Simultaneous reduction of perchlorate and nitrate in a combined heterotrophic-sulfur-autotrophic system: Secondary pollution control, pH balance and microbial community analysis

Water Research 165 (2019) 115004

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Simultaneous reduction of perchlorate and nitrate in a combined heterotrophic-sulfur-autotrophic system: Secondary pollution control, pH balance and microbial community analysis Dongjin Wan a, Qi Li a, Yongde Liu a, *, Shuhu Xiao b, Hongjie Wang c a b c

School of Chemistry, Chemical and Environmental Engineering, Henan University of Technology, Zhengzhou, Henan, 450001, China State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China College of Environmental Science and Engineering, Beijing Forestry University, Beijing, 100083, China

a r t i c l e i n f o

a b s t r a c t

Article history: Received 31 March 2019 Received in revised form 17 August 2019 Accepted 19 August 2019 Available online 19 August 2019

A combined heterotrophic-sulfur-autotrophic system (CHSAS) was established to simultaneously reduce perchlorate and nitrate in water. In this system, the OH
produced by the acetate heterotrophic part (Hpart) could be neutralized with the Hþ produced by the sulfur autotrophic part (S-part); thus, the pH of the final effluent could keep neutral. In addition, the S-part could further reduce the pollutants and residual carbon from the H-part to achieve a high performance. For 19.62 ± 0.30 mg/L ClO
4 and 21.56 ± 0.83 mg/L NO
3 -N in the influent, the operating parameters were optimal at a hydraulic retention
time (HRT) of 1.0 h and an acetate concentration of 70 mg/L. The removal efficiency of ClO
4 and NO3 reached 95.43% and 99.23%, without secondary pollution caused by residual organic carbon. It was also revealed that sulfur (S0) disproportionation can be inhibited by shortening the HRT and reducing the acetate dosage. The dominant heterotrophic and autotrophic bacteria were Thauera and Ferritrophicum, respectively, while Chlorobaculum was related to S0 disproportionation. © 2019 Published by Elsevier Ltd.

Keywords: Perchlorate Nitrate Combined heterotrophic-sulfur-autotrophic system (CHSAS) Secondary pollution control pH balance High-throughput sequencing

1. Introduction Perchlorate (ClO
4 ) is a strong oxidant (Zhao et al., 2011a) that is used in pyrotechnics as well as an explosive and propellant in military and aerospace industries (Mahmudov and Huang, 2010). Because of its high solubility and chemical stability (Kim and Logan, 2001), perchlorate can easily enter water and cause pollution. Furthermore, perchlorate can interfere with the synthesis and secretion of thyroid hormones (Urbansky and Schock, 1999), which affects human metabolism and growth. In a study conducted in 2010, it was found that 6.8e54.4 mg/L perchlorate was detected in surface water samples from Hengyang City, Hunan Province (Wu et al., 2010). A perchlorate concentration of 1e10 mg/L was detected in groundwater near the nitrate deposit in the Atacama Desert, Chile (Duncan et al., 2005). In California, the highest concentration of perchlorate detected in well water was 280 mg/L (Srinivasan and

* Corresponding author. E-mail addresses: [email protected] (D. Wan), [email protected] (Y. Liu). https://doi.org/10.1016/j.watres.2019.115004 0043-1354/© 2019 Published by Elsevier Ltd.

Sorial, 2009). Nitrate (NO
3 ) is widely present in surface water and groundwater and often coexists with perchlorate (Kimbrough and Parekh, 2007; Ginkel et al., 2008). It may cause methemoglobinemia in infants, and could result in malformation and mutation when it was transformed into nitrosamines (Rocca et al., 2007). Groundwater nitrate pollution levels in the US and some European countries have risen to 200 mg/L (Chen et al., 2014). For contaminated groundwater sites, perchlorate is usually present in low concentrations (ppb range) and nitrate is present in high concentrations (ppm range) (Matos et al., 2006). Nevertheless, high concentration perchlorate (ppm range) pollution with the coexistence of nitrate occurred in the water near fireworks plant and rocket propellant manufacturing plant have been reported in recent years (Kosaka et al., 2011; Isobe et al., 2013; Nadaraja et al., 2015; Sijimol et al., 2017). Perchlorate concentration as high as 32,602.60 mg/L was detected in Ammonium Perchlorate Experimental Plant water samples with an average value of 5094.87 mg/L in pre-monsoon (Sijimol et al., 2017). Meanwhile, nitrate concentration in the water was 7.06 mg/L. Therefore, the high concentration of perchlorate in water threat caused by related fields could not be underestimated.

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D. Wan et al. / Water Research 165 (2019) 115004

Strategies for treating perchlorate and nitrate contaminated water include physical-chemical and biological processes (Huq et al., 2007; Zhang et al., 2017; Yang et al., 2017). The physicalchemical technologies, such as ion exchange and reverse osmosis, generate a brine waste that need to be further treated (Gu et al., €yrynen et al., 2009). Chemical catalytic methods require 2007; Ha high cost catalysts and restrict reaction conditions (Yao et al., 2017), limiting theirs large-scale field application. Compared with the physical and chemical methods, biological reduction of perchlorate and nitrate is favored by researchers because of its high efficiency and low cost (Gao et al., 2016; Zhang et al., 2017). Microorganisms
use electron donors to completely transform ClO
4 and NO3 into innocuous Cl
and N2 under anaerobic conditions (Gao et al., 2016), which achieves the transformation of pollutant form. According to the type of electron donors, biological methods can be divided into heterotrophic and autotrophic methods. Acetate, lactate and methanol are the common carbon sources and electron donors for heterotrophic reduction of perchlorate and nitrate (Foglar and Briski, 2003; Shrout and Parkin, 2006; Wan et al., 2018a). The main advantages of the heterotrophic method are the high reduction rates and treatment capacity (Karanasios et al., 2010; Guan et al., 2015; Ucar et al., 2016b). For heterotrophic reduction process with acetate as the electron donor, the stoichiometric of denitrification process has been studied for many years, and the Eq. (1) includes the biomass growth and is often used in many researches (Drtil et al., 1995; Liu et al., 2009; Huang et al., 2012).
NO
3 þ 0:846CH3 COO /0:077C5 H7 O2 N þ 0:462N2 þ 0:077H2 O

