anoxic process

Bioresource Technology 222 (2016) 39–48

Contents lists available at ScienceDirect

Bioresource Technology journal homepage: www.elsevier.com/locate/biortech

Mathematical modeling of nitrous oxide production in an anaerobic/ oxic/anoxic process Xiaoqian Ding a, Jianqiang Zhao a,b,⇑, Bo Hu c, Ying Chen a,b, Guanghuan Ge a, Xiaoling Li c, Sha Wang a, Kun Gao a, Xiaolei Tian a a b c

School of Environmental Science and Engineering, Chang’an University, Xi’an 710064, Shaanxi, China Key Laboratory of Subsurface Hydrology and Ecological Effect in Arid Region of Ministry of Education, Xi’an 710064, Shaanxi, China School of Civil Engineering, Chang’an University, Xi’an 710064, Shaanxi, China

h i g h l i g h t s

g r a p h i c a l a b s t r a c t

 A mathematical model was proposed

for N2O production modeling in an AOA process.  Three pathways in nitritation and denitrification processes were coupled.  N2O production by AOB denitrification in aeration stage was dominant.  N2 was the end-product of heterotrophic denitrification at adequate XSTO.  High nitrite inhibition led to N2O accumulation in heterotrophic denitrification.

a r t i c l e

i n f o

Article history: Received 19 July 2016 Received in revised form 16 September 2016 Accepted 22 September 2016 Available online 24 September 2016 Keywords: N2O modeling N2O production pathway AOA process AOB denitrification Heterotrophic denitrification on intracellular polymers

a b s t r a c t This study incorporates three currently known nitrous oxide (N2O) production pathways: ammoniumoxidizing bacteria (AOB) denitrification, incomplete hydroxylamine (NH2OH) oxidation, and heterotrophic denitrification on intracellular polymers, into a mathematical model to describe N2O production in an anaerobic/oxic/anoxic (AOA) process for the first time. The developed model was calibrated and validated by four experimental cases, then evaluated by two independent anaerobic/aerobic (AO) studies from literature. The modeling results displayed good agreement with the measured data. N2O was primarily generated in the aerobic stage by AOB denitrification (67.84–81.64%) in the AOA system. Smaller amounts of N2O were produced via incomplete NH2OH oxidation (15.61–32.17%) and heterotrophic denitrification on intracellular polymers (0–12.47%). The high nitrite inhibition on N2O reductase led to the increased N2O accumulation in heterotrophic denitrification on intracellular polymers. The new model was capable of modeling nitrification-denitrification dynamics and heterotrophic denitrification on intracellular polymers in the AOA system. Ó 2016 Elsevier Ltd. All rights reserved.

1. Introduction

⇑ Corresponding author at: School of Environmental Science and Engineering, Chang’an University, Xi’an 710064, Shaanxi, China. E-mail address: [email protected] (J. Zhao). http://dx.doi.org/10.1016/j.biortech.2016.09.092 0960-8524/Ó 2016 Elsevier Ltd. All rights reserved.

N2O is an important greenhouse gas with a global warming capacity 265 times as large as CO2 in a 100-year perspective. A small increase in N2O accumulation would exert a large negative

40

X. Ding et al. / Bioresource Technology 222 (2016) 39–48

effect on the environment during its long atmospheric lifetime (121+ years) (IPCC, 2013). This increase also contributes to the destruction of the ozone layer by reacting with oxygen (O2) in the stratosphere (Ravishankara et al., 2009). It is generally accepted that N2O can be produced during both aerobic nitrification and anoxic denitrification in biological nitrogen removal (BNR) processes. N2O production is influenced by various process factors, such as the influent carbon to nitrogen (C/N) ratio, dissolved oxygen (DO) level, nitrite accumulation, type of carbon source, and operational characteristics (Law et al., 2013; Li et al., 2013; Ni et al., 2015). Unfortunately, the complex mechanisms of N2O production in wastewater treatment are not yet fully understood. Mathematical modeling has been demonstrated to be useful for testing hypotheses of pollutant removal in wastewater treatment. Previous modeling efforts primarily focused on determining the nitrogen removal performance in wastewater treatment (Henze et al., 2000). The significance of N2O accumulation has been increasingly recognized in recent years. Firstly, the Activated Sludge Model for Nitrogen (ASMN) proposed by Hiatt and Grady (2008) was successfully developed to understand the mechanism of N2O production by heterotrophic bacteria. This model is able to predict N2O production by modeling anoxic denitrification as a four-step process, using nitrate (NO3 ), nitrite (NO2 ), nitric oxide (NO), and finally, N2O as the terminal electron acceptor in each step. Subsequently, the improved version, named Activated Sludge Model for Indirect Coupling of Electrons (ASM-ICE), was developed to represent the electron competition between the four denitrification steps (Pan et al., 2015). In addition, two autotrophic nitrification pathways, including the AOB denitrification pathway and the incomplete NH2OH oxidation pathway, were recently proposed in several single-pathway and two-pathway models to expose the mechanism of N2O production by autotrophic bacteria (Ni et al., 2011, 2013, 2014). Moreover, several studies have succeeded in integrating the four-step heterotrophic denitrification process of ASMN and the autotrophic nitrification pathways to model N2O production from both batch tests and full-scale wastewater treatment plants (WWTPs) (Ni et al., 2011, 2013, 2015). But the heterotrophic denitrification pathway adopted in the above models did not consider the role of intracellular polymers on N2O production under conditions of external carbon limitation, although the utilization of polyhydroxyalkanoate (PHA) has been reported to lead to potential N2O accumulation during heterotrophic denitrification (Schalk-Otte et al., 2000; Zhou et al., 2012). Later, the relations between heterotroph growth on intracellular polymers and N2O production/consumption were thoroughly investigated in two published models (Liu et al., 2015a, 2015b). Both models satisfactorily described PHA storage/utilization, nitrogen reduction, and N2O accumulation in several denitrification and denitrifying phosphorus removal processes (Liu et al., 2015a, 2015b). However, since some of the published models above were developed for predicting N2O production in autotrophic nitrification process or in heterotrophic denitrification process alone (Hiatt and Grady, 2008; Ni et al., 2014), they are unable to deal with N2O modeling in the full-course BNR processes. Other models that were capable of describing N2O production both in nitrification and denitrification processes were successfully applied to model N2O emission in full-scale WWTPs (Ni et al., 2013, 2015), but the assumed heterotrophic denitrification pathway regarded the readily biodegradable substrate as the sole carbon source, the role of intracellular polymers in denitrification was not considered in these models. Meanwhile, models investigating the role of intracellular polymers in heterotrophic denitrification did not cover the autotrophic pathways in turn (Liu et al., 2015a, 2015b). As a result, none of these currently available models can serve to comprehensively describe N2O production by the heterotrophic denitrification

