Predictions of the Influent and Operational Conditions for Partial

May 10, 2018 - The results provide support to the design and optimization of partial nitritation reactors. ... Among them pH has been considered a key...
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Predictions of the influent and operational conditions for partial nitritation with a model incorporating pH dynamics Min Zheng, Shuang Wu, Zhiqiang Zuo, Zhiyao Wang, Yong Qiu, Yan-chen Liu, Xia Huang, and Zhiguo Yuan Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.8b00202 • Publication Date (Web): 10 May 2018 Downloaded from http://pubs.acs.org on May 10, 2018

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Predictions of the influent and operational conditions for

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partial nitritation with a model incorporating pH dynamics

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Min Zheng,†,‡ Shuang Wu,† Zhiqiang Zuo,† Zhiyao Wang,‡ Yong Qiu,† Yanchen Liu,†,*

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Xia Huang,†,* Zhiguo Yuan†,‡

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6

of Environment, Tsinghua University, Beijing, China, 100084

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8

4072, Australia

State Key Joint Laboratory of Environment Simulation and Pollution Control, School

Advanced Water Management Centre, The University of Queensland, St Lucia, QLD

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Corresponding Author

11

*

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[email protected] (Xia Huang)

E-mail address: [email protected] (Yanchen Liu);

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ABSTRACT

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Ammonium partial oxidation to nitrite (i.e. partial nitritation) is required in a

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two-stage autotrophic nitrogen removal system, to provide effluent suitable for the

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anammox reaction. This study aims to establish influent (ammonium and bicarbonate

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concentrations) and operational (dissolved oxygen (DO) concentration and solids

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retention time (SRT)) conditions that favor partial nitritation. This is achieved through

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extending the nitritation and nitratation models to predict pH variation as well as the

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effects of pH, free ammonia (NH3) and free nitrous acid (HNO2) on the two reactions.

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Experiments were performed on a lab-scale sequencing batch reactor (SBR) operated

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for over 500 days to provide dynamic data for the calibration of model parameters,

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particularly those related to the NH3 and HNO2 inhibition on nitrite-oxidizing bacteria

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(NOB). The influent ammonium (19–84 mM) and bicarbonate (23–72 mM) were

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varied, which led to dynamic ammonium, nitrite and nitrate data suitable for model

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calibration and validation. The model was able to well-describe pH dynamics as well

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as the inhibitory effects of NH3 and HNO2 on NOB. Model-based scenario analysis

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was then undertaken to establish the joint regions of influent ammonium and

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bicarbonate concentrations, and the operational DO, temperature and SRT conditions,

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that favor partial nitritation. The results provide support to the design and

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optimization of partial nitritation reactors.

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Keywords: Nitratation; Nitritation; NOB; Model; pH; Wastewater composition.

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INTRODUCTION

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Partial nitritation followed by the anammox reaction is considered a promising

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technology for nitrogen removal from ammonium-rich streams such as anaerobic

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digester supernatant (reject water),1-3 landfill leachate4-6 and various types of

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nitrogen-containing industrial wastewater.7,8 The process has already been studied

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extensively on lab-scale and pilot-scale by research groups around the world,9 and

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full-scale applications have also been reported.2 With the perspective of more

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full-scale installations worldwide applied to various types of nitrogen-containing

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wastewater, it is critical to establish the influent and operational conditions that favor

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partial nitritation.

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Bioreactors to achieve partial nitritation must selectively retain ammonia oxidizing

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bacteria (AOB) while suppressing nitrite-oxidizing bacteria (NOB).10,11 Many

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different operational conditions such as dissolved oxygen (DO),12-14 pH,6,15

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temperature,16 free ammonia (NH3), free nitrous acid (HNO2),4 and solid retention

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time (SRT)17 have been used to accomplish this requirement. Among them pH has

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been considered a key factor,6 as it has significant impacts on both the nitritation and

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nitration processes, partially through its effects on the NH3 and HNO2

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concentrations.18 NH3 and HNO2 are the key substrate for AOB and NOB,

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respectively, but at elevated concentrations, they inhibit the AOB and NOB activities.

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Ammonium oxidation catalysed by AOB is an acidifying reaction19: ୅୓୆

(1)

ା NHଷ + 1.5Oଶ ሱۛሮ NOି ଶ + H + Hଶ O

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Which produces 1 mole of protons each mole of NH3 oxidized. An additional 1 3

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mole of protons is produced through the conversion of NH4+ to NH3 (eq. 2). This

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means that within a reactor with continuous catalytic oxidation of ammonia: a) two

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moles of alkalinity are consumed per mole of ammonium oxidized leading to pH drop

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(eqs. 3 and 4), and b) the inhibitory effect of NH3 on the NOB activity decreases

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gradually following the pH drop and NH3 consumption; c) the inhibitory effect of

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HNO2 on the NOB activity progressively increases due to the pH drop and nitrite

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accumulation (eq. 5).20

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NHସା ⇋ NHଷ + H ା , pK ୟ = 9.24

(2)

ା HCOଷି ⇋ COଶି ଷ + H , pK ୟ = 10.33

(3)

ା Hଶ COଷ ⇋ HCOି ଷ + H , pK ୟ = 6.35

(4)

ା HNOଶ ⇋ NOି ଶ + H , pK ୟ = 3.25

(5)

where, pKa is acid dissociation constant, and these values are given for 25°C and zero ionic strength.

