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A start-up strategy for high-rate partial nitritation based on DO-HRT control
Accepted Manuscript Title: A start-up strategy for high-rate partial nitritation based on DO-HRT control Author: Lan Wang Ping Zheng Ghulam Abbas Jian Yang Yajuan Xing Wei Li Ru Wang Liangwei Deng Dan Zheng PII: DOI: Reference:
S1359-5113(15)30125-2 http://dx.doi.org/doi:10.1016/j.procbio.2015.11.016 PRBI 10562
To appear in:
Process Biochemistry
Received date: Revised date: Accepted date:
26-8-2015 6-11-2015 14-11-2015
Please cite this article as: Wang Lan, Zheng Ping, Abbas Ghulam, Yang Jian, Xing Yajuan, Li Wei, Wang Ru, Deng Liangwei, Zheng Dan.A start-up strategy for high-rate partial nitritation based on DO-HRT control.Process Biochemistry http://dx.doi.org/10.1016/j.procbio.2015.11.016 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.
A start-up strategy for high-rate partial nitritation based on DOHRT control Lan Wangb, c, Ping Zhenga* [email protected], Ghulam Abbasa, Jian Yangd, Yajuan Xinga, Wei Lia, Ru Wanga, Liangwei Dengb,c, Dan Zhengb,c a
Department of Environmental Engineering, Zhejiang University, Hangzhou, 310058,
China b
c
Biogas Institute of Ministry of Agriculture, Chengdu 610041, China
Laboratory of Development and Application of Rural Renewable Energy, Chengdu
610041, China d
State Key Laboratory of Plant Physiology and Biochemistry, College of Life Science,
Zhejiang University, Hangzhou, 310058, China *
Corresponding author: Tel: +86 571 86971709.
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Graphical Abstract
2
Highlights
The PN was started up with ammonium conversion rate of 4.74 kg-N m-3 d-1.
The RSM with CCD was applied to optimize the parameters of DO and HRT.
Good PN performance was ascribed to the high sludge activity (3.69 g-N g-1 VSS d-1).
The transition of predominant microorganisms was investigated by DGGE.
Nitrosomonas was predominant functional microorganisms.
Abstract Partial nitritation (PN) is the controllable bottleneck of the combined PN- anaerobic ammonium oxidation process, because it has a low nitrogen conversion rate. In this study, a “co-culture and screening” technology was developed to start up PN, and a dual dissolved oxygen-hydraulic retention time (DO-HRT) control strategy was developed to regulate the NH4+-N/NO2--N ratio. The results showed that PN could be successfully started up and it had a high nitrogen loading rate and ammonium conversion rate (9.42 kg-N m-3 d-1 and 4.74 kg-N m-3 d-1), respectively. A response surface methodology (RSM) with a central composite design (CCD) was used to optimize the parameters of DO and HRT. When DO and HRT satisfied the relationships 0.66 - 0.5 • DO ≤ HRT ≤ 0.79 - 0.53 • DO and 0.5 mg L-1 ≤ DO ≤ 0.75 mg L-1, the performance of PN was excellent with an NH4+-N/NO2--N ratio ranging from 1:1.04 to 1:1.47, an ammonium conversion efficiency of 53.6%–62.1% and a nitrite accumulation efficiency greater than 90%. The excellent performance of PN 3
process was attributed to the high specific activity of sludge (3.69 g-N g-1 VSS d-1), the predominance of ammonia-oxidizing bacteria, Nitrosomonas, and the inhibition of nitrite-oxidizing bacteria, Nitrospira.
Keywords: Partial nitritation; Start-up strategy; Ammonium-nitrite ratio regulation; Microbial community; DO-HRT control
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1. Introduction The nitrogen compounds of most wastewaters are in the form of ammonium (NH4+), therefore ammonium removal or conversion becomes the key step for nitrogen removal [1]. In wastewater treatment plants, the traditional nitrification– denitrification process is the most widely used technology for nitrogen removal [2]. However, nitrification–denitrification is costly due to large energy demand for aeration, the need for external carbon addition and high sludge disposal costs [3]. Increasingly, wastewater treatment facilities are seeking innovative and cost-effective processes for nitrogen removal. Partial nitritation (PN), namely the oxidation of NH4+ to nitrite (NO2-) by ammonia-oxidizing microbes, decreases sludge production by 33%–35% and oxygen consumption by 25%, compared with traditional nitrification [4]. Coupled with an anaerobic ammonium oxidation (Anammox) process, which oxidizes NH4+ using NO2- to produce elemental nitrogen gas and a small amount of nitrate under anoxic conditions, PN can reduce oxygen consumption further because only approximately 60% of NH4+ must be converted to NO2- [5]. Additionally, in the PN-Anammox process, nitrogen removal from wastewaters having a low carbon-tonitrogen ratio can be facilitated, thereby avoiding the dependence on costly external organic carbon for nitrogen removal [6]. Traditional nitrification occurs through a series of microbial oxidation reactions performed by ammonia-oxidizing bacteria (AOB) and nitrite-oxidizing bacteria (NOB). In contrast, PN only involves the ammonia oxidation performed by AOB. Therefore, NOB have to be discharged from, or inhibited in the PN system [7]. Due to 5
similar physiological properties and a food chain relationship between AOB and NOB, it is difficult to separate these microbes. Thus, inhibition of NOB activity has been the main strategy for initiating PN; however, this approach adversely affects AOB activity and leads to inefficient PN. PN is a pretreatment for Anammox, which supplies the nitrite to Anammox bacteria. PN has achieved a maximum nitrogen conversion rate of only 3.3 kg-N m-3 day-1 [8] and it is far lower than the maximum nitrogen conversion rate of Anammox (74.3 kg-N m-3 day-1) [9, 10].Thus, PN limited the performance of combined PN-Anammox process. In this study, a “co-culture and screening” technology was developed to enhance the performance of PN. This technology involved two phases, the “co-culture” phase and the “screening” phase. In the “coculture” phase, AOB and NOB were enriched together without any inhibition measurement of NOB, and in the “screening” phase, NOB were inhibited and washed out by using “DO-HRT” control strategy (to be discussed in the following section ). Anammox bacteria require substrates with a suitable NH4+-N/NO2--N ratio. However, it is difficult to accumulate nitrite and obtain a suitable NH4+-N/NO2--N ratio in PN due to the physical similarities and mutual relationship between AOB and NOB [11]. To date, the main means of regulating the NH4+-N/NO2--N ratio in PN have included maintaining a low dissolved oxygen (DO) concentration [12], a high concentration of free ammonia (NH3) and nitrous acid (HNO2) [13], a high temperature [14], a short hydraulic retention time (HRT) [15] and addition of selective chemicals to inhibit NOB growth [16]. Among these techniques, maintenance of either a low DO concentration or a short HRT has been preferred due to economical 6
aspects and practicality [15, 17]. No information is available in the literature about that whether the combined control of DO and HRT to regulate the NH4+-N/NO2--N ratio for PN is more efficient and convenient. In the present study, a dual “DO-HRT” control strategy was developed as a means of obtaining a suitable NH4+-N/NO2--N ratio in PN. This strategy involved two steps, inhibiting NOB activity by limiting DO concentration and then washing out NOB by shortening HRT gradually in “screening” phase. The “co-culture and screening” technology could retain AOB and NOB communities with a high activity and cause a high specific ammonium uptake rate in “co-culture” phase, which laid a solid foundation for the high-rate performance of PN. And the “DO-HRT” strategy gradually inhibited and washed out NOB community and accomplished partial nitritation. The objective of the study was to explore the feasibility and working mechanism for the initiation of a high-rate PN system using two new techniques, “co-culture and screening” and “DO-HRT” control. The parameters for initiating PN process would lay a solid foundation for the development and application of high-rate PN process, and the information of microbial ecology in PN system would broaden the understanding about the necessity of using these two new techniques. 2. Materials and methods 2.1 Experimental set-up The experimental system is illustrated in Fig. 1. A 4 L internal loop air-lift reactor with an effective volume of 2 L was used. A synthetic wastewater was continuously pumped into the bottom of the reactor and air was simultaneously sparged from the 7
bottom of the reactor to supply oxygen and fluidize the biomass. The DO was regulated by adjusting air flow rate and was monitored by DO meter according to nitrogen loading rate and HRT of the reactor. And DO values of different periods were listed in Table 1. The temperature was controlled at 30 ± 1 oC and the pH was kept at 7.5 by an automatic pH controller using pumps connected to controllers with 2 M hydrochloric acid (HCl) and 2 M sodium hydroxide (NaOH). 0.5 L aerobic activated sludge taken from a municipal sewage treatment plant in Hangzhou, China was used for inoculation of the reactor. 2.2 Synthetic wastewater Synthetic wastewater contains 2 g L-1 NaHCO3, 0.5 g L-1 NH4Cl and mineral solutions. The composition of mineral solutions was (g L-1): 0.01 KH2PO4, 0.004 CaCl2.H2O, 0.3 MgSO4·7H2O and trace elements of solution described by Tang et al. [18]. The ammonium concentration was approximately 130.8 mg-N L-1. 2.3 Analytical methods The volatile suspended solids (VSS) and the concentrations of ammonium, nitrite and nitrate were determined using standard procedures [19]. The DO concentration was measured by a SevenGo pro SG9 meter (METLER TOLEDO, Switzerland). The air flow rate was measured by a LZB-4 glass tube rotameter (Zhejiang Yuyao Instrument Factory, China). 2.4 Batch activity test Batch experiments were conducted to determine the specific aerobic ammonia-
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oxidizing activity of PN sludge. The reactor from which sludge was taken for analysis had a volumetric nitrogen loading rate (NLR, the amount of nitrogen compounds added to the PN system per effective volume of reactor per day) of 9.42 kg-N m-3 day1
, an ammonium conversion efficiency (ACE, ammonium concentration in effluent