þ 1:308CO2 þ 1:846OH
(1) The stoichiometric equation for perchlorate reduction process was still unclear. Eq. (2) is the most commonly used equation based on redox balance, un-includes biomass yield and is used in many studies (Ucar et al., 2016a; Wan et al., 2018a). In a previous study (Wan et al., 2018a), it was found that the optimal acetate/perchlorate (m/m) ratio was 1.78 (3-fold of the theoretical value calculated by Eq. (2)).


ClO
4 þ CH3 COO /Cl þ H2 O þ 2CO2 þ OH

(2)

Previous studies have shown that the carbon source dosage was affected by the type of carbon source and the concentration of  mez et al., 2000; Chiu and Chung, 2003; Shrout and pollutants (Go Parkin, 2006; Fern andez-Nava et al., 2010; Wan et al., 2018a). From practical aspects, the dose of carbon source is not easy to control. When the carbon source is in excess, the residual organics in the effluent can support microbial growth in water distribution systems, resulting in the formation of toxic trihalomethanes during disinfection via chlorination (Thrash et al., 2007). Therefore, posttreatment, such as the aerobic polishing stage, is needed after the heterotrophic process (Zhang et al., 2005). When the carbon source is insufficient, pollutants cannot be completely degraded. In addition, inorganic electron donors, such as hydrogen, zero valent iron and elemental sulfur (S0), may be used for the autotrophic reduction of perchlorate and nitrate (Logan and LaPoint, 2002; Cai et al., 2008; Oh et al., 2016). S0 has gained significant attention in recent years (Wang et al., 2016; Guo et al., 2017). For sulfur autotrophic reduction process, the stoichiometric equation of denitrification process has been studied for many years, and the Eq. (3) includes the biomass growth and is often used in many researches (Oh et al., 2003; Sahinkaya et al., 2014; Wan et al., 2017). Meanwhile, the stoichiometric equation for perchlorate was still unclear. Eq. (4) is the most commonly used equation based on

redox balance, and is used in many studies without consideration of biomass yield (Ju et al., 2008; Wan et al., 2017). The stoichiometric equations for autotrophic reduction processes are: 0 1:06NO
3 þ1:11S þ0:785H2 O þ 0:3CO2 /0:06C5 H7 O2 N þ þ0:5N2 þ1:11SO2
4 þ1:16H
2
0 þ 3ClO
4 þ 4S þ 4H2 O/3Cl þ 4SO4 þ 8H

(3) (4)

Though the sulfur autotrophic process could eliminate secondary contamination caused by residual organics, it generates sulfate (SO2
4 ) and consumes the alkalinity of the effluent (Moon et al., 2006; Ju et al., 2007). Meanwhile, S0 disproportionation always occurred in the process of sulfur autotrophic reduction of perchlorate (Ju et al., 2008; Wan et al., 2017 & 2018a). The disproportionation is a reaction in which the reactant itself not only acts as an oxidizing agent but also as a reducing agent. Microorganisms use S0 for disproportionation to produce sulfate and sulfide, the S0 disproportionation is shown in Eq. (5) (Ju et al., 2008): þ 4S0 þ 4H2 O/SO2
4 þ 3H2 S þ 2H

(5)

In order to make up for the deficiencies of heterotrophic or autotrophic processes, this study developed a combined heterotrophic-sulfur-autotrophic system (CHSAS) for the reduction of perchlorate and nitrate. In the combined system, the dosage of the carbon source added to the heterotrophic part (H-part) was insufficient to avoid the threat of organic secondary pollution. Meanwhile, the HRT and carbon source dosage were changed to adjust the load of the sulfur autotrophic part (S-part), thereby controlling the SO2
4 production. In addition, the alkalinity produced by the H-part was consumed by S-part, allowing that the pH value in S-part effluent maintain balance with the influent. At present, most of the studies on mixotrophic reduction are related to denitrification (Liu et al., 2009; Zhao et al., 2011a,b; Sahinkaya and Kilic, 2014; Tong et al., 2014). For nitrate and perchlorate co-existing pollution, the studies are still very limited. Ucar et al. (2017) evaluated the performance of a heterotrophicautotrophic sequential system for nitrate and perchlorate removal under a single operational condition (C/N ¼ 2.44 and HRT ¼ 2 h). However, the competition of the two pollutants for different electron donors, the effects of key operational parameters, such as the HRT and organic carbon source dosage, were not systemically explored. Control strategies for secondary pollution (especially for sulfate and organic carbon) and methods to maintain pH balance, which are the important aspects of the CHSAS technology, still deserve further research. Besides, studies using high-throughput sequencing to describe the microbial community structure in the CHSAS for perchlorate and nitrate reduction are still inadequate. Previous studies have mostly focused on the treatment of cocontamination of nitrate with high concentration (ppm range) and perchlorate with low concentration (ppb range) (Logan and LaPoint, 2002; Matos et al., 2006; Zhao et al., 2014; Ucar et al., 2017; Wan et al., 2017). Hydrogen autotrophic reduction of perchlorate and nitrate has been extensively investigated (Sahu et al., 2009a; Gao et al., 2016; Chen et al., 2017; Epsztein et al., 2017). Logan and LaPoint (2002) explored hydrogen autotrophic reduction of perchlorate (73 ± 2 mg/L) and nitrate (21 ± 2 mg-N/L) in a packed-bed bioreactor, the removal efficiencies reached 25% and 10%, respectively. Zhao et al. (2014) used H2 fed two-stages membrane biofilm reactor (MBfR) to remove perchlorate (160e200 mg/L) and nitrate (8-9 mg-N/L) from water. They found that most of nitrate was removed in the lead MBfR, while perchlorate was mainly removed in the lag MBfR. However, the problem of high