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Many model structures have been developed to describe the partial nitritation

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process. A two-step nitrification model addressed the effects of DO and temperature

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on the two distinct nitrifying groups, AOB and NOB.21 Inhibition kinetics of NH3 and

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HNO2 on the AOB and NOB were also developed,22 and applied to predicting

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operational boundaries for nitrite accumulation at a constant pH condition.23 While

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several model-based predictions

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nitritation,24-28 the dynamic pH condition was not considered in these studies.

had

been reported for achieving partial

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pH calculation models have previously been developed based on acid-base

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equilibrium reactions, and shown to be very important in modelling anaerobic 4

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processes.29 However, currently, model-based studies on partial nitritation towards

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dynamic pH conditions are rarely reported.

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This study aims to develop an extended nitrification model to predict the effect of

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influent and operational conditions on reactor partial nitritation performance with

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consideration of pH dynamics. A lab-scale sequencing batch reactor (SBR) was

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operated over 500 days with elevated substrate levels. Long-term SBR performance of

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nitritation and nitratation was investigated. Key kinetic parameters were

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experimentally determined or estimated by model calibration. Routine SBR

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operational profiles were used for model validation. Afterwards, simulation studies

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were carried out using the calibrated model to evaluate the impacts of wastewater

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composition (ammonium and bicarbonate concentrations) and operational parameters

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such as DO, temperature and SRT on effluent nitrite accumulation of an SBR.

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Operational zones favourable for partial nitritation were established as a function of

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influent compositions.

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MATERIALS AND METHODS

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Nitrification model extension

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A well-known two-step nitrification model21 was simplified (not including

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heterotrophic kinetics or storage processes) in this work to predict pH dynamics in a

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nitritation and nitratation reactor. The simplified model contains 8 compounds,

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including oxygen (ܵ୓మ ), free ammonia (ܵ୒ୌయ ), nitrite (S୒୓షమ ), nitrate (S୒୓షయ ), AOB (ܺ୅୓୆)

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and NOB (ܺ୒୓୆ ), as used in the previous model,21,22 and carbon dioxide (ܵେ୓మ ) and 5

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hydrogen ion (Sୌశ ) as the two newly added compounds. The extension of the model is

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to predict dynamics of pH, NH3 and HNO2 concentrations during nitritation and

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nitratation as well as their combined effects on activities of AOB and NOB. The

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stoichiometric matrix, kinetic expressions, and model parameters are given in Table

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S1–3.

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For the two nitrifying populations, namely AOB and NOB, both growth and decay

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processes were included in the model. The AOB catalyzes the first step of nitrification,

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NH3 oxidation to nitrite, and generates hydrogen ion in the presence of dissolved

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oxygen (eq. 1). The NOB oxidizes nitrite to nitrate (eq. 6), leading to oxygen

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consumption but no pH variation: ୒୓୆

(6)

ି NOି ଶ + 0.5Oଶ ሱۛሮ NOଷ

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The oxygen gas exchange due to bubble aeration was included using a mass

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transfer equation as previously used in IWA Activated Sludge Models.30 The CO2

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exchange is described similarly, as shown in Table S2. Mass transfer coefficients

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KLaO2 and KLaCO2 were estimated using water tests with details described by

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Matsunaga et al.31 Acid-base equilibrium (eqs. 2–5 and 7) were included for

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calculation of pH. Chemical equilibria were modeled with back– and forward

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reactions, as described in Udert et al.32 ଶି ା Hଶ POି ସ ⇋ HPOସ + H , pK ୟ = 7.20

(7)

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Temperature affects the microbial growth and decay rates, saturation concentrations

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of O2 and CO2, and acid dissociation constants. The temperature dependency for the

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microbial processes is expressed as µ(T)= µ(20°C)·exp(θT·(T–20°C)), where θT for 6

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AOB and NOB are 0.120 and 0.078, respectively.21 Relationship between saturation

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concentration of O2 (ܵ୓మ ,ୱୟ୲, mg/L) and temperature (°C) at 101.3 kPa (1 atm) air

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pressure

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Saturation concentrations of CO2 (ܵେ୓మ ,ୱୟ୲ ) at 1 atm CO2 pressure are respectively

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0.045, 0.033 and 0.025 mol/L at 15, 25 and 35°C, respectively (Lange's Handbook of

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Chemistry). Effect of temperature (15–35°C) on pKa values of NH4+ and HNO2 (eqs.

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2 and 5) were described according to Anthonisen et al.,18 and its effect on other

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processes (eqs. 3, 4 and 7) was negligible compared with the above factors affecting

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the nitrification pH modelling.

is

expressed

as ܵ୓మ,ୱୟ୲ = exp(7.7117 − 1.31403 · Ln(T + 45.93)) .33

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Reactor operation and data collection

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A sequencing batch reactor (SBR) was operated at room temperature for collecting

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data for the calibration and validation of the extended nitrification model. The reactor

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was made from Plexiglas cylinders with an effective volume of 8.0 L (30 cm in height

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and 20 cm in inner diameter. Each cycle of the SBR operated for 12 hours, including

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influent (10 min), mixing and aeration (10 h), settling (40 min), effluent (10 min) and

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idling (1 h). The above feeding regime and cycle time give rise to a hydraulic

