, the chemical oxygen demand (COD) removal and

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sludge production are mainly associated with sulfate/sulfite reducing bacteria (SRB)

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while nitrogen removal is achieved through the autotrophic and heterotrophic

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denitrifiers. In order to evaluate the treatment capacity of this process and also for

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further optimization of the performance, the organic degradation and the

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denitrification activities under different conditions need to be well studied and the

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structure of microbial community needs to be investigated. Although SRB activities in

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sulfate and sulfite co-reduction using methanol (Weijma et al., 2000b) and H2 (Lens et

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al., 2003) as the energy source have been reported, no previous studies were found for

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co-reduction of sulfate and sulfite by mixed organic sources provided via synthetic

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wastewater simulating real domestic sewage. Moreover, the mixed denitrification

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involving sulfide, thiosulfate and organics as three different electron donors have

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never been explored in biological wastewater treatment up to date. The diversities of

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microbial communities in the sulfate and sulfite reduction with synthetic organics and

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in the mixed denitrification processes as mentioned above are not available in the

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literature as well.

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This study sets up a lab-scale MD–SANI system treating synthetic wastewater

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and pretreated liquid wastes from simple WFGD in order to: (1) evaluate performance

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of the MD–SANI for a long-term operation; (2) specify the diversity of SRB genera in

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the MD–SANI compared with the SANI process and (3) analyze the microbial

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structure in the mixed denitrification reactor in the MD–SANI system.

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2. Materials and Methods

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2.1 Lab-scale MD–SANI System and Operation

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ACCEPTED MANUSCRIPT 103 The lab-scale system comprises a sulfate/sulfite reducing up-flow sludge bed (SRUSB)

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for sulfate/sulfite reduction and an anoxic up-flow sludge bed (AnUSB) for MD, each

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having an effective volume of 1.37 and 1.7 L (see Fig. 1c). Lactate and sulfite were

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initially used to start up the SRUSB up to 120 days. In this start up period (Phase 1),

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754 mg /L COD and 426 mg S/L sulfite were provided at a sulfite-S to-COD ratio of

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0.56. The synthetic wastewater (composition can be referred to Wang et al. (2009))

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replaced the lactate and sulfite sources from Phase 2 from days 121 to 156. In Phase 3

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(days 157 to 278), sulfate was added to the influent of SRUSB. From day 157 (phase

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3), to induce an effective MD in AnUSB 30 mg N/L NaNO3 was added to the influent

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of AnUSB. AnUSB was cultivated with 30 mg N/L sodium nitrate, 100 mg S/L

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sodium thiosulfate, and other essential nutrients and trace minerals (Wang et al.,

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2009), with an internal recirculation flow rate of 3 Q to ensure effective substrate

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transfer between the bulk liquid and biomass (Qian et al., 2015a). The nominal

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hydraulic retention time (HRT) was set at 6 h for SRUSB and 4 h for AnUSB from

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days 157 to 190 and then decreased to 3 and 2 h respectively afterward. The

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composition and concentration of the SRUSB and AnUSB influent and other

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operating conditions (HRT, Temperature, pH, MLVSS) in all three phases are

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summarized in Table 1.

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2.2 Batch experimentation for SRUSB and AnUSB

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Two sets of batch test were conducted with the SRUSB and AnUSB sludge

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respectively, to determine the SRB activities in terms of organics removal at different

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pH levels and the denitrifier activities in terms of nitrogen removal with sulfide,

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ACCEPTED MANUSCRIPT thiosulfate and acetate-like volatile fatty acids as the electron donor. The SRUSB and

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AnUSB sludge was washed with distilled water for three times to remove background

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substrates, such as sulfate, sulfite, thiosulfate, sulfide, and COD prior to each assay.

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Nitrogen gas was purged into each batch reactor for half an hour prior to Batch Test 1

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to exclude the dissolved oxygen and maintain an anaerobic condition, while helium

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gas was used for Batch Test 2 (for denitrification) instead of nitrogen gas for the same

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purpose, as ambient nitrogen gas in the reactor may affect the denitrification activity

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test results. The batch tests were conducted in glass serum flasks (2 L for Batch Test 1

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and 500 mL for Batch Test 2). All flasks were sealed tightly with butyl rubber

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stoppers and aluminum crimp seals during the assay. Temperature during all the tests

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was controlled at 23±1 oC. All flasks were mixed with magnetic stirrers (250 rpm).

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Batch Test 1 examined the effect of pH on organic degradation by SO42- and

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SO32- reduction. Since operational pH of domestic wastewater treatment is typically

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between 7 and 8, a relatively broader pH range (6.5~8.0) adjusted by Na2HPO4-

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NaH2PO4 buffer solution was chosen in this set of test (see Table 2). Four batch

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reactors were conducted, each starting with 420 mg/L COD prepared from the stock

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solution of the synthetic wastewater and a mixture of Na2SO4 (230 mg S/L) and

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Na2SO3 (115 mg S/L) as the organic and sulfur sources, respectively. Molar ratio of

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sulfate to sulfite was set at 2:1 mol SO42--S/mol SO32--S (a typical S composition in

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simple WFGD effluent). Therefore the stoichiometric level of sulfur compound

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against COD was 150% for all the four reactors. Each lasted for 32 h.