on intracellular polymers, AOB denitrification, and incomplete NH2OH oxidation pathways in a full-course BNR process. In this work, a mathematical model was developed to describe N2O production during autotrophic nitrification and heterotrophic denitrification processes in an anaerobic/oxic/anoxic (AOA) system. AOB denitrification, incomplete NH2OH oxidation, and heterotrophic denitrification on intracellular polymers were integrated to investigate the mechanisms of N2O production and the role of intracellular polymers in denitrification. The model was first calibrated and validated using experimental data from four case studies with different influent characteristics. Then the model was evaluated by two independent anaerobic/aerobic (AO) studies published in literature. Finally the predictive capability of the model in N2O production was tested by an AOA study from literature. The newly presented model is the first to couple biochemical reactions of autotrophic nitrification and heterotrophic denitrification on intracellular polymers observed in experimental studies. It is expected to be beneficial for understanding the mechanisms of N2O production in AOA processes.

2. Materials and methods 2.1. Model development The AOA process undergoes the alternating anaerobic/oxic/ anoxic condition to achieve cell internal product storage and nitrogen removal. In this process, readily biodegradable substrate is stored in the form of intracellular polymers by heterotrophic bacteria under anaerobic conditions. Under the subsequent aerobic stage with low DO levels, ammonium is oxidized to a large quantity of nitrite and a small quantity of nitrate by AOB and nitrite oxidizing bacteria (NOB), respectively, accompanied by the heterotrophic growth on intracellular polymers. Then heterotrophs denitrify nitrate to nitrite, and nitrite to NO, subsequently N2O, finally N2 in the following anoxic stage, using the energy obtained from the heterotrophic growth on intracellular polymers. Simultaneous nitrification-denitrification (SND) process usually occurs during the aerobic stage under oxygen-limited conditions. The mechanisms of nitrogen dynamics and N2O production in the AOA system are expressed in Fig. 1. The developed model synthesized all these relevant reactions and all N2O accumulation steps potentially occurred in the AOA process. It has been known that ASM3 (Henze et al., 2000) is advanced in modeling nitrogen removal by importing the microbial storage and growth processes on organic substrates, but it has limitations in describing the heterotrophic denitrification process as a multistep reaction. It is deficient to predict the obligatory intermediates including nitrite, nitric oxide, and nitrous oxide in BNR processes. Thus the denitrification process based on ASM3 was extended to a four-step reaction in this study to investigate nitrogen conversion in the AOA process. Another modification was importing the published process of anaerobic storage on organic carbon under electron acceptor absent conditions (Liu et al., 2015a). Moreover, considering that nitrite accumulated in the aerobic nitrification stage of this AOA system, the autotrophic microorganisms were divided into two types of bacteria, AOB and NOB. As a result, a model was proposed by incorporating microbial storage-growth and four-step denitrification of heterotrophs, well-known AOB denitrification, and incomplete NH2OH oxidation in this work. The model components, stoichiometry, composition matrix, and kinetic rate expressions are summarized in Supplementary Material Tables S.1–S.3. Fifteen processes were included in this model, thirteen in which were stated to describe the biochemical reactions occurred in the AOA system:

41

X. Ding et al. / Bioresource Technology 222 (2016) 39–48

Three pathways for N2O production in AOA system Aerobic stage

O2

Growth

NH4+ NH4+

Anaerobic stage Storage

SS

NO2-

NH2OH

XA

N2O

XSTO

NO3-

NO3-

Growth

XSTO NO2-

NO

Growth

XSTO N2O

O2

Anoxic stage

NO3-

NO2-

NO

XH N2O

N2

XH

N2O

N2

Growth AOB denitrification pathway

Incomplete NH2OH oxidation pathway

Heterotrophic pathway of denitrification on intracellular polymers

Fig. 1. Schematic representation of the reactions involved in the model for the AOA system.

(R1) Anaerobic storage of intracellular polymers, with the complete depletion of readily biodegradable substrates (SS) and production of cell internal storage products (XSTO); (R5) Anoxic growth on XSTO of heterotrophs, with the four-step denitrification process and N2O as an intermediate, i.e. the heterotrophic pathway of denitrification on intracellular polymers (the heterotrophic denitrification pathway for short) as shown in Fig. 1❸; (R8) Autotrophic nitritation by AOB: (R8.1) NH+4 oxidation to NH2OH, catalyzed by ammonia monooxygenase (AMO) with oxygen consumption; (R8.2) NH2OH oxidation to NO2 , catalyzed by hydroxylamine oxidoreductase (HAO), with O2 as an electron acceptor; (R8.3) NH2OH oxidation, with NO2 as the terminal electron acceptor to produce NO and subsequently N2O, i.e. the AOB denitrification pathway as shown in Fig. 1❶; (R8.4) Incomplete NH2OH oxidation generated a byproduct of N2O, i.e. the incomplete NH2OH denitrification pathway as shown in Fig. 1❷; (R9) NO2 oxidation to NO3 by NOB; It should be noted that, the Haldane FA (free ammonia) inhibition function on ammonium oxidation in a previous model (Pocquet et al., 2013) was adopted in process R8.1, and a FA inhibition on NOB growth was considered by employing a conventional switching function Ki/(Ki + Si) in process R9. In addition, NO production and consumption were omitted in two autotrophic production pathways as NO accumulation is usually rare during AOB denitrification (Chandran et al., 2011). Moreover, N2O can be produced through both biological reduction of NO and chemical decomposition of nitrosyl radical (NOH) during NH2OH oxidation, but the direct source of N2O generation during NH2OH oxidation has not been fully clarified (Ni et al., 2013). Therefore, the incomplete NH2OH oxidation pathway was simplified as a one-step reaction by omitting both NO and NOH. The accompanying reaction processes (R2, R3, R4, R6, R7, R10, R11, R12, and R13) were essentially the same as those in ASM models (Henze et al., 2000).

