The aim of the study was to determine the pH effects on nitrogen removal in the anammox-enriched granular sludge. The experimental data were extracted from a 4 L completely-mixed batch reactor with the granular sludge at different initial pH values (6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10, 10.5) and constant temperature T = 30 °C. Simulations were run in GPS-X 6.4 using a comprehensive mechanistic model Mantis2. Two kinetic parameters, the maximum specific growth rates of ammonia oxidizing bacteria (AOB) and anammox bacteria, were optimized at different pH scenarios. The inhibitory effects of the pH extremes on the anammox-enriched sludge were discussed in terms of the inhibition of free nitrous acid and free ammonia and metabolic mechanisms. Two different pH functions were used to examine the pH effects on the nitrogen removal kinetics. The pH optima for AOB and anammox bacteria were 7.4 and 7.6, respectively. The maximum specific growth rates of AOB and anammox bacteria at the pH optima were 0.81–0.85 d−1 and 0.36–0.38 d−1 (at T = 30 °C). The measured specific anammox activities (SAAs), predicted SAAs by Mantis2 and fitted SAAs by the Michaelis pH function at the pH optima were 0.895, 0.858 and 0.831 gN/(gVSS·d), respectively (VSS: volatile suspended solids).

INTRODUCTION

The anaerobic ammonium oxidation (anammox) process is a viable alternative to nitrogen removal by the conventional nitrification/denitrification. In practice, most of the anammox-based systems utilize mixed cultures of functional consortia predominated by anammox bacteria (Niu et al. 2016). These systems are subjected to inhibition by many factors, including substrates (ammonia and nitrite), organic matter (nontoxic and toxic organic matter), specific compounds (salts, heavy metals, phosphate, sulfide), and variations in the operating conditions (Carvajal-Arroyo et al. 2013).

The pH is considered as one of the most important operating parameters affecting stoichiometry and kinetics of biological processes. The recent study by Carvajal-Arroyo et al. (2013) has indicated sharp pH optima (7.3–7.5) in the specific anammox activities (SAAs) for both suspended and granular anammox enrichments, i.e., 17.32 ± 2.13 mmol N2/(gVSS·d) and 6.78 ± 0.71 mmol N2/(gVSS·d), respectively (VSS: volatile suspended solids). The impact of pH extremes has been attributed to the direct effects of pH or the pH-dependent un-ionized species, free ammonia (FA) and free nitrous acid (FNA), which are presumably toxic for the anammox and nitrification processes (Fernández et al. 2012; Daverey et al. 2015). Chen et al. (2010) proposed that low pH as well as FNA was responsible for anammox inhibition in acid solutions. Puyol et al. (2014b) proposed that high pH instead of FA was responsible for anammox inhibition in alkaline solutions. The inhibition has also been rationalized based on a disruption of the intracellular proton motive force over the anammoxosome membrane, thus directly affecting energy yield and cell survival (van der Star et al. 2010).

Hultman (1973) proposed the first equation describing pH effects on the maximum specific growth rate of microorganisms. Antoniou et al. (1990) proposed another equation describing pH effects on nitrification according to active ionized enzyme theory. The same equation was also suggested by Angelidaki et al. (1993) but in a different form (also known as Michaelis pH function). However, none of these functions have been used in the anammox-enriched granular sludge.

Serralta et al. (2004) extended the activated sludge model ASM2d with pH calculations. Goel et al. (2010) verified the pH predictions of the activated sludge model ASM2d. Hao et al. (2002, 2005) described several simulation studies on the behaviour of a partial nitrification–anammox biofilm system under different process conditions, including oxygen consumption, temperature and inflow variations. However, no mathematical model with pH calculation has been applied in the anammox-enriched system.

In this study, a comprehensive mechanistic model was combined with a pH calculation tool to optimize the kinetic parameters, including the maximum specific growth rates of ammonia oxidizing bacteria (AOB) and anammox bacteria, at different pH scenarios in a single system. Two different pH functions were used to determine the inhibitory effects of pH on the maximum specific growth rates of AOB and anammox bacteria in the anammox-enriched granular sludge.