divided by ammonium concentration in influent) of 52% and a nitrite accumulation efficiency (NIAE, nitrite accumulation rate divided by ammonium conversion rate) of 99%. The sludge was rinsed with the phosphate buffer until no NH4+, NO2- and NO3was detected. A 150 mL Erlenmeyer flask was used for batch activity test. A total of 16.35–523.2 mg-N L-1 NH4Cl solution, 1 mL mineral solution (as used in the synthetic wastewater), 0.1 g VSS, 2 g L-1 NaHCO3 and distilled water was added to 100 mL in each flask. During the experiment, the air was sparged into each flask and DO concentration was controlled at more than 3.0 mg L-1 by adjusting the air flow rate. The pH was controlled at about 7.5 by using the phosphate buffer. The flasks were incubated at 30 ± 1 °C on a shaking table operating at 180 rpm. The samples of the liquor phase were taken every 1–5 hours and filtered over a 0.45 μm filter for the determination of ammonium, nitrite and nitrate. Every test was performed in triplicate. 2.5 Response surface methodology (RSM) In this study, the effect of DO concentration and HRT on the ACE and NIAE of PN was investigated by employing response surface methodology with a central composite design [20]. Design Expert software version V8.0.5.0 (STAT-EASE Inc., Minneapolis, USA) was used for the experimental design and statistical tests. The values of the independent input variables (DO concentration and HRT) were 0.3–0.9 9
mg L-1 and 0.315–0.63 h, respectively. The ACE and NIAE were selected as the dependent output variables. Statistical analysis involving the quadratic models for the ACE and NIAE was performed with the F-test for analysis of variance (ANOVA). Three-dimensional response surfaces and two-dimensional contour plots for the output values of ACE and NIAE were used to show the models obtained from regression analysis. 2.6 PCR-DGGE test Inoculum, nitrification sludge and PN sludge were taken from the reactor on days 0, 130 and 200, respectively, and stored at −80 oC. Genomic DNA was extracted from the samples using the Fast DNA SPIN kit for soil (MP Biochemical, USA). PCRDGGE (denaturing gradient gel electrophoresis) test were performed following the protocol developed recently by Xing et al. (2013). A 468 bp 16S rRNA gene was obtained using bacterial primer set BAC 338F-BAC 805R, and a 40-bp GC clamp was added to the 5′ end of BAC 338F [21]. The PCR conditions were as described by O’Reilly et al. [21]. The PCR product was purified using an Agarose Gel DNA Purification Kit Ver. 2.0 (Takara, Japan), and was separated by DGGE using the DCodeTM Universal Mutation Detection system (Bio-Rad, USA) on 8% (w/v) polyacrylamide gel containing a 20%–50% gradient of denaturant. Electrophoresis was run at 200 V for 300 min (with an initial electrophoresis at 60 V for 30 min) and at 60 oC in 1×TAE buffer. The gel was stained by silver and bands were visualized using Gel Doc-XR (Bio-Rad, USA). The bands excised from the gels were reamplified with the same DGGE primers (without GC clamp) and cloned [22]. 10
A 16S rRNA gene fragment was obtained using archaeal primer set Parch519fARC915r, and a 40-bp GC clamp was added to the 5′ end of ARC915r [23]. The PCR conditions were as described by Berdjeb et al. [23]. 2.7 Cloning and sequencing The cloning of PCR products was performed as described by Hu et al. [24] and the clones were named as DGGE BAC-1 to DGGE BAC-24. The sequences obtained were compared with sequences deposited in GenBank using the BLAST program (http://www.ncbi.nlm.nih.gov/BLAST). Sequences and their closest matches were aligned with MEGA5.1. The phylogenetic tree was constructed by neighbor-joining methods with 1000 resamplings to produce Bootstrap values [25]. The sequences reported in this study have been deposited in GenBank with the accession numbers: KP342430-KP342450. 3. Results and discussion 3.1 Performance of nitrification phase The “co-culture” phase of the “co-culture and screening” technique was observed first. The volumetric NLR was gradually increased by shortening HRT at an influent NH4+-N concentration of 130.8 mg L-1 and DO concentration of 3.0 mg L-1 (Table 1). The NLR, ammonium conversion rate (ACR, the amount of ammonium consumed by microorganisms per effective volume of reactor per day) and nitrate accumulation rate (NAAR, the amount of nitrate produced by microorganisms per effective volume per day) are shown in Fig. 2. 11
During the first 128 days, as NLR was increased from 0.16 ± 0.002 kg-N m-3 d-1 to 7.09 ± 0.31 kg-N m-3 day-1, ACR increased from 0.16 ± 0.002 kg-N m-3 d-1 to 6.81 ± 0.24 kg-N m-3 d-1 and NAAR increased from 0.15 ± 0.008 kg-N m-3 d-1 to 6.75 ± 0.65 kg-N m-3 d-1, with HRT shortening from 20.16 h to 0.42 h. During days 129–140, HRT was further reduced to 0.31 h and NLR was further increased to 9.04 ± 0.24 kgN m-3 d-1, however the ACR and NAAR experienced slow increasing to 7.19 ± 0.11 kg-N m-3 d-1 and 7.15 ± 0.16 kg-N m-3 d-1, respectively. Thus, in the “co-culture” phase, the maximum NLR and ACR reached 9.04 ± 0.24 kg-N m-3 d-1 and 7.19 ± 0.11 kg-N m-3 d-1, respectively, and the ammonium was almost completely converted to nitrate. To our knowledge, this performance of nitrification was superior to the performance of other nitrification and PN processes previously reported in the literature [1, 26, 27]. The high-rate nitrification retained high activity AOB communities and provided solid foundation for high-rate PN. 3.2 Performance of PN phase After 140 days of operation, the performance of the “screening” phase of the “coculturing and screening” technique was investigated. The DO-HRT control strategy was used, which involved gradually shortening HRT at a fixed influent NH4+-N concentration of 130.8 mg L-1 and at a limited DO concentration of 0.3–0.6 mg L-1 (Table 1). The results are shown in Fig. 3. At day 161, NLR increased from 2.73 ± 0.16 kg-N m-3 d-1 to 4.95 ± 0.14 kg-N m-3 d-1 as HRT was reduced from 1.26 h to 0.63 h (Fig. 3A). During days 150–176, the ACE gradually decreased from 82.7 ± 4.1% to 48.5 ± 5.6% and the NIAE gradually 12
increased from 50% to a range of 90%–100% (Fig. 3B), because that the decrease of DO from more than 3.0 mg L-1 to 0.26-0.56 mg L-1 (Table 1) inhibited the activity of AOB and NOB. During days 177–205, NLR increased from 4.95 ± 0.14 kg-N m-3 d-1 to 9.42 ± 0.8 kg-N m-3 d-1 and ACR increased from 2.40 ± 0.38 kg-N m-3 d-1 to 4.74 ± 0.41 kg-N m-3 d-1 as HRT was reduced to 0.31 h. The effluent NH4+-N/NO2--N ratio stayed at 1:1 while ACE reached 50%–60% and NIAE exceeded 90% (Fig. 3B). These results demonstrated that nitrification was successfully transformed to PN by applying the DO-HRT control strategy. The high-rate nitrification enriched AOB and NOB communities with high activities and high substrates conversion rate, and then the initiation of PN washed out NOB communities with DO-HRT control. It laid a solid foundation for high-rate PN process with the maximum NLR and ACR of 9.42 ± 0.8 kg-N m-3 d-1 and 4.74 ± 0.41 kg-N m-3 d-1, respectively, which reached the top levels reported in the literature [1, 26, 27]. 3.3 Effect of DO and HRT on PN The DO concentration and HRT are the key parameters for the DO-HRT control strategy. In this study, the effect of DO concentration and HRT on the ACE and NIAE of PN was investigated by employing RSM with a central composite design [20]. The results for ACE are shown in Table 2 and those for NIAE are shown in Table 3. Threedimensional response surfaces and two-dimensional contour plots for the output values of ACE and NIAE are shown in Fig. 4 and Fig. 5, respectively. 3.3.1 ACE The equation for the coded variables in the quadratic models fitting the experimental 13
results for the ACE is shown in Eq. (1). ACE = -1.308 + 42.352 × DO + 80.850 × HRT
(1)
The ANOVA for the response surface linear model of ACE as a function of DO and HRT (Eq. (1)) is shown in Table 2. The model F-value of 47.19 implies that the model is significant, as there is less than a 0.01% chance that a “Model F-Value” this large could occur at random. Thus, the model is suitable for evaluating the effects on ACE of different combinations of DO and HRT. The Lack-of-Fit is not significant relative to the pure error and there is a 7.69% chance that the calculated “Lack-of-Fit F-Value” could occur at random (Lack-of-Fit F-value = 12.33, Lack-of-Fit p-value = 0.0769). A non-significant Lack-of-Fit is desirable. The R2 regression coefficient was found to be 0.9219, indicating that the actual and predicted values for ACE are in close agreement. The value of “Prob > F” less than 0.0500 indicates that the model terms are significant, i.e., that DO and HRT are significant model terms (p-value = 0.0001). Hence, DO and HRT showed independent effects on ACE of PN, but did not show an interactive effect. Fig. 4 illustrates contour plots and the three-dimensional response surface for ACE with respect to DO concentration versus HRT. In Fig. 4, the steeper the curve, the larger the effect of factors on ACE; similarly, the darker the color of the response surface (i.e., the longer the absorption wavelength), the higher the ACE. A simple linear relation was found between ACE and both DO and HRT. The ACE increased as DO and HRT increased (Fig. 4B). The highest ACE of 85% was achieved at a DO concentration of 0.9 mg L-1 and a HRT of 0.63 h. However, when using PN as a 14
pretreatment for Anammox, only 56.9% of ammonium needs to be oxidized to nitrite [26]. Therefore, if the range of 53.6%–62.1% was regarded as the optimum range for ACE, this goal was achieved when DO and HRT satisfied the relationships 0.66 - 0.5 • DO ≤ HRT ≤ 0.79 - 0.53 • DO, and 0.3 mg L-1 ≤ DO ≤ 0.9 mg L-1 (Fig. 4A). 3.3.2 NIAE The equation for the coded variables in the quadratic models fitting the experimental results for the NIAE is shown in Eq. (2). NIAE = -16.853 + 315.400 × DO + 116.640 × HRT - 223.438 × DO × HRT - 200.984 × DO2 - 15.666 × HRT2
(2)
The ANOVA for the response surface quadratic model of NIAE as a function of DO and HRT (Eq. (2)) is shown in Table 3. The model F-value of 31.20 implies that the model is significant because there is less than a 0.09% chance that a “Model F-Value” this large could occur at random. Thus, the model is suitable for evaluating the effects on NIAE of different combinations of DO and HRT. The Lack-of-Fit is not significant relative to the pure error, and there is a 38.19% chance that the “Lack-of-Fit F-Value” could occur at random (Lack-of-Fit F-value = 1.79, Lack-of-Fit p-value = 0.3819). The R2 regression coefficient was found to be 0.9689, indicating that the actual and predicted values for NIAE are in close agreement. The value of “Prob > F” less than 0.0500 indicates that model terms are significant. In this case, “A-DO” (pvalue=0.0024), “B-HRT” (p-value=0.0257), “AB” (p-value=0.0057) and “A2” (pvalue=0.0002) are significant model terms. Hence, the single factor effect and interactive effect of DO and HRT on NIAE of PN were significant. 15