2.2. Experimental data The AOA process performed under nitrite-route strategies is a promising method for simultaneous carbon storage and nitrogen

removal in wastewater treatment (Miao et al., 2015; Liu et al., 2013), but substantial amounts of harmful N2O can potentially be generated (Jia et al., 2012; Law et al., 2013; Zeng et al., 2003), and knowledge of the N2O production mechanisms acting in the AOA processes is of great importance. Therefore, a 5 L sequencing batch reactor (SBR) operated under the AOA mode was used to explore N2O accumulation mechanisms in the experimental study. The SBR was inoculated with activated sludge taken from a local municipal wastewater treatment plant in Xi’an, China. Synthetic wastewater was used in this study, the influent compositions of the four experimental cases with different influent C/N ratios are shown in Supplementary Material Table S.5. The operation cycles of typical cases are shown in Supplementary Material Table S.6. 2 L of supernatant was discharged from the middle port of the reactor after sludge settling. During the daily run periods (Case 0 in Table 1), HRT (hydraulic retention time) was controlled at 20 h. MLVSS (mixed liquor volatile suspended solid) in the reactor was maintained at approximately 4000 mg L 1 and certain amount of excess sludge was disposed at the end of aerobic phase to control SRT (sludge retention time) at approximately 20 d. Air was supplied at a gas flow rate of 60 L h 1 to maintain a low DO level of approximately 0.5 mg O2 L 1 to achieve short-cut nitrification in aerobic stages. Reaction temperature was controlled at 30 ± 1 °C by using a water jacket. The average pH value was maintained at 7.3–8.4. After 3 months of operation, the reactor reached a steady-state, with more than 98% of NH+4 oxidation to NO2 during the aeration period and greater than 85% of TN removal in effluent. The water quality indexes were quantified by the standard methods (APHA, 2005) throughout the experimental study. The dissolved N2O concentration in liquid was monitored online by a micro-sensor (Unisense, Denmark). N2O production was determined by the calculating methods of Zhao et al. (2016). The pH value, DO, and temperature were measured by online probes. 2.3. Model calibration and validation Model calibration for optimizing parameter values was performed by fitting the simulation results to the experimental data. The most crucial and those rarely obtained parameters were estimated to reduce the calibration complexity. Moreover, mass transfer coefficients of oxygen and N2O, i.e. K L aO2 and K L aN2 O , were determined by the established experiments and calculating

42

X. Ding et al. / Bioresource Technology 222 (2016) 39–48

Table 1 Operation characteristics and results of the experimental cases of the AOA process. Item

Operation characteristic and result Case 0

Case 1

Case 2

Case 3

Case 4

Influent COD (mg COD L 1) Influent NH+4-N (mg N L 1) Influent C/N Cycle length (min) MLVSS (mg L 1) DO (mg O2 L 1) NH+4-N oxidation rate (%) Nitrogen removal rate (%)

500 120 4.17 480 4133 0.50 98.45 97.15

516.10 63.10 8.18 350 4325 0.64 95.45 97.53

530.70 122.20 4.34 580 4225 0.58 99.12 98.30

470.3 232.48 2.02 780 3550 0.76 98.95 85.10

0 59.29 0 655 2918 0.87 97.12 69.20

methods (Dosta et al., 2007; Zhao et al., 2016). Experimental data from Case 2, which represented a common C/N ratio as 4.34 in domestic wastewater, were used for model calibration. Experimental data from Cases 1, 3, 4, which represented the different influent characteristics with both high and low C/N ratios (8.18, 2.02, and 0), were used for model validation. The operation characteristics and results of the four cases and a typical daily running case (Case 0) are summarized in Table 1. The initial biomass concentrations of heterotrophs, AOB, and NOB for modeling in Cases 1–4 were hypothesized as 2000 mg COD L 1, 200 mg COD L 1, and 10 mg COD L 1, respectively (Snip et al., 2014). The auxiliary calculating tool of MATLAB (R2012a) program was selected as the computational platform. The model programs are freely available for research purpose, please visit the website: http://pan.baidu.com/s/1skJqEaL. 2.4. Model evaluation To further verify the validity of the model, experimental data from literature were also applied to evaluate the model structure and parameter values. Due to lack of AOA processes investigating N2O production (the study on N2O accumulation in an AOA system was provided in this work for the first time), two independent AO studies (Ge et al., 2015; Lemaire et al., 2006) with particular focus on N2O accumulation were used to evaluate the model applicability. The detailed experimental setups of the two AO studies are shown in Supplementary Material Table S.7. For AO I evaluation, one set of data from Cycle 1 representing the stable period were used to recalibrate the model parameters. Model evaluation was then carried out with the recalibrated parameter values using another set of experimental data from Cycle 2, which represented the deteriorative period with an increase in the effluent NO3 concentration (Lemaire et al., 2006). And for AO II evaluation, the model parameters were recalibrated using the typical cycle results with low nitrogen load (Cycle 1), and then validated using cycle data with high nitrogen load (Cycle 2) (Ge et al., 2015). To this end, three model parameters were recalibrated for both two cultures. 2.5. Model predictive capability To test the predictive capability of the model, the developed model was used to predict N2O production in an AOA system from literature. The detailed experimental setup of the published AOA study (Semerci and Hasilci, 2016) for N2O prediction testing (AOAT) is shown in Supplementary Material Table S.7. The SBR was operated for 135 days, with different C/N and carbon to phosphorus (C/P) ratios during three operational periods. The reported data of NH+4, NO2 , NO3 and acetate (HAc) in Day 125 with C/N ratio of 8 were used to evaluate the predictive capability of the new model. The parameters calibrated by our AOA system were used to predict N2O accumulation in the reported AOAT system.

