- Email: [email protected]
The effects of influent and operational conditions on nitrogen removal in an upflow microaerobic sludge blanket system: A model-based evaluation
Bioresource Technology 295 (2020) 122225
Contents lists available at ScienceDirect
Bioresource Technology journal homepage: www.elsevier.com/locate/biortech
The effects of influent and operational conditions on nitrogen removal in an upflow microaerobic sludge blanket system: A model-based evaluation Jia Menga,1, Jiuling Lib,1, Jianzheng Lia, Jun Nana, Min Zhengb, a b
T
⁎
State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, 73 Huanghe Road, Harbin 150090, PR China Advanced Water Management Centre, The University of Queensland, St Lucia, Brisbane, QLD 4072, Australia
G R A P H I C A L A B S T R A C T
A R T I C LE I N FO
A B S T R A C T
Keywords: Upflow microaerobic sludge blanket (UMSB) system Nitrogen removal Modeling Influent and operational conditions Anammox
Recently, upflow microaerobic sludge blanket (UMSB) system has been developed to remove ammonium and organic matter simultaneously. This study aims to establish influent and operational conditions promoting anammox-based nitrogen removal process in the UMSB reactor by using a modified Activated Sludge Model. Experiments were performed on a laboratory-scale UMSB reactor treated piggery wastewater for over two years. With the experimentally determined model parameters, the established model well simulated the UMSB reactor performance. The maximum anammox growth rate was calibrated to be 0.41 d−1 at 35 °C. Further simulations showed that UMSB reactor operated with high influent organics or nitrogen loading rates at temperature above 15 °C can achieve efficient nitrogen removal (> 70%). The nitrogen loading over 0.6 kg N/(m3·d)) significantly favors anammox activity. UMSB could also be a promising system for nitrogen removal from low-strength ammonium wastewater with fluctuated COD influence. These results provide support to UMSB design and operational optimization.
1. Introduction Nitrogen must be removed from wastewater because its discharge to environment can cause eutrophication (Liu et al., 2017). Pre-anoxic denitrification followed by aerobic nitrification reaction has been
developed decades ago and applied as the most commonly-used process configuration for the nitrogen removal (Mandel et al., 2019). However, it is being challenged because the denitrification process massively consumes electron donating organic carbon (Bartucca et al., 2016; Moussavi et al., 2015; Zheng et al., 2019). Since the discovery of
⁎
Corresponding author. E-mail address: [email protected] (M. Zheng). 1 Equal first author. https://doi.org/10.1016/j.biortech.2019.122225 Received 11 June 2019; Received in revised form 29 September 2019; Accepted 1 October 2019 Available online 03 October 2019 0960-8524/ © 2019 Elsevier Ltd. All rights reserved.
Bioresource Technology 295 (2020) 122225
J. Meng, et al.
simultaneously removed over 60% COD and 80% total nitrogen (TN) with low energy demand. This clearly showed that, particularly at low influent COD/N ratio, the efficient nitrogen removal was the resultant of the anammox-based process. This achievement was found highly dependent on the influent (COD and nitrogen concentrations as well as loading rates) conditions and operational parameters (temperature and hydraulic retention time (HRT)). Nevertheless, it is still unclear how and to what extent the anammox-based nitrogen removal could be affected by these conditions. A mathematical model is a useful tool to establish parameter ranges that favor nitrogen removal (Ni et al., 2014; Zheng et al., 2018). As an excellent platform, Activated Sludge Model (ASM) is to well simulate nitrogen-related microbial processes in wastewater treatment (Henze et al., 2000). For instance, a modified ASM model could thoroughly evaluate the effects of temperature, inflow variations, oxygen consumption and COD influence on a completely autotrophic nitrogen-removal over nitrite (CANON) process (Hao et al., 2005, 2002; Hao and Van Loosdrecht, 2004). The model typically illustrates nitrogen conversion via two-step nitrification and denitrification (Kaelin et al., 2009; Koch et al., 2000; Sarioglu et al., 2009; Zheng et al., 2013, 2014, 2018) and anammox (Ni et al., 2014, 2009). However, few modeling studies on the UMSB nitrogen removal are found up to now. The goal of this study is to calibrate and validate a modified ASM model to investigate the effects of influent and operational conditions on nitrogen removal of UMSB system. Within a two-year UMSB reactor operation, routine operational data was collected and used for parameter calibration and model validation. Oxygen transfer rate and maximum ammonia-oxidizing bacteria (AOB) and NOB growth rates were experimentally determined, and maximum anammox growth rate was calibrated in model program by implementing the routine UMSB operational data. The model was validated using independent seven groups of UMSB operational data from other seven conditions. With the calibrated model, simulations were conducted in steady-state UMSB system to investigate the effects of different influent COD and nitrogen loading rates as well as concentrations on nitrogen removal and anammox activity. The results would provide further design optimization of UMSB systems for nitrogen removal.
anaerobic ammonium oxidation (anammox) two decades ago (Kuypers et al., 2003), partial nitritation/anammox (PN/A) process has attracted much attention.
NH+4 + 1.5O2 → NO−2 + H2 O+ 2H+
(1)
NH+4 + 1.32NO−2 + 0.066HCO−3 + 0.13H+ → N2 + 0.26NO−3 + 0.066CH2 O0.5 N0.15 + 2H2 O
(2)
The PN/A process is cost-effective and energy-saving as it has big advantages of reducing oxygen consumption, organic matters requirement, and sludge production over the conventional nitrification/denitrification process (Lackner et al., 2014; Xu et al., 2015; Zekker et al., 2019). Innovative anammox-based technology developments have already been studied by many research groups around the world. Yang et al. (2017) achieved efficient nitrogen removal via the PN/A pathway (deammonification) in plug-flow integrated fixed-film activated sludge reactor. While nitrite-oxidizing bacteria (NOB) suppression is a key barrier for achieving the efficient anammox-based nitrogen removal process (Agrawal et al., 2018; McCarty, 2018; Wang et al., 2017; Zheng et al., 2019). Many previous reports showed that influent and operational conditions significantly affected the anammox-based nitrogen removal process (Klein et al., 2017). In wastewater, organic matters have been generally considered a crucial factor affecting anammox performance (Li et al., 2016). It is possible that denitrifiers can outcompete anammox bacteria at high chemical oxygen demand (COD) concentration (Van de Graaf et al., 1996). For example, Miao et al. (Miao et al., 2018) reported with influent COD/N ratio from 1.1 to 1.5, increase of anammox bacteria attributed to the nitrogen removal improvement, whereas the C/N ratio higher than 2.5 promoted denitrifying bacteria and inhibited anammox bacterial growth rate. Temperature is another critical factor. There was a significant drop in anammox activity when the temperature fell below 15 °C (Dosta et al., 2008) or 10 °C (Gilbert et al., 2014), which has been proved in municipal water treatment experiments (Daija et al., 2016). Therefore, it is of vital importance to evaluate the anammox-based nitrogen removal process in bioreactors under different influent and operational conditions. Until recently, upflow microaerobic sludge blanket (UMSB) system has been proved to be useful to achieve anammox-based nitrogen removal (Li et al., 2016; Meng et al., 2015, 2019). The UMSB system developed from a conventional upflow anaerobic sludge blanket (UASB) reactor. Wastewater enters the UMSB from the bottom, flows upward, and mixes with sludge through effluent recirculation with aeration (Fig. 1). As reported in these studies, the UMSB system
2. Materials and methods 2.1. Modified ASM model to simulate multiple nitrogen removal processes The model originated from two-step nitrification and denitrification model as well as anammox model (Kaelin et al., 2009; Koch et al., 2000; Ni et al., 2014; Sarioglu et al., 2009). According to the microbial sequencing analyses (Meng et al., 2015, 2019), the UMSB system allowed aerobic AOB, anaerobes (anammox and denitrifiers), and facultative aerobes (heterotrophs) to thrive together but successfully suppressed the NOB. As such, the modified ASM model used in this work is to describe diverse nitrogen-related microbial processes including aerobic and anaerobic ammonium oxidation, nitrite oxidation, denitrification on nitrite and nitrate. The model contains six particulate components including AOB (XAOB), NOB (XNOB), anammox (XAN), heterotrophic bacteria (XH), slowly biodegradable substrate (XS), and residual inert biomass (XI), and seven soluble components including dissolved oxygen (SO2), readily biodegradable substrate (SS), ammonium (SNH4), nitrite (SNO2), nitrate (SNO3), nitrogen gas (SN2) and soluble inert organic matter (SI). The growth processes of AOB, NOB, anammox and heterotrophic bacteria were included in the model by using the same approach reported in pieces of literature (Hiatt and Grady, 2008; Ni et al., 2014). The decay processes of them were described based on the updated IAWQ ASM No.1 (Hiatt and Grady, 2008). Detailed definition of components, process kinetic rate equations, stoichiometric matrix, parameters, and substrate uptake/production rates by different microorganisms are given in the Supplementary Information (SI).
Fig. 1. Schematic diagram of a laboratory-scale UMSB reactor. 2
Bioresource Technology 295 (2020) 122225
J. Meng, et al.
different flow rates. The Kla,O2 value can then be estimated by using the dissolved oxygen (DO) profile recorded and least-squares based curve fitting. Most of the kinetic parameters are directly taken from the literature because they have been well established in previous (Henze et al., 2000; Hao et al., 2002; Kaelin et al., 2009; Ni et al., 2014; Strous et al., 1998; Wiesmann, 1994). Maximum specific growth rates of AOB, NOB and anammox (i.e. μmax,AOB, μmax,NOB, and μmax,AN, respectively) are important parameters to predict ammonium and nitrite reduction as well as nitrate production. The μmax,AOB and μmax,NOB, were estimated by incubation tests described in the ASM model (Henze et al., 2000). For simplification, around 1 mL sludge from the operated UMSB reactor was initially inoculated into 100 mL synthetic media containing 50–75 mg/L ammonium or nitrite nitrogen and sufficient oxygen supply was provided to control DO > 5 mg/L. Mixed liquor samples were taken every several hours, filtered to analyze nitrite and/or nitrate concentrations in supernatant and then used to estimate the values of μmax,AOB and μmax,NOB. With the implementation of the model in AQUASIM 2.0 (Reichert, 1994), the μmax,AN was calibrated by minimizing the sum of squares of the deviations between the measured data in Phase I and simulated results. The intervals of individual parameter estimates were conducted at confidence regions of 95% calculated from the mean square fitting errors and the sensitivity of the model to the parameters. The effect of temperature on microbial growth rate is expressed as μmax(T) = μmax(20 °C)·exp(θT(T − 20 °C)), where θT is temperature coefficient. The θT values for anammox bacteria, AOB, NOB and heterotrophic bacteria are 0.096, 0.094, 0.061 and 0.069, respectively (Ni et al., 2014). The reactor was modelled as mixed compartment in the AQUASIM. The model validation was carried out with an input of the calibrated parameters and independent data collected from the UMSB reactor in Phase II. The model predictions were compared with the routine operational profiles to validate the model. The variance analysis of the mean values (effluent COD, effluent ammonium and total nitrogen removal loading rate) predicted by the validated model and measured date was conducted to evaluate the validity of the model. Statistical significance was obtained between the simulation results and measured data with p-value < 0.05.
