Full-Scale Modeling Explaining Large Spatial Variations of Nitrous

Article pubs.acs.org/est

Full-Scale Modeling Explaining Large Spatial Variations of Nitrous Oxide Fluxes in a Step-Feed Plug-Flow Wastewater Treatment Reactor Bing-Jie Ni,*,†,∥ Yuting Pan,†,∥ Ben van den Akker,‡ Liu Ye,†,§ and Zhiguo Yuan*,† †

Advanced Wastewater Management Centre, The University of Queensland, St. Lucia, Brisbane, Queensland 4072, Australia Australian Water Quality Centre, Adelaide, South Australia 5000, Australia § School of Chemical Engineering, The University of Queensland, St. Lucia, Brisbane, Queensland 4072, Australia ‡

Downloaded by UNIV OF NEW SOUTH WALES on September 7, 2015 | http://pubs.acs.org Publication Date (Web): July 17, 2015 | doi: 10.1021/acs.est.5b02038

S Supporting Information *

ABSTRACT: Nitrous oxide (N2O) emission data collected from wastewater treatment plants (WWTPs) show huge variations between plants and within one plant (both spatially and temporarily). Such variations and the relative contributions of various N2O production pathways are not fully understood. This study applied a previously established N2O model incorporating two currently known N2O production pathways by ammonia-oxidizing bacteria (AOB) (namely the AOB denitrification and the hydroxylamine pathways) and the N2O production pathway by heterotrophic denitrifiers to describe and provide insights into the large spatial variations of N2O fluxes in a step-feed full-scale activated sludge plant. The model was calibrated and validated by comparing simulation results with 40 days of N2O emission monitoring data as well as other water quality parameters from the plant. The model demonstrated that the relatively high biomass specific nitrogen loading rate in the Second Step of the reactor was responsible for the much higher N2O fluxes from this section. The results further revealed the AOB denitrification pathway decreased and the NH2OH oxidation pathway increased along the path of both Steps due to the increasing dissolved oxygen concentration. The overall N2O emission from this step-feed WWTP would be largely mitigated if 30% of the returned sludge were returned to the Second Step to reduce its biomass nitrogen loading rate.

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The measured N2O fluxes exhibited strong spatial-temporal variation along the reactor path. The step-feed configuration showed a substantial influence on the N2O emissions, with the N2O emission factor in sections following the first and second feed being 0.68% and 3.5%, respectively, of the nitrogen load to the corresponding section. However, such variations and the responsible mechanisms are still not fully understood. N2O is produced during biological nitrogen removal, typically attributed to autotrophic ammonia-oxidizing bacteria (AOB) and heterotrophic denitrifying organisms.1,7,9 N2Oproducing pathways in these microorganisms are complex, involving multiple enzymes with the same function, and require multiple layers of regulatory machinery.10,11 According to the current understanding, N2O production by AOB can occur through two different routes: (i) N2O as the final product of AOB denitrification with NO2− as the terminal electron acceptor, named the AOB denitrification;12,13 and (ii) N2O as a byproduct of incomplete oxidation of hydroxylamine (NH2OH) to NO2−, called the NH2OH pathway.7,13 N2O is

INTRODUCTION Nitrous oxide (N2O) can be produced and directly emitted from wastewater treatment plants (WWTPs). 1−4 N 2 O emissions have been increasingly recognized by water utilities as a significant contributor to the carbon footprint of WWTPs.1,2,5,6 It is estimated that an emission factor as low as 0.5% would lead to a greenhouse gas emission that is comparable to that of the indirect CO2 emission due to energy consumption in conventional biological nutrient removal WWTP.5,7 Therefore, fundamental understanding and effective mitigation of N2O emissions is of great importance to the sustainable operation of WWTPs. During the past years, significant efforts have been made worldwide to quantify and investigate N2O emissions from fullscale WWTPs.1−4 The N2O emission data collected from WWTPs to date show a huge variation in the fraction of influent nitrogen load emitted as N2O (emission factor) in the range of 0.01−1.8%, and in some cases even higher than 10%.1−4 A high degree of temporal and spatial variability in N2O emission has also been observed within the same WWTP.2 Recently, a comprehensive online N2O monitoring campaign was performed using multiple gas collection hoods to characterize N2O emissions along the length of a full-scale, step-fed, plug-flow-like activated sludge reactors in Australia.8 © 2015 American Chemical Society