3. Results and discussion 3.1. Parameter calibration The developed model includes fifty-two stoichiometric and kinetic parameters, as summarized in Supplementary Material Table S.4. Forty-three of these model parameters were well established in previous studies, thus literature values for these parameters were directly adopted in this model. Nine parameters were estimated, including: anoxic growth rates on XSTO of heterotrophs for nitrate, nitrite, nitric oxide, and nitrous oxide reduction (lH;STO;NO;1 , lH;STO;NO;2 , lH;STO;NO;3 , and lH;STO;NO;4 ), reduction factors for AOB denitrification and NH2OH oxidation (gAOB;1 and gAOB;2 ), the aerobic growth rate of heterotrophs on XSTO (lH;STO;O2 ), and the oxygen and ammonium inhibition constants for AOB (K I;AOB;O2 and K I;AOB;NH4 ). The calibrated values for lH;STO;NO;1 , lH;STO;NO;2 , lH;STO;NO;3 , and lH;STO;NO;4 of 3.4, 7, 6, and 5.5 d 1, respectively, were higher than earlier published values (Liu et al., 2015a, 2015b). The lH;STO;O2 value of 8.2 d 1 reflected the average anoxic growth rate on XSTO, which was approximately 68% of the aerobic growth rate. Moreover, the higher gAOB;1 value of 0.48 and the K I;AOB;O2 value of 0.2 mg O2 L 1 indicated a more rapid AOB denitrification rate under the nitrite accumulation conditions in this work compared with the previous study (Ni et al., 2011). The higher values of the calibrated lH;STO;NO;1 , lH;STO;NO;2 , lH;STO;NO;3 , lH;STO;NO;4 , and gAOB;1 than the previously published values (Liu et al., 2015a, 2015b; Ni et al., 2011) were possibly due to the different operation conditions and reaction regimes, resulting in a distinct community structure of microorganisms that contributed to AOB and heterotrophic denitrification.

3.2. Model validation The model was initially calibrated using the experimental data from Case 2 in the AOA system. The predicted NH+4, NO3 , NO2 , N2O, SS, and DO profiles and the measured data are illustrated in Fig. 2. After 60 min of anaerobic storage of XSTO, the influent SS was depleted. Subsequently, the DO concentration increased to 0.43 mg O2 L 1 at the commencement of aeration and maintained a constant level throughout the aerobic stage. N2O increased gradually along with the accumulation of nitrite from ammonium oxidation under aerobic conditions. DO concentrations increased again at the end of aeration when NH+4 was completely oxidized. Finally, NO3 and NO2 were denitrified to N2O and N2 during heterotrophic growth on XSTO in the anoxic stage (Supplementary Material Fig. S.4B). The agreement between the modeled and measured data suggested that the developed model properly captured the relations among N2O accumulation, nitrogen conversion, XSTO storage/consumption and DO variation that occurred in Case 2. The parameter values that provided the optimum model fittings

X. Ding et al. / Bioresource Technology 222 (2016) 39–48

43

Fig. 2. Model calibration with experimental data from Case 2 (influent C/N = 4.34): (A) NH+4, NO2 , NO3 ; (B) N2O; (C) DO and (D) SS profiles. ‘‘Ana”, ‘‘Oxic” and ‘‘Ano” refer to the anaerobic, aerobic and anoxic stage, respectively.

Fig. 3. Model validation with experimental data from Case 1 (influent C/N = 8.18): (A) NH+4, NO2 , NO3 ; (B) N2O; (C) DO and (D) SS profiles. ‘‘Ana”, ‘‘Oxic” and ‘‘Ano” refer to the anaerobic, aerobic and anoxic stage, respectively.

with the experimental data are summarized in Supplementary Material Table S.4. Next, the experimental data obtained from Case 1 and Case 3 were used to validate the model suitability in terms of NH+4, NO3 , NO2 , N2O, SS, and DO dynamics. The calibrated parameters in Case 2 were used to check the model validation. As shown in Figs. 3

and 4, the profiles of the variables involved in Case 1 and Case 3 were similar to Case 2, except for the different amounts of N2O accumulation in the anoxic stages. NO2 was reduced to an endproduct in the form of N2 without N2O accumulation by heterotrophic denitrification in both the aerobic and anoxic stages of Case 1. In contrast, the higher nitrite accumulation and the foregoing

44

X. Ding et al. / Bioresource Technology 222 (2016) 39–48

Fig. 4. Model validation with experimental data from Case 3 (influent C/N = 2.02): (A) NH+4, NO2 , NO3 ; (B) N2O; (C) DO and (D) SS profiles. ‘‘Ana”, ‘‘Oxic” and ‘‘Ano” refer to the anaerobic, aerobic and anoxic stage, respectively.

Table 2 R2 values of the simulation results for four cases.

NH+4 NO2 N2O SS

Case 1

Case 2

Case 3

Case 4

0.9620 0.8610 0.9899 0.9050

0.9982 0.9407 0.9889 0.8443

0.9943 0.9725 0.9947 0.9197

0.9682 0.9914 0.9767 –

aerobic consumption of XSTO led to higher N2O production during the anoxic stage in Case 3 compared with Case 2 (Supplementary Material Fig. S.4). The model captured these trends reasonably well. The R2 values of the main variables for the four cases are illustrated in Table 2. Finally, the measured data from Case 4 were used to validate the model in extreme conditions, such as an influent lacking a carbon supply (Fig. 5). The main distinctions were the slower denitrification rate and lower N2O production value in Case 4 than those values in Cases 1–3. The heterotrophic denitrification rate was zero due to the lack of a carbon source in the anoxic stage, but a decreasing trend in NO2 and an increasing trend in N2O were observed in both the experimental and simulated data. The average R2 value of the main variables was 0.9538 (Table 2), indicating that the established model structure and parameter values are robust in their ability to predict NH+4, NO3 , NO2 , N2O, SS, and DO profiles under different operation conditions in AOA systems.