2.2. UMSB reactor operation and data collection Fig. 1 illustrates a lab-scale UMSB reactor configuration. The overall reactor design was almost the same as conventional UASB reactor except that an aeration device was installed in effluent recirculation line. The main novelty of this microaerobic equipment is to maintain the microaerobic condition using the aerated effluent recirculated into the reactor. This indirect aeration could avoid negative impacts of medium/large air-based bubbles on sludge blanket, compared to the direct aeration in reactors. More design details can be found in our previous studies (Meng et al., 2018a, 2015, 2017). The UMSB inoculum was anaerobic sludge from a lab-scale UASB that only removed COD from piggery wastewater. Sludge retention time (SRT) parameter was set long as around 100 days. The UMSB was continuously fed raw swine piggery wastewater containing COD and ammonium nitrogen at a fixed 8-hour HRT. The overall operation lasted roughly two years, including two major phases: i) initial start-up Phase I (0–290 day) to enrich anammox; and ii) Phase II with different influent and operational conditions (291–650 day). In Phase I, the temperature was controlled at 35 °C by using an electric jacket inside the UMSB reactor. Routine operational profiles collected from the Phase I was implemented for parameter calibration for the growth of anammox. For Phase II, the UMSB reactor was operated with temperature drop down to 15 °C from 35 °C in seven periods, various reflux ratios (equal to effluent recirculating flow-rate of feeding rate), and largely fluctuated influent organic matter and nitrogen concentrations. Seven periods in Phase II with different operational conditions are summarized in Table 1. Each period included around 1–2 month. The operational data from these periods in Phase II were used for the validation of the model. Routine operational profiles were monitored with measurements of total and soluble COD, ammonium, nitrite, nitrate and total nitrogen in influent, and soluble COD, ammonium, nitrite, and nitrate in effluent once per day. The chemical analyses were conducted according to standard methods (APHA, 2005). Nitrogen removal loading rate in term of kg N/(m3·d) was calculated to be the removed amount of total nitrogen per day per cube meter wastewater. Sludge samples were taken from the UMSB reactor 1–2 times every month, to measure mixed liquor volatile suspended solids concentration as well as microbial community structure and diversity by high throughput sequencing method, as described previously (Meng et al., 2018a, 2015, 2017).
2.4. Model simulations under different influent and operational conditions The validated model was used to explore the effects of influent and operational conditions on the nitrogen removal efficiency and nitrogen conversion rates of different microbial processes. The model simulation was performed until steady-state at 35 °C with constant Kla,O2 value of 10 h−1, and with different influent organics loading rates ranging from 0.3 to 1.5 kg COD/(m3·d) with 0.15 kg COD/(m3·d) steps (concentrations from 100 to 500 mg COD/L with 50 mg COD/L steps) and ammonium nitrogen loading rates ranging from 0.3 to 0.9 kg N/(m3·d) with 0.15 kg N/(m3·d) steps (concentrations from 100 to 300 mg N/L with 50 mg N/L steps). The simulation was also performed with relatively low influent COD (concentrations from 0 to 200 mg N/L with
2.3. Model calibration and validation The raw swine piggery wastewater contains different organic matters components. Assessments of biodegradable COD (SS and XS) and inert COD (SI and XI) were carried out using an experimental method described by Orhon et al. (Orhon et al., 1997). Average fractions obtained from triplicate tests were used as the model input values. Oxygen mass transfer rate constant (Kla,O2) was estimated using water tests at room temperature (22 ± 1 °C). The UMSB reactor was initially filled with clean water and sparged with pure nitrogen gas to deprive oxygen. Afterward, it was operated under oxygen-rich water recirculation with
Table 1 Influent and operational conditions in seven different periods (Phase II) of the UMSB reactor. Periods
Time (day)
Organics loading rate (kg COD/(m3·d))
Nitrogen loading rate (kg N/(m3·d))
Temperature (°C)
Reflux ratio
Kla,O2 (h−1)
Ⅰ II III Ⅳ Ⅴ VI VII
291–350 351–392 393–447 448–471 472–513 514–601 602–640
1.25 0.69 0.77 0.91 0.97 1.09 0.95
0.92 0.91 0.78 0.89 0.79 0.88 0.89
35 35 27 23 20 17 15
30 35 45 45 45 45 45
10.06 ± 0.07 10.16 ± 0.12 8.79 ± 0.48 8.92 ± 0.06 8.35 ± 0.05 7.27 ± 0.28 7.35 ± 0.16
± ± ± ± ± ± ±
0.20 0.29 0.32 0.26 0.36 0.27 0.23
± ± ± ± ± ± ±
0.05 0.06 0.15 0.16 0.22 0.07 0.08
3
Bioresource Technology 295 (2020) 122225
J. Meng, et al.
50 mg N/L steps) with fixed ammonium nitrogen concentration (50 mg/ L), and different temperature ranging from 15 to 35 °C with 5 °C steps with fixed influent COD and ammonium nitrogen concentrations (500 mg COD/L and 250 mg N/L, respectively). 3. Results and discussion 3.1. Parameters determination Organic matters fractionation in wastewater characterization is essential for reliable modeling in this study because the UMSB reactor was fed by the raw wastewater. According to the assessments, SS and SI fractions in soluble COD were respectively 0.8 and 0.2, XS fraction in particulate COD (total COD minus soluble COD) was 0.5, and the rest organic matter in total COD was defined as XI. These fraction results on the swine piggery wastewater are comparable with the values of domestic wastewater (Ni et al., 2009). Oxidation of ammonium to nitrite or then to nitrate needs proper oxygen supply. In theory, in our UMSB reactor, oxygen mass transfer rate constant is equal to reflux flow rate multiply dissolved oxygen concentration of the aerated effluent. In fact, the transfer rate can be affected by many operational and environmental conditions. It can be seen that more oxygen is provided in water tests than the theoretical value. The reason might be some micro-air-bubbles were pumped into the reactor with the aerated effluent together. As such, the Kla,O2 values used in the model were estimated based on water tests under different operational conditions. They were ranged in 5–12 h−1 depending on the specific situation. Incubation tests were carried out in laboratory at 35 °C to determine the AOB and NOB specific growth rates. The AOB and NOB net growth rates (μmax – b) were estimated to be 0.224 and 0.151 h−1 at 35 °C, respectively. Based on calculation, the μmaxAOB and μmaxNOB (equal to the sum of these growth rates and decay rates) at 20 °C were respectively evaluated to be 0.054 and 0.061 h−1, which are close to the levels reported in the literature (Ni et al., 2014). 3.2. Calibration of anammox specific growth rate UMSB start-up phase with anammox enrichment lasted around 290 days. The UMSB reactor was inoculated from a lab-scale UASB reactor and then continually fed with the raw swine piggery wastewater. Fig. 2 shows the UMSB reactor start-up performance. With optimization of influent (COD loading rate (OLR) and nitrogen loading rate (NLR)) and operational (reflux ratio and oxygen mass transfer rate) conditions, the highest TN removal loading rate of around 1.0 kg N/ (m3·d) was achieved at the end of the experiment. For example, on day 280, the TN removal efficiency reached 80% even though the influent COD/N ratio was as low as 0.5, suggesting an anammox-based nitrogen removal process. High throughput sequencing analyses on biomass samples collected from inoculum and start-up phase of the UMSB further confirmed that relative abundance of anammox bacteria increased from negligible in the inoculum to 0.27–1.06% after the long-term startup (Meng et al., 2019). The result revealed that the successful enrichment of anammox in the UMSB system, and thereby data collected from the routine operation could be used to calibrated maximum anammox specific growth rate (μmax,AN). The profiles including influent and effluent nitrogen and COD concentrations and operational conditions were implemented in the model program. With the μmax,AN parameter calibration, the model output results well matched with the measured effluent COD and ammonium concentrations and TN removal loading rate (Fig. 2B-D). The model simulations showed low effluent nitrite and nitrate nitrogen (both < 1 mg/L), which is also comparable with the measured data (mostly nitrite and nitrate nitrogen concentrations less than 5 mg/L, data not shown). The μmax,AN was calibrated to be 0.41 d−1 at 35 °C (equal to 0.0041 h−1 at 20 °C). The value is relatively high compared
Fig. 2. Long-term UMSB performance under different influent and operational conditions, including influent COD loading rate (OLR), nitrogen loading rate (NLR) and reflux ratio (A), effluent COD (B) and ammonium nitrogen concentrations (C), and total nitrogen removal loading rate (D). The temperature was controlled at 35 °C. The lines in Figs. B–D represent the model simulated results based on the μmax,AN parameter calibration, respectively.
with the parameter values in the range of 0.0022–0.0027 h−1 (20 °C) reported in previous studies (Ni et al., 2014, 2009; Strous et al., 1998). Zhang et al. (2017) revisited the μmax,AN parameters of different anammox species and found that Candidatus Brocadia sinica (μmax,AN = 0.34 d−1) grew much faster than Candidatus Jettenia caeni (μmax,AN = 0.18 d−1) in immobilized gel beads at 37 °C. Thus, the high anammox growth rate estimated in this study might be related to the anammox population (Candidatus Brocadia predominance in the UMSB reactor). In addition to that, fast growth has been considered an intrinsic kinetic property of anammox bacteria in bioreactor systems with long SRT parameter (Zhang et al., 2017).