Received: Revised: Accepted: Published: 9176

April 23, 2015 July 7, 2015 July 8, 2015 July 8, 2015 DOI: 10.1021/acs.est.5b02038 Environ. Sci. Technol. 2015, 49, 9176−9184

Article


Environmental Science & Technology

Figure 1. Layout of, and sampling locations in the two Steps (4 Paths) in the step-feed full-scale plug-flow activated sludge reactor. Locations 1−6 are the six sampling locations at each Step.

validated by comparing simulation results with comprehensive monitoring data of N2O emission, as well as other water quality parameters from the step-feed plant. The key mechanism responsible for the spatial variations of N2O fluxes in the stepfeed reactor as well as the relative contributions of different production pathways was investigated. A potential strategy to mitigate N2O emission from this plant was also evaluated using the model.

also a known intermediate in heterotrophic denitrification. Incomplete denitrification can lead to N2O emissions, which has been linked to several factors such as the chemical oxygen demand (COD) to N ratio, the substrate and biomass type, pH, temperature, among others.9,14 Mathematical modeling of N2O emissions is of great importance toward understanding the whole environmental impact of WWTPs, which has been recognized as an appropriate method for testing hypotheses related to mechanisms and developing effective mitigation strategies.6,15−19 Ni et al.6 applied a model based on the NH2OH pathway for N2O production by AOB to predict N2O emissions from two full-scale WWTPs. While clearly showing that the NH2OH-pathway model could well describe N2O emission in the two full-scale plants studied, the modeling results do not prove the dominance of the NH2OH pathways in these plants, nor rule out the possibility of AOB denitrification being a potentially dominating pathway due to the fact that a singlepathway model can describe two-pathways through calibration under certain conditions.20 The AOB denitrification based models were also used to describe the data collected on the UCT process from the Eindhoven plant.18,19 These previous full-scale modeling studies only focused on verifying if a selected model, based on a single-pathway of AOB, could adequately describe measured data from full-scale plants. The mechanisms responsible for variations have not been revealed in these modeling studies, nor the effective mitigation strategies developed. Recently, a new mathematical model that considers the two currently known N2O production pathways by AOB, namely the AOB denitrification and NH2OH oxidation pathways, was developed to describe N2O production by AOB.21 The validity of this model to predict the shifts of the dominating N2O pathway at various DO and nitrite levels has been confirmed by several different lab-scale experimental systems particularly with N2O isotopic data sets.21−23 In this work, this previously established multiple-pathway N2O model was applied to describe and provide insights into the large spatial variations of N2O fluxes in a WWTP for the first time, taking a full-scale, step-fed, plug-flow-like activated sludge reactor in Australia as an example, in which large spatial N2O variations has been experimentally observed.8 The model was calibrated and

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MATERIALS AND METHODS Description of the Step-Feed Full-Scale Activated Sludge Plant. The studied full-scale step-feed activated sludge reactor has a design capacity of 50 ML/day. The reactor has a working volume of 21,205 m3, with a designed hydraulic retention time (HRT) of 12 h and sludge retention time (SRT) of 12 days. A simplified process flow diagram of the activated sludge reactor studied is shown in Figure 1. The reactor is a plug-flow reactor consisting of four paths. A bubbling aeration through membrane disc diffuser is applied to the four paths of the plug-flow reactor throughout the aerobic zones (Figure 1) with equal distribution along each path. The influent of the plug-flow reactor is split, entering at the beginning of Paths 1 (56%) and 3 (44%), respectively, forming a two-step configuration (with the First Step including Path 1 and Path 2 and the Second Step including Path 3 and Path 4). Each step consists of an anoxic zone for denitrification at the beginning, followed by an aerated zone for nitrification. The mixed liquor from Path 2 enters Path 3, mixed with the influent fed to this path. The effluent leaves the plug-flow reactor from the end of Path 4. The returned activated sludge (RAS) from the secondary clarifiers is recycled to the beginning of the anoxic zone of Path 1 (Figure 1). Experimental Data with Large Spatial Variations of N2O Fluxes. A long-term 40 day monitoring campaign was conducted between July to September 2013 to quantify N2O emissions from different locations along the step-feed plant and to determine the spatial variations of N2O emissions.8 The sampling locations were deliberately chosen to cover the beginning (Location 2 and 3 of the First Step, Location 2 of the Second Step), the middle (Location 4 of both Steps) and the end (Location 6 of both Steps) of the aerobic zone, as shown in Figure 1. The N2O emitted at these locations were collected 9177