D. Wan et al. / Water Research 165 (2019) 115004

concentration perchlorate and nitrate pollution cannot be underestimated (Isobe et al., 2013; Sijimol et al., 2017). Hence, this study use high concentrations (ppm range) perchlorate and nitrate as the research object. The main objectives of the present study were to (1) evaluate the CHSAS reduction process for the simultaneous removal of ClO
4 and NO
3 ; (2) explore the control strategies for secondary pollution (focusing on sulfate and organic carbon); (3) explore methods to maintain pH and alkalinity consumption balance; (4) determine the dominant microbial community members involved in ClO
4 and NO
3 removal in each part. 2. Materials and methods 2.1. Experimental set-up The experimental set-up consisted of the acetate heterotrophic part (H-part) and the sulfur autotrophic part (S-part). Two cylindrical Plexiglas columns were established as the up-flow bioreactors. The H-part (5 cm inner diameter) contained elastic space packing (Yan Shanpc Co. Ltd., Beijing, China) with a packed height of 45 cm. The S-part (10 cm inner diameter) was filled with S0 granules (Yan Shanpc Co. Ltd., Beijing, China) of 2e4 mm diameter with a packed height of 37 cm. The working volumes of the two bioreactors were 0.84 L and 0.90 L, respectively. A peristaltic pump (Longer, BT100-2J, China) was used to feed synthetic water into the H-part and then into the S-part through three-way connection. This study simulated contaminated water with high concentration of perchlorate (ppm range) and co-existence nitrate. The synthetic water was prepared using tap water with NaClO4$H2O and NaNO3 as the contaminants. The influent concentrations of
ClO
4 and NO3 -N were 19.03e20.10 mg/L and 18.45e22.95 mg/L, respectively. Sodium acetate (CH3COONa) was selected as the sole exogenous electron donor and carbon source in the H-part. KH2PO4 was added to the feed as a source of phosphorous at a concentration of 3.18 mg/L. NaHCO3 (100.00 mg/L) was employed as buffer medium (Wan et al., 2017 & 2019). Other influent water parameters were as follows: SO2
was 80.74e99.43 mg/L; S2
was below 4 detection limit (0.02 mg/L); alkalinity was 199.57e349.41 mg/L; and pH was 7.55e8.09. The reactor was operated under a controlled temperature (26 ± 2  C). 2.2. Inoculum source and culture medium The reactor was inoculated with concentrated activated sludge from the Wulongkou wastewater treatment plant (Zhengzhou, China). The amounts of inoculated culture were approximately 6 g MLVSS for the acetate heterotrophic reactor and the sulfur autotrophic reactor. A standard basal medium was prepared by adding the following elements: NaNO3 (100.00 mg/L); NaClO4$H2O (100.00 mg/L); CH3COONa (874.00 mg/L, only in H-part); and NaHCO3 (100.00 mg/L). Phosphorus sources, such as K2HPO4$3H2O and KH2PO4, were added to the basal medium at 5.00 mg/L. The trace metal solution (1.00 mL/L) used in the experiment was improved based on previous studies (Ju et al., 2008; Wan et al., 2019). The two reactors were operated with an HRT of 8.0 h for 15 days respectively, before shifting to the heterotrophicautotrophic continuous experiment. 2.3. Experimental design After 15 days of acclimation, the reactors achieved stable conditions. In this condition, the fluctuation of effluent indicators (the
2
concentrations of ClO
4 , NO3 -N, SO4 and NPOC, pH value, alkalinity) were less than 5%. Then the heterotrophic-autotrophic

3

continuous experiment was performed. The experiment consisted of three stages with total HRT durations maintained at 4.0 h, 1.5 h and 1.0 h. Each operation stage lasted for more than 50 days. At each of the different HRTs, five acetate concentrations (210 mg/L, 140 mg/L, 100 mg/L, 70 mg/L and 35 mg/L) were tested. Table S1 lists the conditions applied during each experimental stage for the CHSAS. The effluent indicators were allowed to operate for 10 days before the next stage commenced. 2.4. Analytical methods All samples were filtered through a 0.22 mm membrane and
2
stored at 4  C until analysis. ClO
4 , NO3 and SO4 concentrations were measured by ion chromatography (ICS-2100, Dionex, America) equipped with a 4  250 mm AS20 analytical column and a 4  50 mm AG20 guard column. The eluent concentration was 25 mM KOH and the flow rate was 1.0 mL/min. The injection vol
ume was 25 mL, and the retention times of ClO
4 and NO3 were 20.70 and 6.66 min, respectively. The method detection limits of