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retention time (HRT) of 24 hours. The SRT was in the range of 10–40 days with

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controlled sludge discharge. Airflow rate of 1.2 L/min maintained DO concentration

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over 2.0 mg/L during aeration period. Seed sludge was from a nitritation reactor that

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treated urine, as reported in our previous studies.20

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The synthetic wastewater feed contained ammonium (as NH4Cl), inorganic carbon

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source in the form of NaHCO3, 2.0 mM KH2PO4 and 10.5 mM Na2HPO4 as a pH 7

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buffer, and 5 mL/L microelement solution as described previously.34 The SBR was

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operated over 500 days, in which the influent ammonium concentration was stepwise

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increased from 19 mM to 84 mM. Conjointly, the influent bicarbonate concentration

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increased from 11–23 mM to 72 mM. The influent HCO3–/NH4+ molar ratios were in

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the range of 0.5–1.2 during the overall SBR operation. In theory, the ammonia

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oxidation process converts 1 mM ammonium with consumption of 2 mM bicarbonate.

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This indicates that the above influent condition (HCO3–/NH4+ molar ratio < 2.0) is

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inadequate for complete ammonia removal and thereby performance of partial

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ammonia removal was expected during the overall SBR operation.

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Batch tests were carried out to evaluate the variations of pH, bicarbonate, ammonia

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and nitrite concentrations with different influent substrate concentrations. During each

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batch tests, the reactor was filled with synthetic wastewater containing different initial

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NH4+ and HCO3– concentrations and same buffer and microelement solution as used

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in the influent. The ammonium, nitrite, nitrate, bicarbonate concentrations, pH, and

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temperature were monitored during 8–24 h tests. SBR routine operational profiles

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were monitored with measurements of ammonium in influent, and ammonium, nitrite

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and nitrate in effluent 2–4 times every week, as well as mixed liquor volatile

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suspended solids (MLVSS) in reactor 1–2 times a month. The data collected from

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batch tests and long-term routine operation were respectively used for model

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calibration and validation, which will be further described in the following section.

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Chemical analysis

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Measurements of ammonium, nitrite, nitrate, phosphorus and MLVSS in the reactor 8

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liquid phase were performed in accordance with standard methods.35 Inorganic carbon

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concentration was analyzed by using total organic carbon analyzer (Shimadzu TOC–

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5000A, Japan). DO, pH, and temperature were recorded using a pH/DO meter (WTW,

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pH/Oxi340i). Bicarbonate concentration (mM) was calculated as follows: TIC

HCOଷି = 1+

163 164

10ି୮ୌ 10ି୮୏౗భ

+

(8)

10ି୮୏౗మ 10ି୮ୌ

where TIC is total inorganic carbon concentration (mM); pKa1 = 6.35 and pKa2 = 10.33 are constants given at 25°C and zero ionic strength.

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Model calibration and validation

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Most kinetic parameters in the model were well established in previous

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studies21,23,36 and thus they were directly taken from the literature without further

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calibration (listed in Table S3). These previous studies had showed that the maximum

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AOB and NOB growth rates (µmax,AOB and µmax,NOB) and some inhibitive constants

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(KI,NH3,NOB and KI,HNO2,NOB) are sensitive for the prediction of dynamic ammonium,

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nitrite and nitrate in SBR operational cycle. As calculation of pH was a newly added

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process in our model and pH variation is to a large extent related to AOB growth, the

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effect of different KpH values on the simulated pH curves were further analyzed. The

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results showed that an increase or decrease of KpH value by 100% significantly affected

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the pH curves (Figure S1), indicating that KpH is a sensitive parameter in our model. KpH

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along with µmax,AOB, µmax,NOB, KI,NH3,NOB and KI,HNO2,NOB were thus estimated using

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experimental data, as described below.

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Aerobic batch assays (DO ≥ 2.0 mg/L) with inoculated sludge from the SBR were

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conducted to establish the inhibitory effects of NH3 and HNO2 on the NOB activity. 9

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The nitrite oxidation rate was calculated as the slope of the nitrate profile. The rates

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were measured with different NH3 or HNO2 levels in the assays. The inhibition

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constants KI,NH3,NOB and KI,HNO2,NOB were then respectively estimated by fitting NH3

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and HNO2 inhibition models with the measured nitrite oxidation rates.

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pHmin was defined as the minimal pH for AOB growth. To estimate its value, one

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SBR operational cycle was manually prolonged until ammonia oxidation ceased to

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occur. The final pH was taken as pHmin.

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After implementation of the model in AQUASIM 2.0,37 parameter estimation was

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further carried out for the three remaining parameters (µmax,AOB, µmax,NOB, and KpH)

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through minimizing the sum of squares of the deviations between the model

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predictions and the experimentally measured ammonium, nitrite, nitrate, inorganic

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carbon and pH profiles in two groups of 8 h batch tests with different initial

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ammonium and bicarbonate concentrations. The 95% confidence intervals of

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individual parameter estimates were calculated from the mean square fitting errors

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and the sensitivity of the model to the parameters.

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Model validation was carried out by employing the model with the calibrated

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parameters to predict independent experimental data sets. SBR routine operational

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profiles under the different influent conditions were compared with the model

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predicted values to validate the model. The significance of modelling results was

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evaluated by variance analysis, in which p < 0.05 was considered to be statistically

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significant and p > 0.05 showed statistical insignificance.