DOI: 10.1021/acs.est.5b02038 Environ. Sci. Technol. 2015, 49, 9176−9184

Article


Environmental Science & Technology through sampling hoods floating over the mixed liquor. Three hoods were first located on the First Step to monitor the firststep N2O emission continuously from day 1 to day 17, and then were moved to the Second Step to monitor the second-step N2O emission from day 18 to day 40. During these monitoring periods, 24 h composite samples of both influent and effluent were collected daily to measure total COD (TCOD), total Kjeldahl nitrogen (TKN), ammonium (NH4+-N), nitrate (NO3−-N) and nitrite (NO2−-N) concentrations in the influent and effluent. A 4 day intensive sampling campaign was also conducted on the step-feed plug-flow reactor.8 The First Step was monitored on days 14 and 15 and the Second Step was monitored on days 21 and 23. Hourly liquid samples (from 8 am to 3 pm) were taken manually at a depth of about 0.5 m below the surface at 12 different sampling locations along the reactor (Figure 1) for wastewater and mixed liquor composition analysis. The sampling locations (as shown in Figure 1) included influent, anoxic zone (Location 1) and different locations across the aerobic zones (Location 2 to Location 6) in each Step. Samples were analyzed for dissolved N2O, NH4+-N, NO3−-N and NO2−N. Further details of the sampling design and measurement methods are described in Pan et al.8 The obtained experimental data showed a high level of spatial variability of N2O fluxes along the reactor. Figure S1 in Supporting Information (SI) presents the typical one-day N2O flux profiles at all six monitored locations across the two steps. The N2O fluxes measured in the Second Step were substantially higher than the fluxes measured at the equivalent locations in the First Step, particularly for the beginning and middle sections (Figure S1). These spatial patterns described above were consistently observed during the long-term (40 days) monitoring period. Integrated N2O Model with Three Production Pathways. The previously established two-pathway N2O model by AOB21 and heterotrophic denitrification processes6 was applied in this work, which incorporates the nitrifier denitrification pathway, the NH2OH oxidation pathway, and heterotrophic denitrification pathway for N2O productions. The model components, stoichiometry and kinetics of this multiplepathway N2O model by AOB and heterotrophic denitrifiers are summarized in Table S1−S3 in SI. Table S4 in SI shows the definitions, values, and units of all parameters used in the integrated N2O model. The key feature of the two-pathway N2O model of AOB is that the model decouples the oxidation and reduction processes through a pool of electron carriers.21 Electron carriers are introduced as a new component in the model to link electron transfer from oxidation to reduction. The metabolism for NOB in the reaction model is as described by Hao et al.,24 which considered both the growth and decay processes. The commonly used “death-regeneration” approach was used to model heterotrophic growth utilizing decay-produced products. With this approach, biomass decay is assumed to produce slowly biodegradable substances (Xs), which is then hydrolyzed (Process 8 in SI Table S3) to readily biodegradable substances (Ss) that feed heterotrophic growth. Besides aerobic heterotrophic growth (Process 9), the model considers denitrification as sequential reduction of nitrate, nitrite and N2O (Processes 10−12). In both AOB denitrification and heterotrophic denitrification, we describe NO2− reduction to N2O as a one-step process. This simplification was made in order to avoid a direct link