Fig. 5 illustrates contour plots and the three-dimensional response surface for NIAE with respect to DO versus HRT. A quadratic relation was found between NIAE and both DO and HRT. The highest value of NIAE was achieved at multiple DO concentrations (Fig. 5B). If an NIAE value greater than 90% was regarded as the optimum range, this goal was reached when the DO concentration was in the range of 0.5–0.75 mg L-1 (Fig. 5A). Previous research has shown that the half saturation constant (Km) for oxygen of AOB (Km = 0.2–0.4 mg-O2 L-1) is significantly lower than that of NOB (Km = 1.2–1.5 mg-O2 L-1) and the specific affinity for oxygen of AOB is generally higher than that of NOB [28]. Hence, a limited DO concentration can inhibit NOB activity and lead to better growth of AOB compared with that of NOB [15]. Furthermore, a relatively short HRT can successfully remove (i.e., wash out) NOB and cause nitrite to accumulate. Conversely, if the HRT is too long, NOB will not be successfully washed out, even if the DO concentration is controlled within the optimum range. Too long a HRT would promote the conversion of nitrite to nitrate and a decrease in NIAE. Hence, Fig. 5B indicates that NIAE decreased with the increase of HRT when the DO concentration was higher than 0.5 mg L-1. However, an excessively short HRT increased NLR, which led to a low DO concentration (<0.5 mg L-1) and an insufficient oxygen supply for AOB. Furthermore, the imposition of a low DO concentration on denitrifying microbes and Anammox bacteria could in turn enhance the conversion of nitrite to nitrogen, causing a decrease in NIAE. As shown in Fig. 5B, NIAE decreased as HRT decreased when the DO concentration was lower than the optimum range (0.5 mg L-1). 16
Previous studies showed that the influent NH4+-N/NO2--N ratio of 1:1.32 was optimal for Anammox process, hence it was also optimal for effluent of PN process [29]. The foregoing results indicated that the effects of DO concentration and HRT on ACE and NIAE were significant.When DO and HRT satisfied the relationships 0.66 0.5 • DO ≤ HRT ≤ 0.79 - 0.53 • DO, and 0.5 mg L-1 ≤ DO ≤ 0.75 mg L-1, the performance of PN was excellent with an NH4+-N/NO2--N ratio ranging from 1:1.04 to 1:1.47, an ammonium conversion efficiency of 53.6%–62.1%, and a nitrite accumulation efficiency greater than 90%. This DO range was higher than DO values reported in many other studies with limited DO as the control strategy, for instance lower than 0.5 mg L-1 in the study of Bae et al. [27] and 0.5 mg L-1 in the study of Zhang et al. [26], which may be the reason for high ammonium conversion rate. And this HRT range was lower than many other studies with HRT as control strategy, for instance 20 h in the study of Li et al. [15], 21 h in the study of Bae Bae et al. [27] and 4 h in the study of Zhang et al. [26], which may be the reason for high nitrite accumulation efficiency without the strategy of high concentration of free ammonia, inorganic carbon and high pH. 3.4 Specific ammonium conversion activity of sludge The results of batch activity tests are presented in Fig. 6. These tests showed that the specific AOB activity of PN sludge has a significant influence on the performance of PN. Results suggested that the Haldane model was suitable (correlation coefficient of 0.98) for describing the kinetic ammonium conversion characteristics of PN sludge. Based on the Haldane model, the maximum specific ammonium conversion rate 17
reached to 3.69 g-N g-1 VSS d-1, which was among the highest rates previously reported in the literature (from 2.76 g-N g-1 VSS d-1 reported by [30] to 3.6 g-N g-1 VSS d-1 reported by [31]). In addition, the half saturation constant and substrate inhibition constant of ammonium were 42.98 mg L-1 and 714.89 mg L-1, respectively. These values indicated that the PN sludge had a high tolerance for both low and high concentrations of ammonium. Therefore, the high specific ammonium conversion activity and the high tolerance to different ammonium concentrations of PN sludge laid a solid foundation for the excellent performance of the PN process. 3.5 Functional microorganisms Samples of inoculum, nitrification sludge and partial nitritation sludge were taken from the reactor to evaluate the microbial communities and analyze the microbial mechanisms responsible for the transition of nitrification to PN. The analysis of the l6S rRNA gene of archaea indicated that no archaea were detected in the samples. The bacterial community structures of the inoculum (lane 1), nitrification sludge (lane 2) and partial nitritation sludge (lane 3) were explored by PCR-DGGE analysis of l6S rRNA fragment genes. The DGGE profile and phylogenetic tree of 24 DGGE bands are shown in Fig. 7. In the three periods of microbial changes represented by inoculum, nitrification sludge and PN sludge, all the DGGE sequences were contained in six phyla of the bacterial domain: Betaproteobacteria, Nitrospira, Gemmatimonadetes, Actinobacteria, Bacteroidetes and Alphaproteobacteria. The Betaproteobacteria of the I-band region on the DGGE gel was the most abundant bacterial group (Fig. 7). Niastella (DGGE BAC-1) and Gemmatimonas aurantiaca 18
(DGGE BAC-5) were detected in the inoculum and Gemmatimonas aurantiaca was a polyphosphate-accumulating bacteira [32], but they were not detected in nitrification and PN sludge. Cryobacterium (DGGE BAC-17) and Hyphomicrobium (DGGE BAC-8 and 19) were detected in nitrification sludge. Lewinella were detected in PN sludge. Nitrosospira (DGGE BAC-4 in the II-band region) and Nitrosomonas (DGGE BAC-14 and 22 in the III-band region) were the dominant functional microorganism groups. As the operational time of the reactor increased, Nitrosospira were gradually washed out almost below detection in the nitrification sludge and the PN sludge. In contrast, Nitrosomonas were gradually enriched (DGGE BAC-14) and a new DGGE band (DGGE BAC-22) of Nitrosomonas was detected in the PN sludge. During the start-up of PN, the diversity of NOB group, Nitrospira (IV-band region), decreased, and no band corresponding to Nitrospira was detected in the PN sludge. The results indicated that the high-rate nitrifying culture which was dominated by AOB, i.e., Nitrosomonas and NOB, i.e., Nitropira was achieved in the “co-culture” phase at sufficient DO. And then the DO-HRT control strategy successfully inhibited the activity of NOB, i.e., Nitrospira and washed out them in the “screening” phase at limited DO and high HRT. Together, co-culture and screening combined with DOHRT control successfully encouraged the transition of nitrification to PN. In previous research most Nitrosospira groups had a lower half-saturation constant value for oxidation of NH3 (Km = 1.8–11 μM-NH3) [33, 34] than did the Nitrosomonas group (Km = 0.6–158 μM-NH3) [35]. In oligotrophic natural soils and in low substrate natural freshwaters, members of the Nitrosospira group are generally 19
the dominant AOB representatives [36]. This is possibly an important reason why the Nitrosospira group dominated in the inoculum used in the present study, which was taken from a low-NH3 municipal sewage treatment plant (Fig. 7). Compared with Nitrosospira, Nitrosomonas has a higher ammonia tolerance (NH4ClNitrosomonas = 50– 600 mM, NH4ClNitrosospira = 200 mM) [36], a higher specific ammonium uptake rate (KNitrosomonas=0.005-0.023 pmol-N/cell/h, KNitrosospira=0.004 pmol-N/cell/h) [37] and a higher maximum specific growth rate (μmax(Nitrosomonas)=0.088 h-1, μmax(Nitrosospira)=0.035 h-1) [38]. Therefore, as the operation of the reactor in the present study increased, the Nitrosomonas group gradually replaced the Nitrosospira group, and became the dominant functional microorganisms in the PN system at a high ammonium concentration and a short HRT. Furthermore, the enrichment of Nitrosomonas laid a solid foundation for the excellent performance of the PN process. 4. Conclusions (1) The “co-culture and screening” technology developed in this research was successful in initiating the start-up of a high-rate PN system. The maximum nitrogen loading rate and ammonium conversion rate were 9.42 kg-N m-3 d-1 and 4.74 kg-N m-3 d-1, respectively. To our knowledge, this performance was among the best that has been reported so far in the literature. (2) The DO-HRT control strategy that was developed in this study was successful in regulating the NH4+-N/NO2--N ratio for the PN system. When DO and HRT satisfied the relationships 0.66 - 0.5 • DO ≤ HRT ≤ 0.79 - 0.53 • DO, and 0.5 mg L-1 ≤ DO ≤ 0.75 mg L-1, the performance of the PN system was excellent, with an 20
NH4+-N/NO2--N ratio of 1:1.04 to 1:1.47, an ammonium conversion efficiency of 53.6%–62.1% and a nitrite accumulation efficiency of more than 90%. (3) The excellent performance of the PN process was due to the high specific activity of the PN sludge. The maximum specific ammonium conversion rate was 3.69 g-N g-1 VSS d-1, which was among the best performances that has been reported in the literature. (4) The successful regulation of the NH4+-N/NO2--N ratio in the PN system was due to the inhibition of NOB (Nitrospira) activity and the transition of predominant functional microorganisms from Nitrosospira to Nitrosomonas. The high ammonia tolerance, high specific ammonium uptake rate and high specific growth rate of Nitrosomonas laid a solid foundation for the excellent performance of the PN process. Acknowledgments The study was supported by the National Sci-Tech Plan Projects of China (2013BAD21B04), the Natural Science Foundation (51278457), and the China Agriculture Research System (CARS-36-10 B).
21
References [1] Song Y, Ishii S, Rathnayake L, Ito T, Satoh H, Okabe S. Development and Characterization of the Partial Nitrification Aerobic Granules in a Sequencing Batch Airlift Reactor. Bioresour Technol 2013;139:285-291. [2] Wang L, Zheng P, Chen T, Chen J, Xing Y, Ji Q, Zhang M, Zhang J. Performance of autotrophic nitrogen removal in the granular sludge bed reactor. Bioresour Technol 2012;123:78-85. [3] Fux C, Siegrist H. Nitrogen removal from sludge digester liquids by nitrification/denitrification or partial nitritation/anammox: environmental and economical considerations. Water Sci Technol
2004;50:19-26.