MATERIALS AND METHODS

Extraction of experimental data

Experimental setup

The laboratory experiments were conducted in a 4 L completely mixed batch reactor with the anammox-enriched granular sludge at different initial pH values (6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10, 10.5) and constant temperature T = 30 °C. The sludge was cultivated for more than 1 year on synthetic substrates under laboratory conditions in a sequencing batch reactor (SBR) to obtain a granulation effect. The average diameter of the developed granules was approximately 730 μm. The synthetic feed contained sodium nitrite, ammonium chloride and trace elements. The initial concentrations of total ammonia and total nitrite, respectively, were in the ranges of 31–39 g N/m3 and 38–50 g N/m3 to avoid the substrate limitation, and the theoretical NO2-N/NH4-N ratio of 1.3 for the anammox process was maintained during all the batch experiments. In this way, two most important kinetic parameters (maximum specific growth rate of AOB and of anammox bacteria) could be estimated in terms of changing pH. The initial pH was adjusted by the addition of dilute HCl (1 mol/L) or NaOH (2 mol/L). The initial dissolved oxygen (DO) concentrations were between 0.5 and 1 mg O2/L and stable in the same level during the course of the experiments except when pH = 6. During the course of each batch experiment, the pH and DO concentrations were not controlled. More information about the laboratory experiments can be found elsewhere (Sobotka et al. 2016, in press; Yin et al. 2016).

Analytical and microbiological methods

Concentrations of the inorganic N forms (NH4-N, NO3-N, NO2-N) were determined in the filtered mixed liquor every 30 min during the course of the batch experiments. The measurements were carried out using cuvette tests (Hach Lange GmbH, Germany) in a Xion 500 spectrophotometer (Dr Lange GmbH, Germany). The DO, pH and temperature were monitored continuously during the course of each batch experiment. The biomass composition for setting the initial conditions in modeling was determined using the metagenomic analysis (Sobotka et al. in press).

Model description

The comprehensive model Mantis2, pre-installed in GPS-X 6.4 (Hydromantis, Canada), extends ASM2d and ADM1 (Anaerobic Digestion Model No. 1) with side-stream partial nitritation/denitritation and anammox process for nitrogen removal. The addition of a special algebraic pH solver also allows estimation of the actual pH value in the anammox-based process by solving a set of algebraic equations for a charge balance along with the equilibrium equations for each ionic species.

The growth rate function of AOB (μAOB) uses the total ammonia and oxygen saturation terms as well as FA and FNA inhibition terms, as follows:
formula
1
where is the maximum specific growth rate for AOB (d−1); is the saturation coefficient for total ammonia for AOB (g N/m3); is the inhibition coefficient for FA for AOB (g N/m3); is the inhibition coefficient for FNA for AOB (g N/m3); is the saturation coefficient for oxygen for AOB (g O2/m3); is the total ammonia concentration (g N/m3); is the FA concentration (g N/m3); is the FNA concentration (g N/m3); is the DO concentration (g O2/m3).
The growth rate function of anammox bacteria (μAnam) uses the DO inhibition term as well as total nitrite and total ammonia saturation terms, as follows:
formula
2
where is the maximum specific growth rate for anammox bacteria (d−1); is the saturation coefficient for total ammonia for anammox bacteria (g N/m3); is the saturation coefficient for total nitrite for anammox bacteria (g N/m3); is the inhibition coefficient for oxygen for anammox bacteria (g O2/m3); is the total ammonia concentration (g N/m3); is the total nitrite concentration (g N/m3); is the DO concentration (g O2/m3).
In this study, in order to reflect the pH variations, the maximum specific growth rates of AOB and anammox bacteria were adjusted, using the Hultman pH function (Hultman 1973) (Equation (3)) and the Michaelis–Antoniou pH function (further referred to as the Michaelis pH function) (Antoniou et al. 1990; Angelidaki et al. 1993; Weinrich & Nelles 2015) (Equation (4)):
formula
3
formula
4
where the Hultman pH function gives a value of the maximum specific growth rate (μmax(pH)opt) at the optimal pH (when pH = pHopt), and the parameters, pHopt and k determine the location and shape of the Hultman pH curve; the Michaelis pH function gives a value of the maximum specific growth rate (μmax(pH)0.5) at the central pH (when pH= 0.5(pKh1+pKh2)), and the parameters pKh1 and pKh2 determine the location and shape of the Michaelis pH curve.