between the pathways via NO (e.g., Process 4). If NO were modeled as an intermediate for NO2− reduction, the NO produced in this process would be available for oxidation to NO2− by AOB, resulting in an NO and NO2− loop. This assumption is justifiable, as NO accumulation/emission is rarely observed during denitrification by AOB or heterotrophic denitrifiers.21 Model Calibration and Validation. The integrated N2O model was calibrated using the extensive monitoring data from the sampling campaigns at the step-feed plant from day 15 to day 22, including 2 day continuous N2O emission data (days 15−17) and 1 day intensive monitoring data (day 15) at different locations from the First Step of the plant, as well as 4 days continuous N2O emission data (days 18−22) and 1 day intensive monitoring data (day 21) at different locations from the Second Step of the plant. The plug-flow reactor was modeled using continuously stirred tank reactor (CSTR) in series to describe the spatial behavior of the system. Three different configurations were tested in our simulations, namely 8, 16, and 32 CSTRs. The results indicated that the 16 CSTRs configuration model could well describe the experimentally observed substrate gradients along the plug-flow reactor, which was then applied in model calibration and validation (see SI Figure S2). The model contains 40 stoichiometric and kinetic parameters. Among them, 34 model parameter values are well established in literature and thus adopted from literature directly, as presented in SI Table S4. A two-phase procedure was applied to calibrate the model with the remaining six key parameters, in order to accurately estimate both the ammonium oxidation kinetics and the N2O production related parameters. In the first phase, the ammonium oxidation kinetics (i.e., rNH3,ox and KO2,NH3) were calibrated using the ammonium, nitrite, nitrate and DO data. Then three key parameters for the N2O production processes by AOB (rO2,red, rNO2−,red and rNO,red, see SI Table S4) and one key parameters for the N2O production by heterotrophic denitrifiers (ηH3, see Table S4) were further calibrated using the N2O emission data at different locations of the plant in the second phase. These parameters were selected for calibration based on a sensitivity analysis of the parameters in terms of the measured data. All other stoichiometric and kinetic parameters, given in SI Table S4, were taken or adapted directly from the literature. The parameter values were estimated by minimizing the sum of squares of the deviations between the measured data and the model predictions using the secant method embedded in AQUASIM.25 The secant optimization method is well suited for the minimization of numerically integrated equations using linear approximation of the model functions, which can lead to a much faster end convergence being close to a well-defined minimum.25 The parameter estimation and parameter uncertainty evaluation were done according to Batstone et al.,26 with a 95% confidence level for significance testing and parameter uncertainty analysis. The standard errors and 95% confidence intervals of individual parameter estimates were calculated from the mean square fitting errors and the sensitivity of the model to the parameters. Model validation was then carried out with the calibrated model parameters (SI Table S4) by the other sets of the monitoring data from both long-term and intensive sampling campaigns at the plant, with different dynamic inflow and aeration conditions, which has not been used to estimate the parameters. The validation data sets included 14 days 9178


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Figure 2. Model calibration results for N2O emissions using the 2 days continuous N2O emission data (days 15−17) at different locations from the First Step (left panel), as well as 4 days continuous N2O emission data (days 18−22) at different locations from the Second Step (right panel) (real data: symbols; model predictions: lines).

parameters shown in SI Table S4) were first evaluated with the 14 days continuous N2O emission data (days 1−14) and 1 day intensive monitoring data (day 14) at different locations from the First Step. The validation data had different input conditions from the calibration data: different inflow rate and wastewater composition. The validation results in SI Figure S4 and Figure 3 (left panels) show that the model predictions match the measured data in terms of ammonium, nitrite, nitrate, DO, and N2O profiles at all the sampling locations of the First Step for the validation experiments. The good correspondence (R2 = 0.88) for independent data set supports the validity of the integrated N2O model for the full scale stepfeed WWTP. These comprehensive evaluation results together with the model testing performance in previous work16,21−23 further confirm that the model is able to describe nitrogen conversion and N2O production in different mixed culture nitrification and denitrification processes. To further validate the integrated N2O model, experimental results of 14 days continuous N2O emission data (days 24−38) and 1 day intensive monitoring data (day 23) at different locations from the Second Step of the plant were also used to evaluate the developed model. The experimental and simulated results of the ammonium, nitrite, nitrate, DO and N2O profiles are also shown in SI Figure S4 and Figure 3 (right panels). As can be seen in SI Figure S4 and Figure 3, agreement between simulated and measured results was good (R2 = 0.85) for all fitted variables at all locations. These extensive evaluations with different experimental parameters (ammonium, nitrite, nitrate, N2O and DO) at different sampling locations in independent experiments, which reflect different aspects of the kinetics of