[4] Peng Y, Zhu G. Biological nitrogen removal with nitrification and denitrification via nitrite pathway. Appl Microbiol Biotechnol 2006;73:15-26. [5] Chen T, Zheng P, Shen L, Ding S, Mahmood Q. Kinetic characteristics and microbial community of Anammox-EGSB reactor. J Hazard Mater 2011;190:28-35. [6] Zheng P, Lin F-m, Hu B-l, Chen J-s. Start-up of anaerobic ammonia oxidation bioreactor with nitrifying activated sludge. J Environ Sci 2004;16:13-16. [7] Fukushima T, Whang L-M, Chiang T-Y, Lin Y-H, Chevalier L, Chen M-C, Wu Y-J. Nitrifying bacterial community structures and their nitrification performance under sufficient and limited inorganic carbon conditions. Appl Microbiol Biotechnol 2013;97:6513-6523. [8] Ruiz G, Jeison D, Chamy R. Nitrification with high nitrite accumulation for the 22
treatment of wastewater with high ammonia concentration. Water Res 2003;37:1371-1377. [9] Tang C-J, Zheng P, Wang C-H, Mahmood Q, Zhang J-Q, Chen X-G, Zhang L, Chen J-W. Performance of high-loaded ANAMMOX UASB reactors containing granular sludge. Water Res 2011;45:135-144. [10] Jin R-c, Hu B-l, Zheng P, Qaisar M, Hu A-h, Islam E. Quantitative comparison of stability of ANAMMOX process in different reactor configurations. Bioresour Technol 2008;99:1603-1609. [11] Knapp CW, Graham DW. Nitrite‐oxidizing bacteria guild ecology associated with nitrification failure in a continuous‐flow reactor. FEMS Microbiol Ecol 2007;62:195-201. [12] Li J, Healy MG, Zhan X, Norton D, Rodgers M. Effect of aeration rate on nutrient removal from slaughterhouse wastewater in intermittently aerated sequencing batch reactors. Water Air Soil Poll 2008;192:251-261. [13] Okabe S, Oshiki M, Takahashi Y, Satoh H. Development of long-term stable partial nitrification and subsequent anammox process. Bioresour Technol 2011;102:6801-6807. [14] Balmelle B, Nguyen K, Capdeville B, Cornier J, Deguin A. Study of factors controlling nitrite build-up in biological processes for water nitrification. Water Sci Technol 1992;26:1017-1025. [15] Li J, Yu D, Zhang P. Partial nitrification in a sequencing batch reactor treating acrylic fiber wastewater. Biodegradation 2012;24:427-435. 23
[16] Philips S, Laanbroek HJ, Verstraete W. Origin, causes and effects of increased nitrite concentrations in aquatic environments. Rev Environ Sci Bio 2002;1:115-141. [17] Guo J, Peng Y, Wang S, Zheng Y, Huang H, Wang Z. Long-term effect of dissolved oxygen on partial nitrification performance and microbial community structure. Bioresour Technol 2009;100:2796-2802. [18] Tang C-J, Zheng P, Zhang L, Chen J-W, Mahmood Q, Chen X-G, Hu B-L, Wang C-H, Yu Y. Enrichment features of anammox consortia from methanogenic granules loaded with high organic and methanol contents. Chemosphere 2010;79:613-619. [19] Sliekers AO, Derwort N, Gomez JL, Strous M, Kuenen JG, Jetten MS. Completely autotrophic nitrogen removal over nitrite in one single reactor. Water Res 2002;36:2475-2482. [20] Xing B-S, Guo Q, Zhang Z-Z, Zhang J, Wang H-Z, Jin R-C. Optimization of process performance in a granule-based anaerobic ammonium oxidation (anammox) upflow anaerobic sludge blanket (UASB) reactor. Bioresour Technol 2014;170:404-412. [21] O’Reilly J, Lee C, Chinalia F, Collins G, Mahony T, O’Flaherty V. Microbial community dynamics associated with biomass granulation in low-temperature (15 C) anaerobic wastewater treatment bioreactors. Bioresour Technol 2010;101:6336-6344. [22] Xing Y-j, Ji J-y, Zheng P, Zhang J-q, Ghulam A. Microbial consortium and its 24
spatial distribution in a compartmentalized anaerobic reactor. Appl Microbiol Biotechnol 2013;98:1357-1366. [23] Berdjeb L, Pollet T, Chardon C, Jacquet S. Spatio‐temporal changes in the structure of archaeal communities in two deep freshwater lakes. FEMS Microbiol Ecol 2013;86:215-230. [24] Hu Bl, Shen Ld, Zheng P, Hu Ah, Chen Tt, Cai C, Liu S, Lou Lp. Distribution and diversity of anaerobic ammonium‐oxidizing bacteria in the sediments of the Qiantang River. Env Microbiol Rep 2012;4:540-547. [25] Tamura K, Dudley J, Nei M, Kumar S. MEGA4: Molecular Evolutionary Genetics Analysis (MEGA) Software Version 4.0. Mol Biol Evol 2007;24:1596-1599. [26] Zhang L, Yang J, Hira D, Fujii T, Furukawa K. High-rate partial nitrification treatment of reject water as a pretreatment for anaerobic ammonium oxidation (anammox). Bioresour Technol 2011;102:3761-3767. [27] Bae H, Yang H, Chung Y-C, Yoo YJ, Lee S. High-rate partial nitritation using porous poly (vinyl alcohol) sponge. Bioprocess and biosystems engineering 2014;37:1115-1125. [28] Laanbroek H, Bodelier PE, Gerards S. Oxygen consumption kinetics of Nitrosomonas europaea and Nitrobacter hamburgensis grown in mixed continuous cultures at different oxygen concentrations. Arch Microbiol 1994;161:156-162. [29] Strous M, Heijnen JJ, Kuenen JG, Jetten MSM. The sequencing batch reactor as 25
a powerful tool for the study of slowly growing anaerobic ammoniumoxidizing microorganisms. Appl Microbiol Biotechnol 1998;50:589-596. [30] Jianlong W, Ning Y. Partial nitrification under limited dissolved oxygen conditions. Process Biochem 2004;39:1223-1229. [31] Mosquera-Corral A, Gonzalez F, Campos J, Méndez R. Partial nitrification in a SHARON reactor in the presence of salts and organic carbon compounds. Process Biochem 2005;40:3109-3118. [32] Zhang H, Sekiguchi Y, Hanada S, Hugenholtz P, Kim H, Kamagata Y, Nakamura K. Gemmatimonas aurantiaca gen. nov., sp. nov., a Gram-negative, aerobic, polyphosphate-accumulating micro-organism, the first cultured representative of the new bacterial phylum Gemmatimonadetes phyl. nov. International journal of systematic and evolutionary microbiology 2003;53:1155-1163. [33] Bollmann A, Schmidt I, Saunders AM, Nicolaisen MH. Influence of Starvation on Potential Ammonia-Oxidizing Activity and amoA mRNA Levels of Nitrosospira briensis. Appl Environ Microbiol 2005;71:1276-1282. [34] Jiang QQ, Bakken LR. Comparison of Nitrosospira strains isolated from terrestrial environments. FEMS Microbiol Ecol 1999;30:171-186. [35] Garrity GM, Bell JA, Lilburn T. Class II Betaproteobacteria class nov. OrderV Notrosomonadales order nov. . Bergey's manual of systematic bacteriology vol. 5: Springer: New York; 2005. p. 864-870. [36] Koops H-P, Purkhold U, Pommerening-Röser A, Timmermann G, Wagner M. The lithoautotrophic ammonia-oxidizing bacteria. The prokaryotes vol. 5: 26
Springer; 2006. p. 778-811. [37] Wagner M, Rath G, Amann R, Koops H-P, Schleifer K-H. In situ Identification of Ammonia-oxidizing Bacteria. Syst Appl Microbiol 1995;18:251-264. [38] Prosser JI. Autotrophic nitrification in bacteria. Adv Microb Physiol 1989;20:125-192.
27
Figure Captions
Fig. 1 Schematic diagram of internal loop air-lift reactor. (1. Influent tank; 2. Feeding pump; 3. Distribution zone; 4. Sludge; 5. Air bubble; 6. Down comer; 7. Settling zone; 8. Air pump; 9. Gas flow meter; 10. Air distributor; 11. Effluent tank; 12. Automatic pH controller; 13. HCl supply for automatic pH controller; 14. NaOH supply for automatic pH controller; 15. pH probe.)
28
Fig. 2 Performance of nitrification. (NLR, volumetric nitrogen loading rate; ACR, ammonium conversion rate; NAAR, nitrate accumulation rate; HRT, hydraulic retention time.)
29
Fig. 3 Performance of partial nitritation. ((A1). NLR, ACR, HRT versus operation time; (A2). ACE, NIAE, DO concentration versus operation time. NLR, volumetric nitrogen loading rate; ACR, ammonium conversion rate; HRT, hydraulic retention time; ACE, ammonium conversion efficiency; NIAE, nitrite accumulation efficiency.)
30
Fig. 4 Effects of DO and HRT on the ACE of PN. ((A) AB contour plots for the response variable (ACE) with respect to DO versus HRT; (B) AB response surface for the response variable (ACE) with respect to DO versus HRT; ACE, ammonium conversion efficiency.)
31
Fig. 5 Effects of DO and HRT on the NIAE of PN. ((A) AB contour plots for the response variable (NIAE) with respect to DO versus HRT; (B) AB response surface for the response variable (NIAE) with respect to DO versus HRT; NIAE, nitrite accumulation efficiency.)
32
Fig. 6 Specific ammonium conversion rate versus ammonium concentration
33
Fig. 7 DGGE fingerprints and phylogenetic tree based on the 16S rRNA gene of partial nitritation sludge. (The samples of lanes 1, 2, and 3 were taken from the inoculum, the nitrification phase sludge, and the partial nitritation phase sludge, respectively. The phylogenetic tree was constructed using a neighbor-joining algorithm. The percentage shown at each branch was gained from 1000 bootstrap resamplings. The scale bar represents a 2% sequence divergence. Sequences obtained in this study are shown with “DGGE BAC-” in the names. The bacterial phyla are shown between the tree and the DGGE figure.) 34
Tables Table 1 DO and HRT during operation Time (days)
DO (mg L-1)
HRT (h)
0-6
3.31-6.05
20.16
7-10
3.0-4.51
10.08
11-17
3.1-5.29
5.04
18-66
3.43-3.9
2.52
67-92
3.1-4.82
1.26
93-102
3.05-3.53
0.84
103-122
3.21-3.74
0.63
123-128
3.18-3.89
0.42
129-140
3.04-3.77
0.31
150-161
0.26-0.34
1.26
162-176
0.26-0.56
0.63
177-191
0.27-0.61
0.47
192-205
0.47-0.63
0.3
35
Table 2 Analysis of variance (ANOVA) for the response surface of ACE/DO-HRT of partial nitritation Source
df
Sum of Squares
Mean Square
F Value
p-value Prob > F
Model
2
2630.22
1315.11
47.19
<0.0001**
A-DO
1
1291.51
1291.51
46.34
0.0001**
B-HRT
1
1338.71
1338.71
48.04
0.0001**
Residual
8
222.95
27.87
Lack of Fit
6
217.08
36.18
12.33
0.0769
Pure Error
2
5.87
2.93
Cor Total
10
2853.17
R2
0.9219
** = significant at < 0.01, * = significant at < 0.05.
36
Table 3 Analysis of variance (ANOVA) for the response surface of NIAE/DOHRT of partial nitritation Source
df
Sum of Squares
Mean Square
F Value
p-value Prob>F
Model
5
3351.91
670.38
31.20
0.0009**
A-DO
1
682.87
682.87
31.78
0.0024**
B-HRT
1
211.66
211.66
9.85
0.0257*
AB
1
460.10
460.10
21.41
0.0057**
A2
1
1847.69
1847.69
85.99
0.0002**
B2
1
0.91
0.91
0.042
0.8452
Residual
8
107.44
21.49
Lack of Fit
6
77.95
25.98
1.76
0.3819
Pure Error
2
29.48
14.74
Cor Total
10
3459.35
10
R2
0.9689
** = significant at < 0.01, * = significant at < 0.05.
37
S1359-5113(15)30125-2 http://dx.doi.org/doi:10.1016/j.procbio.2015.11.016 PRBI 10562
To appear in:
Process Biochemistry
Received date: Revised date: Accepted date:
26-8-2015 6-11-2015 14-11-2015
Please cite this article as: Wang Lan, Zheng Ping, Abbas Ghulam, Yang Jian, Xing Yajuan, Li Wei, Wang Ru, Deng Liangwei, Zheng Dan.A start-up strategy for high-rate partial nitritation based on DO-HRT control.Process Biochemistry http://dx.doi.org/10.1016/j.procbio.2015.11.016 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.