3.3. Model evaluation The model and its parameters were first evaluated with the data of NH+4, NO2 , NO3 , N2O and HAc from AO I study. The model simulations and the experimental results are shown in Supplementary Material Fig. S.1. Evaluation results showed that the model predictions mostly matched the measured data in experiment, which fur-

ther supported the validity of the developed model. The deviation of N2O profiles brought by model predictions might be attributed to possible unrevealed N2O mechanisms in the system that were not considered in the model. Even so, the tendency of the transient accumulation and the peak value of dissolved N2O were predicted well throughout the study, and the predicted amount of N2O emission (approximately 27.5 mg N in each cycle) was consistent with the provided value by the literature (Lemaire et al., 2006). Three parameters, including the anoxic maximum growth rate on XSTO of heterotrophs for N2O reduction, the saturation constant of oxygen for heterotrophs and the reduction factor for AOB denitrification (lH;STO;NO;4 , K H;O2 and gAOB;1 ), were calibrated for this culture. The obtained lH;STO;NO;4 value of 2.56 d 1 was lower than that in our AOA system, meaning that N2O would be more inclined to accumulate during the heterotrophic denitrification process in this system. The obtained K H;O2 value was 0.15 g O2 m 3, comparable with that of 0.2 g O2 m 3 in our AOA system. The calibrated gAOB;1 value of 0.72 was higher than 0.48 in our AOA system might due to the distinct operational conditions, such as the low temperature and the on–off aeration mode. The experimental results obtained from AO II were also used to evaluate the developed model in terms of NH+4, NO2 , NO3 , N2O and DO dynamics. The model predictions matched the experimental results well under the conditions of both low and high influent nitrogen loads, again supporting the validity of the developed model, as shown in Supplementary Material Fig. S.2. The difference of N2O profiles between Modeling and experimental results was likely that, N2O produced by AOB denitrification pathway was immediately reduced to N2 by the heterotrophic denitrification on the adequate intracellular polymers at the commencement of aeration, and it caused a delay of N2O accumulation observed in the experiment study. After a 3–5 h aerobic consumption of intracellular polymers, the remained storage carbon was insufficient for denitrifying so N2O began to accumulate, as the N2O reduction step owns less competition capability for electron compared with other

X. Ding et al. / Bioresource Technology 222 (2016) 39–48

45

Fig. 5. Model validation with experimental data from Case 4 (influent C/N = 0): (A) NH4+; (B) NO2 ; (C) N2O and (D) DO profiles. ‘‘Ana”, ‘‘Oxic” and ‘‘Ano” refer to the anaerobic, aerobic and anoxic stage, respectively.

denitrification steps (Pan et al., 2013). Therefore, more complete mechanisms of N2O production and consumption should be identified and added to the developed model in the future. Nevertheless, the model predicted nitrogen intermediates and DO dynamics well, and it can serve as a tool to explore the unknown mechanisms of N2O accumulation across nitrification and denitrification systems. Three key parameters, including the maximum reaction rate catalyzed by AMO for AOB, the reduction factor for AOB denitrification and the reduction factor for NH2OH oxidation (qAOB;AMO;O2 , gAOB;1 and gAOB;2 ), were calibrated for this culture. The obtained low qAOB;AMO;O2 , gAOB;1 and gAOB;2 values of 1.85 d 1, 0.025 and 0.08 represented the slow AOB denitrification rate and the low proportion of incomplete NH2OH oxidation in this system. The low values of qAOB;AMO;O2 , gAOB;1 and gAOB;2 might due to the extremely low DO levels during the long-term operation resulting in the low activities of autotrophs in this reported system. It should be noted that the model structure and most of the parameter values in these independent experimental studies (AO I, AO II and our AOA system) were the same. The difference of the few parameter values among these validation and evaluation studies was likely due to that the substantially different conditions (i.e., different reaction temperatures, DO levels, aeration modes, SRT, organic matters and operating strategies) resulted in distinct microbial communities in three systems (Liu et al., 2015b). In addition, having a solid model structure is a critical step towards reliable prediction of N2O accumulation, as N2O production and consumption processes were primarily described by the model structure rather than model parameters (Pan et al., 2015). As demonstrated in this work, this model is attractive for describing the complex N2O production mechanisms in oxygen-limited nitrification, endogenous denitrification and SND processes because its parameters can be identified relatively easily with small uncertainties (three of fifty-two parameters have to be calibrated). Thus,

these extensive evaluations could strongly support the validity and applicability of the developed model in this work. 3.4. Predictive capability of the model A set of NH+4, NO2 , NO3 , HAc and DO data from the published AOAT system were used to predict N2O production and accumulation using the developed model. The Modeling results matched the measured values well as shown in Supplementary Material Fig. S.3. The predicted N2O accumulation and N2 production in the AOAT system were 10.79 mg N L 1 and 16.14 mg N L 1, the N2O and N2 proportions to the removed nitrogen were 36.14% and 54.05%, respectively. N2O was mainly produced during the aerobic nitrification stage, while N2 was primarily generated during the anoxic stage. The features of pollutants transformation in the AOAT study were similar to our AOA system, thus the model parameters for the AOAT system were directly adopted the calibrated values in Supplementary Material Table S.4. The good agreement of predictions with measurements of NH+4, NO2 , NO3 , HAc and DO supported the reliable predictive ability of the model in this work. It also illustrated that the model can be used as an effective tool to predict N2O emission from BNR processes in those N2O could not be monitored. 3.5. N2O production and accumulation mechanisms in AOA process

3.5.1. Nitrogen conversion Under aerobic conditions, 97.07–100% of NH+4 was oxidized to NO2 and less than 3% of NH+4 was converted to NO3 , owning to the low DO levels (0.43–0.86 mg O2 L 1) in Cases 1–4. During the aeration phases, 20.30–38.82% of N2O was generated, along with 3.98–11.85% of accumulated NH2OH. Meanwhile, 11.13–29.88%

46

X. Ding et al. / Bioresource Technology 222 (2016) 39–48

of N2 was released in the aerobic stages of Cases 1–3. During the complete cyclic evolution, the overall amounts of N2O generated from the AOA system were 27.63%, 53.08%, 43.34%, and 34.95% of the total nitrogen loading, and the N2O production factors (N2O production/nitrogen removed) were 28.36%, 57.54%, 67.68%, and 100% in Cases 1–4, respectively. The simulation results predicted that 16.68–69.88% of N2 and a trace amount of NO (0–0.03%) would be produced at the ends of the operation cycles for Cases 1–3.