continuous N2O emission data (days 1−14) and 1 day intensive monitoring data (day 14) at different locations from the First Step of the plant, as well as 14 days continuous N2O emission data (days 24−38) and 1 day intensive monitoring data (day 23) at different locations from the Second Step of the plant.

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RESULTS AND DISCUSSION Model Calibration and Validation. Model calibration of this work involved adjusting key parameter values for the nitrogen conversion (rNH3,ox and KO2,NH3) and N2O production processes (rO2,red, rNO2−,red and rNO,red and ηH3) so that the ammonium, nitrite, nitrate, DO, and N2O profiles produced by the model closely agreed with the measured data (SI Figure S3 and Figure 2) at the different sampling locations of both Steps. The good agreement (R2 = 0.91) between model simulations and measured ammonium, nitrite, nitrate and DO data (SI Figure S3) as well as N2O emission data (Figure 2) supported that the developed model properly captures the relationships among ammonium utilization, N2O production, and DO consumption. Parameter values giving the optimum model fit with the experimental data are listed in SI Table S4, together with their standard errors. The retrieved parameter values appear realistic, which are all comparable with those reported in literature.6,21,22 In addition, the obtained standard errors for the parameter values were small, indicating a good identifiability of these estimated parameters. Model and parameter validation was based on the comparison between the model predictions and the monitoring data collected during different measurement campaigns on the Step-feed plant. The model and its parameters (the same 9179


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Figure 3. Model validation results for N2O emissions using the other 14 days continuous N2O emission data (days 1−14) at different locations from the First Step (left panel), as well as the other 14 days continuous N2O emission data (days 24−38) at different locations from the Second Step (right panel) (real data: symbols; model predictions: lines).

pathways from both AOB and heterotrophic denitrifiers. Thus, the overall relationship between N2ORsp and AORsp in the plant should be determined by the functional N2O production mechanisms as well as operating conditions. In fact, the N2O production rate and the specific growth rate/ammonia consumption rate of AOB were intrinsically linked as both the nitrifier denitrification pathway and NH2OH oxidation pathway could be favored under increased specific ammonium oxidation rate.7,22,23 Indeed, such positive correlations between N2ORsp and AORsp have also been observed previously in laboratory studies using AOB culture enriched under various conditions.7,22,23 This is the first time, however, such a relationship is revealed for a full-scale plant. In addition, Figure S7 in SI showed that the effect of nitrite on N2ORsp at different locations of both steps was not significant (i.e., no clear correlations), compared to the effect of AORsp. The effect of DO on N2ORsp (partially correlated) at different locations of both steps (Figure S8 in SI) should be attributed to the effect of AORsp. Thus, we confirm the highly dynamic AORsp caused the large spatial variation of N2O production in the two steps (Figure 4). More importantly, all the AORsp and N2ORsp predicted in the Second Step were significantly higher than the predicted AORsp and N2ORsp at the equivalent locations in the First Step (Figure 4). Modeling results showed that the Second Step would have much lower biomass concentration (about 70% of the First Step) and the higher DO levels than the First Step due to the particular sludge return strategy. The RAS from the secondary clarifiers was only recycled to the anoxic zone of the First Step, which resulted in higher biomass specific nitrogen loading rate (thus the AORsp) in the Second Step and subsequently resulted in higher N2O production in this Step.