A start-up strategy for high-rate partial nitritation based on DOHRT control Lan Wangb, c, Ping Zhenga* [email protected], Ghulam Abbasa, Jian Yangd, Yajuan Xinga, Wei Lia, Ru Wanga, Liangwei Dengb,c, Dan Zhengb,c a
Department of Environmental Engineering, Zhejiang University, Hangzhou, 310058,
China b
c
Biogas Institute of Ministry of Agriculture, Chengdu 610041, China
Laboratory of Development and Application of Rural Renewable Energy, Chengdu
610041, China d
State Key Laboratory of Plant Physiology and Biochemistry, College of Life Science,
Zhejiang University, Hangzhou, 310058, China *
Corresponding author: Tel: +86 571 86971709.
1
Graphical Abstract
2
Highlights
The PN was started up with ammonium conversion rate of 4.74 kg-N m-3 d-1.
The RSM with CCD was applied to optimize the parameters of DO and HRT.
Good PN performance was ascribed to the high sludge activity (3.69 g-N g-1 VSS d-1).
The transition of predominant microorganisms was investigated by DGGE.
Nitrosomonas was predominant functional microorganisms.
Abstract Partial nitritation (PN) is the controllable bottleneck of the combined PN- anaerobic ammonium oxidation process, because it has a low nitrogen conversion rate. In this study, a “co-culture and screening” technology was developed to start up PN, and a dual dissolved oxygen-hydraulic retention time (DO-HRT) control strategy was developed to regulate the NH4+-N/NO2--N ratio. The results showed that PN could be successfully started up and it had a high nitrogen loading rate and ammonium conversion rate (9.42 kg-N m-3 d-1 and 4.74 kg-N m-3 d-1), respectively. A response surface methodology (RSM) with a central composite design (CCD) was used to optimize the parameters of DO and HRT. When DO and HRT satisfied the relationships 0.66 - 0.5 • DO ≤ HRT ≤ 0.79 - 0.53 • DO and 0.5 mg L-1 ≤ DO ≤ 0.75 mg L-1, the performance of PN was excellent with an NH4+-N/NO2--N ratio ranging from 1:1.04 to 1:1.47, an ammonium conversion efficiency of 53.6%–62.1% and a nitrite accumulation efficiency greater than 90%. The excellent performance of PN 3
process was attributed to the high specific activity of sludge (3.69 g-N g-1 VSS d-1), the predominance of ammonia-oxidizing bacteria, Nitrosomonas, and the inhibition of nitrite-oxidizing bacteria, Nitrospira.
Keywords: Partial nitritation; Start-up strategy; Ammonium-nitrite ratio regulation; Microbial community; DO-HRT control
4
1. Introduction The nitrogen compounds of most wastewaters are in the form of ammonium (NH4+), therefore ammonium removal or conversion becomes the key step for nitrogen removal [1]. In wastewater treatment plants, the traditional nitrification– denitrification process is the most widely used technology for nitrogen removal [2]. However, nitrification–denitrification is costly due to large energy demand for aeration, the need for external carbon addition and high sludge disposal costs [3]. Increasingly, wastewater treatment facilities are seeking innovative and cost-effective processes for nitrogen removal. Partial nitritation (PN), namely the oxidation of NH4+ to nitrite (NO2-) by ammonia-oxidizing microbes, decreases sludge production by 33%–35% and oxygen consumption by 25%, compared with traditional nitrification [4]. Coupled with an anaerobic ammonium oxidation (Anammox) process, which oxidizes NH4+ using NO2- to produce elemental nitrogen gas and a small amount of nitrate under anoxic conditions, PN can reduce oxygen consumption further because only approximately 60% of NH4+ must be converted to NO2- [5]. Additionally, in the PN-Anammox process, nitrogen removal from wastewaters having a low carbon-tonitrogen ratio can be facilitated, thereby avoiding the dependence on costly external organic carbon for nitrogen removal [6]. Traditional nitrification occurs through a series of microbial oxidation reactions performed by ammonia-oxidizing bacteria (AOB) and nitrite-oxidizing bacteria (NOB). In contrast, PN only involves the ammonia oxidation performed by AOB. Therefore, NOB have to be discharged from, or inhibited in the PN system [7]. Due to 5
similar physiological properties and a food chain relationship between AOB and NOB, it is difficult to separate these microbes. Thus, inhibition of NOB activity has been the main strategy for initiating PN; however, this approach adversely affects AOB activity and leads to inefficient PN. PN is a pretreatment for Anammox, which supplies the nitrite to Anammox bacteria. PN has achieved a maximum nitrogen conversion rate of only 3.3 kg-N m-3 day-1 [8] and it is far lower than the maximum nitrogen conversion rate of Anammox (74.3 kg-N m-3 day-1) [9, 10].Thus, PN limited the performance of combined PN-Anammox process. In this study, a “co-culture and screening” technology was developed to enhance the performance of PN. This technology involved two phases, the “co-culture” phase and the “screening” phase. In the “coculture” phase, AOB and NOB were enriched together without any inhibition measurement of NOB, and in the “screening” phase, NOB were inhibited and washed out by using “DO-HRT” control strategy (to be discussed in the following section ). Anammox bacteria require substrates with a suitable NH4+-N/NO2--N ratio. However, it is difficult to accumulate nitrite and obtain a suitable NH4+-N/NO2--N ratio in PN due to the physical similarities and mutual relationship between AOB and NOB [11]. To date, the main means of regulating the NH4+-N/NO2--N ratio in PN have included maintaining a low dissolved oxygen (DO) concentration [12], a high concentration of free ammonia (NH3) and nitrous acid (HNO2) [13], a high temperature [14], a short hydraulic retention time (HRT) [15] and addition of selective chemicals to inhibit NOB growth [16]. Among these techniques, maintenance of either a low DO concentration or a short HRT has been preferred due to economical 6
aspects and practicality [15, 17]. No information is available in the literature about that whether the combined control of DO and HRT to regulate the NH4+-N/NO2--N ratio for PN is more efficient and convenient. In the present study, a dual “DO-HRT” control strategy was developed as a means of obtaining a suitable NH4+-N/NO2--N ratio in PN. This strategy involved two steps, inhibiting NOB activity by limiting DO concentration and then washing out NOB by shortening HRT gradually in “screening” phase. The “co-culture and screening” technology could retain AOB and NOB communities with a high activity and cause a high specific ammonium uptake rate in “co-culture” phase, which laid a solid foundation for the high-rate performance of PN. And the “DO-HRT” strategy gradually inhibited and washed out NOB community and accomplished partial nitritation. The objective of the study was to explore the feasibility and working mechanism for the initiation of a high-rate PN system using two new techniques, “co-culture and screening” and “DO-HRT” control. The parameters for initiating PN process would lay a solid foundation for the development and application of high-rate PN process, and the information of microbial ecology in PN system would broaden the understanding about the necessity of using these two new techniques. 2. Materials and methods 2.1 Experimental set-up The experimental system is illustrated in Fig. 1. A 4 L internal loop air-lift reactor with an effective volume of 2 L was used. A synthetic wastewater was continuously pumped into the bottom of the reactor and air was simultaneously sparged from the 7
bottom of the reactor to supply oxygen and fluidize the biomass. The DO was regulated by adjusting air flow rate and was monitored by DO meter according to nitrogen loading rate and HRT of the reactor. And DO values of different periods were listed in Table 1. The temperature was controlled at 30 ± 1 oC and the pH was kept at 7.5 by an automatic pH controller using pumps connected to controllers with 2 M hydrochloric acid (HCl) and 2 M sodium hydroxide (NaOH). 0.5 L aerobic activated sludge taken from a municipal sewage treatment plant in Hangzhou, China was used for inoculation of the reactor. 2.2 Synthetic wastewater Synthetic wastewater contains 2 g L-1 NaHCO3, 0.5 g L-1 NH4Cl and mineral solutions. The composition of mineral solutions was (g L-1): 0.01 KH2PO4, 0.004 CaCl2.H2O, 0.3 MgSO4·7H2O and trace elements of solution described by Tang et al. [18]. The ammonium concentration was approximately 130.8 mg-N L-1. 2.3 Analytical methods The volatile suspended solids (VSS) and the concentrations of ammonium, nitrite and nitrate were determined using standard procedures [19]. The DO concentration was measured by a SevenGo pro SG9 meter (METLER TOLEDO, Switzerland). The air flow rate was measured by a LZB-4 glass tube rotameter (Zhejiang Yuyao Instrument Factory, China). 2.4 Batch activity test Batch experiments were conducted to determine the specific aerobic ammonia-
8
oxidizing activity of PN sludge. The reactor from which sludge was taken for analysis had a volumetric nitrogen loading rate (NLR, the amount of nitrogen compounds added to the PN system per effective volume of reactor per day) of 9.42 kg-N m-3 day1
, an ammonium conversion efficiency (ACE, ammonium concentration in effluent
divided by ammonium concentration in influent) of 52% and a nitrite accumulation efficiency (NIAE, nitrite accumulation rate divided by ammonium conversion rate) of 99%. The sludge was rinsed with the phosphate buffer until no NH4+, NO2- and NO3was detected. A 150 mL Erlenmeyer flask was used for batch activity test. A total of 16.35–523.2 mg-N L-1 NH4Cl solution, 1 mL mineral solution (as used in the synthetic wastewater), 0.1 g VSS, 2 g L-1 NaHCO3 and distilled water was added to 100 mL in each flask. During the experiment, the air was sparged into each flask and DO concentration was controlled at more than 3.0 mg L-1 by adjusting the air flow rate. The pH was controlled at about 7.5 by using the phosphate buffer. The flasks were incubated at 30 ± 1 °C on a shaking table operating at 180 rpm. The samples of the liquor phase were taken every 1–5 hours and filtered over a 0.45 μm filter for the determination of ammonium, nitrite and nitrate. Every test was performed in triplicate. 2.5 Response surface methodology (RSM) In this study, the effect of DO concentration and HRT on the ACE and NIAE of PN was investigated by employing response surface methodology with a central composite design [20]. Design Expert software version V8.0.5.0 (STAT-EASE Inc., Minneapolis, USA) was used for the experimental design and statistical tests. The values of the independent input variables (DO concentration and HRT) were 0.3–0.9 9
