Modeling of simultaneous denitrification – Anaerobic digestion – Organic matter aerobic oxidation and nitrification in an anoxic–anaerobic–aerobic compact filter reactor

Journal of Biotechnology 160 (2012) 176–188

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Modeling of simultaneous denitrification – Anaerobic digestion – Organic matter aerobic oxidation and nitrification in an anoxic–anaerobic–aerobic compact filter reactor ˜ b , Karol Peredo a , Estrella Aspé a , Marlene Roeckel a,∗ Jaime Moya a , César Huilinir a b

Departamento de Ingeniería Química, Facultad de Ingeniería, Universidad de Concepción, PO Box 4070386, Concepción, Chile Departamento de Ingeniería Química, Facultad de Ingeniería, Universidad de Santiago de Chile, Santiago, Chile

a r t i c l e

i n f o

Article history: Received 26 November 2011 Received in revised form 21 March 2012 Accepted 22 March 2012 Available online 1 April 2012 Keywords: Modeling Biofilm simulation Anoxic-anaerobic-aerobic filter reactor Denitrification-anaerobic digestion-nitrification-organic matter aerobic oxidation

a b s t r a c t A mathematical model was developed for a compact anoxic–anaerobic–aerobic filter reactor with liquid recirculation for the treatment of fishing effluents. The model includes denitrification, anaerobic digestion, aerobic carbon oxidation and nitrification steps, as well as an evaluation of the liquid gas mass transfer and pH. The model was calibrated using one experimental condition at a recycling ratio (R) = 10, and was validated with R equal to 2 and 0, with an organic concentration of 554 ± 24 mg TOC L−1 , salinity of 24 g L−1 and hydraulic retention time (HRT) of 2 d. Carbon total removal is higher than 98%, while maximum nitrogen removal is 62% using total nitrification in the aerobic zone, due to a higher quantity of NOx produced which were recirculated to the anoxic zone. In the aerobic zone, simultaneous nitrification and denitrification processes occur, because the diffusion limitations cause a low oxygen penetration in the biofilm. In the anoxic–anaerobic zone, denitrification or methanogenesis inhibition by DO (caused by the recycled oxygen) is not observed. © 2012 Elsevier B.V. All rights reserved.

1. Introduction Salmon and fishing industry effluents produce a strong environmental impact. After recycling and primary treatment to remove fats and proteins, the effluent contains 4–6 kg Chemical Oxygen Demand (COD) m−3 (1.5–2.2 g of Total Organic Carbon (TOC) L−1 ) (Aspé et al., 1997). Its abatement is achieved with an adequate combination of anaerobic, anoxic and aerobic processes. Conventional treatment to remove carbon and nitrogen compounds consists of three reactors performing separate processes (Aspé et al., 1997). Nevertheless, most recent experiments (Chui et al., 2001; Del Pozo and Diez, 2005; Ros and Vrtovsek, 1998) with different industry effluents have successfully combined these steps in a single unit, without physical separations, for the simultaneous carbon and nitrogen removal in an anaerobic/anoxic/aerobic compact filter reactor (FR). Compared with these previous works, this research proposes a sequential anoxic/anaerobic/aerobic FR. This configuration enhances the process efficiency because: (a) it uses the inlet organic matter as electron donor in the reduction of the nitrogen oxides (NOx ) without need of additional organic carbon supply; (b) it allows partial nitrification rather than total nitrification. The latter

∗ Corresponding author. Tel.: +56 41 2204987; fax: +56 41 2243750. E-mail address: [email protected] (M. Roeckel). 0168-1656/$ – see front matter © 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.jbiotec.2012.03.020

offers some process advantages such as: 25% less O2 requirements for the nitrification, 40% less organic carbon consumption and low sludge production (Bernet et al., 2005). When performing these anoxic–anaerobic and aerobic steps in a compact unit, some problems arise which have to be analyzed using a model. These limitations are: (1) inhibition of nitrate (NO3 − ) reduction and methanogenesis by nitrite (NO2 − ), (2) inhibition of denitrification and methanogenesis by dissolved oxygen (DO), and (3) competition for DO by heterotrophic and autotrophic nitrifying bacteria in the aerobic zone. The methanogenesis inhibition by NOx ˜ in biofilm reactors was included in this work according to Huilinir et al. (2009). Limitations 2 and 3 are related to the aerobic step because if the oxygen injection in the aerobic step is too high, there is a risk that the recycle flow contains a high DO concentration which in turn inhibits at the inlet reactor section the denitrification process (Del Pozo and Diez, 2005; Plósz et al., 2003; Ramos et al., 2007) and the methanogenesis step (An et al., 2008; Celis-García et al., 2004; Estrada-Vázquez et al., 2001; Lyew and Guiot, 2003). On the other hand, if the oxygen injection is too low, DO can drop to less than 3 mg DO L−1 , which lowers drastically the nitrification in the presence of organic matter because in this concentration range heterotrophic biomass outcompetes autotrophic nitrifier bacteria (Akunna et al., 1994; Del Pozo and Diez, 2005; Ling and Chen, 2005). Thus, the oxygen effect on the anoxic–anaerobic–aerobic efficiency process of a compact FR should be analyzed in a model.

J. Moya et al. / Journal of Biotechnology 160 (2012) 176–188

Nomenclature AL ci cprot,0 ci,bulk Di Dli fi Hei HRT IC IpH k1−3 kd,Xi kdes  kh,prot

KI,i,j kL ai KS,i,j L Lw prot pi Pj MW,ij Q0 Q QR qg QAir,0 R TAN TIC VFA Xi Yp YXi/ i

total surface area of the biofilm–liquid interface (m2 ) concentration of i (mgi L−1 ) initial concentration of protein (mg TOC L−1 ) bulk liquid concentration of i (mgi L−1 ) diffusion coefficient in biofilm (m2 d−1 ) diffusion coefficient in water (m2 d−1 ) fraction of the biomass i (Adimensional) Henry’s constant for i (mol L−1 atm−1 ) hydraulic residence time (d) total inorganic carbon inhibition factor by pH proportionality constants bacterial death constant for i (d−1 ) disintegration constant of inert biomass to protein (d−1 ) specific hydrolysis constant (L mg TOC−1 d−1 ) inhibition constant of process j by i (mgi L−1 ) gas–liquid transfer coefficient for component i (d−1 ) saturation constant of process j for i (mgi L−1 ) biofilm thickness (␮m) stagnant liquid layer thickness (␮m) protein partial pressure of gas i in the gas phase (atm) process rate j (mgi L−1 d−1 ) molecular weight of component i (mgi mol−1 ) volumetric flow of fishery wastewater (L d−1 ) volumetric flow at inlet and outlet of the reactor (L d−1 ) volumetric flow recirculated at inlet of reactor (L d−1 ) volumetric flow of gas (L d−1 ) volumetric flow injected in aerobic zone (L d−1 ) recycled volumetric flow/inlet volumetric flow total ammonia nitrogen Theil’s inequality coefficient volatile fatty acids biomass type i (mg TOC L−1 ) fraction of biodegradable protein yield coefficient (biomass i/substrate i) (mg TOC mgi −1 )

Greek symbols biofilm density (mg TOC L−1 ) b vij stoichiometric mass relationship for component i in the process j (mgi mgi −1 ) max,Xi ,j maximum specific growth rate of component Xi in the process j (d−1 ) Subscripts i dissolved or particulate component i process j j

Several models for biological processes have been reported in the literature, such as Activated Sludge Model (ASM) Series (Gujer et al., 1995, 1999; Henze et al., 1987), Anaerobic Digestion Model No. 1, ADM1 (Batstone et al., 2002), Anaerobic Digestion Model of Angelidaki et al. (1999), and Biological Nutrient Removal Model No. 1 (BNRM1) (Seco et al., 2004). Some of these models have been modified. Particularly the COD-based ADM1 model was extended by incorporating the NO3 − reduction (Tugtas et al., 2006, 2010).