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Batch Test 2 examined the different denitrifying activities with different electron

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donor in AnUSB. Three batch reactors were run simultaneously. Same amount of

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NO3- (60 mg N/L) and stoichiometrically sufficient amount of sulfide (120 mg S/L),

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thiosulfate (220 mg S/L) and acetate (240 mg COD/L) were dosed in these three

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reactors, respectively. pH was controlled at 7.5 by using Na2HPO4-NaH2PO4 buffer

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solution. Each reactor lasted for 24 h.

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2.3 Chemical/physical analysis

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During the SRUSB and AnUSB operations, both influent and effluent were sampled

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regularly for analysis of total organic carbon (TOC), VFA, alkalinity, sulfate, sulfite,

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sulfide, thiosulfate, nitrite and nitrate. Samples in each batch test were taken by using

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a 10 mL syringe with a needle. All batch samples were filtrated through a 0.22 um

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filter prior to analysis. TOC was analyzed using a TOC analyzer (Shimadzu TOC-V

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CPH). Sulfate, thiosulfate, acetate, nitrite, and nitrate were determined using ion

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chromatograph (HIC-20A super) equipped with a conductivity detector and an IC-

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SA2 analytical column (Zhang et al., 2015). Organic COD was measured according to

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standard method (APHA, 2005). pH and temperature were monitored with multi-

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meter electrode during each test (WTW multi 3420).

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2.4.1 DNA extraction, PCR amplification and pyrosequencing

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Sludge samples from SRUSB and AnUSB were collected at the end of operation in

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Phase 3 (Day 278 and 228, respectively) to analyze the structure of microbial

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community. The samples were collected by centrifugation under 12000 rpm for 10

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minutes. Around 0.5 g of the pellet was weighted for each sample and stored at -80 oC

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until the DNA extraction. Genomic DNA was extracted using the PowerSoil DNA

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Isolation Kit (MoBio Laboratories, Inc., Carlsbad, CA) following the manufacturer’s

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protocols. The quality and quantity of DNA were checked with a NanoDrop device

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(ND-1000, Thermo Fisher, USA). The bacterial 16S rRNA gene was amplified with primer pair 515F and 926R

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(Table S1) targeting the V1 and V3 regions (Quince et al., 2011). Barcode sequences

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were incorporated between the 454 adaptor and the forward primer (Table S1). A 100

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µL PCR reaction mixture contained 5 U of Pfu Turbo DNA polymerase (Stratagene,

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La Jolla, CA, USA), 1 x Pfu reaction buffer, 0.2 µM of dNTPs (TaKaRa, Dalian,

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China), 0.1 µM of each primer and 20 ng of genomic DNA template. PCR was

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performed with a thermal cycler (Bio-Rad, USA) under the following conditions:

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initial denaturation at 94 oC for 5 min; 30 cycles at 94 oC for 30 s, 53 oC for 30 s and

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72 oC for 45 s; and a final extension at 72 oC for 10 min. The PCR products were

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purified using the TaKaRa Agarose Gel DNA Purification Kit (TaKaRa, China) and

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quantified with the NanoDrop device. The purified PCR amplicons were sequenced

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using the ROCHE 454 FLX Titanium platform (Roche, Basel, Switzerland) at the

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National Human Genome Centre of China at Shang Hai, China.

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2.4.2 Data analysis

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The raw pyrosequencing reads were processed using the Pyrosequencing Pipeline

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Initial Process of the Ribosomal Database Project (RDP) (Cole et al., 2009), to

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remove sequences containing more than one ambiguous ‘N’ or shorter than 150 bps

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(Claesson et al., 2009) and check the completeness of the barcodes and the adaptor.

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The remained sequences were then aligned using the software MOTHUR ver. 1.17.0

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(Schloss et al., 2009). The sequences were clustered into operational taxonomic units

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(OTUs) using the MOTHUR program. The representative sequences from each OTU

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were assigned to taxonomic classifications using the RDP Classifier (Wang et al.,

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2007). Rarefaction curves and the diversity indices (ACE and Chao1) were generated

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in MOTHUR for each sample. Good’s coverage was calculated as G = 1-n/N, where n

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is the number of singleton phlyotypes and N is the total number of sequences in the

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sample (GOOD, 1953).

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2.5 Batch experiments with different sulfur-compounds as electron acceptors

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In order to confirm the effect of different sulfur compounds (sulfite and sulfate) on the

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microbial community composition, sludge samples were further taken from SRUSB

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and then divided into two parts with a similar VSS concentration (~800 mg/L), both

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of which were cultivated in a batch mode in two 2-L flasks with magnetic stirrer

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mixing for two months. In both of the batch cultivation flasks (Batch Reactor A and

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B), diluted synthetic wastewater containing 500 mg/L COD and other trace elements

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(Wang et al., 2009) were supplied. In Batch Reactor A, SO32- alone was used as the

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electron acceptor while SO42- was used as sole electron acceptor in Batch Reactor B.