mg L-1 and 0.315–0.63 h, respectively. The ACE and NIAE were selected as the dependent output variables. Statistical analysis involving the quadratic models for the ACE and NIAE was performed with the F-test for analysis of variance (ANOVA). Three-dimensional response surfaces and two-dimensional contour plots for the output values of ACE and NIAE were used to show the models obtained from regression analysis. 2.6 PCR-DGGE test Inoculum, nitrification sludge and PN sludge were taken from the reactor on days 0, 130 and 200, respectively, and stored at −80 oC. Genomic DNA was extracted from the samples using the Fast DNA SPIN kit for soil (MP Biochemical, USA). PCRDGGE (denaturing gradient gel electrophoresis) test were performed following the protocol developed recently by Xing et al. (2013). A 468 bp 16S rRNA gene was obtained using bacterial primer set BAC 338F-BAC 805R, and a 40-bp GC clamp was added to the 5′ end of BAC 338F [21]. The PCR conditions were as described by O’Reilly et al. [21]. The PCR product was purified using an Agarose Gel DNA Purification Kit Ver. 2.0 (Takara, Japan), and was separated by DGGE using the DCodeTM Universal Mutation Detection system (Bio-Rad, USA) on 8% (w/v) polyacrylamide gel containing a 20%–50% gradient of denaturant. Electrophoresis was run at 200 V for 300 min (with an initial electrophoresis at 60 V for 30 min) and at 60 oC in 1×TAE buffer. The gel was stained by silver and bands were visualized using Gel Doc-XR (Bio-Rad, USA). The bands excised from the gels were reamplified with the same DGGE primers (without GC clamp) and cloned [22]. 10
A 16S rRNA gene fragment was obtained using archaeal primer set Parch519fARC915r, and a 40-bp GC clamp was added to the 5′ end of ARC915r [23]. The PCR conditions were as described by Berdjeb et al. [23]. 2.7 Cloning and sequencing The cloning of PCR products was performed as described by Hu et al. [24] and the clones were named as DGGE BAC-1 to DGGE BAC-24. The sequences obtained were compared with sequences deposited in GenBank using the BLAST program (http://www.ncbi.nlm.nih.gov/BLAST). Sequences and their closest matches were aligned with MEGA5.1. The phylogenetic tree was constructed by neighbor-joining methods with 1000 resamplings to produce Bootstrap values [25]. The sequences reported in this study have been deposited in GenBank with the accession numbers: KP342430-KP342450. 3. Results and discussion 3.1 Performance of nitrification phase The “co-culture” phase of the “co-culture and screening” technique was observed first. The volumetric NLR was gradually increased by shortening HRT at an influent NH4+-N concentration of 130.8 mg L-1 and DO concentration of 3.0 mg L-1 (Table 1). The NLR, ammonium conversion rate (ACR, the amount of ammonium consumed by microorganisms per effective volume of reactor per day) and nitrate accumulation rate (NAAR, the amount of nitrate produced by microorganisms per effective volume per day) are shown in Fig. 2. 11
During the first 128 days, as NLR was increased from 0.16 ± 0.002 kg-N m-3 d-1 to 7.09 ± 0.31 kg-N m-3 day-1, ACR increased from 0.16 ± 0.002 kg-N m-3 d-1 to 6.81 ± 0.24 kg-N m-3 d-1 and NAAR increased from 0.15 ± 0.008 kg-N m-3 d-1 to 6.75 ± 0.65 kg-N m-3 d-1, with HRT shortening from 20.16 h to 0.42 h. During days 129–140, HRT was further reduced to 0.31 h and NLR was further increased to 9.04 ± 0.24 kgN m-3 d-1, however the ACR and NAAR experienced slow increasing to 7.19 ± 0.11 kg-N m-3 d-1 and 7.15 ± 0.16 kg-N m-3 d-1, respectively. Thus, in the “co-culture” phase, the maximum NLR and ACR reached 9.04 ± 0.24 kg-N m-3 d-1 and 7.19 ± 0.11 kg-N m-3 d-1, respectively, and the ammonium was almost completely converted to nitrate. To our knowledge, this performance of nitrification was superior to the performance of other nitrification and PN processes previously reported in the literature [1, 26, 27]. The high-rate nitrification retained high activity AOB communities and provided solid foundation for high-rate PN. 3.2 Performance of PN phase After 140 days of operation, the performance of the “screening” phase of the “coculturing and screening” technique was investigated. The DO-HRT control strategy was used, which involved gradually shortening HRT at a fixed influent NH4+-N concentration of 130.8 mg L-1 and at a limited DO concentration of 0.3–0.6 mg L-1 (Table 1). The results are shown in Fig. 3. At day 161, NLR increased from 2.73 ± 0.16 kg-N m-3 d-1 to 4.95 ± 0.14 kg-N m-3 d-1 as HRT was reduced from 1.26 h to 0.63 h (Fig. 3A). During days 150–176, the ACE gradually decreased from 82.7 ± 4.1% to 48.5 ± 5.6% and the NIAE gradually 12
increased from 50% to a range of 90%–100% (Fig. 3B), because that the decrease of DO from more than 3.0 mg L-1 to 0.26-0.56 mg L-1 (Table 1) inhibited the activity of AOB and NOB. During days 177–205, NLR increased from 4.95 ± 0.14 kg-N m-3 d-1 to 9.42 ± 0.8 kg-N m-3 d-1 and ACR increased from 2.40 ± 0.38 kg-N m-3 d-1 to 4.74 ± 0.41 kg-N m-3 d-1 as HRT was reduced to 0.31 h. The effluent NH4+-N/NO2--N ratio stayed at 1:1 while ACE reached 50%–60% and NIAE exceeded 90% (Fig. 3B). These results demonstrated that nitrification was successfully transformed to PN by applying the DO-HRT control strategy. The high-rate nitrification enriched AOB and NOB communities with high activities and high substrates conversion rate, and then the initiation of PN washed out NOB communities with DO-HRT control. It laid a solid foundation for high-rate PN process with the maximum NLR and ACR of 9.42 ± 0.8 kg-N m-3 d-1 and 4.74 ± 0.41 kg-N m-3 d-1, respectively, which reached the top levels reported in the literature [1, 26, 27]. 3.3 Effect of DO and HRT on PN The DO concentration and HRT are the key parameters for the DO-HRT control strategy. In this study, the effect of DO concentration and HRT on the ACE and NIAE of PN was investigated by employing RSM with a central composite design [20]. The results for ACE are shown in Table 2 and those for NIAE are shown in Table 3. Threedimensional response surfaces and two-dimensional contour plots for the output values of ACE and NIAE are shown in Fig. 4 and Fig. 5, respectively. 3.3.1 ACE The equation for the coded variables in the quadratic models fitting the experimental 13
results for the ACE is shown in Eq. (1). ACE = -1.308 + 42.352 × DO + 80.850 × HRT
(1)
The ANOVA for the response surface linear model of ACE as a function of DO and HRT (Eq. (1)) is shown in Table 2. The model F-value of 47.19 implies that the model is significant, as there is less than a 0.01% chance that a “Model F-Value” this large could occur at random. Thus, the model is suitable for evaluating the effects on ACE of different combinations of DO and HRT. The Lack-of-Fit is not significant relative to the pure error and there is a 7.69% chance that the calculated “Lack-of-Fit F-Value” could occur at random (Lack-of-Fit F-value = 12.33, Lack-of-Fit p-value = 0.0769). A non-significant Lack-of-Fit is desirable. The R2 regression coefficient was found to be 0.9219, indicating that the actual and predicted values for ACE are in close agreement. The value of “Prob > F” less than 0.0500 indicates that the model terms are significant, i.e., that DO and HRT are significant model terms (p-value = 0.0001). Hence, DO and HRT showed independent effects on ACE of PN, but did not show an interactive effect. Fig. 4 illustrates contour plots and the three-dimensional response surface for ACE with respect to DO concentration versus HRT. In Fig. 4, the steeper the curve, the larger the effect of factors on ACE; similarly, the darker the color of the response surface (i.e., the longer the absorption wavelength), the higher the ACE. A simple linear relation was found between ACE and both DO and HRT. The ACE increased as DO and HRT increased (Fig. 4B). The highest ACE of 85% was achieved at a DO concentration of 0.9 mg L-1 and a HRT of 0.63 h. However, when using PN as a 14
pretreatment for Anammox, only 56.9% of ammonium needs to be oxidized to nitrite [26]. Therefore, if the range of 53.6%–62.1% was regarded as the optimum range for ACE, this goal was achieved when DO and HRT satisfied the relationships 0.66 - 0.5 • DO ≤ HRT ≤ 0.79 - 0.53 • DO, and 0.3 mg L-1 ≤ DO ≤ 0.9 mg L-1 (Fig. 4A). 3.3.2 NIAE The equation for the coded variables in the quadratic models fitting the experimental results for the NIAE is shown in Eq. (2). NIAE = -16.853 + 315.400 × DO + 116.640 × HRT - 223.438 × DO × HRT - 200.984 × DO2 - 15.666 × HRT2
(2)
The ANOVA for the response surface quadratic model of NIAE as a function of DO and HRT (Eq. (2)) is shown in Table 3. The model F-value of 31.20 implies that the model is significant because there is less than a 0.09% chance that a “Model F-Value” this large could occur at random. Thus, the model is suitable for evaluating the effects on NIAE of different combinations of DO and HRT. The Lack-of-Fit is not significant relative to the pure error, and there is a 38.19% chance that the “Lack-of-Fit F-Value” could occur at random (Lack-of-Fit F-value = 1.79, Lack-of-Fit p-value = 0.3819). The R2 regression coefficient was found to be 0.9689, indicating that the actual and predicted values for NIAE are in close agreement. The value of “Prob > F” less than 0.0500 indicates that model terms are significant. In this case, “A-DO” (pvalue=0.0024), “B-HRT” (p-value=0.0257), “AB” (p-value=0.0057) and “A2” (pvalue=0.0002) are significant model terms. Hence, the single factor effect and interactive effect of DO and HRT on NIAE of PN were significant. 15