ClO
4 and NO3 were 2 mg/L and 50 mg/L, respectively. NO2 was analyzed using the N-(1-naphthyl) ethylenediamine colorimetric method (TU-1900, Persee, China). Alkalinity was determined based on standard methods (China EPA, 2009). The pH was measured with a pH meter (PHS-3C, Leici, China). Non purgeable organic carbon (NPOC) was measured using a TOC analyzer (TOC-L CPN CN200, Shimadzu, Japan). 2.5. DNA extraction, Illumina MiSeq sequencing and data analysis Six microorganism samples were collected from the inoculated sludge (n ¼ 1) and the acclimated bacteria at different locations within the bioreactors (n ¼ 5). Specifically, bioreactor samples were taken during the steady-state period (HRT ¼ 1.5 h, acetate ¼ 35 mg/ L) from the H-part bottom (HB-1.5 h), H-part top (HT-1.5 h), S-part bottom (SB-1.5 h), S-part middle (SM-1.5 h) and S-part top (ST1.5 h). The samples were immediately stored at 4  C for further processing. DNA was extracted using an E.Z.N.ATM Mag-Bind Soil DNA Kit (OMEGA). The integrity of DNA was detected using 1% agarose gel electrophoresis. The V3-V4 region of the 16S rRNA gene was amplified using bacterial primers 341F and 805R. The PCR procedures were mixed with DNA and sequenced using the PE 300 strategy via Illumina MiSeq 2  300 platform (Sangon, China). The low quality reads containing one or more ambiguous bases were deleted, and the chimera sequences were removed using the UCHIME to ensure quality (Wan et al., 2016 & 2017). 3. Results and discussion 3.1. Removal performance of perchlorate and nitrate Previous studies have shown that both the HRT and carbon source are crucial elements for biodegradation of perchlorate and nitrate (Zhu et al., 2016). In this study, the performance of the CHSAS was investigated by varying the HRT from 4.0 h to 1.0 h and adjusting the concentration of acetate from 210 mg/L to 35 mg/L. According to Eq. (1), 71.31 mg/L acetate is required to reduce 20 mg/L NO
3 -N. In a previous study (Wan et al., 2018a), the optimal acetate/perchlorate (m/m) ratio was 1.78 (3-fold of the theoretical value calculated by Eq. (2)). That is, 35.60 mg/L (1.78  20 ¼ 35.60 mg/L) acetate is required to reduce 20 mg/L

ClO
4 . Therefore, the reduction of 20 mg/L ClO4 and NO3 -N requires 106.91 mg/L acetate. Consequently, an acetate concentration of 35 mg/L represents an insufficient carbon source and 210 mg/L is equivalent to an excessive carbon source. The removal performance of perchlorate and nitrate under

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D. Wan et al. / Water Research 165 (2019) 115004





Fig. 1. Influent and effluent (a) ClO
4 , (b) NO3 -N and NO2 -N variations of the CHSAS; (c) ClO4 and (d) NO3 removal efficiency in H-part under different operate conditions.

different operational condition is represented in Fig. 1. The results indicated that the removal efficiency of the H-part was dependent on the carbon source dosage. When the acetate concentration decreased from 210 mg/L to 35 mg/L at HRT 4.0 h, the ClO
4 concentration in the effluent of the H-part increased from 0.39 mg/L to 19.67 mg/L, and the NO
3 -N concentration in the effluent of the Hpart increased from 0.05 mg/L to 16.13 mg/L (Fig. 1a and b). The residual contaminants could be further reduced in the S-part. Un
der all operation conditions, the concentrations of ClO
4 and NO3 -N were below 1.18 mg/L and 0.20 mg/L, respectively, in final effluent (Fig. 1a and b). When the HRT gradually changed from 4.0 h to 1.0 h, the ClO
4 removal efficiency for the H-part was affected. When the concentration of acetate was fixed at 210 mg/L (Fig. 1c), the ClO
4 removal efficiency in H-part decreased to 80.18% as the HRT dropped to 1.0 h. Meanwhile, there was no obvious effect on NO
3 -N removal (99.52%; Fig. 1d). In brief, decreasing the carbon source dosage and shortening the HRT had a detrimental effect on the reduction of both perchlorate and nitrate in H-part but the nitrate was easier to reduce than perchlorate (Fig. 1c and d). Previous studies have found that the presence of nitrate inhibits perchlorate reductase enzyme, resulting in the decrease in perchlorate reduc
tion rate (Ucar et al., 2016b). Therefore, when ClO
4 and NO3 co
exist, NO3 is the favorable electron acceptor and is preferentially reduced by the microorganisms (Zhao et al., 2011a). Additionally, the decreased acetate concentration and shortened HRT resulted in the accumulation of NO
2 -N in H-part (up to 7.44 mg/L at an HRT of 1.0 h), whereas the S-part further reduced NO
2 -N and the concentration in the effluent was always lower than 0.10 mg/L (Fig. 1b).

Under all operating conditions, pollutants were removed efficiently in the CHSAS. When the acetate concentration was 35 mg/L under an HRT of 1.0 h, the removal efficiencies of perchlorate and nitrate in the H-part were only 1.82% and 33.78%, respectively. After further biological reduction by the S-part, the final removal efficiency of perchlorate and nitrate reached 97.80% and 99.12%, respectively. Thus, even with a short HRT and insufficient carbon source, the H-part and S-part cooperated to achieve high removal efficiencies of the co-existing perchlorate and nitrate. 3.2. SO2
4 generation and control In order to investigate SO2
4 generation in the combined system, the SO2
4 concentration was analyzed in each part. When the carbon source was sufficient, the heterotrophic microorganisms could reduce part of the sulfate. When the acetate concentration was in excess (210 mg/L) and the HRT was 4.0 h and 1.5 h, approximately 38.67% and 12.47% SO2
4 , respectively, was reduced in the H-part (Fig. 2a). At the same time, 6.09 mg/L S2
was detected in the H-part with 210 mg/L acetate and an HRT of 4.0 h. Under other operating conditions, the concentration of SO2
4 (84.15e101.00 mg/L) in the effluent of the H-part was close to that in the influent (80.74e97.28 mg/L). During all stages, the SO2
concentration in the S-part was 4 higher than the theoretical value calculated by Eqs. (3) and (4), indicating that S0 disproportionation had occurred (Ju et al., 2007). Hence, in this study, the generated SO2
4 in the S-part had three sources: perchlorate removal, nitrate removal and S0