4
Bioresource Technology 295 (2020) 122225
J. Meng, et al.
various conditions, including temperatures ranged in 15–35 °C, reflux ratios (30–45), and organics loading rates (0.7–1.3 kg COD/(m3·d)). The operation consisted of seven periods with the parameters summarized in Table 1. In these periods, the average TN removal loading rate changed from 0.3 to 0.8 kg N/(m3·d), and effluent ammonium nitrogen concentration varied in a range of 10–180 mg/L. With the calibrated parameters, model prediction on the UMSB performance was carried out. The model simulated results (i.e., average effluent COD and ammonium concentrations and TN removal loading rate) were in agreement to the measured data in seven different periods (Fig. 3). The statistical analysis evidenced the insignificant differences between the simulated results and the determined information (p-value > 0.05), indicating the validity of the model. Activity measurements and sequencing analyses had shown that UMSB system had good capacity in removing nitrogen via anammoxbased process (Li et al., 2016; Meng et al., 2015, 2019). In this work, the efficient nitrogen removal, as well as the growth of anammox, has been for the first time calibrated and validated within the long-term UMSB operation. This result provides us opportunities to predict the effects of influent and operational conditions on UMSB nitrogen removal and reveal how anammox activity could be affected by these conditions, as described in the following sections.
3.4. Effects of influent and operational conditions on nitrogen removal In order to shed light on the changes in the influent COD and nitrogen concentrations and operational conditions such as temperature, oxygen mass transfer rate and HRT on UMSB nitrogen removal, a simulation study using the calibrated model was carried out. Fig. 4A shows the model simulated results on the TN removal efficiency of a steady state UMSB reactor with different influent COD and nitrogen loading rates. The simulations showed that over 70% TN removal (red region) can be attained either with high influent NLR (e.g., > 0.6 kg N/ (m3·d)) or with high influent OLR (e.g., > 0.8 kg COD/(m3·d)), indicating that high loading rate is critical to achieving high-efficient nitrogen removal. It has been reported that the influent COD/N ratio had an effect on nitrogen removal performance in previous experiments (Li et al., 2016; Meng et al., 2018b). However, this effect was not identified as the key to anammox-based nitrogen removal. In the simulations, the anammox process considerably contributed to the TN removal of the UMSB reactor, under the conditions of both low and high influent OLRs. The simulations also showed COD removal can maintain above 70% in each scenario with the relative abundance of denitrifiers account for 5.0–19.0% (Meng et al., 2017, 2019). Moreover, the established model was employed to assess the feasibility of removing nitrogen at relatively low influent ammonium nitrogen concentration (i.e., 50 mg/L) and loading rate (0.15 kg N/
Fig. 3. The model simulated results and measured data (averaged value) collected from the UMSB reactor in seven different periods. Effluent COD (A) and ammonium nitrogen concentrations (B), and total nitrogen removal loading rate (C). Details of seven periods (I-VII) can be found in Table 1. Error bar represents standard deviation.
3.3. Model validation by using independent operational data The model was validated by comparing the simulated results with independent data collected from the UMSB reactor operated under
Fig. 4. Model predictions on total nitrogen removal efficiency (%) of a steady–state UMSB system at different influent OLR and NLR conditions (A) and relatively low COD concentrations (B). Other parameters included 35 °C, HRT of 8 h and Kla,O2 value of 10 h−1 were fixed in the simulations. For the simulations in the right figure, influent ammonium nitrogen concentration was fixed to be 50 mg/L. 5
Bioresource Technology 295 (2020) 122225
J. Meng, et al.
(m3·d)). Model simulations were conducted with influent COD concentrations in the range from 0 to 200 mg COD/L with 50 mg COD/L steps. The operational temperature, HRT and SRT conditions were respectively fixed to be 20 °C, 8 h and 100 days. The simulated results showed that 72–83% TN and > 90% ammonium would be removed from the low-strength ammonium nitrogen wastewater at the various COD concentrations (Fig. 4B). Anammox process was very active to remove nitrogen at low influent COD concentration, but the anammox bacteria was gradually over-selected by NOB with the COD increasing. Despite this, the TN removal efficiency only slightly decreased as the nitrogen can be removed by conventional nitrification/denitrification process at relatively high influent COD. The results indicated that UMSB could be a promising system to achieve nitrogen removal from low-strength ammonium wastewater with fluctuated COD influence (e.g., domestic sewage). It should be noted that these modeling resulted from the use of different Kla,O2 values in different influent COD. The optimized Kla,O2 value increased from 4 to 12 h−1 with a step increment in 2 h−1 in respect to the stepwise increase in influent COD concentration, ensuring achievement of the high-efficient nitrogen removal in UMSB system. Scenarios analyses at different temperature showed that TN removal > 70% could be located in an operational region with temperature > 20 °C under a fixed influent OLR of 1.5 kg COD/(m3·d) and NLR of 0.75 kg N/(m3·d). However, with the temperature down to 15 °C, the removal efficiency drop to 40% with the presence of much nitrate in the effluent. Anammox activity often has a sharply decrease with the temperature down to 15 °C (Laureni et al., 2016). Similarly, anammox population (Candidatus Brocadia) was reduced in an upflow anammox sludge bed with the reduced temperature (Reino et al., 2018). Also, low TN removal might be attributed to a low AOB activity compared with that of the NOB when the temperature decreased down to 15 °C (Lotti et al., 2014). These results confirmed that low-temperature was not conducive to the anammox-based nitrogen removal in UMSB systems.
increase while unchanged at different influent OLRs. With the influent NLR beyond 0.6 kg N/(m3·d), the ammonium uptake rate by anammox can reach above 0.2 kg N/(m3·d), compared with the pace of around 0.4 kg N/(m3·d) for AOB under the same condition. Nitrite production and uptake of the different microbial processes are shown in Fig. 6. The nitrite production rate by AOB is high enough to support nitrite utilization by denitrifier, NOB and anammox. Mainly, the region of high nitrite uptake rate of NOB (i.e., NLR < 0.6 kg N/(m3·d)) is located oppositely, compared with that of anammox process (Fig. 6C and D). The denitrification rate on nitrite is always less than 0.1 kg N/(m3·d), which is the lowest level for the nitrite reduction. These results indicated that, in comparison with the influent OLR, UMSB operation of high influent NLR is critical to the success of anammox-based nitrogen removal process. Additionally, the denitrification rate on nitrate is higher that nitrate production rate by anammox, showing that the denitrification process is useful to decrease nitrate concentration in UMSB effluent. It has been reported that high influent COD loading rate would deteriorate anammox activity (Miao et al., 2018; Van de Graaf et al., 1996). The reason has been considered that denitrifier can out-compete the anammox bacteria in the biological treatment system. However, based on the modeling results, the nitrite uptake rate of denitrifier is much lower than that of anammox in the UMSB system. Jenni et al. (2014) reported the successful application of nitritation/anammox to treat wastewater with elevated organic carbon to ammonia ratios. They identified a long SRT parameter as the key for the achievement of anammox-based nitrogen removal process at high influent COD concentration. And, the dominant anammox Ca. Brocadia was the same as the anammox population in this study. As such, the reason for anammox prevalence in UMSB system might be due to the SRT parameter (~100 days) as the conventional UASB reactor configuration used. Besides, it is possibly due to high anammox growth rate calibrated in this study. Previous studies have also shown that limited-oxygen condition was essential to suppress NOB (Laureni et al., 2016; Li et al., 2016; Meng et al., 2015). In the UMSB system, AOB process consumes massive oxygen in comparison with heterotrophic and NOB. Therefore, the limited-oxygen condition can be achieved under the operation of high NLR parameter. In another way, oxygen mass transfer rate constant needs to be well-designed to match the oxygen uptake rate by AOB, and to achieve the anammox-based nitrogen removal process. This can be attained by using the method of aerated effluent reflux in UMSB system.
3.5. UMSB operation at high influent nitrogen loading rate favors anammox activity Nitrogen conversion rates of different nitrogen-related microbial processes were simulated to reveal what influent conditions favor anammox activity in a steady-state UMSB system. The simulations were conducted with the same procedure as described in Section 3.4. Fig. 5 presents ammonium uptake rates of anammox and AOB under different influent COD and nitrogen loading rates. The results show that the anammox activities are significantly affected by the influent NLR
Fig. 5. Model predictions on ammonium uptake rate by AOB (A) and anammox (B) of a steady-state UMSB at different influent OLR and NLR conditions. Substrate uptake rates were calculated from the steady-state biomass concentration and growth rate according to Table S5. 6
Bioresource Technology 295 (2020) 122225
J. Meng, et al.
Fig. 6. Model predictions on nitrite production rate by AOB (A), nitrite uptake rates by denitrifier (B), NOB (C) and anammox (D) of a steady-state UMSB at different influent OLR and NLR conditions.
4. Conclusion
References
A modified ASM model was calibrated and validated against a labscale UMSB reactor fed with piggery wastewater of various operational conditions. The model simulated a gradual increase of total nitrogen removal rate up to 1.0 kg N/(m3·d) over one year in the UMSB and calibrated the maximum anammox specific growth rate to be 0.41 d−1 at 35 °C. A further simulation revealed that with influent nitrogen loading rate over 0.6 kg N/(m3·d), varied organics loading rate (0.3–1.5 kg COD/(m3·d)), and temperature above 15 °C, can achieve high TN removal (> 70%). The UMSB operation under these conditions significantly favors anammox activity over denitrification.
A.P.H.A, 2005. Standard Methods for the Examination of Water and Wastewater, 19th ed. American Public Health Association, Washington, DC. Agrawal, S., Seuntjens, D., De Cocker, P., Lackner, S., Vlaeminck, S.E., 2018. Success of mainstream partial nitritation/anammox demands integration of engineering, microbiome and modeling insights. Curr. Opin. Biotechnol. 50, 214–221. Bartucca, M.L., Mimmo, T., Cesco, S., Del Buono, D., 2016. Nitrate removal from polluted water by using a vegetated floating system. Sci. Total Environ. 542, 803–808. Daija, L., Selberg, A., Rikmann, E., Zekker, I., Tenno, T., Tenno, T., 2016. The influence of lower temperature, influent fluctuations and long retention time on the performance of an upflow mode laboratory-scale septic tank. Desalin. Water Treat. 57 (40), 18679–18687. Dosta, J., Fernández, I., Vázquez-Padín, J.R., Mosquera-Corral, A., Campos, J.L., MataÁlvarez, J., Méndez, R., 2008. Short- and long-term effects of temperature on the Anammox process. J. Hazard. Mater. 154 (1), 688–693. Gilbert, E.M., Agrawal, S., Karst, S.M., Horn, H., Nielsen, P.H., Lackner, S., 2014. Low temperature partial nitritation/anammox in a moving bed biofilm reactor treating low strength wastewater. Environ. Sci. Technol. 48 (15), 8784–8792. Henze, M., Gujer, W., Mino, T., van Loosdrecht, M.C.M., 2000. Activated sludge models ASM1, ASM2, ASM2d and ASM3. IWA Publishing. Hao, X.-D., Cao, X.-Q., Picioreanu, C., Van Loosdrecht, M., 2005. Model-based evaluation of oxygen consumption in a partial nitrification-anammox biofilm process. Water Sci. Technol. 52 (7), 155–160. Hao, X.-D., Van Loosdrecht, M., 2004. Model-based evaluation of COD influence on a partial nitrification-Anammox biofilm (CANON) process. Water Sci. Technol. 49 (11–12), 83–90. Hao, X., Heijnen, J.J., Van Loosdrecht, M.C., 2002. Model-based evaluation of temperature and inflow variations on a partial nitrification–ANAMMOX biofilm process. Water Res. 36 (19), 4839–4849. Hiatt, W.C., Grady, C., 2008. An updated process model for carbon oxidation, nitrification, and denitrification. Water Environ. Res. 80 (11), 2145–2156. Jenni, S., Vlaeminck, S.E., Morgenroth, E., Udert, K.M., 2014. Successful application of nitritation/anammox to wastewater with elevated organic carbon to ammonia ratios. Water Res. 49, 316–326. Kaelin, D., Manser, R., Rieger, L., Eugster, J., Rottermann, K., Siegrist, H., 2009. Extension
Acknowledgments This study was supported in part by the National Natural Science Foundation of China (No. 51478141 and 51908163). Dr Jia Meng gratefully acknowledges the China Postdoctoral Science Foundation funded project (No. 2017M611376), the Hei Long Jiang Postdoctoral Foundation funded project (No. LBH-Z17087) and Fundamental Research Funds for the Central Universities (Grant No. HIT.NSRIF.2019045).
Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.biortech.2019.122225. 7
Bioresource Technology 295 (2020) 122225
J. Meng, et al.
C/N ratios. Chem. Eng. J. 334, 664–672. Moussavi, G., Jafari, S.J., Yaghmaeian, K., 2015. Enhanced biological denitrification in the cyclic rotating bed reactor with catechol as carbon source. Bioresour. Technol. 189, 266–272. Ni, B.-J., Joss, A., Yuan, Z., 2014. Modeling nitrogen removal with partial nitritation and anammox in one floc-based sequencing batch reactor. Water Res. 67, 321–329. Ni, B.J., Chen, Y.P., Liu, S.Y., Fang, F., Xie, W.M., Yu, H.Q., 2009. Modeling a granulebased anaerobic ammonium oxidizing (ANAMMOX) process. Biotechnol. Bioeng. 103 (3), 490–499. Orhon, D., Ateş, E., Sözen, S., Çokgör, E.U., 1997. Characterization and COD fractionation of domestic wastewaters. Environ. Pollut. 95 (2), 191–204. Reichert, P., 1994. AQUASIM – a tool for simulation and data analysis of aquatic systems. Water Sci. Technol. 30 (2), 21–30. Reino, C., Suárez-Ojeda, M.E., Pérez, J., Carrera, J., 2018. Stable long-term operation of an upflow anammox sludge bed reactor at mainstream conditions. Water Res. 128, 331–340. Sarioglu, M., Insel, G., Artan, N., Orhon, D., 2009. Model evaluation of simultaneous nitrification and denitrification in a membrane bioreactor operated without an anoxic reactor. J. Membr. Sci. 337 (1), 17–27. Strous, M., Heijnen, J., Kuenen, J., Jetten, M., 1998. The sequencing batch reactor as a powerful tool for the study of slowly growing anaerobic ammonium-oxidizing microorganisms. Appl. Microbiol. Biotechnol. 50 (5), 589–596. Van de Graaf, A.A., de Bruijn, P., Robertson, L.A., Jetten, M.S., Kuenen, J.G., 1996. Autotrophic growth of anaerobic ammonium-oxidizing micro-organisms in a fluidized bed reactor. Microbiology 142 (8), 2187–2196. Wang, Q., Duan, H., Wei, W., Ni, B., Laloo, A., Yuan, Z., 2017. Achieving stable mainstream nitrogen removal via the nitrite pathway by sludge treatment using free ammonia. Environ. Sci. Technol. 51 (17), 9800–9807. Wiesmann, U., 1994. Biological nitrogen removal from wastewater. In: Biotechnics/ Wastewater. Springer, pp. 113–154. Xu, G., Zhou, Y., Yang, Q., Lee, Z.M.-P., Gu, J., Lay, W., Cao, Y., Liu, Y., 2015. The challenges of mainstream deammonification process for municipal used water treatment. Appl. Microbiol. Biotechnol. 99 (6), 2485–2490. Yang, Y., Zhang, L., Cheng, J., Zhang, S., Li, B., Peng, Y., 2017. Achieve efficient nitrogen removal from real sewage in a plug-flow integrated fixed-film activated sludge (IFAS) reactor via partial nitritation/anammox pathway. Bioresour. Technol. 239, 294–301. Zhang, L., Narita, Y., Gao, L., Ali, M., Oshiki, M., Okabe, S., 2017. Maximum specific growth rate of anammox bacteria revisited. Water Res. 116, 296–303. Zekker, I., Kivirüüt, A., Rikmann, E., Mandel, A., Jaagura, M., Tenno, T., Tenno, T., 2019. Enhanced efficiency of nitritating-anammox sequencing batch reactor achieved at low decrease rates of oxidation–reduction potential. Environ. Eng. Sci. 36 (3), 350–360. Zheng, M., Liu, Y., Wang, C., Xu, K., 2013. Study on enhanced denitrification using particulate organic matter in membrane bioreactor by mechanism modeling. Chemosphere 93 (11), 2669–2674. Zheng, M., Liu, Y., Wang, C.W., 2014. Modeling of enhanced denitrification capacity with microbial storage product in MBR systems. Sep. Purif. Technol. 126, 1–6. Zheng, M., Wu, S., Zuo, Z., Wang, Z., Qiu, Y., Liu, Y., Huang, X., Yuan, Z., 2018. Predictions of the influent and operational conditions for partial nitritation with a model incorporating pH dynamics. Environ. Sci. Technol. 52 (11), 6457–6465. Zheng, M., Wu, S., Dong, Q., Huang, X., Yuan, Z., Liu, Y., 2019. Achieving mainstream nitrogen removal via the nitrite pathway from real municipal wastewater using intermittent ultrasonic treatment. Ultrason. Sonochem. 51, 406–411.
of ASM3 for two-step nitrification and denitrification and its calibration and validation with batch tests and pilot scale data. Water Res. 43 (6), 1680–1692. Klein, K., Kivi, A., Dulova, N., Zekker, I., Mölder, E., Tenno, T., Tenno, T., 2017. A pilot study of three-stage biological–chemical treatment of landfill leachate applying continuous ferric sludge reuse in Fenton-like process. Clean Technol. Environ. 19 (2), 541–551. Koch, G., Kühni, M., Gujer, W., Siegrist, H., 2000. Calibration and validation of activated sludge model no. 3 for Swiss municipal wastewater. Water Res. 34 (14), 3580–3590. Kuypers, M.M.M., Sliekers, A.O., Lavik, G., Schmid, M., Jorgensen, B.B., Kuenen, J.G., Sinninghe Damste, J.S., Strous, M., Jetten, M.S.M., 2003. Anaerobic ammonium oxidation by anammox bacteria in the Black Sea. Nature 422 (6932), 608–611. Lackner, S., Gilbert, E.M., Vlaeminck, S.E., Joss, A., Horn, H., van Loosdrecht, M.C., 2014. Full-scale partial nitritation/anammox experiences–an application survey. Water Res. 55, 292–303. Laureni, M., Falås, P., Robin, O., Wick, A., Weissbrodt, D.G., Nielsen, J.L., Ternes, T.A., Morgenroth, E., Joss, A., 2016. Mainstream partial nitritation and anammox: longterm process stability and effluent quality at low temperatures. Water Res. 101, 628–639. Li, J., Meng, J., Li, J., Wang, C., Deng, K., Sun, K., Buelna, G., 2016. The effect and biological mechanism of COD/TN ratio on nitrogen removal in a novel upflow microaerobic sludge reactor treating manure-free piggery wastewater. Bioresour. Technol. 209, 360–368. Liu, T., Ma, B., Chen, X., Ni, B.-J., Peng, Y., Guo, J., 2017. Evaluation of mainstream nitrogen removal by simultaneous partial nitrification, anammox and denitrification (SNAD) process in a granule-based reactor. Chem. Eng. J. 327, 973–981. Lotti, T., Kleerebezem, R., Hu, Z., Kartal, B., Jetten, M.S.M., van Loosdrecht, M.C.M., 2014. Simultaneous partial nitritation and anammox at low temperature with granular sludge. Water Res. 66, 111–121. Mandel, A., Zekker, I., Jaagura, M., Tenno, T., 2019. Enhancement of anoxic phosphorus uptake of denitrifying phosphorus removal process by biomass adaption. Int. J. Environ. Sci. Technol. 1–14. McCarty, P.L., 2018. What is the best biological process for nitrogen removal: when and why? Environ. Sci. Technol. 52 (7), 3835–3841. Meng, J., Li, J., Li, J., Antwi, P., Deng, K., Nan, J., Xu, P., 2018a. Enhanced nitrogen removal from piggery wastewater with high NH 4+ and low COD/TN ratio in a novel upflow microaerobic biofilm reactor. Bioresour. Technol. 249, 935–942. Meng, J., Li, J., Li, J., Antwi, P., Deng, K., Wang, C., Buelna, G., 2015. Nitrogen removal from low COD/TN ratio manure-free piggery wastewater within an upflow microaerobic sludge reactor. Bioresour. Technol. 198, 884–890. Meng, J., Li, J., Li, J., Astals, S., Nan, J., Deng, K., Antwi, P., Xu, P., 2018b. The role of COD/N ratio on the start-up performance and microbial mechanism of an upflow microaerobic reactor treating piggery wastewater. J. Environ. Manage. 217, 825–831. Meng, J., Li, J., Li, J., Deng, K., Nan, J., Xu, P., 2017. Effect of reflux ratio on nitrogen removal in a novel upflow microaerobic sludge reactor treating piggery wastewater with high ammonium and low COD/TN ratio: efficiency and quantitative molecular mechanism. Bioresour. Technol. 243, 922–931. Meng, J., Li, J., Li, J., Nan, J., Deng, K., Antwi, P., 2019. Effect of temperature on nitrogen removal and biological mechanism in an up-flow microaerobic sludge reactor treating wastewater rich in ammonium and lack in carbon source. Chemosphere 216, 186–194. Miao, Y., Peng, Y., Zhang, L., Li, B., Li, X., Wu, L., Wang, S., 2018. Partial nitrificationanammox (PNA) treating sewage with intermittent aeration mode: effect of influent
8
Contents lists available at ScienceDirect
Bioresource Technology journal homepage: www.elsevier.com/locate/biortech
The effects of influent and operational conditions on nitrogen removal in an upflow microaerobic sludge blanket system: A model-based evaluation Jia Menga,1, Jiuling Lib,1, Jianzheng Lia, Jun Nana, Min Zhengb, a b
T
⁎
State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, 73 Huanghe Road, Harbin 150090, PR China Advanced Water Management Centre, The University of Queensland, St Lucia, Brisbane, QLD 4072, Australia
G R A P H I C A L A B S T R A C T
A R T I C LE I N FO
A B S T R A C T
Keywords: Upflow microaerobic sludge blanket (UMSB) system Nitrogen removal Modeling Influent and operational conditions Anammox
Recently, upflow microaerobic sludge blanket (UMSB) system has been developed to remove ammonium and organic matter simultaneously. This study aims to establish influent and operational conditions promoting anammox-based nitrogen removal process in the UMSB reactor by using a modified Activated Sludge Model. Experiments were performed on a laboratory-scale UMSB reactor treated piggery wastewater for over two years. With the experimentally determined model parameters, the established model well simulated the UMSB reactor performance. The maximum anammox growth rate was calibrated to be 0.41 d−1 at 35 °C. Further simulations showed that UMSB reactor operated with high influent organics or nitrogen loading rates at temperature above 15 °C can achieve efficient nitrogen removal (> 70%). The nitrogen loading over 0.6 kg N/(m3·d)) significantly favors anammox activity. UMSB could also be a promising system for nitrogen removal from low-strength ammonium wastewater with fluctuated COD influence. These results provide support to UMSB design and operational optimization.