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The S sources were both added at a stoichiometric level (250 mg SO42--S/L in Batch

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Reactor A and 330 mg SO32--S/L in Batch Reactor B). pH in both reactors was

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adjusted to 7.5 with Na2HPO4-NaH2PO4 buffer solution. Both reactors were fed as

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above mentioned every other day. Before each feeding magnetic stirring was stopped

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for 30 mins, 1 L supernatant was decanted and sludge was then washed by distilled

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water for three times. Nitrogen gas was filled to maintain an anaerobic condition in

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each of the cultivation reactors.

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The sludge samples from Batch Reactors A and B were collected after two

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months cultivation. The diversity of the microbial community was revealed by 454-

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pyrosequencing of 16S rRNA gene following the above methods.

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3. Results and Discussion

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3.1.1 Performance of the anaerobic reactor: SRUSB

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On Day 157 to 190 in Phase 3 when mixture of sulfate and sulfite was supplied to

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SRUSB, the COD removal efficiency gradually increased to 95% in SRUSB after

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adaption (Fig. 2a), corresponding to an average effluent COD of 104 mg/L. However,

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when HRT of the SRUSB reactor was halved from 6 to 3 h from Day 191 onward, the

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effluent COD initially increased to 260 mg/L then gradually decreased to 113 mg/L

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on average. The COD removal efficiency decreased to about 60%. After this short

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period of stabilization, the COD removal efficiency was maintained at 80%, resulted

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in the specific organic removal rate of 0.26 kg COD/kg VSS/d in the SRUSB reactor.

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3.1.2 Performance of the anoxic reactor: AnUSB

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Since the SRUSB effluent contained organics residual, thiosulfate, and sulfide (see

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Table 1), two types autotrophic denitrification driven by sulfide and thiosulfate and

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one heterotrophic denitrification (referred to as mixed denitrification) could be

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induced in AnUSB. Initially, more than 80% of nitrate was removed, with only a

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small amount of nitrite generated (see Fig. 2b). Two weeks later, 100% nitrate was

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denitrified without any nitrite accumulation (Fig. 2b). This short start-up period could

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be attributed to the MD, because when organics was supplied to the AD reactor with

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sulfide as electron donor the mixed denitrification rate sharply increased to

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approximately 10 times faster than previous that of AD only (Gommers et al., 1988;

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ACCEPTED MANUSCRIPT Lee et al., 2001; Kim et al., 2002). AD could induce faster NO3- denitrification and

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heterotrophic denitrifiers performed a more important function in NO2- denitrification

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(Reyes-Avila et al., 2004; Chen et al., 2009). The complete nitrogen removal with

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biomass-specific nitrogen loading rate of 0.33 kg N/kg VSS/d in this MD reactor

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indicates the abundance of autotrophic and heterotrophic denitrifiers (see microbial

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analysis results below). Also our previous study has shown an average of nitrogen

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mass balance of 98.5% over the AuUSB during its operation and confirmed NO3- was

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denitrified to N2 only but not NH4+ (Qian et al., 2015a). To offer insights on the

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bioactivity of SRB and mixed denitrifying biomass in MD–SANI, we designed a set

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of batch tests which are discussed in the next section.

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3.2 Bio-activity of organics removal and denitrification

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3.2.1 Effect of pH on organics removal in the SRUSB

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The organics degradation rate can be separated into two stages before and after

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reaction time of 8 h (see Fig. 3a). The specific COD removal rates at pH 7.5 were

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40.9 and 10 mg COD/g VSS/h before and after 8 h, respectively, according to the

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linear regression of biomass-specific COD concentration profile in Fig. 3a.

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Interestingly both rates exceed that at pH=6.5, 7 and 8 (see Table 2). The reason for

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such a pH dependent rate is unclear, though it is common in most enzyme-driven

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biological reactions, as each enzyme has an optimal activity at a certain pH level (Pan

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et al., 2012).

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Acetate profile in Fig. 3b shows a variation tendency that accumulated at the

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beginning of each test and then degraded afterward. Sulfate reduction can produce

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acetate (Min and Zinder, 1990) as an intrinsic feature under sulfate and sulfite

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ACCEPTED MANUSCRIPT reducing conditions (Weijma et al., 2003). Moreover, Lovley et al. (1982) reported

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that acetate uptake rate by SRB is lower than acetate production rate. As a result,

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acetate degradation becomes the rate-limiting step of sulfidogesis (Hulshoff Pol et al.,

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1998; Dries et al., 1998; Vallero et al., 2003; Omil et al., 1997). All of these previous

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works support our results on the acetate profile in Fig. 3b. From the microbial point of

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view, one possible explanation for acetate accumulation at four tested pH levels is that

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the amount of acetate-utilizing SRB (complete oxidizing SRB) was at a very low level

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(see below microbial analysis results of SRUSB), causing a lag phase for the net

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acetate reduction. Corresponding to the COD removal profile, acetate was completely

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mineralized at pH 7.5 after 32 h but incompletely removed at other three pH levels.