177

Table 1 Experimental operation parameters of tubular filter reactors for the model adjustment and validation. Operation parameters

Reactor 1 (R1)

Reactor 2 (R2)

Reactor 3 (R3)

Effluent recirculation ratio Influent flow rate (L d−1 ) TOC influent (mg TOC L−1 ) IC influent (mg IC L−1 ) NO2 − N influent (mg NO2 − -N L−1 ) NO2 − N influent (mg NO3 − -N L−1 ) TAN-N influent (mg TAN-N L−1 ) TKN-N influent (mg TKN-N L−1 ) pH influent Air flow rate (L d−1 ) HRT (d) Temperature (◦ C)

0 2.45 578 ± 24 62 ± 3 0±0 59 ± 1 17 ± 2 232.3 ± 2 6.70 ± 0.30 640 2.0 30

2 2.45 529 ± 9 12 ± 2 0±0 0±0 17 ± 2 206.9 ± 2 6.71 ± 0.35 640 2.0 30

10 2.45 593 ± 16 54 ± 4 0±0 0±0 17 ± 2 231.9 ± 2 6.47 ± 0.22 640 2.0 30

For batch, semi-continuous, and continuous flow systems with suspended biomass, the pH calculation has been modified due to the presence of the nitrate reduction (Rousseau et al., 2008). The ˜ Angelidaki’s Anaerobic Digestion model was modified by Huilinir et al. (2011a) to include denitrification, pH as state variable, and the effect of the protein hydrolysis in a filter reactor in order to treat salmon fishery wastewater as a substrate. Finally, the BNRM1 ˜ et al. (2011b) model has been used as a base case by Huilinir to develop a simpler model in order to study the overall performance of an anoxic–anaerobic–aerobic filter reactor. Unlike the latter work, the present study seeks to incorporate pH and inorganic carbon concentration as state variables and study the axial profiles as well as along the biofilm depth. Then, a more complex model was developed, using as a base case the model published by ˜ et al. (2011a) who worked with the same substrate. Huilinir The objectives of this study are: (1) To calibrate and validate a dynamic model in steady-state of the anoxic–anaerobic–aerobic process for a compact filter reactor that treats fishery wastewater. (2) To study the DO concentration effect on the organic matter and nitrogen removal efficiencies and on the pH and to determine the DO concentration in the fluid bulk (cDO,bulk ) that favors the nitrogen removal. (3) To analyze the aerobic step by studying the competition between heterotrophic bacteria and autotrophic nitrifying bacteria. 2. Methodology 2.1. Experiments Three anoxic–anaerobic–aerobic filter reactors with recirculation (total volume, V = 6.33 L; total height of the reactor, H = 168 cm; internal diameter = 7.1 cm) filled with rough PVC (support surface area: volume ratio of 438 m2 m−3 ) randomly distributed throughout the bioreactors were used. Reactor porosity (␧L ) was 0.78 without biomass. The liquid volume in the reactors was 4.56 L, while the support volume was 1.33 L without biomass and the reactor headspace was 0.44 L. The reactor was divided in an anoxic–anaerobic zone and an aerobic zone. In this last zone, the air was injected with a diffuser installed in the bulk liquid at approximately half the reactor’s height. The anaerobic/aerobic volume was 1:1. The filters were operated under three conditions as shown in Table 1 (Unpublished data). The recycle ratio was defined as the recycled volumetric flow divided by the outlet flow. As a substrate, ˜ et al., 2011a) was diluted with salmon fishery wastewater (Huilinir tap water to reach the composition shown in Table 1; NaCl was added if necessary to have a constant inlet salt concentration.

178

J. Moya et al. / Journal of Biotechnology 160 (2012) 176–188

2.2. Analytical methods Nitrate, nitrite and total ammonia nitrogen (TAN) were spectrophotometrically measured according to Sánchez et al. (2005a). TOC was calculated as the difference between total carbon (TC) and inorganic carbon (IC) according to Aspé et al. (2001). pH was measured by Standard Methods (APHA et al., 1992). Analyses were performed in triplicate. It was experimentally observed that the air injection in the aerobic zone of the tubular reactor diluted the amount of biogas produced in the anoxic–anaerobic zone. Gas analysis in the effluent showed mainly O2 and N2 and very small amounts of CH4 as a result of the dilution produced by the air injection for aeration. Since the biogas measurements at the exit of the tubular reactor were below the equipment’s threshold detection limit. These measurements are not shown. 2.3. Theory 2.3.1. Conceptual model The flow, biofilm and physical-chemical processes model was ˜ et al. (2009), who studied a based on the previous work of Huilinir tubular reactor with a pseudo two-dimensional model using continuously stirred tank reactors (CSTR). In our work, as shown in Fig. 1, six CSTR were used according to previous Residence Time Distribution (RTD) tests (unpublished data), which refer to the hydrodynamic behavior in both the anoxic–anaerobic and aerobic zones. Since the volume ratio between both zones is 1:1, three CSTR were considered for each zone. The balance equations of particulate (biomass) and dissolved substances in the biofilm depth and ˜ et al., in the fluid and gas bulk are expressed as elsewhere (Huilinir 2009). 2.3.2. Stoichiometry and process kinetics First, for the denitrification and anaerobic digestion reaction, stoichiometries and kinetics of fish effluents biological treatment ˜ et al. (2011a) were used. Parameters for denireported by Huilinir trification inhibition by DO from the Activated Sludge Model (ASM) (Henze et al., 2000) and inhibition terms from the Biological Nutrient Removal Model No. 1 (BNRM1) (Seco et al., 2004) were also used. Secondly, for the nitrification, stoichiometry and kinetics, the data published by Wiesmann (1994) were used although fishery wastewater substrates were considered; thus, NaCl inhibitory effects on the maximum specific rate (Sánchez et al., 2004) and also non-competitive inhibition by VFA (Delgado et al., 2004) were added. Thirdly, for the aerobic oxidation experimental values of the protein, fishery wastewater substrate were used (unpublished data); these data were compared with other data published by Béline et al. (2007), who used piggery wastewater as a substrate (see Table 2). This table shows that data for both authors are within the same range, and model results did not show any significant Table 2 Comparison of the kinetic parameters of the aerobic oxidation process of piggery wastewater and saline proteinic fishery wastewater substrates. Kinetic parameter

KS,HVa,18 KS,HBu,19 KS,HPr,20 KS,HAc,21

Parameter values

Unit

Using piggery wastewater (Béline et al., 2007)

Using saline protein fishery wastewater

36.9 36.9 36.9 36.9

72.4 61.2 17.3 7.3

mg TOC L−1 mg TOC L−1 mg TOC L−1 mg TOC L−1

Fig. 1. Scheme of multiple CSTR in series.

differences between their use (unpublished data). Phosphorus (P) removal was not included in the model because the salmon effluent contains about 8 mg P L−1 (Aspé et al., 2001) smaller to be considered an environmental problem if compared to nitrogen dumping. Table 3 shows the mass based stoichiometric coefficients for dissolved and particulate compounds. Table 4 shows the reaction rates of the different processes involved. Table 5 presents the physical model’s parameters and Table 6 the process parameters of denitrification–anaerobic digestion–organic matter aerobic oxidation–nitrification process parameters. 2.3.3. Physicochemical processes To predict pH, a charge balance in the medium was performed (Campos and Flotats, 2003) using the algorithm

Table 3 Stoichiometric coefficients (vi,j ) matrix for the compounds in the denitrification-anaerobic digestion-nitrification-organic matter aerobic oxidation.

j 1 2 3 4 5 6

8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

Dissolved component

i Process

1 NO3

2 NO2

Denitratation with HVa Denitratation with HBu Denitratation with HPr Denitratation with HAc Denitritation with HVa Denitritation with HBu Denitritation with HPr Denitritation with HAc Protein hydrolysis Acidogenesis Acetogenesis from HVa Acetogenesis from HVa by XHAe Acetogenesis from HBu Acetogenesis from HBu por XHAe Acetogenesis from HPr Acetogenesis from HPr by XHAe Methanogenesis of HAc Aerobic oxidation of HVa Aerobic oxidation of HBu Aerobic oxidation of HPr Aerobic oxidation of Hac Nitritation Nitratation Deactivation of XHAe Deactivation of XAA Deactivation of XVaBu Deactivation of XProp Deactivation of XAc Deactivation of XAO Deactivation of XNO