1. Introduction Nitrogen must be removed from wastewater because its discharge to environment can cause eutrophication (Liu et al., 2017). Pre-anoxic denitrification followed by aerobic nitrification reaction has been
developed decades ago and applied as the most commonly-used process configuration for the nitrogen removal (Mandel et al., 2019). However, it is being challenged because the denitrification process massively consumes electron donating organic carbon (Bartucca et al., 2016; Moussavi et al., 2015; Zheng et al., 2019). Since the discovery of
⁎
Corresponding author. E-mail address: [email protected] (M. Zheng). 1 Equal first author. https://doi.org/10.1016/j.biortech.2019.122225 Received 11 June 2019; Received in revised form 29 September 2019; Accepted 1 October 2019 Available online 03 October 2019 0960-8524/ © 2019 Elsevier Ltd. All rights reserved.
Bioresource Technology 295 (2020) 122225
J. Meng, et al.
simultaneously removed over 60% COD and 80% total nitrogen (TN) with low energy demand. This clearly showed that, particularly at low influent COD/N ratio, the efficient nitrogen removal was the resultant of the anammox-based process. This achievement was found highly dependent on the influent (COD and nitrogen concentrations as well as loading rates) conditions and operational parameters (temperature and hydraulic retention time (HRT)). Nevertheless, it is still unclear how and to what extent the anammox-based nitrogen removal could be affected by these conditions. A mathematical model is a useful tool to establish parameter ranges that favor nitrogen removal (Ni et al., 2014; Zheng et al., 2018). As an excellent platform, Activated Sludge Model (ASM) is to well simulate nitrogen-related microbial processes in wastewater treatment (Henze et al., 2000). For instance, a modified ASM model could thoroughly evaluate the effects of temperature, inflow variations, oxygen consumption and COD influence on a completely autotrophic nitrogen-removal over nitrite (CANON) process (Hao et al., 2005, 2002; Hao and Van Loosdrecht, 2004). The model typically illustrates nitrogen conversion via two-step nitrification and denitrification (Kaelin et al., 2009; Koch et al., 2000; Sarioglu et al., 2009; Zheng et al., 2013, 2014, 2018) and anammox (Ni et al., 2014, 2009). However, few modeling studies on the UMSB nitrogen removal are found up to now. The goal of this study is to calibrate and validate a modified ASM model to investigate the effects of influent and operational conditions on nitrogen removal of UMSB system. Within a two-year UMSB reactor operation, routine operational data was collected and used for parameter calibration and model validation. Oxygen transfer rate and maximum ammonia-oxidizing bacteria (AOB) and NOB growth rates were experimentally determined, and maximum anammox growth rate was calibrated in model program by implementing the routine UMSB operational data. The model was validated using independent seven groups of UMSB operational data from other seven conditions. With the calibrated model, simulations were conducted in steady-state UMSB system to investigate the effects of different influent COD and nitrogen loading rates as well as concentrations on nitrogen removal and anammox activity. The results would provide further design optimization of UMSB systems for nitrogen removal.
anaerobic ammonium oxidation (anammox) two decades ago (Kuypers et al., 2003), partial nitritation/anammox (PN/A) process has attracted much attention.
NH+4 + 1.5O2 → NO−2 + H2 O+ 2H+
(1)
NH+4 + 1.32NO−2 + 0.066HCO−3 + 0.13H+ → N2 + 0.26NO−3 + 0.066CH2 O0.5 N0.15 + 2H2 O
(2)
The PN/A process is cost-effective and energy-saving as it has big advantages of reducing oxygen consumption, organic matters requirement, and sludge production over the conventional nitrification/denitrification process (Lackner et al., 2014; Xu et al., 2015; Zekker et al., 2019). Innovative anammox-based technology developments have already been studied by many research groups around the world. Yang et al. (2017) achieved efficient nitrogen removal via the PN/A pathway (deammonification) in plug-flow integrated fixed-film activated sludge reactor. While nitrite-oxidizing bacteria (NOB) suppression is a key barrier for achieving the efficient anammox-based nitrogen removal process (Agrawal et al., 2018; McCarty, 2018; Wang et al., 2017; Zheng et al., 2019). Many previous reports showed that influent and operational conditions significantly affected the anammox-based nitrogen removal process (Klein et al., 2017). In wastewater, organic matters have been generally considered a crucial factor affecting anammox performance (Li et al., 2016). It is possible that denitrifiers can outcompete anammox bacteria at high chemical oxygen demand (COD) concentration (Van de Graaf et al., 1996). For example, Miao et al. (Miao et al., 2018) reported with influent COD/N ratio from 1.1 to 1.5, increase of anammox bacteria attributed to the nitrogen removal improvement, whereas the C/N ratio higher than 2.5 promoted denitrifying bacteria and inhibited anammox bacterial growth rate. Temperature is another critical factor. There was a significant drop in anammox activity when the temperature fell below 15 °C (Dosta et al., 2008) or 10 °C (Gilbert et al., 2014), which has been proved in municipal water treatment experiments (Daija et al., 2016). Therefore, it is of vital importance to evaluate the anammox-based nitrogen removal process in bioreactors under different influent and operational conditions. Until recently, upflow microaerobic sludge blanket (UMSB) system has been proved to be useful to achieve anammox-based nitrogen removal (Li et al., 2016; Meng et al., 2015, 2019). The UMSB system developed from a conventional upflow anaerobic sludge blanket (UASB) reactor. Wastewater enters the UMSB from the bottom, flows upward, and mixes with sludge through effluent recirculation with aeration (Fig. 1). As reported in these studies, the UMSB system
2. Materials and methods 2.1. Modified ASM model to simulate multiple nitrogen removal processes The model originated from two-step nitrification and denitrification model as well as anammox model (Kaelin et al., 2009; Koch et al., 2000; Ni et al., 2014; Sarioglu et al., 2009). According to the microbial sequencing analyses (Meng et al., 2015, 2019), the UMSB system allowed aerobic AOB, anaerobes (anammox and denitrifiers), and facultative aerobes (heterotrophs) to thrive together but successfully suppressed the NOB. As such, the modified ASM model used in this work is to describe diverse nitrogen-related microbial processes including aerobic and anaerobic ammonium oxidation, nitrite oxidation, denitrification on nitrite and nitrate. The model contains six particulate components including AOB (XAOB), NOB (XNOB), anammox (XAN), heterotrophic bacteria (XH), slowly biodegradable substrate (XS), and residual inert biomass (XI), and seven soluble components including dissolved oxygen (SO2), readily biodegradable substrate (SS), ammonium (SNH4), nitrite (SNO2), nitrate (SNO3), nitrogen gas (SN2) and soluble inert organic matter (SI). The growth processes of AOB, NOB, anammox and heterotrophic bacteria were included in the model by using the same approach reported in pieces of literature (Hiatt and Grady, 2008; Ni et al., 2014). The decay processes of them were described based on the updated IAWQ ASM No.1 (Hiatt and Grady, 2008). Detailed definition of components, process kinetic rate equations, stoichiometric matrix, parameters, and substrate uptake/production rates by different microorganisms are given in the Supplementary Information (SI).
Fig. 1. Schematic diagram of a laboratory-scale UMSB reactor. 2
Bioresource Technology 295 (2020) 122225
J. Meng, et al.
different flow rates. The Kla,O2 value can then be estimated by using the dissolved oxygen (DO) profile recorded and least-squares based curve fitting. Most of the kinetic parameters are directly taken from the literature because they have been well established in previous (Henze et al., 2000; Hao et al., 2002; Kaelin et al., 2009; Ni et al., 2014; Strous et al., 1998; Wiesmann, 1994). Maximum specific growth rates of AOB, NOB and anammox (i.e. μmax,AOB, μmax,NOB, and μmax,AN, respectively) are important parameters to predict ammonium and nitrite reduction as well as nitrate production. The μmax,AOB and μmax,NOB, were estimated by incubation tests described in the ASM model (Henze et al., 2000). For simplification, around 1 mL sludge from the operated UMSB reactor was initially inoculated into 100 mL synthetic media containing 50–75 mg/L ammonium or nitrite nitrogen and sufficient oxygen supply was provided to control DO > 5 mg/L. Mixed liquor samples were taken every several hours, filtered to analyze nitrite and/or nitrate concentrations in supernatant and then used to estimate the values of μmax,AOB and μmax,NOB. With the implementation of the model in AQUASIM 2.0 (Reichert, 1994), the μmax,AN was calibrated by minimizing the sum of squares of the deviations between the measured data in Phase I and simulated results. The intervals of individual parameter estimates were conducted at confidence regions of 95% calculated from the mean square fitting errors and the sensitivity of the model to the parameters. The effect of temperature on microbial growth rate is expressed as μmax(T) = μmax(20 °C)·exp(θT(T − 20 °C)), where θT is temperature coefficient. The θT values for anammox bacteria, AOB, NOB and heterotrophic bacteria are 0.096, 0.094, 0.061 and 0.069, respectively (Ni et al., 2014). The reactor was modelled as mixed compartment in the AQUASIM. The model validation was carried out with an input of the calibrated parameters and independent data collected from the UMSB reactor in Phase II. The model predictions were compared with the routine operational profiles to validate the model. The variance analysis of the mean values (effluent COD, effluent ammonium and total nitrogen removal loading rate) predicted by the validated model and measured date was conducted to evaluate the validity of the model. Statistical significance was obtained between the simulation results and measured data with p-value < 0.05.