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Model predictions under different influent and operational conditions 10

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The effect of influent and operational conditions on SBR performance of nitritation

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and nitratation was predicted using the validated model. The extended nitrification

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model was employed to make an assessment of the nitrite accumulation ratio (NO2– /

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(NO2– + NO3–)) in the SBR effluent under different combinations of influent

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ammonium concentrations (ranging from 0 mM to 120 mM with an increment of 3.57

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mM each step) and bicarbonate concentrations (ranging from 0 mM to 240 mM with

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an increment of 7.14 mM in each step). The SBR was regarded to have achieved

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stable nitritation when the effluent nitrite accumulation ratio was over 90% in steady

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state. The above simulation studies were carried out for different operational

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parameters including DO (0.5, 1.0, 2.0 mg/L), SRT (10, 20, 40 days), and temperature

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(15, 25, 35°C).

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RESULTS AND DISCUSSION

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Experimental results

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Figure 1 shows the SBR performance in terms of effluent ammonium, nitrite and

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nitrate concentrations, which varied with progressively increased substrate levels. The

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SBR was operated at around 24°C, DO > 2.0 mg/L, and was fed with influent

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containing approximately 20 mM ammonium and 20 mM bicarbonate at the

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beginning. Initially, nitrite accumulation was achieved in effluent of the SBR, likely

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due to the lack of NOB in inoculated nitritation sludge. Afterwards, effluent nitrate

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build-up appeared, indicating the NOB growth. The effluent ammonium, nitrite and

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nitrate concentrations were obtained at stable levels on day 100. Since then, the

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effluent nitrite concentration was close to 0. Restoration of effluent nitrite 11

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accumulation occurred on day 292 when the influent ammonium and bicarbonate

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concentrations both increased and respectively reached 84 mM and 57 mM.

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Following this period, the effluent nitrite increased considerably, and its concentration

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reached approximately 40 mM and stabilized at this level in the remaining 150 days

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of the SBR operation. The effluent nitrite accumulation ratio increased progressively

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and then remained above 90%. The results showed that the nitritation and nitratation

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processes in the SBR were significantly affected by the substrate conditions (i.e. the

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ammonium and bicarbonate concentrations), as all other operational parameters

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remained unchanged.

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Variations of ammonium, NOx– (nitrite plus nitrate), bicarbonate and pH during a

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typical SBR operational cycle in the operational period with the highest influent

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ammonium level are shown in Figure 2. The ammonium and bicarbonate

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concentrations decreased, accompanied by the increase in NOx–. The molar ratio of

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the consumed bicarbonate to consumed ammonium was close to its theoretical value

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of 2.0. pH initially increased up to 8.0 due to CO2 stripping caused by aeration and

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then continuously dropped with the consumption of bicarbonate by ammonium

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oxidation. The typical SBR operation cycle test was manually prolonged to 24 hours.

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pH finally stabilized at 6.06. This results in a cessation of ammonia oxidation, as

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indicated by the constant ammonium, nitrite and nitrate concentrations after 24 hours

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(Figure 2). As such, the minimal pH for AOB growth (pHmin) was estimated to be 6.06

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in this work. This is consistent with previous studies.20,34

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NOB growth can be affected by many environmental conditions, including pH, DO, 12

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NH3 and HNO2.23 Within the operational stages of ammonia oxidation to nitrate (day

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100–300), the ammonium and bicarbonate concentrations both stepwise increased in

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the influent. This gave very similar pH variation in the SBR operational cycles at

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different substrate levels. The DO concentration was consistently higher than 2.0

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mg/L and the HNO2 concentration was always lower than 1 µM (almost no nitrite

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accumulation). The pH, DO and HNO2 conditions are not expected to significantly

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affect the NOB growth.18 However, NH3-levels became distinctly different because of

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stepwise increase in the influent ammonium concentrations from 21 mM (day 100–

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150) to 42 mM (150–240 day) and then to 84 mM (day 240–300). Therefore, the SBR

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performance shift from full nitrification (nitritation followed by nitratation) to

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nitritation on day 300 should be the result of strong inhibition of high-level NH3 on

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NOB growth.

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Model calibration with batch tests data

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Nitrite oxidation rates of the sludge were estimated at NH3 concentrations ranging

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from 0.01 to 2.8 mM in batch tests. The NOB activity significantly decreased with the

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NH3 concentration increased (Figure 3). This inhibitory effect of NH3 on the NOB

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activity can be well described by the non-substrate inhibition model. Parameter

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KI,NH3,NOB was estimated to be 0.27 ± 0.04 mM (or 3.8 ± 0.6 mg NH3-N/L), with an

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R2-square correlation coefficient of 0.99. Similarly, the half-saturation inhibition

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constant of HNO2 concentrations on the NOB activity (KI,HNO2,NOB) was estimated to

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be 10 ± 7 µM (or 0.14 ± 0.10 mg HNO2-N/L). The results are comparable with the

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reported values in the literature.22,38 13

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Mass transfer including oxygen supply and dissolved CO2 stripping was of

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significant importance in modelling a bioreactor system. For KLaO2 estimation, the

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SBR was initially filled with clean water and sparged with N2. After the water was

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deprived of oxygen, the reactor was aerated at an airflow rate of 1.2 L/min, with the

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DO concentration recorded. KLaO2 was estimated to be 25 h-1 from the DO profile

273

using the least-square based curve fitting. KLaCO2 was estimated by using a similar

274

method. Clean water in the SBR was sparged with pure CO2 gas, leading to elevated

275

bicarbonate concentration. The reactor was then sparged with air. CO2 stripping in this

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phase led to pH rise, which was recorded. KLaCO2 was estimated to be 15.5 h-1 through

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least-square based curve fitting.