Organization of the modeling study procedure

Model layout

A completely mixed tank layout was set up in GPS-X 6.4 with a working volume of 4 L, using a DO controller and pH setup. The measured process variables, including NH4-N, NO3-N, NO2-N, DO, pH, temperature and mixed liquor volatile suspended solids as well as the constant microbial community composition (anammox, nitrifiers, heterotrophs) were imported for the simulation of the nitrogen removal processes at the different pH scenarios (6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10, 10.5).

Initial microbial composition

The initial microbial composition of the anammox-enriched granular sludge was estimated based on the metagenomic analysis. The identified Proteobacteria phylum included heterotrophic denitrifiers and AOB (the AOB content in that phylum was approximately 0.5%). The Planctomycetes phylum was recognized as the main bacteria responsible for the anammox process. The other recognized bacteria were assumed to be initial particulate inert organic material in the model (Figure 1).
Figure 1

Microbial composition of the measured biomass and model input biomass (the assumed particulate chemical oxygen demand (g) to volatile suspended solids (g) ratio = 1.48 (Comeau 2008; Ekama & Wentzel 2008)). Xi: particulate inert organic material; XAOB: active ammonia-oxidizing biomass; XHET: active heterotrophic biomass; XAnam: active anammox biomass.

Figure 1

Microbial composition of the measured biomass and model input biomass (the assumed particulate chemical oxygen demand (g) to volatile suspended solids (g) ratio = 1.48 (Comeau 2008; Ekama & Wentzel 2008)). Xi: particulate inert organic material; XAOB: active ammonia-oxidizing biomass; XHET: active heterotrophic biomass; XAnam: active anammox biomass.

Simulation of the pH effects on nitrogen removal

For model calibration, a special GPS-X utility called ‘Optimizer’ was used. Two kinetic parameters, the maximum specific growth rates of AOB (μmax,AOB) and anammox bacteria (μmax,Anam), were optimized based on the Nelder–Mead simplex method with the maximum likelihood objective functions, using the measured NH4-N and NO2-N concentrations as the target variables, while NO3-N was not used as a target variable. The remaining kinetic and stoichiometric parameters (55 parameters) (Table S1, available with the online version of this paper) were adopted without any change from the Mantis2 model (Hydromantis, Canada). The 95% liner-approximation confidence limits for the parameter estimates were calculated from the variance–covariance matrix. Furthermore, correlation matrices (μmax,AOB and μmax,Anam) at the different pH scenarios were developed to evaluate the degree of correlation between the adjusted parameters.

RESULTS AND DISCUSSION

Model-based optimization of the maximum specific growth rates at the different pH scenarios

The two adjusted parameters (μmax,AOB and μmax,Anam) at the different pH scenarios (from 6 to 10.5) (T = 30 °C) are listed in Table 1. Samples of the optimization results (R2 close to 1) at three typical pH scenarios (pH = 6, 8, 9.5) are shown in Figure 2, which indicated a significant inhibitory effect of the extreme pH values (low pH and high pH) on the NH4-N and NO2-N removal performance by the anammox-enriched granular sludge. The actual pH values were simulated at the different pH scenarios by the algebraic pH solver.
Table 1

List of the adjusted model parameters at the different pH scenarios (from 6 to 10.5) (T = 30 °C)