D. Wan et al. / Water Research 165 (2019) 115004

2
Fig. 2. (a) Influent and effluent SO2
concentration of the 4 variations and effluent S CHSAS; (b) theoretical increase in SO2
4 concentration. The error bars represent the standard deviation of the samples for the last three days at each stage.

disproportionation. The theoretical increase in SO2
4 was calculated by the following formula:

CClO
4 ¼ ðCinf

ClO
4

CNO
3
N ¼ ðCinf CS ¼ Ceff

SO2
4


Ceff

NO
3
N


Cinf

Þ ClO
4


Ceff

SO2
4

 1:29 Þ NO
3
N

(6)  7:18

(7)


CClO
4
CNO
3
N

(8)

Where CClO
4 , CNO
3
N and CS are the theoretical sulfate concentrations (mg/L) produced by perchlorate reduction, nitrate reduction and S0 disproportionation, respectively. Cinf ClO
4 and Ceff ClO
4 are influent and effluent perchlorate concentrations (mg/L) in S-part, respectively. Cinf NO
3
N and Ceff NO
3
N are influent and effluent nitrate concentrations (mg/L) in S-part, respectively. Cinf Ceff

SO2
4

SO2
4

and

are influent and effluent sulfate concentrations (mg/L) in S-

part, respectively. The coefficients of 1.29 and 7.18 are determined by Eqs. (3) and (4), respectively. The theoretical increase in SO2
4 concentrations in the S-part under each operational condition, and their distribution, is shown in Fig. 2b. It should be noted that more SO2
4 was generated in the Spart when the acetate concentration in the H-part was lower. Under HRT of 4.0 h, when the acetate concentration was 210 mg/L, the theoretical increase in SO2
4 concentration was 51.27 mg/L. While when the acetate concentration decreased to 35 mg/L, the theoretical increase in SO2
4 concentration reached 227.62 mg/L. When the dosage of acetate in the H-part was reduced, the S-part should bear more removal load, resulting in more SO2
4 generation. In addition, the HRT also had an effect on the generated SO2
4 in the S-part, which was mainly reflected in the S0 disproportionation. When the HRT was shortened from 4.0 h to 1.0 h, with a fixed

5

acetate concentration in the H-part of 35 mg/L, the theoretical concentration of SO2
produced by S0 disproportionation 4 decreased from 87.26 mg/L to 29.94 mg/L and the corresponding 0 theoretical proportion of SO2
4 generated by S disproportionation decreased from 38.31% to 18.22%. Wan et al. (2017) found that when the HRT was long (>1.0 h), both nitrate and perchlorate decreased to low concentrations and S0 disproportionation was accelerated in the sulfur autotrophic system. A long HRT increases the contact time of water with sulfur, which promotes S0 disproportionation. Therefore, it is not recommended to use a CHSAS to reduce perchlorate and nitrate under long HRTs. Fig. S2 indicates the theoretical proportion of SO2
4 production in the S-part of the CHSAS under different operating conditions. With a lower acetate dosage in H-part, the SO2
4 theoretical pro
portion produced by the reduction of ClO
4 and NO3 gradually 2
increased, and the SO4 theoretical proportion produced by S0 disproportionation gradually decreased. As the acetate concentration was reduced from 210 mg/L to 35 mg/L at an HRT of 4.0 h, the

theoretical proportion of SO2
4 generated by ClO4 and NO3 reduction increased from 1.15% to 10.99% and 0.40% to 50.70%, respectively. In other words, the theoretical proportion of SO2
4 generated by S0 disproportionation decreased from 98.45% to 38.31%. This phenomenon is related to the influent nitrate and perchlorate concentrations of the S-part. As reported, S0 disproportionation is mainly accelerated when perchlorate is reduced to low concentrations, whereas it is restricted when nitrate is not completely removed (Wan et al., 2017). When the carbon source was sufficient (210 mg/L acetate), the pollutants in the H-part were almost completely reduced and the S-part mainly performed S0 disproportionation. Both the nitrate and perchlorate concentrations in the influent of the S-part were low (at an HRT ¼ 1.0 h, the concentra
tions of ClO
4 and NO3 -N in the S-part influent were 3.89 mg/L and 0.10 mg/L, respectively); thus, S0 disproportionation was accelerated. When the carbon source was insufficient (35 mg/L acetate), the perchlorate and nitrate reduction were mainly performed in the S-part. Both the nitrate and perchlorate concentrations in the influent of the S-part were high (at an HRT ¼ 1.0 h, the concentra
tions of ClO
4 and NO3 -N in the S-part influent were 19.35 mg/L and 14.93 mg/L, respectively); thus, S0 disproportionation could be restricted. The Gibb's free energies of perchlorate and nitrate reduction were calculated to be
2397.73 kJ/mol and
2595.95 kJ/mol, respectively, indicating that the reduction reaction was spontaneous. At the same time, the Gibb's free energy of nitrate reduction was less than that of perchlorate reduction, indicating that nitrate reduction was more likely to occur than perchlorate reduction. On the other hand, the Gibb's free energy of S0 disproportionation is 103.31 kJ/mol, indicating that the reaction is non-spontaneous process. However, S0 disproportionation always occurred in the process of sulfur autotrophic reduction of perchlorate (Sahu et al., 2009b; Boles et al., 2012; Wan et al., 2017 & 2019), indicating that only chemical thermodynamics analysis is not enough to predict the reaction direction and extent, and the involvement of microbial reaction complicates the reaction, which needs further study. S2
was detected in the S-part effluent as a product of S0 disproportionation. Fig. 2a shows that when the HRT was longer and the carbon source was sufficient (at an HRT ¼ 4.0 h, the concentrations of acetate was 210 mg/L), a higher concentration of S2
(14.42 mg/L) was detected in the S-part effluent. Adjusting the HRT and acetate concentration inhibited the S0 disproportionation reaction and also decreased the concentration of S2
in the S-part effluent. Thus, S0 disproportionation, an unfavorable side reaction, 2
generated excessive SO2
4 and S , thereby limiting the application