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3.2.2 Denitrification with different electron donors

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Sulfide at a concentration of as low as 10 mg S/L exhibits toxicity on many

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microorganisms, including denitrifying bacteria (Brunet and GarciaGil, 1996;

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Sorensen et al., 1980), because sulfide can combine with iron from cytochromes to

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inhibit organism respiration (Visser et al., 1997). Its inhibitory effect has been shown

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earlier to exert towards both heterotrophic (Knowles, 1982; Schonharting et al., 1998)

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and autotrophic denitrifiers (Cardoso et al., 2006). During the denitrification process,

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Cardoso et al. (2006) found that sulfide inhibited denitrification of NO3- to NO2-. In

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this study, it was found that sulfide led to a much lower denitratation and denitritation

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activities than thiosulfate and acetate (Table 3). Reyes-Avila et al. (2004) and Chen et

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al. (2009) found that compared to sulfide, acetate could induce a much higher

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denitritation rate. Based on our results, acetate-based denitritation was also much

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faster than thiosulfate-based denitritation, possibly due to the higher microbial growth

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with organics as the carbon source (Cardoso et al., 2006).

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ACCEPTED MANUSCRIPT The nitrite reduction can be divided into two steps: nitrite reduction in the

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presence of nitrate and nitrite reduction in the absence of nitrate, for both autotrophic

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and heterotrophic denitrifying reactions (Glass and Silverstein, 1998; Qian et al.,

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2015b). Therefore, the nitrite reduction rates in both the presence and the absence of

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nitrate were calculated and the results are shown in Table 3 (raw results of Batch Test

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2 can be seen in Fig. S1 in SI). Compared with these three batch reactors, using the

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acetate as the electron donor, both of these two rates are higher than that with either

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thiosulfate or sulfide. Moreover thiosulfate could induce a higher nitrite reduction

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rates with and without nitrate than sulfide (Table 3).

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Therefore, from the perspective of both nitrate reduction and nitrite reduction, the

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organics, thiosulfate and sulfide-based MD reaction may lead to a much high BNR

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rate in MD–SANI process than that in original SANI® built on sulfide alone.

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3.3 Microbial community analysis

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Approximately 15000 and 12911 raw pyrosequencing reads of the 16S rRNA gene

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spanning the hypervariable regions V1 and V3, were obtained from the SRUSB and

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AnUSB sludge samples. After quality filtering, approximately 9732 and 7896 reads

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with an average read length of 378 bp were used for subsequent analyses. The

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sequences were clustered into 1385 and 2474 operational taxonomic units for the

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tested sludge in SRUSB and AnUSB, respectively (Table S2 and Fig. S2 in SI).

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3.3.1 Diversity of microbial community in SRUSB

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Altogether, 15 bacterial phyla were recovered from the SRUSB sludge sample. The

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majority of 16s rRNA gene sequences belong to Proteobacteria, Firmicutes, Chlorobi,

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ACCEPTED MANUSCRIPT Bacteroidetes, Actinobacteria, representing approximately 56.6, 16.97, 14.84, 6.06

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and 2.74% of the sequences, respectively (Fig. 4a). On a finer scale, the 16s rRNA

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sequences were classified into 18 classes (Fig. 4b) and the dominate classes were

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Deltaproteobacteria, Chlorobi, Bacilli and Actinobacteria, accounting for 50.46, 13.2,

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9.5 and 5.6% of the total sequences, respectively. In contrast, the bacterial community

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in the seeding sludge sample was dominated by Alphaproteobacteria (59.7%),

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Betaproteobacteria (4.0%), Gammaproteobacteria (4.5%) and Actinobacteria (9.8%)

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(Hao et al., 2013). As most of the recognized species of SRB belong to the class

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Deltaproteobacteria (Castro et al., 2000), the remarkable shift of the bacterial

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communities towards Deltaproteobacteria suggest the possibility of the SRB

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enrichment. Such changes are possibly due to the bacteria aggregation acclimation

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selection (Zhang et al., 2001). Indeed, seven out of the ten reported SRB genera

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(Warren et al., 2005) within Deltaproteobacteria were identified and accounted for

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46.8% of total sequences retrieved from the SRUSB sludge (see Fig. 5), supporting

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the good organic removal performance in SRUSB (Fig. 2a).

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In a sulfur-reducing reactor, organics are removed by the cooperation of

344

fermenting biomass with SRB (Jiang et al., 2013). Lactococcus and Trichococcus are

345

two types of fermenting bacteria at 5.9% and 2.1% genus level respectively in the

346

SRUSB reactor in this study, which can degrade the complex organic compounds

347

those are hard for SRB utilization into more readily utilized ones, such as short-chain

348

VFAs, as the SRB’s substrates (Liu et al., 2002; Revesz, 2009). The dominant SRB

349

genera were Desulfomicribium, Desulfobulbus and Desulfovibrio which accounted for

350

24.03%, 14.91% and 4.8% of the total sequences, respectively (Fig. 5).