Ammonia oxidizing bacteria (XAOB): μmax,AOB (1/d)
Anammox bacteria (XAnam): μmax,Anam (1/d)
Mantis2 value at 30 °CAdjusted value ( ± standard errora)Mantis2 value at 30 °CAdjusted value ( ± standard errora)
1.80 pH = 6 0.08 ( ± 0.24) 0.049 pH = 6 0.040 ( ± 0.017) 
pH = 6.5 0.32 ( ± 0.23) pH = 6.5 0.170 ( ± 0.037) 
pH = 7 0.64 ( ± 0.16) pH = 7 0.294 ( ± 0.067) 
pH = 7.5 0.81 ( ± 0.38) pH = 7.5 0.366 ( ± 0.064) 
pH = 8 0.56 ( ± 0.24) pH = 8 0.298 ( ± 0.092) 
pH = 8.5 0.26 ( ± 0.10) pH = 8.5 0.184 ( ± 0.032) 
pH = 9 0.10 ( ± 0.30) pH = 9 0.078 ( ± 0.022) 
pH = 9.5 0.03 ( ± 0.27) pH = 9.5 0.035 ( ± 0.013) 
pH = 10 5E − 4 ( ± 0.22) pH = 10 0.015 ( ± 0.012) 
pH = 10.5 5E − 4 ( ± 0.31) pH = 10.5 0.003 ( ± 0.014) 
Ammonia oxidizing bacteria (XAOB): μmax,AOB (1/d)
Anammox bacteria (XAnam): μmax,Anam (1/d)
Mantis2 value at 30 °CAdjusted value ( ± standard errora)Mantis2 value at 30 °CAdjusted value ( ± standard errora)
1.80 pH = 6 0.08 ( ± 0.24) 0.049 pH = 6 0.040 ( ± 0.017) 
pH = 6.5 0.32 ( ± 0.23) pH = 6.5 0.170 ( ± 0.037) 
pH = 7 0.64 ( ± 0.16) pH = 7 0.294 ( ± 0.067) 
pH = 7.5 0.81 ( ± 0.38) pH = 7.5 0.366 ( ± 0.064) 
pH = 8 0.56 ( ± 0.24) pH = 8 0.298 ( ± 0.092) 
pH = 8.5 0.26 ( ± 0.10) pH = 8.5 0.184 ( ± 0.032) 
pH = 9 0.10 ( ± 0.30) pH = 9 0.078 ( ± 0.022) 
pH = 9.5 0.03 ( ± 0.27) pH = 9.5 0.035 ( ± 0.013) 
pH = 10 5E − 4 ( ± 0.22) pH = 10 0.015 ( ± 0.012) 
pH = 10.5 5E − 4 ( ± 0.31) pH = 10.5 0.003 ( ± 0.014) 

Note: the Arrhenius coefficients for the maximum specific growth rates are 1.072 (AOB) and 1.101 (anammox).

aStandard error is under 95% confidence level for the confidence limits.

Figure 2

Samples of measured data vs. optimized simulation results at pH = 6, 8 and 9.5.

Figure 2

Samples of measured data vs. optimized simulation results at pH = 6, 8 and 9.5.

The adjusted model parameters (μmax,AOB, μmax,Anam) were from the optimization. The peak value μmax,AOB at the different pH scenarios (from 6 to 10.5) was 0.81 d−1 at pH = 7.5 (T = 30 °C), which was much smaller than the Mantis2 value of 1.80 d−1 (T = 30 °C). The peak value of μmax,Anam at the different pH scenarios (from 6 to 10.5) was 0.366 d−1 at pH = 7.5 (T = 30 °C), which was much higher than the Mantis2 value of 0.037 d−1 (T = 30 °C). Both parameters (μmax,AOB and μmax,Anam) decreased greatly (90%) when pH deviated from the estimated pH optimum (pH = 7.5) to pH extremes (pH = 6 or pH = 9.5).

The correlation coefficients were extracted from the off-diagonal elements of the correlation matrices at the different pH scenarios, which, by definition, indicate the degree of correlation between pairs of parameters (μmax,AOB and μmax,Anam) and are always between 0 and ±1. The correlation coefficients, calculated in GPS-X 6.4 for the different pH scenarios, varied in the range of −0.45 and −1 (Figure 3). A negative sign implied that an increased μmax,AOB was compensated for by a decreased μmax,Anam. This provided the evidence that AOB and anammox bacteria are highly correlated due to their shared substrate and product.
Figure 3

Correlation coefficients of parameters (μmax,AOB and μmax,Anam) at the different pH scenarios (from 6 to 10.5).

Figure 3

Correlation coefficients of parameters (μmax,AOB and μmax,Anam) at the different pH scenarios (from 6 to 10.5).