−1

1

−1

1

−1

1

−1

1

3 Prot

4 AA

Particulate component 5 Va

6 Bu

7 Pr

8 Ac

−0.41 −0.42 −0.44 −0.53

−1

−0.69

−1

−0.72

−1

−0.78

−1 −1

1 −1

5.8 × 10−2 −1

11 N2

12 CH4

13 O2

−2.3 × 10−2

0.31

0.10

−2.3 × 10−2

0.32

0.10

−2.3 × 10−2

0.35

0.10

−2.3 × 10−2

0.43

0.10

−2

−6.1 × 10

0.43

1

0.26

−6.1 × 10−2

0.46

1

0.26

−6.1 × 10−2

0.51

1

0.26

−2

1

0.26

14 XHAe

−6.1 × 10

0.64

0.21 0.60

0.39 0.36

0.32 −1.5 × 10−2

0.07 −0.11

0.09

0.60

0.36

−1.5 × 10−2

−0.11

0.09

−1

0.95

−1.9 × 10−2

−0.14

0.11

−1

0.95

−1.9 × 10−2

−0.14

0.11

0.62

−2.4 × 10−2

5.4 × 10−2

0.22

0.62

−2

−2.4 × 10

−2

5.4 × 10

0.22

−1

−1.3 × 10−2

0.47

0.47

−0.19

0.19

−1.32

0.81

−0.18

0.25

−1.32

0.76

−0.16

0.31

−1.28

0.69

−0.15

0.37

−0.99

0.63

−1 −1.7 × 10−2

−1.71 −1.4 × 10−2

−3.37 −0.95

7.1 × 10−2

−1 −1

−1 −1 −1 −1 0.99 −1

10 IC

−0.91

−1

1

9 TAN

15 XAA

16 XVaBu

17 XProp

18 XAc

19 XAO

20 XNO

21 XI

J. Moya et al. / Journal of Biotechnology 160 (2012) 176–188

7

Component

0.20 6.53 × 10−2 6.53 × 10−2 8.16 × 10−2 8.16 × 10−2 0.10 0.10 5.5 × 10−2

7.8 × 10−2

2.2 × 10−2

−1

1 −1

1 1

−1 −1

1 −1 −1

179

−1

1 1 1

−1 −1 −1 −1

11 N2 10 IC

−1

9 TAN 8 Ac 7 Pr 6 Bu 5 Va 1

4 AA 3 Prot 1 NO3 i Process

36

35

34

33

32

Protein production from XI NH3 liquid–gas transfer CO2 liquid–gas transfer N2 liquid–gas transfer CH4 liquid–gas transfer O2 liquid–gas transfer 31

j

2 NO2

Dissolved component Component

Table 3 (Continued )

NO3 – nitrate, mg NO3 –N L−1 ; NO2 – nitrite, mg NO2 –N L−1 ; Prot – proteins, mg TOC L−1 ; AA – aminoacids, mg TOC L−1 ; Va – total valerate, mg TOC L−1 ; Bu – total butirate, mg TOC L−1 ; Pr – total propionate, mg TOC L−1 ; Ac – total acetate, mg TOC L−1 ; TAN – total ammonia nitrogen, mg N L−1 ; IC – inorganic carbon, mg C L−1 ; N2 – molecular nitrogen, mg N2 -N L−1 ; CH4 – methane, total, mg TOC L−1 ; O2 – dissolved oxygen, mg DO L−1 ; XHAe – aerobic heterotrophic degraders, mg TOC L−1 ; XAA – amino acid degraders, mg TOC L−1 ; XVaBu – valerate and butirate degraders, mg TOC L−1 ; XProp – propionate degraders, mg TOC L−1 ; XAc – acetate degraders, mg TOC L−1 ; XAO – ammonia-oxidants, mg TOC L−1 ; XNO – nitrite-oxidants, mg TOC L−1 ; XI – inert biomass, mg TOC L−1 .

16 XVaBu 15 XAA 14 XHAe 12 CH4

13 O2

Particulate component

17 XProp

18 XAc

19 XAO

20 XNO

−1

J. Moya et al. / Journal of Biotechnology 160 (2012) 176–188

21 XI

180

˜ et al. (2011a). Dissociation fractions of presented by Huilinir H2 CO3 /HCO3 − /CO3 −2 , NH4 + /NH3 and HNO2 /NO2 − were calculated following Angelidaki’s procedure (Angelidaki et al., 1999). For the DO partial pressure determination, the reactor was assumed to operate at atmospheric pressure and that the DO pressure is proportional to the DO fraction in the gas flow. 2.3.4. Relationship of kL a and DO Bello et al. (1985) and Jurascik et al. (2006) have shown an expression for kL a where kL a is inversely proportional to the bubble diameter (dB ) and proportional to the Grashof number (Gr) and gas hold up (ε) as shown in Eq. (1): kL a = k1 ·

Gr 1/3 1.2 ε dB

(1)

The gas hold up is determined from ε = vg /(vg + vL ) where ␯g and ␯L are the ascending velocity of the gas and the liquid, respectively. The ascending velocity in a column is shown in Eq. (2):

vL = k2 · ε0.5

(2)

Replacing Eq. (1) in (2), the relationship between vL and kL a is obtained as expressed in Eq. (3): kL a = k3 · v2.4 L

(3)

where k1 , k2 and k3 are proportionality constants. Then, the influence of vL and kL a is incorporated into the equation presented by Sánchez et al. (2005b) and Eq. (4) is obtained: kL aO2 =  ·

Gr 1/3 v2.4 L Gr  1/3 v 2.4 L

· v1.52 g

(4)

where Gr  and vL are the Grashof number and the liquid velocity respectively, for recycle ratio (R) = 2; and Gr and vL correspond to other flows and recycle ratios in the reactor. The adjustment is done with the incorporation of a factor “” into this equation. This factor is based on the expression used by Bello et al. (1985). 2.4. Model resolution. The FR model was solved using six equal CSTR, which were in turn solved sequentially, where each reactor’s outlet was the inlet ˜ et al., 2009). Each CSTR was conditions for the next reactor (Huilinir solved by discretizing the biofilm in 30 nodes as shown elsewhere ˜ et al. (2009), obtaining 671 ordinary differential equaby Huilinir tions (ODE). These are stiff equations; therefore they were solved using Numerical Differentiation Formulas in the MATLAB 6.5 software (Shampine and Reichelt, 1997). The balance is dynamically determined but the results analysis is done at steady state; therefore all ODE equations were integrated in a total FR operation period of 300 d. This limit value was obtained from the FR behavior until steady state was obtained (Unpublished data). The recycle to the reactor was simulated with the Wegstein method, which accelerates the convergence of the proposed problem (Wegstein, 1958). The model convergence criteria was set when the relative error of NO3 − , NO2 − , TAN, TOC, IC and pH reactor outlet parameters were less than 1% for larger concentrations than 1 mg L−1 ; whereas the used criteria for concentrations below 1 mg L−1 was an absolute error less than 0.1 mg L−1 for the aforementioned parameters. From Table 5, PT,gas was assumed; from the reactors design conditions V and ␧L were experimentally determined. Lw and b were obtained from literature. Di and Hei were calculated from literature data at 30 ◦ C. Hei for O2 and for CO2 were corrected due to the presence of salts following Gros et al. procedure (1999). Finally, the adjustment for kL aO2 was performed.