3.5.2. N2O production by three different pathways To investigate the N2O production mechanisms in the AOA process, three pathways involving AOB denitrification, incomplete NH2OH oxidation and heterotrophic denitrification on XSTO, were integrated in this model. The corresponding amounts of N2O production from these three pathways were calculated by the developed model (Fig. 6). N2O accumulation mainly occurred during the aeration stage (67.84–81.64%), in which the AOB denitrification pathway was the predominant process (65.24–75.48%). It was mainly due to high nitrite accumulations and low DO levels in the four cases (Ni et al., 2014; Peng et al., 2014). The incomplete NH2OH oxidation pathway was the second most important process (15.61–32.17%), and the heterotrophic denitrification pathway during the SND process played a subordinate and supplementary role (0–12.47%). In addition, regarding the inhibition of AOB denitrification by DO (Ni et al., 2014), less N2O was generated in Cases 3–4 with higher DO concentrations compared with Case 1 and Case 2 with lower DO concentrations, which was consistent with the result of a previous study (Peng et al., 2014). Conversely, N2O production by the incomplete NH2OH oxidation pathway increased with an increase in DO in all four cases, which confirmed that the incomplete NH2OH oxidation pathway was favored at high DO levels (Ni et al., 2015). Little N2O was produced by the heterotrophic denitrification pathway in Case 2 (2.70%) and Case 3 (4.60%) during the aeration stages. Moreover, 11.13–29.88% of N2 was released in the aerobic stage in Cases 1–3, indicating that SND reactions occurred in the AOA system. Similarly, a previous study on N2O production during the SND process via nitrite recognized heterotrophic denitrification as a minor source of N2O accumulation (Jia et al., 2013). The reason that the AOB denitrification pathway rather than the heterotrophic denitrification pathway represented the dominant source of N2O production in SND process might have been that the AOB community changed under oxygen-limited conditions and that N2O production by heterotrophic denitrification was limited by the presence of oxygen (Jia et al., 2013). At the ends of the modeling cycles, N2O production by the heterotrophic denitrification pathway increased to 10.24–12.47% in Case 2 and Case

3, while no N2O was produced by the heterotrophic denitrification pathway throughout the model in Case 1 (Fig. 6).

3.5.3. Effect of XSTO storage and consumption on N2O production The readily biodegradable substrate glucose (500 mg COD L 1) was added to the influent in the experimental studies of Cases 1– 3. During the anaerobic stage, cell internal storage was the main pathway for removing organic carbon, as microbial growth was suppressed by the unbalanced conditions (with organic carbon present as the electron donor but no nitrogen as the electron acceptor) (Qin et al., 2005). XSTO storage was completed along with the depletion of SS during the anaerobic stage (Figs. 2D, 3D and 4D). During the anoxic stage, the high nitrite accumulation and the rapid XSTO consumption for the aerobic growth of heterotrophs resulted in N2O accumulation in Cases 2–3 (Supplementary Material Fig. S.4). Conversely, a low-level nitrite and an adequate amount of XSTO led to an end-product of N2 rather than N2O in Case 1 (Supplementary Material Fig. S.4), although an internal carbon source from XSTO was the sole electron donor. The results indicated that heterotrophic denitrification on intracellular polymers did not necessarily generate N2O in the AOA process unless intracellular carbon was insufficient under famine conditions. Similar studies have reported that when the amounts of PHA available for complete denitrification were not sufficient, it inevitably led to N2O accumulation in the anoxic phase, and it was also found that N2O production in the anoxic phase decreased when anaerobic PHA synthesis increased (Wang et al., 2011). The dissolved N2O produced by AOB was further reduced to N2 in the anoxic stage using the residual XSTO as an electron donor when NO2 was denitrified completely (Supplementary Material Fig. S.4). After the dissolved N2O was depleted, a constant N2O level was observed (Fig. 3B). In addition, it seems that the low C/N ratio and inadequate amounts of XSTO for denitrification during anoxic stages led to slower XSTO degradation rates in Case 2 and Case 3 (Figs. 2A, 3A, 4A, and Supplementary Material Fig. S.4). But during the aerobic stages with adequate XSTO for denitrification in all cases, the degradation rates of XSTO for denitrification in Cases 2– 3 were slower than those in Case 1. Thus the lower degradation rate of XSTO for denitrification was mainly due to the inhibitory effect on heterotrophs by the higher nitrite accumulation (Wei et al., 2014). Moreover, on the premise that XSTO for denitrification was sufficient both in the aerobic and anoxic stages of Case 1, the XSTO degradation rate in the anoxic stage was also slower than that in the aerobic stage. This observation further suggested that nitrite might play a much more important role in heterotrophic denitrification on intracellular polymers than that played by influent C/N. Additionally, among four nitrite inhibition constants for oxynitride

Fig. 6. Modeling results of N2O production by three pathways for Case 1–4: at the ends of the aerobic stage (A) and the anoxic stage (B).