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Further model calibration involved estimating three important parameter values

279

(µmax,AOB, µmax,NOB and KpH) for the SBR system so that the ammonium, nitrite, nitrate,

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bicarbonate, pH, NH3 and HNO2 concentrations predicted by the model closely

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agreed with the measured profiles in two groups of batch tests. The inoculations were

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exactly the same in the two tests. The initial molar ratio of bicarbonate to ammonium

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was set relatively low at 0.5 in one test and high as 2.0 in the other test. The calibrated

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parameter values with their 95% confidence intervals are listed in Table 1. The

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calibrated maximum AOB growth rate of 0.32 ± 0.05 d-1 (20 °C) is relatively low

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compared with the values reported in literature.21,30 This could be related to the way

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how the potential inhibitory effects of NH3 and HNO2 on AOB was modelled. For

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simplicity, we ignored the potential effects of NH3 on AOB, and chose a relatively

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high KI,HNO2,AOB value (146 µM, which is close to the higher end of the literature 14

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reported values22,36,39) to model the inhibitory effect of HNO2 on AOB. These

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assumptions were made because the NH3 and HNO2 concentrations in the SBR would

292

not support accurate calibration of these inhibition-related parameters for AOB. It is

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possible that part of the unmodeled (or under-modelled) inhibitory effects were

294

lumped into the µmax,AOB value. KpH was fitted to be 0.34 ± 0.12. The relatively narrow

295

confidence intervals indicated acceptable identifiabiltiy of these parameters.

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The comparison of the model predicted and measured profiles are presented in

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Figure 4. With the calibrated parameters, the model simulations portrayed the

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variations of ammonium, nitrite, nitrate and bicarbonate, and in particular accurately

299

depicted the NH3 and HNO2 concentrations under the dynamic pH conditions. This

300

indicates that the model adequately described the high-level inhibitory effects of NH3

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and HNO2 on nitrite oxidation. As reported previously, NH3 and HNO2 inhibition had

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been considered to be two key factors to achieve and maintain stable partial nitritation

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in treating ammonium-rich wastewater.4 In addition to that, when the molar ratio of

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bicarbonate to ammonium is less than 2.0, a relatively low pH always appears with

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the progression of NH3 oxidation. As a result, the HNO2 concentration increases and

306

maintains the high-level inhibition on the NOB activity. The plots of model-predicted

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net specific growth rate (expressed as (µ−b)) further support the modelling concept of

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pH−NH3−HNO2 inhibition, as depicted in Figure 4c and 4f. In comparison to an

309

initial HCO3−/NH4+ of 2.0, the net AOB growth was similar while the net NOB

310

growth was significantly lowered with lower bicarbonate to ammonium ratios.

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Model validation with routine operational profiles 15

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The extended nitrification model with calibrated parameters was validated with the

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routine operational profiles obtained from the long-term operational SBR. As shown

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in Figure 1, the simulation results matched well with the measured effluent

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ammonium, nitrite and nitrate concentrations during the entire operational period in

316

all cases. In the routine monitoring of SBR performance, the initial nitrate build-up

317

lasted for around 300 days and the considerable effluent nitrite was re-achieved in the

318

next 200 days. These time nodes for the SBR performance shift from nitritation to

319

nitratation and then back to nitritation were all successfully predicted by the calibrated

320

model. The results demonstrated the capability of the extended nitrification model to

321

simulate the reactive processes of nitritation and nitratation under dynamic pH

322

conditions. The modelling results also suggested that the nitrite accumulation around

323

day 300 was caused by influent ammonium concentration increase from 42 to 84 mM

324

50 days earlier, although the occurrence coincided with an increase in the influent

325

bicarbonate concentration.

326

According to the validated model, achievement and maintenance of the SBR partial

327

nitritation are to a large extent due to the dynamic pH condition as well as the

328

alternating NH3 and HNO2 inhibitions on the NOB activity. To the best of our

329

knowledge, the key pH dynamic condition has been for the first time investigated

330

within a model-based study of the long-term operational reactor system.

331

Effect of influent and operational conditions on partial nitritation

332

SBR operated under different influent and operational conditions for a long time

333

had been experimentally demonstrated to have different effects on the reactor 16

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performance of nitritation and nitratation.4,5,7,40-43 In order to shed light on the changes

335

in the influent ammonium and bicarbonate concentrations and operational conditions

336

such as SRT, DO and temperature on the attainment of partial nitritation, a simulation

337

study using the extended nitrification model was carried out. The results are presented

338

in Figure 5.