Table 4 Process rates (Pi,j ) of denitrification – anaerobic digestion – organic matter aerobic oxidation – nitrification. j 1

2

3

4

5

7

8 9 10 11 12 13 14 15 16 17 18 19 20 21

Denitratation with HVa

Denitratation with HBu

Denitratation with HPr

Denitratation with HAc

Denitritation with HVa

Denitritation with HBu

Denitritation with HPr

Denitritation with HAc Protein hydrolysis Acidogenesis Acetogenesis from HVa Acetogenesis from HVa by XHAe Acetogenesis from HBu Acetogenesis from HBu by XHAe Acetogenesis from HPr Acetogenesis from HPr by XHAe Methanogenesis of HAc Aerobic oxidation of HVa Aerobic oxidation of HBu Aerobic oxidation of HPr Aerobic oxidation of HAc

Process rates, Pj , mg of component L−1 d−1 max,X

HAe ,1

Y

XHAe /NO− 3

max,X

HAe ,2

Y

XHAe /NO− 3

max,X

HAe ,3

Y

XHAe /NO− 3

max,X

HAe ,4

Y

XHAe /NO− 3

max,X

HAe ,5

Y

XHAe /NO− 2

max,X

HAe ,6

Y

XHAe /NO− 2

max,X

HAe ,7

Y

XHAe /NO− 2

max,X

HAe ,8

Y

XHAe /NO− 2

 

YX

AA /AA

max,X

 

S,NO− ,5 2

S,NO− ,6 2

·

HAe ,16

HAe ,18

HAe /HVa

max,X

HAe ,19

YX

HAe /HBu

max,X

HAe ,20

YX

HAe /HPr

max,X YX

HAe ,21

HAe /HAc

NO− 2

NO− 2

·

+(c 2

/KI,NO ,5 )) 2 NO2



/KI,NO ,6 )) 2 NO2



· · ·

cHBu KS,HBu,14 +cHBu

  

  ·

  ·

cHBu KS,HBu,13 +cHBu

c

NO− 3

·

K

I,NO− ,5 3

c

NO− 3

1−

ˇNO−  3 ·

K

I,NO− ,6 3



c

NO− 3

1−

ˇNO−  3 ·

K

I,NO− ,7 3



c

NO− 3

1−

ˇNO−  3 ·

K

I,NO− ,8 3

·



 

KI,DO,4 KI,DO,4 +cDO

·

cHVa KS,HVa,5 +cHVa

cHBu KS,HBu,6 +cHBu

cHPr KS,HPr,7 +cHPr

cHAc KS,HAc,8 +cHAc

Tugtas et al. (2006), Soto et al. (2007), Seco et al. (2004)

3



KI,DO,2 KI,DO,2 +cDO

KI,DO,3 KI,DO,3 +cDO

· IpH,NO− · XHAe · IpH,NO− · XHAe

Tugtas et al. (2006), Soto et al. (2007), Seco et al. (2004)

· IpH,NO− · XHAe

Tugtas et al. (2006), Soto et al. (2007), Seco et al. (2004)

· IpH,NO− · XHAe

Tugtas et al. (2006), Soto et al. (2007), Seco et al. (2004)

3



3



3

  ·

  ·

 

KI,DO,5 KI,DO,5 +cDO

KI,DO,6 KI,DO,6 +cDO

KI,DO,7 KI,DO,7 +cDO

·

  ·

KI,DO,8 KI,DO,8 +cDO



· IpH,NO− · XHAe

Tugtas et al. (2006), Soto et al. (2007), Seco et al. (2004)

· IpH,NO− · XHAe

Tugtas et al. (2006), Soto et al. (2007), Seco et al. (2004)

· IpH,NO− · XHAe

Tugtas et al. (2006), Soto et al. (2007), Seco et al. (2004)

· IpH,NO− · XHAe

Tugtas et al. (2006), Soto et al. (2007), Seco et al. (2004)

2



2



2



2

·

  ·

·

·

 

cHVa KS,HVa,18 +cHVa cHBu KS,HBu,19 +cHBu cHPr KS,HPr,20 +cHPr cHAc KS,HAc,21 +cHAc

·

KI,HAc,13 KI,HAc,13 +cHAc

· IpH,HBu · XVaBu

K

S,NO− ,14 3 K +c − S,NO− ,14 NO 3 3



KI,NH ,17 3

·

  ·

  ·

  ·

cNH

3

KS,NH ,18 +cNH 3 3 cNH

3

KS,NH ,19 +cNH 3 3 cNH

3

KS,NH ,20 +cNH 3 3 cNH

3

KS,NH ,21 +cNH 3 3

·

 

·

S,NO− ,14 2 K +c − S,NO− ,14 NO 2 2

· IpH,HPr · XPro K

·

S,NO− ,16 2 K +c − S,NO− ,16 NO 2 2

 

KI,NH ,17 +cNH 3 3

 

S,NO− ,12 2 K +c − S,NO− ,12 NO 2 2

K

K

S,NO− ,16 3 K +c − S,NO− ,16 NO 3 3

 

K

·

KI,HAc,15 KI,HAc,15 +cHAc

 

· IpH,HVa · XVaBu

S,NO− ,12 3 K +c − S,NO− ,12 NO 3 3



˜ et al. (2009) Huilinir Angelidaki et al. (1999)



KI,HAc,11 KI,HAc,11 +cHAc K

 

 

cHPr KS,HPr,16 +cHPr

cHAc KS,HAc,17 +cHAc



ˇNO−  3

  ·

cHAc KS,HAc,4 +cHAc

·

· XAA

cHVa KS,HVa,11 +cHVa

cHPr KS,HPr,15 +cHPr



ˇNO−  2

KI,DO,1 KI,DO,1 +cDO

 

cHPr KS,HPr,3 +cHPr

·



· (cprot − (1 − Yp ) · cprot,0 ) · (XAA + XVaBu + XPr + XHAe )



cHVa KS,HVa,12 +cHVa





 ·



ˇNO−  2

1−

·

+(c 2

cHBu KS,HBu,2 +cHBu

·



·

0.55

ˇNO−  2



c − NO 2 +c − +(c 2 /KI,NO ,8 )) − S,NO ,8 NO 2 NO2 2 2 cHAc

·

· ·

+c

K

·

·

HAe /HPr

YX

+c

AA KS,AA,10 +cAA

·

YX

max,X

NO− 2

·

 I,HAc,9c

·

HAe ,14

Ac ,17

c

cHVa KS,HVa,1 +cHVa

·

I,NO− ,4 2

c − NO 2 +c − +(c 2 /KI,NO ,7 )) − S,NO ,7 NO 2 NO2 2 2

(K

·

HAe /HBu

Ac /HAc

K

(K

·

YX

YX

1−

I,NO− ,3 2

NO− 2

(K

VaBu /HBu

max,X

K

c

·

YX

max,X

·

NO− 3

NO− 2

1−

NO− 2

(K

VaBu ,13

Pro /HPr

c

 

+c

NO− 2

I,NO− ,2 2

References

ˇNO−  2

K

c

HAe ,12

YX

NO− 3

NO− 3

S,NO− ,4 3

VaBu ,11

Pro ,15

·

+c

NO− 2 K I,NO− ,1 2

c

1−

 

c K

·

HAe /HVa

max,X

S,NO− ,3 3

·

YX

max,X

NO− 3

NO− 3

K

1−

·

+c

c

·

VaBu /HVa

max,X

S,NO− ,2 3

c

 

NO− 3

K

YX

max,X

·

c

·

 kh,prot · 1− AA ,10

NO− 3 K +c − S,NO− ,1 NO 3 3

·



max,X

 

c

·

·

·

  ·

   

I,NO− ,17 3

+c

NO− 3

cDO KS,DO,18 +cDO cDO KS,DO,19 +cDO

cDO KS,DO,20 +cDO cDO KS,DO,21 +cDO

cHVa cHVa +cHBu +cHPr

 

 

· IpH,HVa · XHAe

Tugtas et al. (2006) ˜ et al. (2008) Huilinir

cHBu cHVa +cHBu +cHPr



· IpH,HBu · XHAe

Tugtas et al. (2006) ˜ et al. (2008) Huilinir

KI,HAc,16 KI,HAc,16 +cHAc

 

I,NO− ,17 3

 

·

 

K K

·

·

˜ et al. (2008) Huilinir



J. Moya et al. / Journal of Biotechnology 160 (2012) 176–188

6

Process ↓

·

  ·

K

I,NO− ,17 2

K

I,NO− ,17 2

+c

NO− 2

cHPr cHVa +cHBu +cHPr

  ·



KI,DO,17 KI,DO,17 +cDO

· IpH,HPr · XHAe



· IpH,HAc · XAc

Tugtas et al. (2006) Angelidaki et al. (1999), This work

· XHAe

Béline et al. (2007)

· XHAe

Béline et al. (2007)

· XHAe

Béline et al. (2007)

· XHAe

Béline et al. (2007)

181

˜ et al. (2009) Huilinir

This work

˜ et al. (2009) Huilinir

This work

˜ et al. (2009) Huilinir

Batstone et al. (2002)

Angelidaki et al. (1999)

Angelidaki et al. (1999)

Angelidaki et al. (1999)

Angelidaki et al. (1999)

Angelidaki et al. (1999)

Angelidaki et al. (1999)

Table 5 Physical parameters used in process model.