X. Ding et al. / Bioresource Technology 222 (2016) 39–48

reduction obtained from a previous study (Liu et al., 2015a), the one for N2O reduction of 8 g N m 3 is lower than others (12, 10, and 17 g N m 3). It indicated that N2O reductase is more susceptible to the inhibition by nitrite. In brief, nitrite inhibition on heterotrophs led to a slow XSTO uptake rate, which slowed the denitrification rate, particularly N2O reduction rate, and the slow N2O reduction rate ultimately resulted in N2O accumulation during denitrification on intracellular polymers under conditions of low influent C/N (Kampschreur et al., 2009). As a result, the proportions of N2O production increased with an increase in nitrites under low influent C/N ratios (Case 2 and Case 3). Moreover, aeration in the four experimental cases stopped when nitritation was complete, so that aerobic consumption of XSTO could be minimized to keep a carbon source available for heterotrophic denitrification (Liu et al., 2013; Miao et al., 2015). The simulation results showed that the proportions of aerobic XSTO consumption increased (27.21%, 45.24%, and 63.76%) with the aeration time (1 h, 2.25 h, and 3.5 h) in Cases 1–3 (Supplementary Material Fig. S.4). In addition, due to the high aerobic growth rate of heterotrophs on XSTO (Jia et al., 2012), a high DO level was harmful in preserving XSTO for subsequent anoxic denitrification. However, a low DO level would inevitably lead to a long aeration time for ammonium oxidation. Therefore, a proper DO levelaeration time strategy would not only achieve more nitrogen removal via nitrite but would also guarantee more XSTO to satisfy the carbon requirements and shorten the duration of the anoxic stage. It should be noted that a decreasing trend in NO2 and an increasing trend in N2O in the anoxic stage of Case 4 were observed, although the heterotrophic denitrification rate was zero due to the lack of carbon sources. This result was potentially due to the occurrence of AOB denitrification under anoxic conditions. As a consequence, the simulated N2O concentration maintained a constant level after NH2OH was depleted (data not shown). 3.5.4. Microorganisms responsible for heterotrophic denitrification Phosphate was not removed concomitantly with anoxic denitrification on XSTO in Cases 1–3 (Supplementary Material Fig. S.5). These experimental and modeling results provisionally demonstrate that denitrifying glycogen-accumulating organisms (DGAOs), rather than denitrifying polyphosphate-accumulating organisms (DPAOs) were responsible for the heterotrophic denitrification activities. Liu et al. (2013) have reported that heterotrophic denitrification by utilization of internal carbon sources, such as glycogen, could be implemented by DGAOs. DGAOs have also been previously found to be a major contributor to N2O production in wastewater treatment (Zeng et al., 2003). Heterotrophic denitrification appeared to be mainly attributable to DGAOs, whereas phosphate release and uptake was likely accomplished by polyphosphate-accumulating organisms (PAOs). One possible reason for why DGAOs prevailed over DPAOs in this system was that the low influent phosphorous/carbon (P/C) ratio of 0.02 (<0.1) favored the dominant growth of DGAOs rather than DPAOs (Zeng et al., 2003). Speculation about the microbial communities responsible for heterotrophic denitrification in this AOA system requires further investigation. 4. Conclusions In this work, a mathematical model was proposed to describe nitrogen conversion and N2O production in an AOA process. Application of the developed model successfully reproduced the experimental data obtained from four case studies and the reported AO studies. The modeling results indicated a predominant N2O production pathway of AOB denitrification during the aeration stage

47

in the AOA system. The high nitrite inhibition and low XSTO degradation rate led to a subordinate N2O production by the heterotrophic denitrification pathway. The established model is an effective and useful tool for understanding the N2O production mechanisms in AOA processes. Author disclosure statement The authors declare that they have no conflict of interest. Acknowledgement This work was supported by the Shaanxi Province Science & Technology Development Program (Grant No. 2014K15-03-02) and the National Natural Science Foundation of China (Grant No. 51308050). Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.biortech.2016.09. 092. References APHA, AWWA, WEF, 2005. Standards Methods for the Examination of Water and Wastewater. . Washington, DC. Chandran, K., Stein, L.Y., Klotz, M.G., van Loosdrecht, M.C., 2011. Nitrous oxide production by lithotrophic ammonia-oxidizing bacteria and implications for engineered nitrogen-removal systems. Biochem. Soc. Trans. 39 (6), 1832–1837. Dosta, J., Gali, A., Benabdallah El-Hadj, T., Mace, S., Mata-Alvarez, J., 2007. Operation and model description of a sequencing batch reactor treating reject water for biological nitrogen removal via nitrite. Bioresour. Technol. 98 (11), 2065–2075. Ge, G., Zhao, J., Gao, K., Ding, X., Li, X., Chen, A., Chen, B., 2015. Impact of N2O emissions on nitritation in two sequencing batch reactors: activated sludge reactor and biofilm system. Environ. Eng. Sci. 33, 125–132. Henze, M., Gujer, W., Mino, T., van Loosdrecht, M.C.M., 2000. Activated Sludge Models ASM1, ASM2, ASM2d and ASM3. IWA Publishing, London, UK. Hiatt, W.C., Grady, C.P.L., 2008. An updated process model for carbon oxidation, nitrification, and denitrification. Water Environ. Res. 80 (11), 2145–2156. IPCC, 2013. The final draft Report, dated 7 June 2013, of the Working Group I contribution to the IPCC 5th Assessment Report. In: Climate Change 2013: The Physical Science Basis. Jia, W., Zhang, J., Xie, H., Yan, Y., Wang, J., Zhao, Y., Xu, X., 2012. Effect of PHB and oxygen uptake rate on nitrous oxide emission during simultaneous nitrification denitrification process. Bioresour. Technol. 113, 232–238. Jia, W., Liang, S., Zhang, J., Ngo, H.H., Guo, W., Yan, Y., Zou, Y., 2013. Nitrous oxide emission in low-oxygen simultaneous nitrification and denitrification process: sources and mechanisms. Bioresour. Technol. 136, 444–451. Kampschreur, M.J., Temmink, H., Kleerebezem, R., Jetten, M.S.M., van Loosdrecht, M. C.M., 2009. Nitrous oxide emission during wastewater treatment. Water Res. 43, 4093–4103. Law, Y., Lant, P., Yuan, Z., 2013. The confounding effect of nitrite on N2O production by an enriched ammonia-oxidizing culture. Environ. Sci. Technol. 47 (13), 7186–7194. Lemaire, R., Meyer, R., Taske, A., Crocetti, G.R., Keller, J., Yuan, Z., 2006. Identifying causes for N2O accumulation in a lab-scale sequencing batch reactor performing simultaneous nitrification, denitrification and phosphorus removal. J. Biotechnol. 122, 62–72. Li, C., Zhang, J., Liang, S., Ngo, H.H., Guo, W., Zhang, Y., Zou, Y., 2013. Nitrous oxide generation in denitrifying phosphorus removal process: main causes and control measures. Environ. Sci. Pollut. Res. 20 (8), 5353–5360. Liu, G., Xu, X., Zhu, L., Xing, S., Chen, J., 2013. Biological nutrient removal in a continuous anaerobic–aerobic–anoxic process treating synthetic domestic wastewater. Chem. Eng. J. 225, 223–229. Liu, Y., Peng, L., Chen, X., Ni, B.-J., 2015a. Mathematical modeling of nitrous oxide production during denitrifying phosphorus removal process. Environ. Sci. Technol. 49 (14), 8595–8601. Liu, Y., Peng, L., Guo, J., Chen, X., Yuan, Z., Ni, B.-J., 2015b. Evaluating the role of microbial internal storage turnover on nitrous oxide accumulation during denitrification. Sci. Rep. 5, 15138. Miao, L., Wang, S., Li, B., Cao, T., Xue, T., Peng, Y., 2015. Advanced nitrogen removal via nitrite using stored polymers in a modified sequencing batch reactor treating landfill leachate. Bioresour. Technol. 192, 354–360. Ni, B.-J., Ruscalleda, M., Pellicer-Nacher, C., Smets, B.F., 2011. Modeling nitrous oxide production during biological nitrogen removal via nitrification and denitrification: extensions to the general ASM models. Environ. Sci. Technol. 45 (18), 7768–7776.