the N2O production in the plant, supported the validity of the integrated N2O model. Spatial Variations of N2O Production Rate. The available online monitoring data (SI Figure S1 and Figures 23) and the model predicted N2O fluxes during the 40 days operation of the step-feed reactor at different locations (SI Figure S5) showed that the N2O emissions were highly dynamic along the step-feed reactor. In particular, all locations in the Second Step of the reactor had a much higher N2O emission than the First Step (SI Figure S5). SI Figure S6 shows the model predicted biomass specific ammonia oxidation rate (AORsp) and biomass specific N2O production rate (N2ORsp) at different locations with aeration (Figure 1) of the First Step (Locations 2−6) and the Second Step (Locations 2−6) during the 40 days operation of the step-feed full-scale reactor. The results showed a strong spatial variability of both AORsp and N2ORsp along the two steps of the step-feed reactor. For the First Step, both AORsp and N2ORsp were relatively low at Location 2. Increasing AORsp and N2ORsp were observed at Location 3 and Location 4. Both AORsp and N2ORsp decreased from Location 5 toward the end of aeration zone of the First Step (Location 6). Overall, the predicted AORsp and N2ORsp from the middle of the aeration zone (Location 4) were much higher than peaks from the beginning and the end of the aeration zone (e.g., Locations 3 and 6). The spatial variation of AORsp and N2ORsp from the Second Step showed a similar pattern in comparison with that of the First Step. The modeling results (SI Figure S6) clearly showed a strong correlation between N2ORsp and AORsp in all the locations of both steps, that is, the N2ORsp linearly increased with the increasing AORsp, as demonstrated in Figure 4. The integrated model of this work included three different N2O production 9180


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Figure 4. Linear correlations between the model predicted biomass specific ammonia oxidation rate (AORsp) and biomass specific N2O production rate (N2ORsp) at different locations from the First Step (left panel) and the Second Step (right panel).

Spatial Variations of N2O Production Pathways. There are three main microbial pathways involved in N2O production in WWTP based on current knowledge: nitrifier denitrification and NH2OH pathways by AOB, as well as heterotrophic denitrification pathway.1,27−29 The relative contributions of these three pathways to total N2O production from WWTP varied under different ammonium, nitrite and DO concentration conditions.21−23,30 Since the ammonium, nitrite and DO profiles showed significant spatial variations at different locations of both Steps in the step-feed plant (SI Figures S3−S4 and 2−3), the relative contributions of the three N2O pathways to total N2O production would likely change along the locations spatially.

Figure 5 shows the model predicted percentage contributions from the three pathways to the total N2O production at six different locations (Figure 1) of the First Step and the Second step, respectively. For the First Step (left panel), negligible N2O production was predicted at Location 1 (anoxic zone) due to the lack of nitrite and nitrate substrates. N2O was mostly produced by AOB at all the remained locations (Locations 2− 6) with a very small fraction of N2O production by heterotrophic denitrification at Location 3. The nitrifier denitrification pathway was the dominant pathway at Locations 2−5 and decreased along the path of the First Step because of the increase in DO concentrations. On the contrary, the NH2OH oxidation pathway increased along the path of the First Step and was the dominant pathway at Location 6 where 9181


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Figure 5. Model predicted percentage contributions from the three N2O pathways to total N2O productions at six different locations of the First Step (left panel) and the Second Step (right panel), that is, the nitrifier denitrification pathway, the NH2OH pathway and the heterotrophic denitrification pathway.