2.2. UMSB reactor operation and data collection Fig. 1 illustrates a lab-scale UMSB reactor configuration. The overall reactor design was almost the same as conventional UASB reactor except that an aeration device was installed in effluent recirculation line. The main novelty of this microaerobic equipment is to maintain the microaerobic condition using the aerated effluent recirculated into the reactor. This indirect aeration could avoid negative impacts of medium/large air-based bubbles on sludge blanket, compared to the direct aeration in reactors. More design details can be found in our previous studies (Meng et al., 2018a, 2015, 2017). The UMSB inoculum was anaerobic sludge from a lab-scale UASB that only removed COD from piggery wastewater. Sludge retention time (SRT) parameter was set long as around 100 days. The UMSB was continuously fed raw swine piggery wastewater containing COD and ammonium nitrogen at a fixed 8-hour HRT. The overall operation lasted roughly two years, including two major phases: i) initial start-up Phase I (0–290 day) to enrich anammox; and ii) Phase II with different influent and operational conditions (291–650 day). In Phase I, the temperature was controlled at 35 °C by using an electric jacket inside the UMSB reactor. Routine operational profiles collected from the Phase I was implemented for parameter calibration for the growth of anammox. For Phase II, the UMSB reactor was operated with temperature drop down to 15 °C from 35 °C in seven periods, various reflux ratios (equal to effluent recirculating flow-rate of feeding rate), and largely fluctuated influent organic matter and nitrogen concentrations. Seven periods in Phase II with different operational conditions are summarized in Table 1. Each period included around 1–2 month. The operational data from these periods in Phase II were used for the validation of the model. Routine operational profiles were monitored with measurements of total and soluble COD, ammonium, nitrite, nitrate and total nitrogen in influent, and soluble COD, ammonium, nitrite, and nitrate in effluent once per day. The chemical analyses were conducted according to standard methods (APHA, 2005). Nitrogen removal loading rate in term of kg N/(m3·d) was calculated to be the removed amount of total nitrogen per day per cube meter wastewater. Sludge samples were taken from the UMSB reactor 1–2 times every month, to measure mixed liquor volatile suspended solids concentration as well as microbial community structure and diversity by high throughput sequencing method, as described previously (Meng et al., 2018a, 2015, 2017).
2.4. Model simulations under different influent and operational conditions The validated model was used to explore the effects of influent and operational conditions on the nitrogen removal efficiency and nitrogen conversion rates of different microbial processes. The model simulation was performed until steady-state at 35 °C with constant Kla,O2 value of 10 h−1, and with different influent organics loading rates ranging from 0.3 to 1.5 kg COD/(m3·d) with 0.15 kg COD/(m3·d) steps (concentrations from 100 to 500 mg COD/L with 50 mg COD/L steps) and ammonium nitrogen loading rates ranging from 0.3 to 0.9 kg N/(m3·d) with 0.15 kg N/(m3·d) steps (concentrations from 100 to 300 mg N/L with 50 mg N/L steps). The simulation was also performed with relatively low influent COD (concentrations from 0 to 200 mg N/L with
2.3. Model calibration and validation The raw swine piggery wastewater contains different organic matters components. Assessments of biodegradable COD (SS and XS) and inert COD (SI and XI) were carried out using an experimental method described by Orhon et al. (Orhon et al., 1997). Average fractions obtained from triplicate tests were used as the model input values. Oxygen mass transfer rate constant (Kla,O2) was estimated using water tests at room temperature (22 ± 1 °C). The UMSB reactor was initially filled with clean water and sparged with pure nitrogen gas to deprive oxygen. Afterward, it was operated under oxygen-rich water recirculation with
Table 1 Influent and operational conditions in seven different periods (Phase II) of the UMSB reactor. Periods
Time (day)
Organics loading rate (kg COD/(m3·d))
Nitrogen loading rate (kg N/(m3·d))
Temperature (°C)
Reflux ratio
Kla,O2 (h−1)
Ⅰ II III Ⅳ Ⅴ VI VII
291–350 351–392 393–447 448–471 472–513 514–601 602–640
1.25 0.69 0.77 0.91 0.97 1.09 0.95
0.92 0.91 0.78 0.89 0.79 0.88 0.89
35 35 27 23 20 17 15
30 35 45 45 45 45 45
10.06 ± 0.07 10.16 ± 0.12 8.79 ± 0.48 8.92 ± 0.06 8.35 ± 0.05 7.27 ± 0.28 7.35 ± 0.16
± ± ± ± ± ± ±
0.20 0.29 0.32 0.26 0.36 0.27 0.23
± ± ± ± ± ± ±
0.05 0.06 0.15 0.16 0.22 0.07 0.08
3
Bioresource Technology 295 (2020) 122225
J. Meng, et al.
50 mg N/L steps) with fixed ammonium nitrogen concentration (50 mg/ L), and different temperature ranging from 15 to 35 °C with 5 °C steps with fixed influent COD and ammonium nitrogen concentrations (500 mg COD/L and 250 mg N/L, respectively). 3. Results and discussion 3.1. Parameters determination Organic matters fractionation in wastewater characterization is essential for reliable modeling in this study because the UMSB reactor was fed by the raw wastewater. According to the assessments, SS and SI fractions in soluble COD were respectively 0.8 and 0.2, XS fraction in particulate COD (total COD minus soluble COD) was 0.5, and the rest organic matter in total COD was defined as XI. These fraction results on the swine piggery wastewater are comparable with the values of domestic wastewater (Ni et al., 2009). Oxidation of ammonium to nitrite or then to nitrate needs proper oxygen supply. In theory, in our UMSB reactor, oxygen mass transfer rate constant is equal to reflux flow rate multiply dissolved oxygen concentration of the aerated effluent. In fact, the transfer rate can be affected by many operational and environmental conditions. It can be seen that more oxygen is provided in water tests than the theoretical value. The reason might be some micro-air-bubbles were pumped into the reactor with the aerated effluent together. As such, the Kla,O2 values used in the model were estimated based on water tests under different operational conditions. They were ranged in 5–12 h−1 depending on the specific situation. Incubation tests were carried out in laboratory at 35 °C to determine the AOB and NOB specific growth rates. The AOB and NOB net growth rates (μmax – b) were estimated to be 0.224 and 0.151 h−1 at 35 °C, respectively. Based on calculation, the μmaxAOB and μmaxNOB (equal to the sum of these growth rates and decay rates) at 20 °C were respectively evaluated to be 0.054 and 0.061 h−1, which are close to the levels reported in the literature (Ni et al., 2014). 3.2. Calibration of anammox specific growth rate UMSB start-up phase with anammox enrichment lasted around 290 days. The UMSB reactor was inoculated from a lab-scale UASB reactor and then continually fed with the raw swine piggery wastewater. Fig. 2 shows the UMSB reactor start-up performance. With optimization of influent (COD loading rate (OLR) and nitrogen loading rate (NLR)) and operational (reflux ratio and oxygen mass transfer rate) conditions, the highest TN removal loading rate of around 1.0 kg N/ (m3·d) was achieved at the end of the experiment. For example, on day 280, the TN removal efficiency reached 80% even though the influent COD/N ratio was as low as 0.5, suggesting an anammox-based nitrogen removal process. High throughput sequencing analyses on biomass samples collected from inoculum and start-up phase of the UMSB further confirmed that relative abundance of anammox bacteria increased from negligible in the inoculum to 0.27–1.06% after the long-term startup (Meng et al., 2019). The result revealed that the successful enrichment of anammox in the UMSB system, and thereby data collected from the routine operation could be used to calibrated maximum anammox specific growth rate (μmax,AN). The profiles including influent and effluent nitrogen and COD concentrations and operational conditions were implemented in the model program. With the μmax,AN parameter calibration, the model output results well matched with the measured effluent COD and ammonium concentrations and TN removal loading rate (Fig. 2B-D). The model simulations showed low effluent nitrite and nitrate nitrogen (both < 1 mg/L), which is also comparable with the measured data (mostly nitrite and nitrate nitrogen concentrations less than 5 mg/L, data not shown). The μmax,AN was calibrated to be 0.41 d−1 at 35 °C (equal to 0.0041 h−1 at 20 °C). The value is relatively high compared
Fig. 2. Long-term UMSB performance under different influent and operational conditions, including influent COD loading rate (OLR), nitrogen loading rate (NLR) and reflux ratio (A), effluent COD (B) and ammonium nitrogen concentrations (C), and total nitrogen removal loading rate (D). The temperature was controlled at 35 °C. The lines in Figs. B–D represent the model simulated results based on the μmax,AN parameter calibration, respectively.
with the parameter values in the range of 0.0022–0.0027 h−1 (20 °C) reported in previous studies (Ni et al., 2014, 2009; Strous et al., 1998). Zhang et al. (2017) revisited the μmax,AN parameters of different anammox species and found that Candidatus Brocadia sinica (μmax,AN = 0.34 d−1) grew much faster than Candidatus Jettenia caeni (μmax,AN = 0.18 d−1) in immobilized gel beads at 37 °C. Thus, the high anammox growth rate estimated in this study might be related to the anammox population (Candidatus Brocadia predominance in the UMSB reactor). In addition to that, fast growth has been considered an intrinsic kinetic property of anammox bacteria in bioreactor systems with long SRT parameter (Zhang et al., 2017).
4
Bioresource Technology 295 (2020) 122225
J. Meng, et al.
various conditions, including temperatures ranged in 15–35 °C, reflux ratios (30–45), and organics loading rates (0.7–1.3 kg COD/(m3·d)). The operation consisted of seven periods with the parameters summarized in Table 1. In these periods, the average TN removal loading rate changed from 0.3 to 0.8 kg N/(m3·d), and effluent ammonium nitrogen concentration varied in a range of 10–180 mg/L. With the calibrated parameters, model prediction on the UMSB performance was carried out. The model simulated results (i.e., average effluent COD and ammonium concentrations and TN removal loading rate) were in agreement to the measured data in seven different periods (Fig. 3). The statistical analysis evidenced the insignificant differences between the simulated results and the determined information (p-value > 0.05), indicating the validity of the model. Activity measurements and sequencing analyses had shown that UMSB system had good capacity in removing nitrogen via anammoxbased process (Li et al., 2016; Meng et al., 2015, 2019). In this work, the efficient nitrogen removal, as well as the growth of anammox, has been for the first time calibrated and validated within the long-term UMSB operation. This result provides us opportunities to predict the effects of influent and operational conditions on UMSB nitrogen removal and reveal how anammox activity could be affected by these conditions, as described in the following sections.