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Bacteria in the genus Desulfomicrobium were reported to effectively oxidize

352

many organic matters such as lactate, pyruvate, glycerol, acetate and ethanol (Barton

14

ACCEPTED MANUSCRIPT and Tomei 1995), and utilizing sulfate, thiosulfate, or sulfite as electron acceptor (Leu

354

et al., 1999). Similarly, the Desulfobulbus are also capable to reduce sulfite, sulfate

355

and thiosulfate to sulfide with degradation of glucose, propionate and pyruvate to

356

acetate (Suzuki et al., 2007). The three major SRB groups in the SRUSB

357

(Desulfomicribium, Desulfobulbus and Desulfovibrio) are all incomplete oxidizers

358

which only partially oxidized organics to simpler forms (e.g. acetate), characterized as

359

the incomplete oxidizing SRB (Rozanova et al., 1988; Suzuki et al., 2007; Devereux

360

et al., 1989). In contrast, complete oxidizing SRB could fully oxidize organics into

361

inorganic carbon, which are reported as acetate-utilizing SRB group and defined by

362

its ability to grow well on acetate (Devereux et al., 1989; Devereux and Mundfrom,

363

1994; Rabus et al., 2006). In this study, three complete oxidizing SRB genera were

364

detected, Desulfobacterium, Desulfobacter and Desulfococcus, totally accounting for

365

only 2.4%. From the microbial point, the low level of these incomplete oxidizing SRB

366

may explain why acetate accounted for the majority of SRUSB effluent COD (Qian et

367

al., 2015a) and the lagged acetate reduction in Batch Test 1 (Fig. 3b).

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The domain genus groups in previously reported sulfite- or sulfate-reducing

369

reactors (Jiang et al., 2013; Hao et al., 2013) are quite different from the co-sulfite-

370

sulfate-reducing reactor in this study (SRUSB), even though the seeding sludge in all

371

of those reactors was from the same sewage treatment plants and the reactors type,

372

carbon sources were all the same. In sulfate-reducing UASB, the dominant group was

373

Desulfobulbus (18.1%) and Desulfobacter (13.6%) (Hao et al., 2013). The sulfite-

374

reducing reactor mainly contained Lactococcus (72.67%) and Desulfomicrobium

375

(15.03%) (Jiang et al., 2013). It seems reasonable that in our study when both sulfate

376

and sulfite were supplied as the sulfur source, the main SRB were Desulfomicribium

377

(24%) and Desulfobulbus (14.9%). Therefore, microbial composition in SRUSB may

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ACCEPTED MANUSCRIPT 378

quite be dependent on different forms of sulfur as electron acceptors. Also based on

379

experimental results, we hypothesized that in the SRUSB of this study

380

Desulfomicribium is dominant in sulfite reduction while the major sulfate reduction

381

SRB group is Desulfobulbus. To test such hypothesis, further studies were conducted using two parallel

383

reactors with sulfite (SO32-) and sulfate (SO42-) as sole electron acceptor, respectively.

384

Desulfomicrobium and Desulfobulbus were two most abundant genera in both SO42--

385

and SO32--reducing reactors (Fig. 6), with all the other SRB related genera below 1%

386

in both reactors (Fig. S3). However, obvious differences were observed between the

387

two reactors regarding proportions of the two SRB genera. In SO32--reducing reactor,

388

Desulfomicrobium was at relatively higher level (15.46%) compared to Desulfobulbus

389

(6.42%) (Fig. 6). In contrast, with SO42- as the electron acceptor, Desulfobulbus

390

became predominant (23.35%) over Desulfomicrobium (11.45%) (Fig. 6). These

391

results support the hypothesis that SRB group in SRUSB may quite be dependent on

392

different sulfur as electron acceptors and Desulfomicrobium-like species are dominant

393

in sulfite reduction while Desulfobulbus-like species are dominant in sulfate reduction.

394

Similar with the study from Wang et al. (2011) and Jiang et al. (2013), there is no

395

methane producing bacteria (MPB) presented in SRUSB according to the microbial

396

testing results. From the thermodynamic point of view, the sulfate/sulfite reduction by

397

SRB released more energy than the production of methane by MPB, thereby enabling

398

SRB to out-compete MPB (Khanal, 2002). MPB only dominate in a low-sulfate

399

environment (Stams, 1994).

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400 401

3.3.2 Microbial community in AnUSB

402

The Proteobacteria account for more than 80% of the total 16s rRNA gene sequences

16

ACCEPTED MANUSCRIPT in AnUSB sludge supplied with three electron donors, i.e. sulfide, thiosulfate and

404

organics (Fig. 4a). The dominate classes of Proteobacteria were Betaproteobacteria,

405

Gammaproteobacteria, Alphaproteobacteria and Deltaproteobacteria, accounting for

406

61.03, 7.78, 5.36 and 2.6% of total sequences, respectively (Fig. 4b). Proteobacteria

407

were also widely found to be dominant in other denitrifying reactors, including sulfur-

408

based (Koenig et al., 2005), thiosulfate-based (Fernandez et al., 2008), sulfide-based

409

(Fernandez et al., 2009) and hydrogen-based (Mao et al., 2013) autotrophic

410

denitrification bioreactor, mixotrophic denitrification reactor (Fernandez et al., 2009;

411

Chen et al., 2008) and heterotrophic denitrification reactor (Fernandez et al., 2009).

412

The results suggest that this phylum may contain the major denitrifying bacteria in

413

those bio-reactors.