reduced by increasing the sludge concentration (in order to reduce the AORsp) through directly returning a fraction of the total Returned Activated Sludge (RAS) to the Second Step rather than just returning all the RAS to the First Step of the reactor (Figure 1). This potential strategy to mitigate N2O emission from this plant was then evaluated using the model. The model was run with different percentages of RAS split to the First and Second Steps to test the impact of a better balanced RAS strategy on the N2O emissions from the plant. As shown in the Figure 6, the N2O emission factor from the First Step would increase with the increase in the fraction of RAS returned to the Second Step (Figure 6A), which was due to a decrease in sludge concentration at the First Step. On the contrary, the N2O emission factor from the Second Step decreased significantly (Figure 6B). The model showed that the overall N2O emission factor of the whole step-feed reactor would be reduced to the lowest value of< 1% if 30% of the total RAS was returned to the Second Step. In summary, an integrated N2O model based on the nitrifier denitrification and NH2OH pathways by AOB as well as heterotrophic denitrification pathway was applied to predict and provide insights into the spatially and temporally varied N2O fluxes from a step-feed full-scale WWTP in this work. The model was successfully calibrated and validated using 40 days of N2O emission and water quality monitoring data. The model should be applicable to a wide range of plants, with appropriate calibration efforts being devoted, which might serve as a unified model for N2O production in wastewater treatment systems. The nitrifier denitrification pathway decreased and the NH2OH oxidation pathway increased along the path of the both Steps, with the Second Step of the full-scale WWTP having much higher N2O emission than the First Step. The relatively high biomass specific nitrogen loading rate in the Second Step of the reactor was responsible for the much higher N2O fluxes seen from this Step. The overall N2O emission from the step-feed full-scale WWTP would be largely mitigated if 30% of the total returned activated sludge was returned to the Second Step.

DO was highest (up to 4.0 mg/L). For the Second Step (right panel), a considerable amount of N 2O production by heterotrophic denitrification was predicted in the anoxic zone at Location 1. Different from the First Step, significant accumulation of nitrite and high nitrate levels were observed in the anoxic zone of the Second Step, which favored the N2O production by heterotrophic denitrification. The heterotrophic denitrification pathway would then largely decrease at Locations 2 and 3 with an increase in DO. The nitrifier denitrification pathway was dominant at Locations 2−4 and decreased along the path of the Second Step. The NH2OH pathway also increased with the increasing DO from Location 2 to Location 6. The relative contribution from NH2OH pathway at the Second Step was clearly higher than that at the First Step, which was most likely due to the higher ammonium oxidation rate under higher DO conditions at the Second Step. These results are also in agreement with the previous reported experimental findings.7,22 The nitrifier denitrification pathway has been identified to decrease in activity with increasing DO concentration whereas N 2O production from NH 2 OH oxidation could be favored under increased DO concentration.21−23 The integrated N2O model captured all these trends regarding shifts between the different N2O pathways in full-scale WWTP. In addition, these spatial patterns were consistently predicted during the 40 days operation, without significant temporal variation between relative contributions from different pathways between days and even within a day. Potential Strategy to Mitigate N2O Emissions. Both the modeling and experimental results (SI Figures S3−S4 and Figures 2−3) demonstrated that the Second Step of the fullscale WWTP had a much higher N2O emission compared to the First Step. The determined N2O emission factor at the Second Step was 3.5% of the nitrogen load applied to this step, which was five times higher thanthe First Step (0.69%). In addition to the N2O production from heterotrophic denitrification and AOB played an important role in influencing N2O emission from the two Steps due to the fact that the lower sludge concentration and higher DO levels at the Second Step resulted in higher AORsp and subsequently a higher N2ORsp within the Second Step (see Figure 4). Therefore, the N2O emission from the Second Step of the plant could likely be 9182




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ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.est.5b02038.

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AUTHOR INFORMATION

Corresponding Authors

*(B.-J.N.) Phone +61 7 3346 3230; fax: +61 7 3365 4726; email: [email protected]. *(Z.Y.) Phone: + 61 7 3365 4374; fax: +61 7 3365 4726; e-mail [email protected]. Author Contributions ∥

REFERENCES

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Figure 6. Impact of fraction of the returned activated sludge (RAS) that returning to the Second Step on the N2O emissions from the stepfeed full-scale WWTP: (A) N2O emission from the First Step; (B) N2O emission from the Second Step; and (C) Total N2O emission from the whole plant.

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Article

B.-J.N. and Y.P. contributed equally to this work.

Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS B.-J.N. acknowledges the supports of Australian Research Council Discovery Early Career Researcher Award DE130100451 and Australian Research Council Discovery Project DP130103147. Experimental studies were financially supported by the South Australia Water Corporation. 9183


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Full-Scale Modeling Explaining Large Spatial Variations of Nitrous

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