Angelidaki et al. (1999)

Sánchez et al. (2001, 2004), Wiesmann (1994), Delgado et al. (2004)

Sánchez et al. (2001, 2004), Wiesmann (1994), Delgado et al. (2004)

J. Moya et al. / Journal of Biotechnology 160 (2012) 176–188

References

182

Parameter

Value

Unit

Reference

AL DAA

2.69 3.50 × 10−6

m2 m2 d−1

DCH4

8.63 × 10−5

m2 d−1

DCO2

1.29 × 10−4

m2 d−1

DHAc DHBu

6.48 × 10−6 5.04 × 10−6

m2 d−1 m2 d−1

DHPr DHVa

6 × 10−6 4.58 × 10−6

m2 d−1 m2 d−1

DN 2

1.42 × 10−4

m2 d−1

DNH3 DNO−

1.91 × 10−4 1.97 × 10−4

m2 d−1 m2 d−1

˜ et al. (2011a) Huilinir Coulson and Richardson (1977) Coulson and Richardson (1977) Coulson and Richardson (1977) Buffiere et al. (1995) Coulson and Richardson (1977) Buffiere et al. (1995) Coulson and Richardson (1977) Coulson and Richardson (1977) Bernet et al. (2005) @ 30 ◦ C Bernet et al. (2005) @ 30 ◦ C

DNO−

1.86 × 10−4

m2 d−1

Bernet et al. (2005) @ 30 ◦ C

DDO Dprot

−4

2.19 × 10 1.42 × 10−6

−1

m d m2 d−1

HeCH4 HeCO2 HeN2 HeO2 kL aCH4 kL aCO2 kL aN2 Lw PT,gas V εL b

1.29 × 10−3 3.39 × 10−2 6.41 × 10−4 1.02 × 10−3 50 50 50 50 × 10−6 1 6.33 0.78 5000

mol CH4 atm−1 L−1 mol CO2 atm−1 L−1 mol N2 atm−1 L−1 mol O2 atm−1 L−1 d−1 d−1 d−1 m atm L – mg TOC L−1

Bernet et al. (2005) @ 30 ◦ C Coulson and Richardson (1977) Batstone et al. (2002) Batstone et al. (2002) Tugtas et al. (2006) Poughon et al. (1999) Merkel and Krauth (1999) Merkel and Krauth (1999) Merkel and Krauth (1999) Antileo et al. (2007) Assumed Experimental Experimental ˜ et al. (2011a) Huilinir

2

· XNO

 cDO KS,DO,23 +cDO

  

KI,VFA,23 KI,VFA,23 +cVFA (KS,HNO ,23 ·(1+cNH /KI,NH ,23 )+cHNO +(c 2 /KI,HNO ,23 )) 3 3 2 2 2 HNO

kL aO2 · (cDO,bulk − MW,O2 · HeO2 · pO2 )

kL aCH4 · (cCH4 ,bulk − MW,CH4 · HeCH4 · pCH4 )

kL aN2 · (cN2 ,bulk − MW,N2 · HeN2 · pN2 )

kL aCO2 · (cCO2 ,bulk − MW,CO2 · HeCO2 · pCO2 )

O2 liquid–gas transfer

CH4 liquid–gas transfer

N2 liquid–gas transfer

CO2 . liquid–gas transfer

2

cHNO

Experimental data from R3 was used for the calibration, and experimental data from R2 and R1 were used for validation (Table 1). For the model calibration kL aO2 was changed and default values for the remaining model parameters were assigned. To determine validity, the Theil’s inequality coefficient (TIC) (Hvala et al., 2005) was calculated as shown in Eq. (5):



TIC =



i

(yi − ym,i )2

y2 i i

+



(5)

y2 i m,i

where y is the analyzed parameter, yi is the experimental value and ym,i is the model predicted value. The model adequately predicts the experimental data when the TIC value is smaller than 0.3 (Hvala et al., 2005). 2.6. Parametric sensitivity analysis Parametric sensitivity analysis was performed as presented by ˜ et al. (2009) as shown in Eq. (6): Huilinir

NH3 liquid–gas transfer

kdes · XI Protein production from XI

kd,XNO · XNO Deactivation of XNO

kd,XAO · XAO Deactivation of XAO

kd,XAc · XAc Deactivation of XAc

kd,XProp · XProp Deactivation of XProp

kd,XVaBu · XVaBu Deactivation of XVaBu

kd,XHAe · XHAe

kd,XAA · XAA Deactivation of XAA

Deactivation of XHAe

kL aNH3 · (cNH3 ,bulk − MW,NH3 · HeNH3 · pNH3 )

2

2.5. Calibration and validation of the model

· ·(1−0.01402·cNaCl )

NO /HNO2

YX

NO ,23

max,X

Nitratation

· AO /NH3

YX

·(1−0.01194·cNaCl ) AO ,22

max,X

Nitritation

Process ↓

2

M − Mj M = · 100% Mj Mj

(6)

where M is the predicted parameter and Mj is the reference value. 3. Results and discussion

36

35

34

33

32

31

30

29

28

27

26

25

24

23

22

3.1. Parametric sensitivity analysis of the model

j

Table 4 (Continued )

Process rates, Pj , mg of component L−1 d−1

cNH

3

3

(KS,NH ,22 ·(1+cHNO /KI,HNO ,22 )+cNH +(c 2 /KI,NH ,22 )) 3 3 3 2 2 NH

·



·

 

·

·

KI,VFA,22 KI,VFA,22 +cVFA

cDO KS,DO,22 +cDO



· XAO

3

Fig. 2 shows the parametric sensitivity analysis (Eq. (6)) of the model in the aerobic zone. The following physical chemical and

J. Moya et al. / Journal of Biotechnology 160 (2012) 176–188

183

Table 6 Process parameters of the denitrification – anaerobic digestion – organic matter aerobic oxidation – nitrification. Parameter

Value

Unit

Reference

kd,XAA kd,XAc kd,XAO kd,XHAe kd,XNO kd,XProp kd,XVaBu kdes kh,prot KI,NO− ,1–4

0.375 0.025 0.20 0.10 0.17 0.06 0.06 0.17 0.031 1149.4

d−1 d−1 d−1 d−1 d−1 d−1 d−1 d−1 L mg TOC−1 d−1 mg NO2 -N L−1

Batstone et al. (2002) Batstone et al. (2002) Jubany et al. (2008) Tugtas et al. (2006) Jubany et al. (2008) Batstone et al. (2002) Batstone et al. (2002) Batstone et al. (2002) ˜ et al. (2011a) Huilinir Soto et al. (2007)

KI,DO,1–4 KI,NO− ,5–8

0.1 906

Henze et al. (2000) Soto et al. (2007)

2 KI,NO− ,5–8 3

mg DO L−1 mg NO2 -N L−1

34.7

mg NO3 -N L−1

Soto et al. (2007)