Fig. 5 illustrates contour plots and the three-dimensional response surface for NIAE with respect to DO versus HRT. A quadratic relation was found between NIAE and both DO and HRT. The highest value of NIAE was achieved at multiple DO concentrations (Fig. 5B). If an NIAE value greater than 90% was regarded as the optimum range, this goal was reached when the DO concentration was in the range of 0.5–0.75 mg L-1 (Fig. 5A). Previous research has shown that the half saturation constant (Km) for oxygen of AOB (Km = 0.2–0.4 mg-O2 L-1) is significantly lower than that of NOB (Km = 1.2–1.5 mg-O2 L-1) and the specific affinity for oxygen of AOB is generally higher than that of NOB [28]. Hence, a limited DO concentration can inhibit NOB activity and lead to better growth of AOB compared with that of NOB [15]. Furthermore, a relatively short HRT can successfully remove (i.e., wash out) NOB and cause nitrite to accumulate. Conversely, if the HRT is too long, NOB will not be successfully washed out, even if the DO concentration is controlled within the optimum range. Too long a HRT would promote the conversion of nitrite to nitrate and a decrease in NIAE. Hence, Fig. 5B indicates that NIAE decreased with the increase of HRT when the DO concentration was higher than 0.5 mg L-1. However, an excessively short HRT increased NLR, which led to a low DO concentration (<0.5 mg L-1) and an insufficient oxygen supply for AOB. Furthermore, the imposition of a low DO concentration on denitrifying microbes and Anammox bacteria could in turn enhance the conversion of nitrite to nitrogen, causing a decrease in NIAE. As shown in Fig. 5B, NIAE decreased as HRT decreased when the DO concentration was lower than the optimum range (0.5 mg L-1). 16
Previous studies showed that the influent NH4+-N/NO2--N ratio of 1:1.32 was optimal for Anammox process, hence it was also optimal for effluent of PN process [29]. The foregoing results indicated that the effects of DO concentration and HRT on ACE and NIAE were significant.When DO and HRT satisfied the relationships 0.66 0.5 • DO ≤ HRT ≤ 0.79 - 0.53 • DO, and 0.5 mg L-1 ≤ DO ≤ 0.75 mg L-1, the performance of PN was excellent with an NH4+-N/NO2--N ratio ranging from 1:1.04 to 1:1.47, an ammonium conversion efficiency of 53.6%–62.1%, and a nitrite accumulation efficiency greater than 90%. This DO range was higher than DO values reported in many other studies with limited DO as the control strategy, for instance lower than 0.5 mg L-1 in the study of Bae et al. [27] and 0.5 mg L-1 in the study of Zhang et al. [26], which may be the reason for high ammonium conversion rate. And this HRT range was lower than many other studies with HRT as control strategy, for instance 20 h in the study of Li et al. [15], 21 h in the study of Bae Bae et al. [27] and 4 h in the study of Zhang et al. [26], which may be the reason for high nitrite accumulation efficiency without the strategy of high concentration of free ammonia, inorganic carbon and high pH. 3.4 Specific ammonium conversion activity of sludge The results of batch activity tests are presented in Fig. 6. These tests showed that the specific AOB activity of PN sludge has a significant influence on the performance of PN. Results suggested that the Haldane model was suitable (correlation coefficient of 0.98) for describing the kinetic ammonium conversion characteristics of PN sludge. Based on the Haldane model, the maximum specific ammonium conversion rate 17
reached to 3.69 g-N g-1 VSS d-1, which was among the highest rates previously reported in the literature (from 2.76 g-N g-1 VSS d-1 reported by [30] to 3.6 g-N g-1 VSS d-1 reported by [31]). In addition, the half saturation constant and substrate inhibition constant of ammonium were 42.98 mg L-1 and 714.89 mg L-1, respectively. These values indicated that the PN sludge had a high tolerance for both low and high concentrations of ammonium. Therefore, the high specific ammonium conversion activity and the high tolerance to different ammonium concentrations of PN sludge laid a solid foundation for the excellent performance of the PN process. 3.5 Functional microorganisms Samples of inoculum, nitrification sludge and partial nitritation sludge were taken from the reactor to evaluate the microbial communities and analyze the microbial mechanisms responsible for the transition of nitrification to PN. The analysis of the l6S rRNA gene of archaea indicated that no archaea were detected in the samples. The bacterial community structures of the inoculum (lane 1), nitrification sludge (lane 2) and partial nitritation sludge (lane 3) were explored by PCR-DGGE analysis of l6S rRNA fragment genes. The DGGE profile and phylogenetic tree of 24 DGGE bands are shown in Fig. 7. In the three periods of microbial changes represented by inoculum, nitrification sludge and PN sludge, all the DGGE sequences were contained in six phyla of the bacterial domain: Betaproteobacteria, Nitrospira, Gemmatimonadetes, Actinobacteria, Bacteroidetes and Alphaproteobacteria. The Betaproteobacteria of the I-band region on the DGGE gel was the most abundant bacterial group (Fig. 7). Niastella (DGGE BAC-1) and Gemmatimonas aurantiaca 18
(DGGE BAC-5) were detected in the inoculum and Gemmatimonas aurantiaca was a polyphosphate-accumulating bacteira [32], but they were not detected in nitrification and PN sludge. Cryobacterium (DGGE BAC-17) and Hyphomicrobium (DGGE BAC-8 and 19) were detected in nitrification sludge. Lewinella were detected in PN sludge. Nitrosospira (DGGE BAC-4 in the II-band region) and Nitrosomonas (DGGE BAC-14 and 22 in the III-band region) were the dominant functional microorganism groups. As the operational time of the reactor increased, Nitrosospira were gradually washed out almost below detection in the nitrification sludge and the PN sludge. In contrast, Nitrosomonas were gradually enriched (DGGE BAC-14) and a new DGGE band (DGGE BAC-22) of Nitrosomonas was detected in the PN sludge. During the start-up of PN, the diversity of NOB group, Nitrospira (IV-band region), decreased, and no band corresponding to Nitrospira was detected in the PN sludge. The results indicated that the high-rate nitrifying culture which was dominated by AOB, i.e., Nitrosomonas and NOB, i.e., Nitropira was achieved in the “co-culture” phase at sufficient DO. And then the DO-HRT control strategy successfully inhibited the activity of NOB, i.e., Nitrospira and washed out them in the “screening” phase at limited DO and high HRT. Together, co-culture and screening combined with DOHRT control successfully encouraged the transition of nitrification to PN. In previous research most Nitrosospira groups had a lower half-saturation constant value for oxidation of NH3 (Km = 1.8–11 μM-NH3) [33, 34] than did the Nitrosomonas group (Km = 0.6–158 μM-NH3) [35]. In oligotrophic natural soils and in low substrate natural freshwaters, members of the Nitrosospira group are generally 19
the dominant AOB representatives [36]. This is possibly an important reason why the Nitrosospira group dominated in the inoculum used in the present study, which was taken from a low-NH3 municipal sewage treatment plant (Fig. 7). Compared with Nitrosospira, Nitrosomonas has a higher ammonia tolerance (NH4ClNitrosomonas = 50– 600 mM, NH4ClNitrosospira = 200 mM) [36], a higher specific ammonium uptake rate (KNitrosomonas=0.005-0.023 pmol-N/cell/h, KNitrosospira=0.004 pmol-N/cell/h) [37] and a higher maximum specific growth rate (μmax(Nitrosomonas)=0.088 h-1, μmax(Nitrosospira)=0.035 h-1) [38]. Therefore, as the operation of the reactor in the present study increased, the Nitrosomonas group gradually replaced the Nitrosospira group, and became the dominant functional microorganisms in the PN system at a high ammonium concentration and a short HRT. Furthermore, the enrichment of Nitrosomonas laid a solid foundation for the excellent performance of the PN process. 4. Conclusions (1) The “co-culture and screening” technology developed in this research was successful in initiating the start-up of a high-rate PN system. The maximum nitrogen loading rate and ammonium conversion rate were 9.42 kg-N m-3 d-1 and 4.74 kg-N m-3 d-1, respectively. To our knowledge, this performance was among the best that has been reported so far in the literature. (2) The DO-HRT control strategy that was developed in this study was successful in regulating the NH4+-N/NO2--N ratio for the PN system. When DO and HRT satisfied the relationships 0.66 - 0.5 • DO ≤ HRT ≤ 0.79 - 0.53 • DO, and 0.5 mg L-1 ≤ DO ≤ 0.75 mg L-1, the performance of the PN system was excellent, with an 20
NH4+-N/NO2--N ratio of 1:1.04 to 1:1.47, an ammonium conversion efficiency of 53.6%–62.1% and a nitrite accumulation efficiency of more than 90%. (3) The excellent performance of the PN process was due to the high specific activity of the PN sludge. The maximum specific ammonium conversion rate was 3.69 g-N g-1 VSS d-1, which was among the best performances that has been reported in the literature. (4) The successful regulation of the NH4+-N/NO2--N ratio in the PN system was due to the inhibition of NOB (Nitrospira) activity and the transition of predominant functional microorganisms from Nitrosospira to Nitrosomonas. The high ammonia tolerance, high specific ammonium uptake rate and high specific growth rate of Nitrosomonas laid a solid foundation for the excellent performance of the PN process. Acknowledgments The study was supported by the National Sci-Tech Plan Projects of China (2013BAD21B04), the Natural Science Foundation (51278457), and the China Agriculture Research System (CARS-36-10 B).
21
References [1] Song Y, Ishii S, Rathnayake L, Ito T, Satoh H, Okabe S. Development and Characterization of the Partial Nitrification Aerobic Granules in a Sequencing Batch Airlift Reactor. Bioresour Technol 2013;139:285-291. [2] Wang L, Zheng P, Chen T, Chen J, Xing Y, Ji Q, Zhang M, Zhang J. Performance of autotrophic nitrogen removal in the granular sludge bed reactor. Bioresour Technol 2012;123:78-85. [3] Fux C, Siegrist H. Nitrogen removal from sludge digester liquids by nitrification/denitrification or partial nitritation/anammox: environmental and economical considerations. Water Sci Technol
2004;50:19-26.