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A clear predominance of sequences was related to the family Rhodocyclaceae

415

under Betaproteobacteria. Among them, 36.3% (Fig. 5) of total OTUs were related to

416

the genus Thauera. Thiobacillus under Betaproteobacteria was the second most

417

abundant genera (23.4%) in the reactor (Fig. 5). Besides Thauera and Thiobacillus,

418

another two denitrifying genera Denitratisoma and Sulfurovum were also detected,

419

accounting for 6.8% and 1.95% of total sequences from AnUSB sludge, respectively.

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Thauera has been reported to perform heterotrophic denitrification with acetate as

421

the carbon source (Osaka et al., 2008). In this study, the organics source to AnUSB

422

was acetate-like VFAs from SRUSB effluent. Comparatively, previous studies

423

(Ginige et al., 2005; Osaka et al., 2008) have shown that a dose of acetate to

424

denitrifying reactors leads to a selection of specific bacterial populations within the

425

families Rhodocyclaceae. Osaka et al. (2008) found 71% of total sequences belonged

426

to Rhodocyclaceae family in heterotrophic denitrification reactor with acetate as the

427

sole carbon source. A combination of molecular methods was used to generate data

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ACCEPTED MANUSCRIPT 428

that strongly suggest that bacteria related to Thauera in activated sludge are capable

429

of utilizing acetate under anoxic conditions (Ginige et al., 2005). Those results well

430

explain the reason for the dominance of Thauera in the AnUSB of this study. Thiobacillus under Betaproteobacteria was the second most abundant genera

432

(23.4%) in the reactor (Fig. 5). It was reported to reduce nitrate to nitrogen gas while

433

oxidizing elemental sulfur or reduced sulfur (sulfide and thiosulfate) compounds to

434

sulfate (Koening et al., 2005). In our case, the AnUSB is feed with effluent from

435

SRUSB which contains the reduced sulfur. The condition of the AnUSB is therefore

436

favored the development of Thiobacillus population, making it a dominant reduced

437

sulfur-based autotrophic denitrifying bacteria in the reactor.

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Denitratisoma is a Gram-negative, motile, denitrifying bacterium (Fahrbach et al.,

439

2006). With nitrate as the electron acceptor, this bacterium also grew on short-chain

440

fatty acids, i.e. acetate. Sulfurovum, a mesophilic genus within Epsilonproteobacteria

441

class, could oxidize thiosulfate to sulfate as the end product coupled with

442

denitrification for its chemolithoautotrophic growth (Inagaki et al., 2004).

443

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3.4 Field application

445

As discussed above (see section 3.3.1), the Desulfobulbus (14.91%) and

446

Desulfomicrobium (24.03%) are the dominant SRB-related genera in biological

447

sulfate/sulfite-reducing reactor in the MD–SANI process. And for the SANI® process

448

with influent sulfate as the sole electron acceptor, the most abundant genus is

449

Desulfobulbus (18.1%) (Hao et al., 2013). Both Desulfobulbus and Desulfomicrobium

450

could effectively degrade organics for the anaerobic biological sulfate/sulfite

451

reduction (Jiang et al., 2013; Hao et al., 2013). Therefore, both SANI® and MD–SANI

452

processes possess the similarly specific organic removal rate of as high as 0.26-0.3 g

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ACCEPTED MANUSCRIPT 453

COD/g VSS/d, the short HRT of 3 hr as well as the high organic loading rate of 3~4.5

454

kg COD/m3/d

455

(23.4%) for autotrophic denitrification and sulfide/thiosulfate oxidation as well as

456

Thauera (36.3%) for heterotrophic denitrification and organics degradation were the

457

main predominant groups compared with the SANI process (Thiobacillus (29%) and

458

Sulfurovum (14%), Shi, 2009). Subsequently, it was caused the mixed denitrification

459

(both heterotrophic and autotrophic) and much higher denitrification rate (0.33 g N/g

460

VSS/d) and nitrogen loading rate (0.4 kg N/m3/d) in the MD–SANI process than those

461

in the SANI® process (0.04 g N/g VSS/d and 0.1 kg N/m3/d, respectively).

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(Wang et al., 2009). In the MD–SANI process, the Thiobacillus

463

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464

This study presents a novel study on sulfur cycle-based wastewater treatment process

466

built on MD for co-treatment of freshwater sewage and simple WFGD wastes. The

467

main findings are summarized as follows:

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1. The high organic removal rate in SRUSB (0.26 kg COD/kg VSS/d) and high

470

N removal rate in AnUSB (0.33 kg N/kg VSS/d) confirmed the feasibility of

472 473

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this proposed process and suggested the enrichment of SRB and denitrifiers in each reactor.

2. The bacterial community in SRUSB was dominated by diverse sulfate/sulfite-

474

reducing bacteria (SRB) genera (46.8 % of total sequences) and no methane

475

producing bacteria (MPB) were detected, supporting the high SRB activities in

476

SRUSB reactors.

19

ACCEPTED MANUSCRIPT 477

3. Different S source may have an obvious effect on the SRB genera selection in

478

the reactor, i.e., Desulfomicrobium may be enriched in sulfite-reducing reactor

479

while Desulfobulbus may be enriched in sulfate-reducing reactor. 4. Diverse denitrifying bacteria were observed in the AnUSB, supporting the

481

possibility of MD metabolism in the reactor. Thauera- and Thiobacillus-like

482

bacteria were the major denitrifying bacteria in AnUSB, contributing to the

483

nitrogen removal by autotrophic and heterotrophic ways, respectively.