KI,DO,5–8 KI,HAc,9 KI,HAc,11,12 KI,HAc,13,14 KI,HAc,15,16 KI,NH3 ,17 KI,NO− ,17

0.1 448 160 288 384 17 0.70

mg DO L−1 mg TOC L−1 mg TOC L−1 mg TOC L−1 mg TOC L−1 mg NH3 -N L−1 mg NO2 -N L−1

Henze et al. (2000) González et al. (2005) Angelidaki et al. (1999) Angelidaki et al. (1999) Angelidaki et al. (1999) Siegrist et al. (2002) Tugtas et al. (2006)

KI,NO− ,17

42

mg NO3 -N L−1

Tugtas et al. (2006)

KI,DO,17 KI,VFA,22 KI,HNO2 ,22 KI,NH3 ,22 KI,VFA,23 KI,HNO2 ,23 KI,NH3 ,23 KS,HVa,1 KS,NO− ,1–4,12,14,16

6.40 274 0.003 540 30 0.260 0.010 6.84 0.47

mg DO L−1 mg TOC L−1 mg HNO2 -N L−1 mg NH3 -N L−1 mg TOC L−1 mg HNO2 -N L−1 mg NH3 -N L−1 mg TOC L−1 mg NO3 -N L−1

Estimated from Celis-García et al. (2004) Delgado et al. (2004) Wiesmann (1994) Wiesmann (1994) Delgado et al. (2004) Wiesmann (1994) Wiesmann (1994) Wiesmann (1994) Soto et al. (2002)

KS,HBu,2 KS,HPr,3 KS,HAc,4 KS,HVa,5 KS,NO− ,5–8,12,14,16

7.50 9.37 9.1 6.84 0.36

mg TOC L−1 mg TOC L−1 mg TOC L−1 mg TOC L−1 mg NO2 -N L−1

Wiesmann (1994) Wiesmann (1994) Wiesmann (1994) Wiesmann (1994) Soto et al. (2002)

KS,HBu,6 KS,HPr,7 KS,HAc,8 KS,AA,10 KS,HVa,11,12 KS,HBu,13,14 KS,HPr,15,16 KS,HAc,17 KS,HVa,18 KS,NH3 ,18–21 KS,DO,18–21 KS,HBu,19 KS,HPr,20 KS,HAc,21 KS,NH3 ,22 KS,DO,22 KS,HNO2 ,23 KS,DO,23 ˇNO−

7.50 9.37 9.10 20 18 24 150 36 72.4 0.05 0.08 61.2 17.3 7.3 0.028 0.3 3.2 × 10−5 1.1 1.578

mg TOC L−1 mg TOC L−1 mg TOC L−1 mg TOC L−1 mg TOC L−1 mg TOC L−1 mg TOC L−1 mg TOC L−1 mg TOC L−1 mg NH3 -N L−1 mg DO L−1 mg TOC L−1 mg TOC L−1 mg TOC L−1 mg NH3 -N L−1 mg DO L−1 mg HNO2 -N L−1 mg DO L−1 –

Wiesmann (1994) Wiesmann (1994) Wiesmann (1994) Batstone et al. (2002) Batstone et al. (2002) Batstone et al. (2002) Batstone et al. (2002) Batstone et al. (2002) Béline et al. (2007) Wiesmann (1994) Wiesmann (1994) Béline et al. (2007) Béline et al. (2007) Béline et al. (2007) Wiesmann (1994) Wiesmann (1994) Wiesmann (1994) Wiesmann (1994) Soto et al. (2007)

ˇNO−

1.005

–

Soto et al. (2007)

max,XHAe ,1–4 max,XHAe ,5–8 max,XAA ,10 max,XVaBu ,11 max,XHAe ,12 max,XVaBu ,13 max,XHAe ,14 max,XPro ,15 max,XHAe ,16 max,XAc ,17 max,XHAe ,18–21 max,XAO ,22 max,XNO ,23

3.0 3.1 9.50 0.8 0.8 0.7 0.7 0.44 0.44 0.35 7.2 0.768 1.08

d−1 d−1 d−1 d−1 d−1 d−1 d−1 d−1 d−1 d−1 d−1 d−1 d−1

Henze et al. (1997) Henze et al. (1997) ˜ et al. (2011a) Huilinir ˜ et al. (2011a) Huilinir ˜ et al. (2011a) Huilinir Batstone et al. (2002) Batstone et al. (2002) Batstone et al. (2002) Batstone et al. (2002) Batstone et al. (2002) Wiesmann (1994) Wiesmann (1994) Wiesmann (1994)

2

2 3

3

2

2 3

J. Moya et al. / Journal of Biotechnology 160 (2012) 176–188

240 200 160 120 80 40 0 160

8

120

6

80

4

40

2

0 9.0

0

DO Concentration, mg DO L-1

Nitrogen Concentration, mgN L-1 Carbon Concentration, mgC L-1

184

8.5

pH

8.0 7.5 7.0 6.5 6.0 0

20

40

60

80

100

120

140

160

Reactor height, cm Fig. 3. Model validation. Simulations for T = 30 ◦ C, cTOC,0 = 529 mg TOC L−1 , cIC,0 = 62 mg IC L−1 , cTAN,0 = 17 mg TAN-N L−1 , cNO− = 0 mg NO2 − -N L−1 , cNO− = 0 mg 2,0

2,0

NO2 -N L−1 , cNO− = 59 mg NO3 -N L−1 and pH = 7.0. M/Mj = percentage variation of 3,0

Mj over reference value. CTAN-N /CTAN-N = percentage variation of cTAN over reference value. CTOC /CTOC = percentage variation of cTOC over reference value.

biochemical parameters had the largest impact on the aerobic step: kL aO2 , max,XAO ,22 , max,XNO ,23 , KS,DO,22 , KS,DO,23 and KI,HNO2 ,23 . The parameters from the aerobic oxidation of organic matter did not show a significant influence on the results. This figure shows that the parameters with the greatest impact on the process are max,XNO ,23 , KI,HNO2 ,23 , and kL aO2 . These results are coincident with ˜ et al. (2010) who modeled a Rotating Disk Biofilm those of Huilinir Reactor (RDBR) using a synthetic substrate only with inorganic carbon and observed that the parameters that most affected nitrification were max,XAO ,22 and kL ; in contrast, variations in the affinity constants KS,DO,22 and KS,DO,23 did not produce effects on the process. The effect of autotrophic bacteria over organic matter draws attention because although autotrophic biomass does not consume TOC it does consume alkalinity (potentially bicarbonate) and generates NO2 − and NO3 − which are then recycled to the entrance of the reactor and are related to the TOC consumption in the denitrification. 3.2. Model calibration. ˜ et al. The model was adjusted only with kL aO2 , as did Huilinir (2011b), because the parametric sensitivity analysis demonstrated that kL a is the parameter that mainly affects the results. The other two parameters affecting the model are: max for nitratation, max,XNO ,23 and the inhibition constant, KI,HNO2 ,23 . However, both have a small range of variation, and thus their effect on the results is smaller than kL a. The kL aO2 value was adjusted modifying  from

2

model cNO− ; () experimental cNO− ; (— • • —) model cNO− ; (– • –) model cDO ; () 2

3

3

experimental pH; (— —) model pH.