339

Figure 5 shows that, under constant operational condition of DO > 2.0 mg/L, SRT =

340

10 days, and T = 25°C, a minimal ammonium concentration of 54 mM (750 mg

341

NH4+–N) is required, below which partial nitritation (effluent nitrite concentration

342

representing >90% of oxidized nitrogen) would not occur independent of the HCO3–

343

/NH4+ ratio. Beyond this ammonium-level, partial nitritation can be achieved for

344

certain HCO3–/NH4+ ratios. The range of the HCO3–/NH4+ ratios increases with

345

increased ammonium concentrations. However, partial nitritation cannot be achieved

346

when the HCO3–/NH4+ model ratio is higher than 2:1, regardless how high the

347

ammonium concentration is. The partial nitritation feasible region is consistent with

348

the long-term SBR partial nitritation performance data (effluent nitrite was

349

considerable with the increased substrate concentrations) reported in the

350

“experimental results” section (Fig 5a). The feasible region predicted is also

351

supported by experimental data previously reported in literature for the treatment of

352

real reject water,25,44 swine/piggery wastewater,7 black water8 and landfill leachate.4

353

The influent ammonium and bicarbonate concentrations in these studies were found to

354

be located in the partial nitritation feasible region predicted by our model (Figure 5).

355

Moreover, with the same feed and operational parameters (DO, SRT and 17

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356

temperature) as applied above, model predictions depicted that partial nitritation

357

would not be achieved in a continuous stirred-tank reactor (CSTR) (i.e., steady state

358

stimulated pH = 7.2, FA = 0.42 mM and FNA = 0.03 µM in a CSTR with influent 100

359

mM NH4+ and 100 mM HCO3–). Simulation shows that the steady state pH in the

360

CSTR would stabilize at 7.0–7.5 in comparison to the widely varying pH (6.0–8.5) in

361

the case of an SBR so that the inhibitory effects of NH3 and HNO2 on NOB growth

362

significantly weakened. This agrees with the common understanding that a short SRT

363

(< 3 day) is typically needed for achieving partial nitritation in a CSTR (like the

364

SHARON process17). The use of short SRTs reduces the nitrogen conversion rate of

365

the system due to the retention of a lower amount of biomass.45 However, shorter SRT

366

is not required for an SBR, as the fluctuating pH level and ammonium and nitrite

367

concentrations over an SBR-based cycle essentially provide the selection pressure

368

against NOB.

369

The effects of different DO, SRT and temperature on the feasible region of partial

370

nitritation were also investigated through simulation studies (Figure S3–5). For

371

example, with a constant influent HCO3–/NH4+ molar ratio of 1.0, the minimal

372

ammonium concentration in general became lower at shorter SRT, lower DO and

373

higher temperature (Figure 6). Specifically, shortening SRT from 40 to 10 days and

374

reducing DO concentration from 2.0 to 0.5 mg/L would cause a significant decrease in

375

minimal ammonium from 65 to 55 mM level. To the contrary, reducing temperature

376

from 25°C down to 15°C would significantly increase the minimal ammonium

377

concentration required for partial nitritation, to 75 mM in comparison to 65 mM found 18

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for 25°C. This further indicates that out-competition of NOB mainly depends on

379

high-level NH3 and HNO2 inhibitions in the SBR system. It is important to note that

380

the NH3 and HNO2 concentrations are very sensitive to temperature in addition to pH;

381

for example, NH3 concentration halves with temperature decreasing from 25 to 15°C

382

at pH 8.0. As a result, the effective inhibitory effect would not be available for the

383

NOB washout, and consequently, partial nitritation could only be achieved with

384

influent with further elevated ammonium concentration. These established boundaries

385

for influent characteristics and operational parameters would provide useful support

386

for reactor design and optimization to advance nitrogen removal via partial nitritation.

387

In summary, this study reported on the development of a biokinetic model to

388

predict the operational and influent conditions required to support partial nitritation.

389

The model has been given special attention on pH dynamics and its relationship to

390

NH3 and HNO2 concentrations, which are crucial for accurate modelling of AOB and

391

NOB biokinetics given that NH3 and HNO2 are the actual substrates for AOB and

392

NOB metabolism and are also inhibitory at elevated concentrations. The model was

393

calibrated and validated against a lab scale SBR fed with a synthetic wastewater of

394

varied influent ammonium and bicarbonate concentrations. The model accurately

395

predicted the extent of ammonia oxidation (nitritation) and nitrite oxidation

396

(nitratation) in the lab scale SBR under several step changes in influent ammonium

397

and bicarbonate concentrations. With the calibrated/validated model, a simulation

398

study was performed to find the influent/operation space for successful maintenance

399

of partial nitritation, i.e., minimal ammonium concentration is found to be 54 mM 19

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(750 mg NH4+–N/L) with a HCO3–/NH4+ molar ratio range of 1.0–1.3 in influent for

401

the achievement of SBR partial nitritation (effluent nitrite accumulation over 90% at

402

steady state) under operational conditions of DO > 2.0 mg/L, SRT = 10 days, and T =

403

25°C. The results provide support to the design and optimization of partial nitritation

404

reactors.

405 406

ASSOCIATED CONTENT

407

Supporting Information

408

The Supporting Information is available free of charge on the ACS Publications

409

website.

410

Stoichiometric matrix, kinetic expressions and model parameters, sensitivity

411

analysis, pH variation in SBR operational cycles and model predictions of SBR

412

performance under different SRT, DO and temperature conditions (PDF).

413

AUTHOR INFORMATION

414

Corresponding Author

415

*

416

[email protected] (Xia Huang).

417

Notes

418

The authors declare no competing financial interest.