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D. Wan et al. / Water Research 165 (2019) 115004

of autotrophic sulfur reduction. However, in this combined system, a short HRT and low carbon source dosage effectively restricted S0 disproportionation in the S-part. 3.3. Residual organic carbon in the effluent The variation of NPOC in the influent and effluent from the Hpart and S-part under different operational conditions is shown in Fig. 3. The residual organic carbon in the H-part could be further decomposed and utilized in the S-part, and the secondary pollution could be effectively avoided by controlling the carbon source dosage and the HRT. Under an HRT ¼ 1.0 h, when the acetate concentration was 210 mg/L, the NPOC of the effluent from the H-part was 38.45 ± 2.90 mg/L and the residual carbon source in the final effluent (from the S-part) was 17.27 ± 3.68 mg/L, indicating that the organic secondary pollution in the final effluent was serious. When the acetate concentration was further reduced to 70 mg/L, the NPOC of the final effluent was less than 1.94 mg/L, indicating that the organic secondary pollution in the final effluent was avoided. Under a longer HRT (HRT ¼ 4.0 h), even at a high acetate dosage (210 mg/L), less organic carbon remained in the effluent of both the H-part and S-part (12.39 mg/L and 3.07 mg/L NPOC, respectively). It is speculated that a long HRT is beneficial because microorganisms can make full use of the carbon sources to reduce pollutants and sulfate, as well as maintain their own growth. Therefore, an appropriate HRT and organic carbon source can eliminate secondary pollution caused by residual organic carbon under the premise of guaranteeing a high removal efficiency of the reactor.

3.4. pH variation and alkalinity consumption The variation of pH and alkalinity in the influent and effluent under different operational conditions is shown in Fig. 4. Under all conditions, the influent pH was between 7.55 and 8.09. The pH of effluent from the H-part ranged from 8.09 to 8.77. According to Eqs.
(1) and (2), the heterotrophic reduction processes of ClO
4 and NO3
is accompanied by the generation of OH . Therefore, across all test stages, the pH of the effluent from the H-part was higher than that of the influent. Meanwhile, the pH of the effluent from the S-part was between 6.85 and 7.98, which was lower than the H-part throughout the operation time. Hþ was produced by sulfur auto
trophic reduction of ClO
4 and NO3 (Eqs. (3) and (4)). At the same 0 time, S disproportionation also generated Hþ (Eq. (5)). Those three sources of Hþ led to a low pH in the S-part. The influent alkalinity varied between 199.57 and 349.41 mg/L.
Since the heterotrophic reduction of ClO
4 and NO3 produced alkalinity in the H-part, the alkalinity of the effluent from the Hpart was higher than that of the influent. The decreased acetate concentration led to the decreased alkalinity production of the Hpart. When the acetate concentration was lowered from 210 mg/L to 35 mg/L at HRT 1.0 h, the generated alkalinity of the H-part decreased from 126.69 mg/L to 45.21 mg/L. In the S-part, theoretically, 1.34 mg CaCO3 alkalinity is consumed to reduce 1.0 mg ClO
4; 3.91 mg CaCO3 alkalinity is consumed to reduce 1.0 mg NO
3 -N; and 0 1.04 mg CaCO3 alkalinity is consumed to generate 1.0 mg SO2
4 by S disproportionation. When the HRT was 4.0 h and the acetate concentration was decreased from 210 mg/L to 35 mg/L, the consumed alkalinity increased from 56.93 mg/L to 183.62 mg/L, which was very close to the theoretical value (53.53 mg/L to 179.61 mg/L). When the acetate concentration was 35 mg/L and the HRT was shortened from 4.0 h to 1.0 h, the consumed alkalinity decreased from 183.62 mg/L to 139.89 mg/L. Therefore, the CHSAS is able to achieve balanced pH and alkalinity in the effluent when the carbon source dosage and HRT are adjusted. In summary, the optimal operating conditions of the CHSAS were at HRT ¼ 1.0 h and 70 mg/L acetate. Under such conditions,
the ClO
4 and NO3 removal efficiencies were 95.43% and 99.23%, respectively, and there was no accumulation of NO
2 -N in effluent (0.10 ± 0.03 mg/L). The effluent pH and alkalinity can maintain a balance with the influent. Additionally, the increased SO2
4 concentration was 94.43 mg/L and the SO2
concentration in final 4 effluent was 192.02 mg/L, which is lower than the Secondary Drinking Water Regulations of US EPA (250 mg/L). The concentration of residual organic carbon in the effluent was less than 1.83 mg/L, indicating that the secondary pollution was eliminated. Thus, in the CHSAS, an insufficient carbon source in the H-part avoids secondary pollution and the low load of the S-part reduces the production of sulfate, while at the same time balancing the pH and alkalinity of the effluent. 3.5. Microbial community analysis

Fig. 3. NPOC in influent and effluent from both H-part and S-part. The error bars represent the standard deviation of the samples for the last three days at each stage.