Eq. (4) and comparing it with the experimental data of NO3 − , NO2 − , TAN, TOC, IC and pH parameters for the reactor R3 until obtaining a satisfactory approximation with a value of  of 0.98, and kL aO2 = 128 d−1 for R = 2 and Qair,0 = 640 L d−1 . 3.3. Model validation The model was validated with the experimental data from reactors R2 (Fig. 3) and R1 (data not shown). Furthermore, the aerobic step was validated comparing simulating data with the published data of Akunna et al. (1994) (Fig. 4), who used two sequential

N-NO3 Concentration, mgN L-1

Fig. 2. Parametric sensitivity analysis of the model. (A) TAN. (B) TOC. HRT = 2.9 d, cTOC,0 = 578 mg TOC L−1 , cIC,0 = 62 mg IC L−1 , cTAN,0 = 17 mg TAN-N L−1 , cNO− = 0 mg

3,0

NO3 − -N L−1 , pH = 7.0 and R = 2. Protein concentration in the fresh feed at 529 mg TOC L−1 . (䊉) Experimental cTOC ; (—) model cTOC ; () experimental cIC ; (— —) model cIC ; () experimental cTAN ; (• • • • •) model cTAN ; () experimental cNO− ; (— • —)

200 180 160 140 120 100 80 60 40 20 0 0

20

40

60

80

100

Reactor height, cm Fig. 4. Validation of the model’s aerobic section. NO2 profile. Experimental data reported by Akunna et al. (1994). () R = 0 experimental; (—) R = 0 model; () R = 1 experimental; (— —) R = 1 model; (♦) R = 3 experimental; (– –) R = 3 model; () R = 5 experimental; (— —) R = 5 model.

300

200 150 100 50 0 200 150 125 100 75 50 25 0 8,0

C 7,0

Once the model was validated, the effect of the injected DO on the process efficiency was studied. The simulated inlet conditions were those of the reactor R2 because these data showed the best experimental results. Removal efficiencies were determined from Fig. 5. On the one hand, TOC concentration was low for the entire range of experimental DO concentrations, and removal was over 98% for all cases, as shown Fig. 5A. On the other hand, nitrogen removal reached 55 and 62% for partial and complete nitrification, respectively, as shown from Fig. 5B. Complete nitrification results in higher nitrogen removal than partial nitrification because, in this case, the greatest amount of NOx is produced in the aerobic zone and then is recirculated into the anoxic zone where they are denitrified, passing into the gaseous phase N2 . It is noteworthy that even for high oxygen concentrations (cDO,bulk > 5.0 mg DO L−1 ), it is still observed that nitrification is not complete. Two reasons can explain this behavior: first, nitritation and nitratation inhibition by NH3 and HNO2 produced by the pH decrease (see Fig. 5C); and second, the diffusion limitations that hinder the free access of the oxygen inside the biofilm. With our model, this result can be predicted because of the inclusion of the inorganic carbon concentration (cIC ) and pH. This is an important difference because previous models assumed that the pH was constant and usually close to neutrality, resulting in an overestimation of the nitrification and consequently also in the overestimation of the overall nitrogen removal in the tubular reactor.

6,0 0

1

2

3

4

5

6

DO concentration in the liquid bulk at the reactor outlet, mg DO L-1 Fig. 5. Dissolved oxygen concentration effect on the outlet concentration of the tubular filter reactor. Simulations at 30 ◦ C and R = 2. Protein concentration in the fresh feed for the reactor at 529 mg TOC L−1 . (—) cTOC ; (– –) cIC ; (• • • • •) cTAN ; (— • —) cNO− ; (— • • —) cNO− ; (—) cN2 ∗ , N2 concentration in the gas phase, produced during 2

3

denitrification, expressed as the concentration in the liquid phase; (— —) pH. (A) Dissolved carbon species, (B) nitrogen dissolved species, (C) pH.

oxidized due mainly to denitrification in the aerobic zone of the tubular FR and in less amount to the TAN consumption by heterotrophic growth. A simultaneous nitrification–denitrification process is possible because of the diffusion limitations that prevent the necessary oxygen transfer into the biofilm; therefore, denitrification produces nitrogen gas in the aerobic zone of the reactor. The nitrification process can also be expressed using two parameters, namely ˛ and ˇ that show the TAN oxidation and how much ˜ et al., 2010), respectively. TAN is transformed to NO2 − (Huilinir These values are shown in Fig. 6, where ␣ values larger than 65% are obtained if cDO,bulk > 2.0 mg DO L−1 , with a maximum of 75% if cDO,bulk > 5.0 mg DO L−1 ; also ˇ values larger than 80% when 100

TAN degradation α, % NO2 accumulation β, %

Fig. 5B shows that for DO values below there is no NO2 − , first due to larger affinity to DO of XHAe than XAO , and second because the NO2 − formed is denitrified inside of the biofilm forming N2 . Under low availability of DO (0.8 < cDO,bulk < 1.6 mg DO L−1 ), partial nitrification occurs due to larger affinity of the XAO to oxygen (Bernet et al., 2001). No NO2 − and complete nitrification are observed for larger DO concentration values. Profiles of different nitrogen species with respect to partial or total nitrification as a function of DO are similar to those reported in previous studies, even with the presence of organic matter. The sum of NO2 − and NO3 − concentrations do not match with the amount of TAN

B

175

6,5

0.4 mg L−1 ,

A

250

3.4. Effect of the DO concentration on the removal efficiency

3.5. The effect of DO concentration on the nitrification

185

7,5

pH

anaerobic–aerobic FR with recycle for the removal of glucose and ammonia nitrogen. In the latter case, the axial profiles in the aerobic reactor depend on the recycled flow to the anoxic/anaerobic zone. Nevertheless, for the simulation in this work, the inlet conditions in the reactor were assumed to be known for each recycle ratio experimentally used. Fig. 3 shows that the model adequately predicts experimental data for R2 with TIC values of 0.64, 0.15, 0.08, 0.29, 0.19 and 0.003 for NO3 − , NO2 − , TAN, TOC, IC and pH, respectively. These are satisfactory values showing concordance with the criteria of Eq. (5) except for NO3 − . Since these parameter concentrations are lower than unity, the calculated relative error for this parameter is very high, which in turn negatively influences the TIC value. On the other hand, the TIC value for R1 was 0.10, 0.24, 0.18, 0.02, 0.15 and 0.008 for NO3 − , NO2 − , TAN, TOC, IC and pH, respectively. From Fig. 4, it can be observed that the model adequately predicts experimental data for aerobic filter with TIC values of 0.15, 0.24, 0.14 and 0.11 for ratios of 0, 1, 3 and 5, respectively. These results show that the model effectively represents the anaerobic–anoxic–aerobic FR presented in this work for R = 2 and also that the model can predict the behavior of other reactors such as the aerobic FR used by Akunna et al. (1994), demonstrating its robustness and versatility.

Nitrogen concentration, mgN L-1 Carbon concentration, mgC L-1

J. Moya et al. / Journal of Biotechnology 160 (2012) 176–188

80 60 40 20 0 0

1

2

3

4

5

6

DO concentration at the reactor outlet, mg DO L-1 Fig. 6. Effect of the dissolved oxygen concentration in the fluid bulk on ˛ and ˇ at the reactors outlet (˛: TAN percent oxidation, ˇ: NO2 percent production). Simulations at 30 ◦ C and R = 2. Protein concentrations in the fresh feed to the reactor at 529 mg TOC L−1 . (• • • • •) ˛; (— • —) ˇ.