The mechanisms of the pH effects on the anammox-enriched sludge

Figure 4 indicates that the initial FA concentration exceeded the inhibition threshold value of 1.7 g N/m3 (Jung et al. 2007) when pH >8, and the initial FNA concentration exceeded the inhibition threshold value of 0.0015 g N/m3 (Fernández et al. 2012) when pH <7.5. The negative effect of FA was found to be attributed to the diffusion of FA through the cell membrane into the cell, which could cause the neutralization of the membrane potential and even cell death (Jaroszynski et al. 2011). The negative effect of FNA was found to be attributed to the non-competitive inhibition at pH <7.1 (Puyol et al. 2014a). Apart from the indirect influence of pH on the speciation of NH3/NH4+ and HNO2/NO2, the extreme pH values could also directly affect anammox bacteria by altering other metabolic processes which rely on the pH gradients, e.g., energy-generating intracellular proton gradient over the anammoxosome membrane or pH-dependent active transport proteins such as NO2 transporters (van der Star et al. 2010; Lotti et al. 2012). Puyol et al. (2014b) stated that high pH values instead of high FA concentrations were responsible for the anammox inhibition in alkaline solutions. Chen et al. (2010) stated that both low pH values and FNA were responsible for the anammox inhibition in acid solutions. However, in the present study, FA concentrations significantly exceeded the inhibition threshold value (when pH >8) and thus those concentrations may also have potential inhibitory effects on anammox activities in alkaline solutions. Therefore, the pH effects on nitrogen removal in the anammox-enriched granular sludge could reasonably be explained by the inhibition of high FA concentration (at high pH), the inhibition of high FNA concentration (at low pH) and a disruption of metabolic processes at extreme pH values.
Figure 4

The pH dependence of the initial free ammonia (FA) and free nitrous acid (FNA) concentrations and inhibition thresholds for the anammox bacteria (TAN – total ammonia, TNI – total nitrite).

Figure 4

The pH dependence of the initial free ammonia (FA) and free nitrous acid (FNA) concentrations and inhibition thresholds for the anammox bacteria (TAN – total ammonia, TNI – total nitrite).

Implementation of pH functions in the maximum specific growth rates

The optimized parameters, maximum specific growth rates of two consortia of bacteria (AOB and anammox bacteria), are shown in Figure 5. The two examined pH functions, the Hultman pH function and the Michaelis pH function, were used in the non-linear fitting process to explain the pH dependence of the maximum specific growth rates of both groups of bacteria (Table 2).
Table 2

Fit results of the pH functions with respect to the maximum specific growth rates

 Hultman pH function
 Michaelis pH function
Equation parameterValueStandard errorEquation parameterValueStandard error
AOB  AOB  
μmax(pH)opt 0.852 0.022 μmax(pH)0.5 0.812 0.013 
pHopt 7.44 0.02 pKh1 7.09 0.05 
k 0.214 0.017 pKh2 7.80 0.05 
Adj. R2 0.995 Adj. R2 0.997 
Anammox  Anammox  
μmax(pH)opt 0.376 0.011 μmax(pH)0.5 0.362 0.009 
pHopt 7.54 0.02 pKh1 6.82 0.06 
k 0.133 0.013 pKh2 8.25 0.06 
Adj. R2 0.991 Adj. R2 0.992 
 Hultman pH function
 Michaelis pH function
Equation parameterValueStandard errorEquation parameterValueStandard error
AOB  AOB  
μmax(pH)opt 0.852 0.022 μmax(pH)0.5 0.812 0.013 
pHopt 7.44 0.02 pKh1 7.09 0.05 
k 0.214 0.017 pKh2 7.80 0.05 
Adj. R2 0.995 Adj. R2 0.997 
Anammox  Anammox  
μmax(pH)opt 0.376 0.011 μmax(pH)0.5 0.362 0.009 
pHopt 7.54 0.02 pKh1 6.82 0.06 
k 0.133 0.013 pKh2 8.25 0.06 
Adj. R2 0.991 Adj. R2 0.992 
Figure 5

Non-linear curve fit of pH dependence of maximum specific growth rates.

Figure 5

Non-linear curve fit of pH dependence of maximum specific growth rates.

Both Hultman pH function and Michaelis pH function gave a superior description of the measured data (R2 close to 1).The pH optima for AOB and anammox bacteria were 7.4 and 7.6, respectively. The maximum specific growth rate of AOB at the pH optimum was 0.81–0.85 d−1 (at T = 30 °C). The maximum specific growth rate of anammox bacteria at the pH optimum was 0.36–0.38 d−1 (at T = 30 °C), which could be attributed to the fast-growing anammox-enriched cultures (0.33 d−1 at 30 °C, 0.39 d−1 at 37 °C, 0.59 d−1 at 35 °C) (Isaka et al. 2006; Bae et al. 2010; Lotti et al. 2015) rather than the slow-growing anammox cultures (0.02 d−1 at 30 °C, 0.04–0.077 d−1 at 32–33 °C, 0.13–0.19 d−1 at 37 °C) (van de Graaf et al. 1996; van der Star et al. 2007; Hao et al. 2009).