3.5.1. Microbial community diversity High-throughput sequencing technology was adopted to analyze six microorganism samples. The number of raw sequences of all samples was over 34,000. After quality control, the effective number of sequences exceeded 33,647. For ease of analysis and comparison, the number of sequences was normalized to 31,000. The coverage of all samples was greater than 99%, indicating that the probability of an undetected sequence was very low and that the sequencing results represented the actual microbial community the samples. The alpha diversity of the sample reflects the abundance and diversity of the microbial community and can be represented by the

D. Wan et al. / Water Research 165 (2019) 115004

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Fig. 4. The variations of (a) pH and (b) alkalinity in influent and effluent under different operate conditions. The error bars represent the standard deviation of the samples for the last three days at each stage.

Chao 1, ACE and Shannon indices, as well as the operational taxonomic units (OTUs), (Hwang et al., 2012). Table 1 summarizes the parameters associated with alpha diversity. The measured richness estimators of the inoculated sludge were the largest, indicating that this sample had the highest microbial abundance and diversity. Conversely, the abundance and diversity of microorganisms in the bioreactor was obviously lower than the inoculum. In the H-part, the abundance and diversity of the microbial community gradually
decreased along the height of the reactor. Because ClO
4 and NO3 were the only electron acceptors, some microorganisms that did not participate in the specific reduction reactions were gradually outcompeted, leading to a decreased microbial community abundance and diversity. In the S-part, the Shannon, Chao and ACE indices first increased and then decreased along the height of the reactor. When the HRT was 1.5 h and the acetate concentration was
35 mg/L, the concentrations of ClO
4 and NO3 in the S-part influent were 19.38 mg/L and 15.27 mg/L, respectively. It is inferred that the pollutant reduction reactions occurred mainly at the bottom of the

reactor and that the microbial community structure was simple; when the concentration of pollutants was reduced to a low level, S0 disproportionation was accompanied by reduction reactions in the middle of the reactor, which resulted in an increased microbial community abundance and diversity. S0 disproportionation mainly occurred at the top of the reactor due to the depletion of electron acceptors (Wan et al., 2017), resulting in a decreased community diversity. UniFrac analysis uses evolutionary information between sample sequences to compare microbial population differences in evolutionary lineages. UniFrac can be used for beta diversity analysis, that is, a comparative analysis between two samples by obtaining a UniFrac distance matrix (Lozupone et al., 2011). As shown in Fig. 5, heterotrophic and autotrophic bacteria each formed a cluster. The similarity between the bottom and the top part of the H-part was 82.68%. The similarity of the bottom and middle part of the S-part was 83.37%, while the similarity with the top part was 70.85%. The
ClO
4 and NO3 reduction processes mainly occur in the bottom and

Table 1 Numbers of raw, effective sequences reads, richness estimators (OTUs, Shannon, Chao 1 and ACE index) and coverage of each sample. Sample

Inoculated sludge HB-1.5 h HT-1.5 h SB-1.5 h SM-1.5 h ST-1.5 h

Sequencing Raw

Effective

Normalization

65404 34872 59137 47398 39032 51420

64840 33647 57128 45472 37582 49788

31000 31000 31000 31000 31000 31000

OTUs

Shannon index

Chao 1 index

ACE index

Coverage (%)

1900 1263 1209 937 1023 1035

5.99 4.66 4.10 3.93 4.05 3.71

2250.60 1644.26 1598.63 1367.80 1533.06 1527.79

2312.91 1693.87 1696.32 1642.36 1913.43 1819.66

100 99 99 99 99 99

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D. Wan et al. / Water Research 165 (2019) 115004

Fig. 5. Weighted UniFrac cluster analysis.

middle part of the S-part; therefore, the similarity was higher than the top part. Compared with the S-part, the H-part had a higher similarity with the inoculated sludge (58.05%). This is likely because the inoculated sludge comes from a heterotrophic environment. 3.5.2. Bacterial taxonomic identification The results of the (a) taxonomic tree and (b) taxonomic classification at the genus level are shown in Fig. 6. The results indicated that the microbial community was mainly composed of Proteobacteria, Bacteroidetes and Chloroflexi. Fig. S3 shows the taxonomic classification at phylum level for each sample. Proteobacteria, Bacteroidetes and Chloroflexi were the dominant bacteria in the microbial samples of the H-part. The abundance of Proteobacteria increased from 62.22% to 70.49% along the height of the reactor. Many of the confirmed perchlorate-reducing and denitrifying bacteria belong to Proteobacteria (Zhu et al., 2016). Under heterotrophic conditions, the rapid growth rate of microorganisms leads to an increased abundance of Proteobacteria. The abundance of Chloroflexi increased from 5.24% to 5.75%. In contrast, the abundance of Bacteroidetes decreased from 19.64% to 14.83% (Fig. S3). In the S-part, Proteobacteria had an absolute advantage and its abundance decreased from 86.99% (bottom) to 84.45% (middle) to 57.45% (top) along the height of the reactor. As the concentration of
ClO
4 and NO3 gradually decreased, the electron acceptors were gradually depleted, leading to a gradual decrease in the proportion of Proteobacteria. Similarly, the abundance of Bacteroidetes and Chloroflexi gradually decreased from 3.43% to 2.66% and 4.01% to 2.74%, respectively, along the height of reactor. The enrichment of Bacteroidetes and Chloroflexi has been described in previous studies on sulfur autotrophic reduction of perchlorate and nitrate (Zhang et al., 2015, 2017). Significantly, the abundance of Chlorobi, which may be related to S0 disproportionation, increased from 0.94% to 30.84% along the height of the reactor. Analysis at the genus level can further understand the function of microorganisms. Fig. 6b summarizes the most representative genera (abundance > 1%). In the H-part, Thauera was the most dominant genus with an abundance greater than 31%. Thauera and Comamonas can use organic carbon sources to reduce nitrate under anaerobic conditions (Etchebehere et al., 2001; Mechichi et al., 2005). Yun et al. (2018) claims that Thauera and Comamonas are versatile pollutant-reducing bacteria; therefore, it is speculated that they have the ability to reduce perchlorate in this study. Pseudomonas can use acetate as an electron donor for the reduction of perchlorate and nitrate to obtain energy under anoxic conditions (Shah, 2014; Liu et al., 2018). In summary, Thauera, Comamonas and Pseudomonas are effective denitrifying bacteria (DB)/perchlorate reducing bacteria (PRB) in this study. In addition, the abundance of Owenweeksia, which belong to the phylum Bacteroidetes (Lau et al., 2005), reached 6.89% in the H-part; however, whether it played a