J. Moya et al. / Journal of Biotechnology 160 (2012) 176–188

200

A)

160 120 80 40

0 100

8

B)

80

6

60

4 40

2

20

0

0 8.0

DO concentration, mg DO L-1

Nitrogen concentration, mgN L-1

Carbon concentration, mgC L-1

3.6.1. Axial profiles of dissolved compounds and of biomass throughout the reactor Fig. 7 shows that with air injection, two reactor zones are produced. In the lower anoxic-anaerobic zone the aerobic oxidation of VFA (with depletion of recycled DO), denitrification (with total reduction of NOx ) and anaerobic digestion (organic matter consumption and IC y TAN generation) are produced. In the upper zone the aerobic oxidation of remnant VFA and nitrification occur. Also due to nitrification, pH values decrease up to slightly over 6.25, resulting in a decrease of the NH3 available for nitritation. A significant result is related with the recirculated DO concentration, which does not inhibit denitrification in all the cases. This

C)

pH

7.5 7.0 6.5

Fraction of active biomass

0.6 0.4 0.2

0

20

40

60

80

100

120

140

160

Reactor height, cm Fig. 8. Biomass and dissolved oxygen axial distribution in the tubular filter reactor. Simulations at 30 ◦ C and R = 2. Protein concentrations in the fresh feed to the reactor at 529 mg TOC L−1 . Injected air flow in the aerobic zone of 2400 L d−1 . (– –) fHAe , (— —) fAA , (—) fHAn , (— • —) fAO , (• • • • •) fNO .

phenomenon is due to the quick consumption of DO in the first step at the reactor entrance where aerobic oxidation of volatile fatty acids (VFA) occurs. Here, the inlet DO is consumed, and no nitrifying bacteria are observed. The absence of inhibition can be observed in the axial profiles of Fig. 7B where recirculated NO3 − is completely denitrified in the first CSTR. In addition, no methanogenesis inhibition by DO is observed since the DO concentration is higher than the threshold inhibition DO concentration of denitrification. Fig. 8 presents biomass profiles in the FR calculated as mean values along the biofilm. In the anaerobic zone heterotrophic aerobic biomass (XHAe ), amino-acids degraders biomass (XAA ) and Stagnant liquid layer

Biofilm

80

A) 60 40 20 0 40

8

B) 30

6

20

4

10

2

0

0

DO Concentration, mg DO L-1

The following sections discuss the case for the injection of 2400 L d−1 of air into the aerobic zone, resulting in cDO,bulk = 2.6 mg DO L−1 in the outlet of the FR. As observed in Figs. 5 and 6, TOC and nitrogen removal of 98 and 60% as well as ˛ and ˇ of 68 and 5%, respectively are obtained under these conditions.

0.8

0.0

Carbon concentration ,mgC L-1

3.6. Reactor performance for R = 2 and 2.6 mg DO L−1 .

1.0

Nitrogen concentration, mgN L-1

cDO,bulk < 1.4 mg DO L−1 , for a pH range between 6 and 7 in the outlet reactors flow. These results are similar to those published ˜ et al. (2010) who reported that ˛ is less than 50% for by Huilinir cDO,bulk < 1.5 mg DO L−1 for all pH values between 7 and 9, whereas ˛ is increased for cDO,bulk > 2 mg DO L−1 and for basic pH values. Low ammonia oxidation is shown in Fig. 6 due to acidity during the determination, which should not be the case for substrates at neutral pH. In the latter scenario, nitritation is not inhibited and an increase in XNO is expected until reaching a final value defined by complete ammonia oxidation and total nitrification. A pH control system for nitrifying media (Bernet et al., 2005) can be experimentally installed in order to define requirements.

1.0

C)

Fraction of active biomass

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0.8 0.6 0.4 0.2 0.0 0.0

0.2

0.4

0.6

0.8

1.0

1.2

Dimensionless length of the biofilm 6.0

0

20

40

60

80

100

120

140

160

Reactor height, cm Fig. 7. Axial profiles of dissolved compounds in the tubular filter reactor. Simulations at 30 ◦ C and R = 2. Protein concentrations in the fresh feed to the reactor at 529 mg TOC L−1 . Injected air flow in the aerobic zone of 2400 L d−1 . (—) cTOC ; (– –) cIC ; (• • • • •) cTAN ; (— • —) cNO− ; (— • • —) cNO− ; (– • –) cDO ; (— —) pH. (A) Dissolved 2

3

carbon species, (B) nitrogen and dissolved oxygen species, C) pH.

Fig. 9. Axial distribution in the biofilm at the reactor’s height of 140 cm (Fifth CSTR). Simulations at 30 ◦ C and R = 2. Injected air flow in the aerobic zone of 2400 L d−1 . Protein concentrations in the fresh feed to the reactor at 529 mg TOC L−1 . Nondimensional length is 0 at the support limit and 1 at the interphase limit. (A) Dissolved carbon species, (B) nitrogen and dissolved oxygen species, (C) Biomass. L: Biofilm thickness = 250 ␮m. (A and B) (—) cTOC ; (– –) cIC ; (• • • • •) cTAN ; (— • —) cNO− ; (— • • 2

—) cNO− ; (— • —) cDO . (C) (– –) fHAe , (— —) fAA , (—) fHAn , (— • —) fAO , (• • • • •) fNO . 3

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heterotrophic anaerobic biomass (XHAn ) are present. Here XHAn = XVaBu + XPro + XAc where XVaBu , XPro , XAc are valerate–butyrate, propionate and acetate degraders biomass, respectively. While in the aerobic zone XHAe , ammonio-oxidants biomass (XAO ) and XAA are present. Denitrification is carried out by XHAe mainly in the lower part of the reactor; VFA oxidation and denitrification in zones of low DO availability are present in the upper part of filter. In the aerobic zone, as expected, XAO is larger than nitrite-oxidants biomass (XNO ). 3.6.2. Profiles inside the biofilm for R = 2, Qair,0 = 2400 L d−1 in the fifth CSTR Fig. 9 shows that dissolved nitrogen and carbon species are relatively constant and that the limiting substrate is the DO concentration, which decreases along the biofilm depth. For most cases, this behavior is the same in all the reactors sections and for all simulated conditions. Fig. 9C shows that a change in the biofilm biomass fractions occurs as a result of the decrease of DO concentrations up to values of 1.0 mg DO L−1 ; indeed, one of the main results is the XHAe remain practically constant throughout the biofilm due to the lack of organic matter required for aerobic oxidation of VFA. This fact highlights the simulation result of nitrification and denitrification phenomena in the aerobic zone of the FR. 4. Conclusions The model predicts the behavior and operation performance of the proposed compact anoxic–anaerobic–aerobic FR used to treat fishery effluents at a recycle ratio (R) of 2 as well as operation performance values reported for denitrification, anaerobic digestion, aerobic carbon oxidation and nitrification processes in a compact FR, including pH and inorganic carbon as a states variables. In the compact FR, nitrogen removal increases until reaching 62% when the DO concentration increases. High amounts of DO do not significantly affect nitrogen removal as the heterotrophic biomass in the anoxic zone consumes all available DO in the aerobic oxidation of the VFA, avoiding denitrification and methanogenesis inhibition. There is no NO2 − in the aerobic zone for cDO,bulk < 0.4 mg DO L−1 , first due to larger affinity to DO of XHAe than XAO , and second because the NO2 − formed is denitrified inside of the biofilm forming N2 . Also partial nitrification is produced for cDO,bulk < 1.6 mg DO L−1 due to the larger DO affinity of XAO in comparison with XNO ; meanwhile complete nitrification takes place for larger cDO,bulk . In this FR zone, the cDO decreases inside the biofilm for depths up to values of 1.0 mg DO L−1 , allowing simultaneous nitrification and denitrification processes. Acknowledgement This work was possible through FONDECYT (Chile) Grant No. 1080198. References APHA, AWWA, WPCF, 1992. Standard Methods for the Examination of Water and Wastewater, 18th ed., Washington, DC. Akunna, J., Bizeau, C., Moletta, R., Bernet, N., Héduit, A., 1994. Combined organiccarbon and complete nitrogen removal using anaerobic and aerobic upflow filters. Water Sci. Technol. 30, 297–306. An, Y.Y., Yang, F.L., Wong, F.S., Chua, H.C., 2008. Simultaneous bioenergy (CH4 ) production and nitrogen removal in a combined upflow anaerobic sludge blanket and aerobic membrane bioreactor. Energy Fuels 22, 103–107. Angelidaki, I., Ellegaard, L., Ahring, B.K., 1999. A comprehensive model of anaerobic bioconversion of complex substrates to biogas. Biotechnol. Bioeng. 63, 363–372. Antileo, C., Roeckel, M., Lindemann, J., Wiesmann, U., 2007. Operating parameters for high nitrite accumulation during nitrification in a rotating biological nitrifying contactor. Water Environ. Res. 79, 1006–1014. Aspé, E., Martí, M.C., Jara, A., Roeckel, M., 2001. Ammonia inhibition in the anaerobic treatment of fishery effluents. Water Environ. Res. 73, 154–164.

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