E-mail addresses: [email protected] (Yanchen Liu);

419 420

ACKNOWLEDGEMENTS

421

Dr. Min Zheng acknowledges the support of National Natural Science Foundation of 20

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China (No. 51708326) and international Postdoctoral Exchange Fellowship Program

423

(China). Dr. Yanchen Liu thanks to the support of National Natural Science

424

Foundation of China (No. 51678337), Major Science and Technology Program for

425

Water Pollution Control and Treatment of China (No. 2014ZX07305001). The

426

authors like to thank Prof. Minyu Ding (Department of Chemistry, Tsinghua

427

University) for the helpful discussion about pH modelling.

428 429

References

430

1. Joss, A.; Salzgeber, D.; Eugster, J.; König, R.; Rottermann, K.; Burger, S.;

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Fabijan, P.; Leumann, S.; Mohn, J.; Siegrist, H. Full-scale nitrogen removal from

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digester liquid with partial nitritation and anammox in one SBR. Environ. Sci.

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2. Lackner, S.; Gilbert, E. M.; Vlaeminck, S. E.; Joss, A.; Horn, H.; van Loosdrecht,

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to nitrite of high ammonium content urban landfill leachates. Water Res. 2007, 41

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6. Li, H.; Zhou, S.; Huang, G.; Xu, B. Achieving stable partial nitritation using

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treatment enhanced ammonia-oxidizing bacterial (AOB) activity for nitritation

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14. Bagchi, S.; Biswas, R.; Nandy, T. Alkalinity and dissolved oxygen as controlling

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22. Park, S.; Bae, W. Modeling kinetics of ammonium oxidation and nitrite oxidation

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23. Park, S.; Bae, W.; Rittmann, B. E. Operational boundaries for nitrite accumulation

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in nitrification based on minimum/maximum substrate concentrations that include

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effects of oxygen limitation, pH, and free ammonia and free nitrous acid

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25. Dosta, J.; Galí, A.; El-Hadj, T. B.; Macé, S.; Mata-Alvarez, J. Operation and model

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description of a sequencing batch reactor treating reject water for biological

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nitrogen removal via nitrite. Bioresour. Technol. 2007, 98 (11), 2065–2075.

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26. Brockmann, D.; Morgenroth, E. Evaluating operating conditions for outcompeting

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nitrite oxidizers and maintaining partial nitrification in biofilm systems using

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biofilm modeling and Monte Carlo filtering. Water Res. 2010, 44 (6), 1995–2009.

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27. Ganigué, R.; Volcke, E.; Puig, S.; Balaguer, M. D.; Colprim, J. Impact of influent

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characteristics on a partial nitritation SBR treating high nitrogen loaded

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wastewater. Bioresour. Technol. 2012, 111, 62–69.

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28. Liu, X.; Kim, M.; Nakhla, G. A model for determination of operational conditions

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for successful shortcut nitrification. Environ. Sci. Pollut. Res. 2017, 24 (4), 3539–

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model no 1 (ADM1). Water Sci Technol. 2002, 45 (10), 65–73.

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30. Henze, M.; Gujer, W.; Mino, T.; van Loosdrecht, M. C. M. Activated sludge models ASM1, ASM2, ASM2d and ASM3. IWA publishing. 2000.

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31. Matsunaga, N.; Kano, K.; Maki, Y.; Dobashi, T. Culture scale-up studies as seen

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33. Mortimer, C. H. The oxygen content of air saturated fresh waters over ranges of

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34. Zheng, M.; Liu, Y.; Wang, C.; Xu, K. Study on enhanced denitrification using

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Chemosphere. 2013, 93, 2669–2674.

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35. Ministry of Environmental Protection, P. R. C. Monitoring and Analytical Methods

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of Water and Wastewater. 4th ed., China Environmental Science Press: Beijing,

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36. Van Hulle, S.W.H.; Volcke, E.I.P.; Teruel, J.L.; Donckels, B.; van Loosdrecht,

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M.C.M.; Vanrolleghem, P.A. Influence of temperature and pH on the kinetics of the

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37. Reichert, P. AQUASIM 2.0-User Manual, Computer Program for the Identification

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38. Carrera, J.; Jubany, I.; Carvallo, L.; Chamy, R.; Lafuente, J. Kinetic models for

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39. Vadivelu, V. M.; Keller, J.; Yuan, Z. Effect of free ammonia and free nitrous acid

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concentration on the anabolic and catabolic processes of an enriched Nitrosomonas

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culture. Biotechnol. Bioeng. 2006, 95 (5), 830–839.

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40. Law, Y.; Ye, L.; Wang, Q.; Hu, S.; Pijuan, M.; Yuan, Z. Producing free nitrous acid

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41. Qiao, S.; Matsumoto, N.; Shinohara, T.; Nishiyama, T.; Fujii, T.; Bhatti, Z.;

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Furukawa, K. High-rate partial nitrification performance of high ammonium

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containing wastewater under low temperatures. Bioresour. Technol. 2010, 101 (1),

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42. Li, H.; Zhou, S.; Huang, G.; Xu, B. Partial nitritation of landfill leachate with

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Environ. Prot. 2013, 91 (4), 285–294.

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43. Wei, D.; Xue, X.; Yan, L.; Sun, M.; Zhang, G.; Shi, L.; Du, B. Effect of influent

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ammonium concentration on the shift of full nitritation to partial nitrification in a

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sequencing batch reactor at ambient temperature. Chem. Eng. J. 2014, 235, 19–26.