3.4. Effects of influent and operational conditions on nitrogen removal In order to shed light on the changes in the influent COD and nitrogen concentrations and operational conditions such as temperature, oxygen mass transfer rate and HRT on UMSB nitrogen removal, a simulation study using the calibrated model was carried out. Fig. 4A shows the model simulated results on the TN removal efficiency of a steady state UMSB reactor with different influent COD and nitrogen loading rates. The simulations showed that over 70% TN removal (red region) can be attained either with high influent NLR (e.g., > 0.6 kg N/ (m3·d)) or with high influent OLR (e.g., > 0.8 kg COD/(m3·d)), indicating that high loading rate is critical to achieving high-efficient nitrogen removal. It has been reported that the influent COD/N ratio had an effect on nitrogen removal performance in previous experiments (Li et al., 2016; Meng et al., 2018b). However, this effect was not identified as the key to anammox-based nitrogen removal. In the simulations, the anammox process considerably contributed to the TN removal of the UMSB reactor, under the conditions of both low and high influent OLRs. The simulations also showed COD removal can maintain above 70% in each scenario with the relative abundance of denitrifiers account for 5.0–19.0% (Meng et al., 2017, 2019). Moreover, the established model was employed to assess the feasibility of removing nitrogen at relatively low influent ammonium nitrogen concentration (i.e., 50 mg/L) and loading rate (0.15 kg N/
Fig. 3. The model simulated results and measured data (averaged value) collected from the UMSB reactor in seven different periods. Effluent COD (A) and ammonium nitrogen concentrations (B), and total nitrogen removal loading rate (C). Details of seven periods (I-VII) can be found in Table 1. Error bar represents standard deviation.
3.3. Model validation by using independent operational data The model was validated by comparing the simulated results with independent data collected from the UMSB reactor operated under
Fig. 4. Model predictions on total nitrogen removal efficiency (%) of a steady–state UMSB system at different influent OLR and NLR conditions (A) and relatively low COD concentrations (B). Other parameters included 35 °C, HRT of 8 h and Kla,O2 value of 10 h−1 were fixed in the simulations. For the simulations in the right figure, influent ammonium nitrogen concentration was fixed to be 50 mg/L. 5
Bioresource Technology 295 (2020) 122225
J. Meng, et al.
(m3·d)). Model simulations were conducted with influent COD concentrations in the range from 0 to 200 mg COD/L with 50 mg COD/L steps. The operational temperature, HRT and SRT conditions were respectively fixed to be 20 °C, 8 h and 100 days. The simulated results showed that 72–83% TN and > 90% ammonium would be removed from the low-strength ammonium nitrogen wastewater at the various COD concentrations (Fig. 4B). Anammox process was very active to remove nitrogen at low influent COD concentration, but the anammox bacteria was gradually over-selected by NOB with the COD increasing. Despite this, the TN removal efficiency only slightly decreased as the nitrogen can be removed by conventional nitrification/denitrification process at relatively high influent COD. The results indicated that UMSB could be a promising system to achieve nitrogen removal from low-strength ammonium wastewater with fluctuated COD influence (e.g., domestic sewage). It should be noted that these modeling resulted from the use of different Kla,O2 values in different influent COD. The optimized Kla,O2 value increased from 4 to 12 h−1 with a step increment in 2 h−1 in respect to the stepwise increase in influent COD concentration, ensuring achievement of the high-efficient nitrogen removal in UMSB system. Scenarios analyses at different temperature showed that TN removal > 70% could be located in an operational region with temperature > 20 °C under a fixed influent OLR of 1.5 kg COD/(m3·d) and NLR of 0.75 kg N/(m3·d). However, with the temperature down to 15 °C, the removal efficiency drop to 40% with the presence of much nitrate in the effluent. Anammox activity often has a sharply decrease with the temperature down to 15 °C (Laureni et al., 2016). Similarly, anammox population (Candidatus Brocadia) was reduced in an upflow anammox sludge bed with the reduced temperature (Reino et al., 2018). Also, low TN removal might be attributed to a low AOB activity compared with that of the NOB when the temperature decreased down to 15 °C (Lotti et al., 2014). These results confirmed that low-temperature was not conducive to the anammox-based nitrogen removal in UMSB systems.
increase while unchanged at different influent OLRs. With the influent NLR beyond 0.6 kg N/(m3·d), the ammonium uptake rate by anammox can reach above 0.2 kg N/(m3·d), compared with the pace of around 0.4 kg N/(m3·d) for AOB under the same condition. Nitrite production and uptake of the different microbial processes are shown in Fig. 6. The nitrite production rate by AOB is high enough to support nitrite utilization by denitrifier, NOB and anammox. Mainly, the region of high nitrite uptake rate of NOB (i.e., NLR < 0.6 kg N/(m3·d)) is located oppositely, compared with that of anammox process (Fig. 6C and D). The denitrification rate on nitrite is always less than 0.1 kg N/(m3·d), which is the lowest level for the nitrite reduction. These results indicated that, in comparison with the influent OLR, UMSB operation of high influent NLR is critical to the success of anammox-based nitrogen removal process. Additionally, the denitrification rate on nitrate is higher that nitrate production rate by anammox, showing that the denitrification process is useful to decrease nitrate concentration in UMSB effluent. It has been reported that high influent COD loading rate would deteriorate anammox activity (Miao et al., 2018; Van de Graaf et al., 1996). The reason has been considered that denitrifier can out-compete the anammox bacteria in the biological treatment system. However, based on the modeling results, the nitrite uptake rate of denitrifier is much lower than that of anammox in the UMSB system. Jenni et al. (2014) reported the successful application of nitritation/anammox to treat wastewater with elevated organic carbon to ammonia ratios. They identified a long SRT parameter as the key for the achievement of anammox-based nitrogen removal process at high influent COD concentration. And, the dominant anammox Ca. Brocadia was the same as the anammox population in this study. As such, the reason for anammox prevalence in UMSB system might be due to the SRT parameter (~100 days) as the conventional UASB reactor configuration used. Besides, it is possibly due to high anammox growth rate calibrated in this study. Previous studies have also shown that limited-oxygen condition was essential to suppress NOB (Laureni et al., 2016; Li et al., 2016; Meng et al., 2015). In the UMSB system, AOB process consumes massive oxygen in comparison with heterotrophic and NOB. Therefore, the limited-oxygen condition can be achieved under the operation of high NLR parameter. In another way, oxygen mass transfer rate constant needs to be well-designed to match the oxygen uptake rate by AOB, and to achieve the anammox-based nitrogen removal process. This can be attained by using the method of aerated effluent reflux in UMSB system.
3.5. UMSB operation at high influent nitrogen loading rate favors anammox activity Nitrogen conversion rates of different nitrogen-related microbial processes were simulated to reveal what influent conditions favor anammox activity in a steady-state UMSB system. The simulations were conducted with the same procedure as described in Section 3.4. Fig. 5 presents ammonium uptake rates of anammox and AOB under different influent COD and nitrogen loading rates. The results show that the anammox activities are significantly affected by the influent NLR
Fig. 5. Model predictions on ammonium uptake rate by AOB (A) and anammox (B) of a steady-state UMSB at different influent OLR and NLR conditions. Substrate uptake rates were calculated from the steady-state biomass concentration and growth rate according to Table S5. 6
Bioresource Technology 295 (2020) 122225
J. Meng, et al.
Fig. 6. Model predictions on nitrite production rate by AOB (A), nitrite uptake rates by denitrifier (B), NOB (C) and anammox (D) of a steady-state UMSB at different influent OLR and NLR conditions.
4. Conclusion
References
A modified ASM model was calibrated and validated against a labscale UMSB reactor fed with piggery wastewater of various operational conditions. The model simulated a gradual increase of total nitrogen removal rate up to 1.0 kg N/(m3·d) over one year in the UMSB and calibrated the maximum anammox specific growth rate to be 0.41 d−1 at 35 °C. A further simulation revealed that with influent nitrogen loading rate over 0.6 kg N/(m3·d), varied organics loading rate (0.3–1.5 kg COD/(m3·d)), and temperature above 15 °C, can achieve high TN removal (> 70%). The UMSB operation under these conditions significantly favors anammox activity over denitrification.
A.P.H.A, 2005. Standard Methods for the Examination of Water and Wastewater, 19th ed. American Public Health Association, Washington, DC. Agrawal, S., Seuntjens, D., De Cocker, P., Lackner, S., Vlaeminck, S.E., 2018. Success of mainstream partial nitritation/anammox demands integration of engineering, microbiome and modeling insights. Curr. Opin. Biotechnol. 50, 214–221. Bartucca, M.L., Mimmo, T., Cesco, S., Del Buono, D., 2016. Nitrate removal from polluted water by using a vegetated floating system. Sci. Total Environ. 542, 803–808. Daija, L., Selberg, A., Rikmann, E., Zekker, I., Tenno, T., Tenno, T., 2016. The influence of lower temperature, influent fluctuations and long retention time on the performance of an upflow mode laboratory-scale septic tank. Desalin. Water Treat. 57 (40), 18679–18687. Dosta, J., Fernández, I., Vázquez-Padín, J.R., Mosquera-Corral, A., Campos, J.L., MataÁlvarez, J., Méndez, R., 2008. Short- and long-term effects of temperature on the Anammox process. J. Hazard. Mater. 154 (1), 688–693. Gilbert, E.M., Agrawal, S., Karst, S.M., Horn, H., Nielsen, P.H., Lackner, S., 2014. Low temperature partial nitritation/anammox in a moving bed biofilm reactor treating low strength wastewater. Environ. Sci. Technol. 48 (15), 8784–8792. Henze, M., Gujer, W., Mino, T., van Loosdrecht, M.C.M., 2000. Activated sludge models ASM1, ASM2, ASM2d and ASM3. IWA Publishing. Hao, X.-D., Cao, X.-Q., Picioreanu, C., Van Loosdrecht, M., 2005. Model-based evaluation of oxygen consumption in a partial nitrification-anammox biofilm process. Water Sci. Technol. 52 (7), 155–160. Hao, X.-D., Van Loosdrecht, M., 2004. Model-based evaluation of COD influence on a partial nitrification-Anammox biofilm (CANON) process. Water Sci. Technol. 49 (11–12), 83–90. Hao, X., Heijnen, J.J., Van Loosdrecht, M.C., 2002. Model-based evaluation of temperature and inflow variations on a partial nitrification–ANAMMOX biofilm process. Water Res. 36 (19), 4839–4849. Hiatt, W.C., Grady, C., 2008. An updated process model for carbon oxidation, nitrification, and denitrification. Water Environ. Res. 80 (11), 2145–2156. Jenni, S., Vlaeminck, S.E., Morgenroth, E., Udert, K.M., 2014. Successful application of nitritation/anammox to wastewater with elevated organic carbon to ammonia ratios. Water Res. 49, 316–326. Kaelin, D., Manser, R., Rieger, L., Eugster, J., Rottermann, K., Siegrist, H., 2009. Extension
Acknowledgments This study was supported in part by the National Natural Science Foundation of China (No. 51478141 and 51908163). Dr Jia Meng gratefully acknowledges the China Postdoctoral Science Foundation funded project (No. 2017M611376), the Hei Long Jiang Postdoctoral Foundation funded project (No. LBH-Z17087) and Fundamental Research Funds for the Central Universities (Grant No. HIT.NSRIF.2019045).
Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.biortech.2019.122225. 7
Bioresource Technology 295 (2020) 122225
J. Meng, et al.
C/N ratios. Chem. Eng. J. 334, 664–672. Moussavi, G., Jafari, S.J., Yaghmaeian, K., 2015. Enhanced biological denitrification in the cyclic rotating bed reactor with catechol as carbon source. Bioresour. Technol. 189, 266–272. Ni, B.-J., Joss, A., Yuan, Z., 2014. Modeling nitrogen removal with partial nitritation and anammox in one floc-based sequencing batch reactor. Water Res. 67, 321–329. Ni, B.J., Chen, Y.P., Liu, S.Y., Fang, F., Xie, W.M., Yu, H.Q., 2009. Modeling a granulebased anaerobic ammonium oxidizing (ANAMMOX) process. Biotechnol. Bioeng. 103 (3), 490–499. Orhon, D., Ateş, E., Sözen, S., Çokgör, E.U., 1997. Characterization and COD fractionation of domestic wastewaters. Environ. Pollut. 95 (2), 191–204. Reichert, P., 1994. AQUASIM – a tool for simulation and data analysis of aquatic systems. Water Sci. Technol. 30 (2), 21–30. Reino, C., Suárez-Ojeda, M.E., Pérez, J., Carrera, J., 2018. Stable long-term operation of an upflow anammox sludge bed reactor at mainstream conditions. Water Res. 128, 331–340. Sarioglu, M., Insel, G., Artan, N., Orhon, D., 2009. Model evaluation of simultaneous nitrification and denitrification in a membrane bioreactor operated without an anoxic reactor. J. Membr. Sci. 337 (1), 17–27. Strous, M., Heijnen, J., Kuenen, J., Jetten, M., 1998. The sequencing batch reactor as a powerful tool for the study of slowly growing anaerobic ammonium-oxidizing microorganisms. Appl. Microbiol. Biotechnol. 50 (5), 589–596. Van de Graaf, A.A., de Bruijn, P., Robertson, L.A., Jetten, M.S., Kuenen, J.G., 1996. Autotrophic growth of anaerobic ammonium-oxidizing micro-organisms in a fluidized bed reactor. Microbiology 142 (8), 2187–2196. Wang, Q., Duan, H., Wei, W., Ni, B., Laloo, A., Yuan, Z., 2017. Achieving stable mainstream nitrogen removal via the nitrite pathway by sludge treatment using free ammonia. Environ. Sci. Technol. 51 (17), 9800–9807. Wiesmann, U., 1994. Biological nitrogen removal from wastewater. In: Biotechnics/ Wastewater. Springer, pp. 113–154. Xu, G., Zhou, Y., Yang, Q., Lee, Z.M.-P., Gu, J., Lay, W., Cao, Y., Liu, Y., 2015. The challenges of mainstream deammonification process for municipal used water treatment. Appl. Microbiol. Biotechnol. 99 (6), 2485–2490. Yang, Y., Zhang, L., Cheng, J., Zhang, S., Li, B., Peng, Y., 2017. Achieve efficient nitrogen removal from real sewage in a plug-flow integrated fixed-film activated sludge (IFAS) reactor via partial nitritation/anammox pathway. Bioresour. Technol. 239, 294–301. Zhang, L., Narita, Y., Gao, L., Ali, M., Oshiki, M., Okabe, S., 2017. Maximum specific growth rate of anammox bacteria revisited. Water Res. 116, 296–303. Zekker, I., Kivirüüt, A., Rikmann, E., Mandel, A., Jaagura, M., Tenno, T., Tenno, T., 2019. Enhanced efficiency of nitritating-anammox sequencing batch reactor achieved at low decrease rates of oxidation–reduction potential. Environ. Eng. Sci. 36 (3), 350–360. Zheng, M., Liu, Y., Wang, C., Xu, K., 2013. Study on enhanced denitrification using particulate organic matter in membrane bioreactor by mechanism modeling. Chemosphere 93 (11), 2669–2674. Zheng, M., Liu, Y., Wang, C.W., 2014. Modeling of enhanced denitrification capacity with microbial storage product in MBR systems. Sep. Purif. Technol. 126, 1–6. Zheng, M., Wu, S., Zuo, Z., Wang, Z., Qiu, Y., Liu, Y., Huang, X., Yuan, Z., 2018. Predictions of the influent and operational conditions for partial nitritation with a model incorporating pH dynamics. Environ. Sci. Technol. 52 (11), 6457–6465. Zheng, M., Wu, S., Dong, Q., Huang, X., Yuan, Z., Liu, Y., 2019. Achieving mainstream nitrogen removal via the nitrite pathway from real municipal wastewater using intermittent ultrasonic treatment. Ultrason. Sonochem. 51, 406–411.
of ASM3 for two-step nitrification and denitrification and its calibration and validation with batch tests and pilot scale data. Water Res. 43 (6), 1680–1692. Klein, K., Kivi, A., Dulova, N., Zekker, I., Mölder, E., Tenno, T., Tenno, T., 2017. A pilot study of three-stage biological–chemical treatment of landfill leachate applying continuous ferric sludge reuse in Fenton-like process. Clean Technol. Environ. 19 (2), 541–551. Koch, G., Kühni, M., Gujer, W., Siegrist, H., 2000. Calibration and validation of activated sludge model no. 3 for Swiss municipal wastewater. Water Res. 34 (14), 3580–3590. Kuypers, M.M.M., Sliekers, A.O., Lavik, G., Schmid, M., Jorgensen, B.B., Kuenen, J.G., Sinninghe Damste, J.S., Strous, M., Jetten, M.S.M., 2003. Anaerobic ammonium oxidation by anammox bacteria in the Black Sea. Nature 422 (6932), 608–611. Lackner, S., Gilbert, E.M., Vlaeminck, S.E., Joss, A., Horn, H., van Loosdrecht, M.C., 2014. Full-scale partial nitritation/anammox experiences–an application survey. Water Res. 55, 292–303. Laureni, M., Falås, P., Robin, O., Wick, A., Weissbrodt, D.G., Nielsen, J.L., Ternes, T.A., Morgenroth, E., Joss, A., 2016. Mainstream partial nitritation and anammox: longterm process stability and effluent quality at low temperatures. Water Res. 101, 628–639. Li, J., Meng, J., Li, J., Wang, C., Deng, K., Sun, K., Buelna, G., 2016. The effect and biological mechanism of COD/TN ratio on nitrogen removal in a novel upflow microaerobic sludge reactor treating manure-free piggery wastewater. Bioresour. Technol. 209, 360–368. Liu, T., Ma, B., Chen, X., Ni, B.-J., Peng, Y., Guo, J., 2017. Evaluation of mainstream nitrogen removal by simultaneous partial nitrification, anammox and denitrification (SNAD) process in a granule-based reactor. Chem. Eng. J. 327, 973–981. Lotti, T., Kleerebezem, R., Hu, Z., Kartal, B., Jetten, M.S.M., van Loosdrecht, M.C.M., 2014. Simultaneous partial nitritation and anammox at low temperature with granular sludge. Water Res. 66, 111–121. Mandel, A., Zekker, I., Jaagura, M., Tenno, T., 2019. Enhancement of anoxic phosphorus uptake of denitrifying phosphorus removal process by biomass adaption. Int. J. Environ. Sci. Technol. 1–14. McCarty, P.L., 2018. What is the best biological process for nitrogen removal: when and why? Environ. Sci. Technol. 52 (7), 3835–3841. Meng, J., Li, J., Li, J., Antwi, P., Deng, K., Nan, J., Xu, P., 2018a. Enhanced nitrogen removal from piggery wastewater with high NH 4+ and low COD/TN ratio in a novel upflow microaerobic biofilm reactor. Bioresour. Technol. 249, 935–942. Meng, J., Li, J., Li, J., Antwi, P., Deng, K., Wang, C., Buelna, G., 2015. Nitrogen removal from low COD/TN ratio manure-free piggery wastewater within an upflow microaerobic sludge reactor. Bioresour. Technol. 198, 884–890. Meng, J., Li, J., Li, J., Astals, S., Nan, J., Deng, K., Antwi, P., Xu, P., 2018b. The role of COD/N ratio on the start-up performance and microbial mechanism of an upflow microaerobic reactor treating piggery wastewater. J. Environ. Manage. 217, 825–831. Meng, J., Li, J., Li, J., Deng, K., Nan, J., Xu, P., 2017. Effect of reflux ratio on nitrogen removal in a novel upflow microaerobic sludge reactor treating piggery wastewater with high ammonium and low COD/TN ratio: efficiency and quantitative molecular mechanism. Bioresour. Technol. 243, 922–931. Meng, J., Li, J., Li, J., Nan, J., Deng, K., Antwi, P., 2019. Effect of temperature on nitrogen removal and biological mechanism in an up-flow microaerobic sludge reactor treating wastewater rich in ammonium and lack in carbon source. Chemosphere 216, 186–194. Miao, Y., Peng, Y., Zhang, L., Li, B., Li, X., Wu, L., Wang, S., 2018. Partial nitrificationanammox (PNA) treating sewage with intermittent aeration mode: effect of influent
8