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484 References

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Suzuki, D., Ueki, A., Amaish, A., Ueki, K., 2007. Desulfobulbus japonicus sp. nov., a

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novel Gram-negative propionate-oxidizing, sulfate-reducing bacterium isolated from

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an estuarine sediment in Japan. International Journal of Systematic and Evolutionary

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Vallero, M.V.G., Lens, P.N.L., Bakker, C., Lettinga, G., 2003. Sulfidogenic volatile

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fatty acid degradation in a baffled reactor. Water Science and Technology 48 (3), 81–

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production by obligately chemolitho autotrophic Thiobacillus species. Applied and

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process for saline wastewater treatment. Water Research 43 (9), 2363–2372.

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Loosdrecht, M.C.M., Chen, G.H., 2011. Microbial community of sulfate-reducing up-

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Warren, Y.A., Citron, D.M., Vreni Merriam, C., Goldstein, E.J.C., 2005. Biochemical

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similar genera. Journal of Clinical Microbiology 43 (8), 4041–4045.

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Weijma, J., Haerkens, J.P., Stams, A.J.M., Hulshoff, P.L.W., Lettinga, G., 2000a.

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reactor. Water Science and Technology 42 (5–6), 251–258.

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thermophilic sulfate and sulfite reducing high rate anaerobic reactor fed with

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methanol. Biodegradation 11 (6), 429–439.

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Weijma, J., Chi, T.M., Hulshoff Pol, L.W., Stams, A.J.M., Lettinga, G., 2003. The

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effect of sulphate on methanol conversion in mesophilic upflow anaerobic sludge bed

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reactors. Process Biochemistry 38 (9), 1259–1266.

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Annual Report 2008/2009.

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2001. Dynamic and distribution of ammonia-oxidizing bacteria communities during

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ACCEPTED MANUSCRIPT List of tables

Table 2 Kinetic analysis in Batch Test 1

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Table 3 Kinetic analysis in Batch Test 2

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Table 1 Operating conditions of SRUSB and AnUSB in the MD–SANI

ACCEPTED MANUSCRIPT Table 1 Operating conditions of SRUSB and AnUSB in the MD–SANI AnUSB*

SRUSB Experiment stage

Nominal HRT (h) Actual HRT (h) Internal recirculation Reactor effective volume (L) Upflow velocity (m/h) Carbon source Sulfur source

Phase 3.1

Phase 3.2

1 to 120

121 to 156

157 to278

157 to 190

191 to 228

10

5.5

11

10.2

20.4

6

6

6 to 3

4

2

2.2

0.68

0.68 to 0.61

0.57

0.5

1.7 Q

7.8 Q

3.9 Q

12 Q

6Q

2.5

1.37

1.37

1.7

1.7

0.5

0.88

0.88 to 0.98

1.24

1.42

Sodium

Synthetic

Synthetic

Residual

Residual

lactate

wastewater

wastewater

organics

organics

SO3

Influent COD (mg/L)

2-

754±29.2

2-

Influent SO3 (mgS/L)

426±21.5

2-

Influent COD/ SO3 -S

1.77

ratio Influent SO42- (mg S/L)

Influent pH o

Influent temperature ( C) MLVSS conc. (mg/L)

SO3

2-

2-

SO3 /SO4

2-

FSS/S2O3

18.5±16.5

58±21.6

370±25

99±11.2

0

0

1.32

5.66

–

–

0

190±16.2

76±11.6

68.2±13.7

32.3±4.8

23.8±7.1

N/A

N/A

N/A

7.5±0.1

7.0±0.1

7.0±0.1

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FSS/S2O32-

560±79.3

8.5±0.3

23±0.1

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*The AnUSB was operated after connection to the SRUSB at start of Phase 3.

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2-

490±59.2

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Influent NO3- (mg N/L)

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(L/d)

Phase 3

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Influent flow rate Q

Phase 2

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Operating Period (days)

Phase 1

2500

ACCEPTED MANUSCRIPT Table 2 Kinetic analysis in Batch Test 1 pH level 6.5

7.0

7.5

8.0

24.92

33.28

40.7

34.69

4.59

5.53

removal rate before 8 hour (mg COD/g VSS/h) Biomass-specific COD removal rate after 8

10

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hour (mg COD/g

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Biomass-specific COD

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VSS/h)

9.69

ACCEPTED MANUSCRIPT Table 3 Kinetic analysis in Batch Test 2 Electron donor Biomass-specific NO3- reduction rate (mg N/g VSS/d)

FSS

S2O32-

acetate

94.02

734.9

851.2

5.84

46.4

385.2

20.36

82.7

783.8

rate in the presence of NO3- (mg N/g VSS/d) Biomass-specific NO2- reduction

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rate in the absence of NO3- (mg

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Biomass-specific NO2- reduction

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N/g VSS/d)

ACCEPTED MANUSCRIPT Figure captions Figure 1. Concepts of SANI® (a) and MD–SANI (b) and a schematic of the lab-scale MD–SANI system (c) including: (1) sodium sulfite solution, (2) synthetic freshwater

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sewage and sodium sulfate solution, (3) SRUSB, (4) flow balancing tank, (5) AnUSB, (6) sodium nitrate solution, and (7) effluent tank.