48

X. Ding et al. / Bioresource Technology 222 (2016) 39–48

Ni, B.-J., Ye, L., Law, Y., Byers, C., Yuan, Z., 2013. Mathematical modeling of nitrous oxide (N2O) emissions from full-scale wastewater treatment plants. Environ. Sci. Technol. 47 (14), 7795–7803. Ni, B.-J., Peng, L., Law, Y., Guo, J., Yuan, Z., 2014. Modeling of nitrous oxide production by autotrophic ammonia-oxidizing bacteria with multiple production pathways. Environ. Sci. Technol. 48 (7), 3916–3924. Ni, B.-J., Pan, Y., van den Akker, B., Ye, L., Yuan, Z., 2015. Full-scale modeling explaining large spatial variations of nitrous oxide fluxes in a step-feed plugflow wastewater treatment reactor. Environ. Sci. Technol. 49 (15), 9176–9184. Pan, Y., Ni, B.-J., Bond, P.L., Ye, L., Yuan, Z., 2013. Electron competition among nitrogen oxides reduction during methanol-utilizing denitrification in wastewater treatment. Water Res. 47 (10), 3273–3281. Pan, Y., Ni, B.-J., Lu, H., Chandran, K., Richardson, D., Yuan, Z., 2015. Evaluating two concepts for the modelling of intermediates accumulation during biological denitrification in wastewater treatment. Water Res. 71, 21–31. Peng, L., Ni, B.-J., Erler, D., Ye, L., Yuan, Z., 2014. The effect of dissolved oxygen on N2O production by ammonia-oxidizing bacteria in an enriched nitrifying sludge. Water Res. 66, 12–21. Pocquet, M., Queinnec, I., Sperandio, M., 2013. Adaptation and identification of models for nitrous oxide (N2O) production by autotrophic nitrite reduction. In: Proceedings 11th IWA Conference on Instrumentation, Control and Automation (ICA2013). Narbonne, France, September, pp. 18–20. Qin, L., Liu, Y., Tay, J.H., 2005. Denitrification on poly-beta-hydroxybutyrate in microbial granular sludge sequencing batch reactor. Water Res. 39 (8), 1503– 1510.

Ravishankara, A.R., Daniel, J.S., Portmann, R.W., 2009. Nitrous oxide (N2O): the dominant ozone-depleting substance emitted in the 21st century. Science 326, 123–125. Schalk-Otte, S., Seviour, R.J., Kuenen, J.G., Jetten, M.S.M., 2000. Nitrous oxide (N2O) production by Alcaligenes faecalis during feast and famine regimes. Water Res. 34, 2080–2088. Semerci, N., Hasilci, N.B., 2016. Fate of carbon, nitrogen and phosphorus removal in a post-anoxic system treating low strength wastewater. Int. Biodeter. Biodeg. 108, 166–174. Snip, L.J., Boiocchi, R., Flores-Alsina, X., Jeppsson, U., Gernaey, K.V., 2014. Challenges encountered when expanding activated sludge models: a case study based on N2O production. Water Sci. Technol. 70 (7), 1251–1260. Wang, Y., Geng, J., Ren, Z., He, W., Xing, M., Wu, M., Chen, S., 2011. Effect of anaerobic reaction time on denitrifying phosphorus removal and N2O production. Bioresour. Technol. 102 (10), 5674–5684. Wei, Y., Wang, S., Ma, B., Li, X., Yuan, Z., He, Y., Peng, Y., 2014. The effect of polybeta-hydroxyalkanoates degradation rate on nitrous oxide production in a denitrifying phosphorus removal system. Bioresour. Technol. 170, 175–182. Zeng, R.J., Lemaire, R., Yuan, Z., Keller, J., 2003. Simultaneous nitrification, denitrification, and phosphorus removal in a lab-scale sequencing batch reactor. Biotechnol. Bioeng. 84 (2), 170–178. Zhao, J., Huang, N., Hu, B., Jia, L., Ge, G., 2016. Potential of nitrous oxide recovery from an aerobic/oxic/anoxic SBR process. Water Sci. Technol. 73 (5), 1061–1066. Zhou, Y., Lim, M., Harjono, S., Ng, W.J., 2012. Nitrous oxide emission by denitrifying phosphorus removal culture using polyhydroxyalkanoates as carbon source. J. Environ. Sci. 24 (9), 1616–1623.