Subsequently, the SAAs were calculated based on the NH4-N and NO2-N measurements. Predicted SAAs were obtained through model simulations after applying the optimized maximum specific growth rates for each examined pH. The Michaelis pH function was also used to fit the measured SAAs (Table 3).

Table 3

Prediction and fit results with respect to the SAAs

Prediction – Mantis2 
Adj. R2 0.988 
Fit – Michaelis pH function 
SAA(pH)0.5 ± SE 0.831 0.055 
pKh1 ± SE 6.89 0.16 
pKh2 ± SE 8.40 0.15 
Adj. R2 0.944 
Prediction – Mantis2 
Adj. R2 0.988 
Fit – Michaelis pH function 
SAA(pH)0.5 ± SE 0.831 0.055 
pKh1 ± SE 6.89 0.16 
pKh2 ± SE 8.40 0.15 
Adj. R2 0.944 

SE: standard error.

The predicted SAAs, shown in Figure 6, corresponded well with the measured SAAs (R2 = 0.988). The measured SAAs could accurately be described by the Michaelis pH function (R2 = 0.944). Sharp pH optima were observed in the measured SAAs, predicted SAAs by Mantis2 and fitted SAAs by the Michaelis pH function for the anammox-enriched granular sludge. The maximum SAA values at the optimal pHs were, respectively, 0.895 gN/(gVSS·d) (measured SAAs), 0.858 gN/(gVSS·d) (predicted SAAs by Mantis2) and 0.831 gN/(gVSS·d) (fitted SAAs by the Michaelis pH function). These observed maximum SAAs were approximately four times higher compared to the maximum SAA value of 0.19 gN/(gVSS·d) for granular anammox cultures reported by Carvajal-Arroyo et al. (2013), but close to the maximum SAA value of 0.9 gN/(gVSS·d) for the granules in a gas-lift reactor (Dapena-Mora et al. 2004) and in the range of the maximum SAA values of 0.4–2.14 gN/(gVSS·d) for granules in an SBR (Arrojo et al. 2006) and a submerged anaerobic membrane bioreactor (Li et al. 2014). Furthermore, the observed SAAs decreased considerably (more than 90%) when pH deviated from the optimal value (pH = 7.6) to pH extremes (pH = 6 or pH = 10).
Figure 6

Predicted SAAs in Mantis2 and non-linear curve fit of the measured SAAs.

Figure 6

Predicted SAAs in Mantis2 and non-linear curve fit of the measured SAAs.

CONCLUSIONS

The estimated optimal pH values for AOB and anammox bacteria were 7.4 and 7.6, respectively. The maximum specific growth rates of AOB and anammox bacteria at the pH optima were 0.81–0.85 d−1 and 0.36–0.38 d−1 (at T = 30 °C), respectively. The measured SAAs, predicted SAAs by Mantis2 and fitted SAAs by the Michaelis pH function at the pH optima were 0.895, 0.858 and 0.831 gN/(gVSS·d), respectively. The pH effects on nitrogen removal in the anammox-enriched granular sludge could be described by the two examined pH functions, i.e., the Michaelis pH function and the Hultman pH function. The impact of the pH extremes on the anammox-enriched granular sludge resulted from the inhibition of FA (at high pH) and FNA (at low pH) and the inhibition of the pH extremes on the intracellular proton transfer for cell survival. Therefore, the existing mechanistic models need extensions with respect to the pH inhibition functions on the maximum specific growth rates of both AOB and anammox bacteria.

ACKNOWLEDGEMENTS

This study was financially supported by the National Science Centre (Poland) under project no. UMO-2011/01/B/ST8/07289. During this study, Xi Lu and Zhixuan Yin were visiting researchers at Gdansk University of Technology within the framework of the CARBALA Project (CARbon BALAncing for nutrient control in wastewater treatment), People Maria Curie Actions (FP7-PEOPLE-2011-IRSES).

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Supplementary data