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Figure 2. Performance of the anaerobic reactor (a) and anoxic reactor (b) in Phase 3.

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Figure 3. COD (a), acetate (b) profiles under different pH conditions in Batch Test 1.

Figure 4. Taxonomic classification of bacterial 16s rRNA gene reads retrieved from SRUSB and AnUSB at phylum (a) and class (b) levels using RDP classifier with a

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confidence threshold of 97%.

Figure 5. Relative abundance and phylogenetic relationships of different genera

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retrieved from the sludge of the SRUSB and AnUSB. The phylogenetic relationships were calculated by visualizing as a heatmap and using MeV software. The color

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indicates the percentage of a genus in total sequences.

Figure 6. Profiles of Desulfomicrobium and Desulfobulbus in both sulfite- and sulfate-reducing batch reactors.

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Fig. 1 Concepts of SANI® (a) and MD–SANI (b) and a schematic of the lab-scale MD-SANI system (c) including: (1) sodium sulfite solution, (2) synthetic freshwater

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sewage and sodium sulfate solution, (3) SRUSB, (4) flow balancing tank, (5) AnUSB,

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(6) sodium nitrate solution, and (7) effluent tank

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Fig. 2 Performance of the anaerobic reactor (a) and anoxic reactor (b) in Phase 3.

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Fig. 3 COD (a), acetate (b) profiles under different pH conditions in Batch Test 1.

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Fig. 4 Taxonomic classification of bacterial 16s rRNA gene reads retrieved from SRUSB and AnUSB at phylum (a) and class (b) levels using RDP classifier with a confidence threshold of 97%.

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Fig. 5 Relative abundance and phylogenetic relationships of different genera retrieved from the sludge of the SRUSB and AnUSB. The phylogenetic relationships were

ACCEPTED MANUSCRIPT calculated by visualizing as a heatmap and using MeV software. The color indicates

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the percentage of a genus in total sequences.

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Fig. 6 Profiles of Desulfomicrobium and Desulfobulbus in both sulfite- and sulfate-

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reducing batch reactors.

ACCEPTED MANUSCRIPT •

High organic and N removal rates suggest the diverse SO42-/SO32--reducing bacteria and denitrifiers.

•

Organics are removed at an optimal pH of 7.5 with Ac- production and

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reduction. •

Organics and S2O32- can induce a much higher denitrifying activity than S2-.

•

Desulfomicrobium and Desulfobulbus are the dominant SO42-/SO32--reducing

•

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genera.

Thiobicillus and Thauera are the major denitrifying genera in anoxic up-flow

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sludge bed.

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Supporting Information System Evaluation and Microbial Analysis of a Sulfur Cycle-based Wastewater Treatment Process for Co-treatment of Simple Wet Flue

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Gas Desulfurization Wastes with Freshwater Sewage

Jin Qiana, Rulong Liua, Li Weia, Hui Lub*, Guang-Hao Chena* a

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Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology,

Clear Water Bay, Kowloon, Hong Kong, China b

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School of Environmental Science and Engineering, Sun Yat-sen University, Guangzhou, China

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*Corresponding authors (E-mail: [email protected]; [email protected])

ACCEPTED MANUSCRIPT Table S1 Primer of the DNA amplification for SRUSB and AnUSB Reactors

Barcode Sequence

Primer (V1-V3）

SRUSB

GTACTATAGA

8F: 5’-AGAGTTTGATCCTGGCTCAG-3’

(V1-V3) AnUSB

GTACTGAGTC

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533R: 5’-TTACCGCGGCTGCTGGCAC-3’

8F: 5’-AGAGTTTGATCCTGGCTCAG-3’

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533R: 5’-TTACCGCGGCTGCTGGCAC-3’

ACCEPTED MANUSCRIPT Table S2 Similarity-based OTUs and species richness estimates with a confidence threshold of 97% ace

chao

shannon

simpson

coverage

SRUSB

1385

3700.01

2616.908

5.275482

0.019162

0.922919

AnUSB

2474

3671.19

2774.668

6.06041

0.010359

0.999336

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OTUs

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Fig. S1 NO3- (a) and NO2- (b) profiles with different electron donors for

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denitrification activity measurement in Batch Test 2.

ACCEPTED MANUSCRIPT 7000

SRUSB-0.03 SRUSB-0.05 SRUSB-0.1 AnUSB-0.03 AnUSB-0.05 AnUSB-0.1

6000

OTUs

5000 4000 3000

1000 0 0

2000 4000 6000 8000 10000 12000 14000

Number of Tags Sampled

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2000

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Fig. S2 Rarefaction analysis of the sludge sample from the SRUSB and AnUSB. Rarefaction is shown for OTUs that contain unique sequences and OTUs with

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differences that do not exceed 3%, 5% or 10%. OTUs with ≥97% pairwise sequence

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identity are assumed to form the same species and genus, respectively.

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Fig. S3 Profile of SRB genus in SO32-- (a) and SO42--reducing (b) batch reactors.