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44. Zhang, L.; Yang, J.; Hira, D.; Fujii, T.; Furukawa, K. High-rate partial nitrification

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treatment of reject water as a pretreatment for anaerobic ammonium oxidation

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45. Galí, A.; Dosta, J.; van Loosdrecht, M. C. M.; Mata-Alvarez, J. Two ways to

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achieve an anammox influent from real reject water treatment at lab-scale: Partial

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SBR nitrification and SHARON process. Process Biochem. 2007, 42 (4), 715–720.

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Table 1. Estimated parameters values with their 95% confidence interval. Process

AOB

NOB

Unit

0.32 ± 0.05

0.67 ± 0.17

1/day

1. Cell growth µmax

Maximal growth rate (20°C)

2. Effect of pH on ammonia oxidation activity pHmin

Constant

6.06

-

-

KpH

Constant

0.34 ± 0.12

-

-

3. Effect of NH3 and HNO2 on ammonia and nitrite oxidation activity

574

‫୍ܭ‬,୒ୌయ

Half-saturation inhibition constant

-

0.27 ± 0.04

mM

‫୍ܭ‬,ୌ୒୓మ

Half-saturation inhibition constant

146a

10 ± 7

µM

a

Van Hulle, et al.36

575

29

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576

Figure Captions

577

Figure 1. Influent ammonium, bicarbonate (a) and effluent ammonium, nitrite, nitrate

578

concentrations (b) during the SBR operation. The line in Figure 1b represents model

579

predicted effluent ammonium, nitrite and nitrate results (as discussed in the model

580

validation section).

581

Figure 2. Variations of ammonium, NOx– (nitrite plus nitrate), bicarbonate and pH

582

during a typical SBR cycle with influent ammonium concentration of 84 mM. This

583

cycle was manually extended to 24 hours to determine the minimal pH for AOB

584

growth.

585

Figure 3. Measured rates of nitrite oxidation (‫୓୒ݎ‬୆ ) under different NH3 or HNO2

586

concentrations (experimental conditions: T = 25°C and NO2− = 14−30 mM). Line

587

represents fitting results using the non-substrate inhibition model (‫୓୒ݎ‬୆ = ‫୓୒ݎ‬୆,୫ୟ୶ ·

588

௄౅ ୗା௄౅

). Error bars represent standard deviations.

589

Figure 4. Profiles of ammonium, nitrite, nitrate, bicarbonate, pH, NH3, HNO2 and net

590

specific growth rates (µ−b) of AOB and NOB in two groups of batch tests with initial

591

bicarbonate to ammonium molar ratios of 0.5 (a, b and c) and 2.0 (d, e and f). The

592

lines represent model predicted profiles using the calibrated parameters.

593

Figure 5. Model prediction of partial nitritation feasible region defined by influent

594

ammonium and bicarbonate concentrations in SBR (DO > 2.0 mg/L, SRT = 10 days,

595

and T = 25°C.

596

Figure 6. Minimum ammonium concentration in influent for achieving partial

597

nitritation (NO2–/(NO2– + NO3–) > 90%) in SBR under different SRT, DO and

598

temperature (details of the simulation results can be found in Figure S3–S5).

599

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600 601

Figure 1. Influent ammonium, bicarbonate (a) and effluent ammonium, nitrite, nitrate

602

concentrations (b) during the SBR operation. The line in Figure 1b represents model

603

predicted effluent ammonium, nitrite and nitrate results (as discussed in the model

604

validation section).

605

31

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606 607

Figure 2. Variations of ammonium, NOx– (nitrite plus nitrate), bicarbonate and pH

608

during a typical SBR cycle with influent ammonium concentration of 84 mM. This

609

cycle was manually extended to 24 hours to determine the minimal pH for AOB

610

growth.

611

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612 613

Figure 3. Measured rates of nitrite oxidation (‫୓୒ݎ‬୆) under different NH3 or HNO2

614

concentrations (experimental conditions: T = 25°C and NO2− = 14−30 mM). Line

615

represents fitting results using the non-substrate inhibition model (‫୓୒ݎ‬୆ = ‫୓୒ݎ‬୆,୫ୟ୶ ·

616

௄౅ ୗା௄౅

). Error bars represent standard deviations.

617

33

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618 619

Figure 4. Profiles of ammonium, nitrite, nitrate, bicarbonate, pH, NH3, HNO2 and net

620

specific growth rates (µ−b) of AOB and NOB in two groups of batch tests with initial

621

bicarbonate to ammonium molar ratios of 0.5 (a, b and c) and 2.0 (d, e and f). The lines

622

represent model predicted profiles using the calibrated parameters.

623

34

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624 625

Figure 5. Model prediction of partial nitritation feasible region defined by influent

626

ammonium and bicarbonate concentrations in SBR (DO > 2.0 mg/L, SRT = 10 days,

627

and T = 25°C).

628

35

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629 630

Figure 6. Minimum ammonium concentration in influent for achieving partial

631

nitritation (NO2–/(NO2– + NO3–) > 90%) in SBR under different SRT, DO and

632

temperature (details of the simulation results can be found in Figure S3–S5).

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237x96mm (300 x 300 DPI)

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