Fig. 6. The (a) taxonomic tree and (b) taxonomic classification at genus level of the six test samples. Communities making up <1% of the total composition across all the samples were classified as “others”.

positive role in the degradation of perchlorate and nitrate requires further study. The dominant genera in the S-part were Ferritrophicum, Thiobacillus and Sulfurospirillum. Wan et al. (2017) speculated that Ferritrophicum acts as a DB in sulfur autotrophic reduction perchlorate and nitrate systems. In this study, the maximum abundance of Ferritrophicum reached 23.97%, suggesting that Ferritrophicum may be related to the reduction of perchlorate and nitrate (DB/PRB). The genera Sulfurospirillum and Sulfurovum have the ability to oxidize sulfides while reducing nitrate or perchlorate (Wang et al., 2015; Zhang et al., 2017). Geobacter has been identified in previous studies on the microbial reduction of nitrate or

D. Wan et al. / Water Research 165 (2019) 115004

perchlorate (Wen et al., 2017; Wan et al., 2018b). In this study, its abundance was maintained at approximately 4.83% in the reactor and it is speculated to be a DB/PRB. The abundances of Thiobacillus, Sulfurimonas and Sulfurisoma decreased along the reactor height from 11.11% to 0.71%, 4.95%e0.45% and 7.89%e3.02%, respectively. They are the common DB that use elemental sulfur, sulfides and
thiosulfate to reduce NO
3 and NO2 (Kelly and Wood, 2000; Zhang et al., 2009; Kojima and Fukui, 2014). Some nitrate reducers can use perchlorate as an electron acceptor (Srinivasan and Sorial, 2009), thereby indicating that, in this study, Thiobacillus, Sulfurimonas and Sulfurisoma have the ability to simultaneously reduce perchlorate and nitrate (DB/PRB). Desulfocapsa is sulfate-reducing bacteria (SRB) that reduce sulfur oxides, such as sulfates, sulfites, thiosulfates, and S0, to hydrogen sulfide (Abed et al., 2011). In this study, the maximum abundance of Desulfocapsa was 8.82% in middle of the reactor. The excess theoretical value of SO2
4 produced by the S-part was attributed to the presence of the genus Chlorobaculum. Chlorobaculum tepidum is a green sulfur bacterium belonging to the Chlorobi phylum, and has the ability to oxidize sulfide and S0 to SO2
4 (Rodriguez et al., 2011). Green sulfur bacteria are specialized anaerobic photoautotrophic bacteria, and their growth requires the simultaneous presence of light and sulfide (Marschall et al., 2010). The S-part was an anaerobic environment with the presence of S0 and the reactor was exposed to natural light, providing the necessary conditions for the growth of Chlorobaculum. The abundance of Chlorobaculum increased dramatically from 0.50% to 28.29% at the top part of reactor. Wan et al. (2017) found that S0 disproportionation notably occurs at the top of reactors during sulfur autotrophic reduction of perchlorate and nitrate when accompanied by an increase of Chloroobaculum. Therefore, it is considered that Chlorobaculum is closely related to S0 disproportionation. 4. Conclusion The effective removal of perchlorate and nitrate by microorganisms was achieved in the CHSAS, and the removal efficiencies of perchlorate and nitrate were higher than 93.96%. Shortening the HRT and decreasing the influent acetate concentration inhibited S0 disproportionation, thereby reducing the production of SO2
4 . The alkalinity and pH of the effluent were balanced with the influent by adjusting the influent acetate concentration and the HRT. At the same time, the S-part further reduced the pollutants and the residual organic carbon from the H-part, eliminated the secondary pollution and achieved synergism. Microbial community analysis showed that the perchlorate and nitrate reducing bacteria of the Hpart were different from those of the S-part. The appearance of Chlorobaculum was related to the occurrence of S0 disproportionation. This study systematically investigated the reduction performance of CHSAS for high concentration perchlorate (ppm range) pollution with the coexistence of nitrate occurred in the water, establishing a practical foundation for treatment of potential water contaminated by perchlorate and nitrate with high concentrations (ppm range) in the future. Declaration of competing interest 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. Acknowledgements This work was supported by the National Natural Science Foundation of China (NO. 51878251, 51778054); and the Young

9

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