[4] Peng Y, Zhu G. Biological nitrogen removal with nitrification and denitrification via nitrite pathway. Appl Microbiol Biotechnol 2006;73:15-26. [5] Chen T, Zheng P, Shen L, Ding S, Mahmood Q. Kinetic characteristics and microbial community of Anammox-EGSB reactor. J Hazard Mater 2011;190:28-35. [6] Zheng P, Lin F-m, Hu B-l, Chen J-s. Start-up of anaerobic ammonia oxidation bioreactor with nitrifying activated sludge. J Environ Sci 2004;16:13-16. [7] Fukushima T, Whang L-M, Chiang T-Y, Lin Y-H, Chevalier L, Chen M-C, Wu Y-J. Nitrifying bacterial community structures and their nitrification performance under sufficient and limited inorganic carbon conditions. Appl Microbiol Biotechnol 2013;97:6513-6523. [8] Ruiz G, Jeison D, Chamy R. Nitrification with high nitrite accumulation for the 22
treatment of wastewater with high ammonia concentration. Water Res 2003;37:1371-1377. [9] Tang C-J, Zheng P, Wang C-H, Mahmood Q, Zhang J-Q, Chen X-G, Zhang L, Chen J-W. Performance of high-loaded ANAMMOX UASB reactors containing granular sludge. Water Res 2011;45:135-144. [10] Jin R-c, Hu B-l, Zheng P, Qaisar M, Hu A-h, Islam E. Quantitative comparison of stability of ANAMMOX process in different reactor configurations. Bioresour Technol 2008;99:1603-1609. [11] Knapp CW, Graham DW. Nitrite‐oxidizing bacteria guild ecology associated with nitrification failure in a continuous‐flow reactor. FEMS Microbiol Ecol 2007;62:195-201. [12] Li J, Healy MG, Zhan X, Norton D, Rodgers M. Effect of aeration rate on nutrient removal from slaughterhouse wastewater in intermittently aerated sequencing batch reactors. Water Air Soil Poll 2008;192:251-261. [13] Okabe S, Oshiki M, Takahashi Y, Satoh H. Development of long-term stable partial nitrification and subsequent anammox process. Bioresour Technol 2011;102:6801-6807. [14] Balmelle B, Nguyen K, Capdeville B, Cornier J, Deguin A. Study of factors controlling nitrite build-up in biological processes for water nitrification. Water Sci Technol 1992;26:1017-1025. [15] Li J, Yu D, Zhang P. Partial nitrification in a sequencing batch reactor treating acrylic fiber wastewater. Biodegradation 2012;24:427-435. 23
[16] Philips S, Laanbroek HJ, Verstraete W. Origin, causes and effects of increased nitrite concentrations in aquatic environments. Rev Environ Sci Bio 2002;1:115-141. [17] Guo J, Peng Y, Wang S, Zheng Y, Huang H, Wang Z. Long-term effect of dissolved oxygen on partial nitrification performance and microbial community structure. Bioresour Technol 2009;100:2796-2802. [18] Tang C-J, Zheng P, Zhang L, Chen J-W, Mahmood Q, Chen X-G, Hu B-L, Wang C-H, Yu Y. Enrichment features of anammox consortia from methanogenic granules loaded with high organic and methanol contents. Chemosphere 2010;79:613-619. [19] Sliekers AO, Derwort N, Gomez JL, Strous M, Kuenen JG, Jetten MS. Completely autotrophic nitrogen removal over nitrite in one single reactor. Water Res 2002;36:2475-2482. [20] Xing B-S, Guo Q, Zhang Z-Z, Zhang J, Wang H-Z, Jin R-C. Optimization of process performance in a granule-based anaerobic ammonium oxidation (anammox) upflow anaerobic sludge blanket (UASB) reactor. Bioresour Technol 2014;170:404-412. [21] O’Reilly J, Lee C, Chinalia F, Collins G, Mahony T, O’Flaherty V. Microbial community dynamics associated with biomass granulation in low-temperature (15 C) anaerobic wastewater treatment bioreactors. Bioresour Technol 2010;101:6336-6344. [22] Xing Y-j, Ji J-y, Zheng P, Zhang J-q, Ghulam A. Microbial consortium and its 24
spatial distribution in a compartmentalized anaerobic reactor. Appl Microbiol Biotechnol 2013;98:1357-1366. [23] Berdjeb L, Pollet T, Chardon C, Jacquet S. Spatio‐temporal changes in the structure of archaeal communities in two deep freshwater lakes. FEMS Microbiol Ecol 2013;86:215-230. [24] Hu Bl, Shen Ld, Zheng P, Hu Ah, Chen Tt, Cai C, Liu S, Lou Lp. Distribution and diversity of anaerobic ammonium‐oxidizing bacteria in the sediments of the Qiantang River. Env Microbiol Rep 2012;4:540-547. [25] Tamura K, Dudley J, Nei M, Kumar S. MEGA4: Molecular Evolutionary Genetics Analysis (MEGA) Software Version 4.0. Mol Biol Evol 2007;24:1596-1599. [26] Zhang L, Yang J, Hira D, Fujii T, Furukawa K. High-rate partial nitrification treatment of reject water as a pretreatment for anaerobic ammonium oxidation (anammox). Bioresour Technol 2011;102:3761-3767. [27] Bae H, Yang H, Chung Y-C, Yoo YJ, Lee S. High-rate partial nitritation using porous poly (vinyl alcohol) sponge. Bioprocess and biosystems engineering 2014;37:1115-1125. [28] Laanbroek H, Bodelier PE, Gerards S. Oxygen consumption kinetics of Nitrosomonas europaea and Nitrobacter hamburgensis grown in mixed continuous cultures at different oxygen concentrations. Arch Microbiol 1994;161:156-162. [29] Strous M, Heijnen JJ, Kuenen JG, Jetten MSM. The sequencing batch reactor as 25
a powerful tool for the study of slowly growing anaerobic ammoniumoxidizing microorganisms. Appl Microbiol Biotechnol 1998;50:589-596. [30] Jianlong W, Ning Y. Partial nitrification under limited dissolved oxygen conditions. Process Biochem 2004;39:1223-1229. [31] Mosquera-Corral A, Gonzalez F, Campos J, Méndez R. Partial nitrification in a SHARON reactor in the presence of salts and organic carbon compounds. Process Biochem 2005;40:3109-3118. [32] Zhang H, Sekiguchi Y, Hanada S, Hugenholtz P, Kim H, Kamagata Y, Nakamura K. Gemmatimonas aurantiaca gen. nov., sp. nov., a Gram-negative, aerobic, polyphosphate-accumulating micro-organism, the first cultured representative of the new bacterial phylum Gemmatimonadetes phyl. nov. International journal of systematic and evolutionary microbiology 2003;53:1155-1163. [33] Bollmann A, Schmidt I, Saunders AM, Nicolaisen MH. Influence of Starvation on Potential Ammonia-Oxidizing Activity and amoA mRNA Levels of Nitrosospira briensis. Appl Environ Microbiol 2005;71:1276-1282. [34] Jiang QQ, Bakken LR. Comparison of Nitrosospira strains isolated from terrestrial environments. FEMS Microbiol Ecol 1999;30:171-186. [35] Garrity GM, Bell JA, Lilburn T. Class II Betaproteobacteria class nov. OrderV Notrosomonadales order nov. . Bergey's manual of systematic bacteriology vol. 5: Springer: New York; 2005. p. 864-870. [36] Koops H-P, Purkhold U, Pommerening-Röser A, Timmermann G, Wagner M. The lithoautotrophic ammonia-oxidizing bacteria. The prokaryotes vol. 5: 26
Springer; 2006. p. 778-811. [37] Wagner M, Rath G, Amann R, Koops H-P, Schleifer K-H. In situ Identification of Ammonia-oxidizing Bacteria. Syst Appl Microbiol 1995;18:251-264. [38] Prosser JI. Autotrophic nitrification in bacteria. Adv Microb Physiol 1989;20:125-192.
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Figure Captions
Fig. 1 Schematic diagram of internal loop air-lift reactor. (1. Influent tank; 2. Feeding pump; 3. Distribution zone; 4. Sludge; 5. Air bubble; 6. Down comer; 7. Settling zone; 8. Air pump; 9. Gas flow meter; 10. Air distributor; 11. Effluent tank; 12. Automatic pH controller; 13. HCl supply for automatic pH controller; 14. NaOH supply for automatic pH controller; 15. pH probe.)
28
Fig. 2 Performance of nitrification. (NLR, volumetric nitrogen loading rate; ACR, ammonium conversion rate; NAAR, nitrate accumulation rate; HRT, hydraulic retention time.)
29
Fig. 3 Performance of partial nitritation. ((A1). NLR, ACR, HRT versus operation time; (A2). ACE, NIAE, DO concentration versus operation time. NLR, volumetric nitrogen loading rate; ACR, ammonium conversion rate; HRT, hydraulic retention time; ACE, ammonium conversion efficiency; NIAE, nitrite accumulation efficiency.)
30
Fig. 4 Effects of DO and HRT on the ACE of PN. ((A) AB contour plots for the response variable (ACE) with respect to DO versus HRT; (B) AB response surface for the response variable (ACE) with respect to DO versus HRT; ACE, ammonium conversion efficiency.)
31
Fig. 5 Effects of DO and HRT on the NIAE of PN. ((A) AB contour plots for the response variable (NIAE) with respect to DO versus HRT; (B) AB response surface for the response variable (NIAE) with respect to DO versus HRT; NIAE, nitrite accumulation efficiency.)
32
Fig. 6 Specific ammonium conversion rate versus ammonium concentration
33
Fig. 7 DGGE fingerprints and phylogenetic tree based on the 16S rRNA gene of partial nitritation sludge. (The samples of lanes 1, 2, and 3 were taken from the inoculum, the nitrification phase sludge, and the partial nitritation phase sludge, respectively. The phylogenetic tree was constructed using a neighbor-joining algorithm. The percentage shown at each branch was gained from 1000 bootstrap resamplings. The scale bar represents a 2% sequence divergence. Sequences obtained in this study are shown with “DGGE BAC-” in the names. The bacterial phyla are shown between the tree and the DGGE figure.) 34
Tables Table 1 DO and HRT during operation Time (days)
DO (mg L-1)
HRT (h)
0-6
3.31-6.05
20.16
7-10
3.0-4.51
10.08
11-17
3.1-5.29
5.04
18-66
3.43-3.9
2.52
67-92
3.1-4.82
1.26
93-102
3.05-3.53
0.84
103-122
3.21-3.74
0.63
123-128
3.18-3.89
0.42
129-140
3.04-3.77
0.31
150-161
0.26-0.34
1.26
162-176
0.26-0.56
0.63
177-191
0.27-0.61
0.47
192-205
0.47-0.63
0.3
35
Table 2 Analysis of variance (ANOVA) for the response surface of ACE/DO-HRT of partial nitritation Source
df
Sum of Squares
Mean Square
F Value
p-value Prob > F
Model
2
2630.22
1315.11
47.19
<0.0001**
A-DO
1
1291.51
1291.51
46.34
0.0001**
B-HRT
1
1338.71
1338.71
48.04
0.0001**
Residual
8
222.95
27.87
Lack of Fit
6
217.08
36.18
12.33
0.0769
Pure Error
2
5.87
2.93
Cor Total
10
2853.17
R2
0.9219
** = significant at < 0.01, * = significant at < 0.05.
36
Table 3 Analysis of variance (ANOVA) for the response surface of NIAE/DOHRT of partial nitritation Source
df
Sum of Squares
Mean Square
F Value
p-value Prob>F
Model
5
3351.91
670.38
31.20
0.0009**
A-DO
1
682.87
682.87
31.78
0.0024**
B-HRT
1
211.66
211.66
9.85
0.0257*
AB
1
460.10
460.10
21.41
0.0057**
A2
1
1847.69
1847.69
85.99
0.0002**
B2
1
0.91
0.91
0.042
0.8452
Residual
8
107.44
21.49
Lack of Fit
6
77.95
25.98
1.76
0.3819
Pure Error
2
29.48
14.74
Cor Total
10
3459.35
10
R2
0.9689
** = significant at < 0.01, * = significant at < 0.05.
37