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Modelling simultaneous anaerobic methane andammonium removal in a granular sludge reactor

M-K.H Winkler a,b,*, K.F. Ettwig c, T.P.W. Vannecke a, K. Stultiens c,A. Bogdan a, B. Kartal c, E.I.P. Volcke a

a Department of Biosystems Engineering, Ghent University, Coupure Links 653, 9000 Gent, Belgiumb Department of Civil and Environmental Engineering, University of Washington, Seattle, WA 98195-2700, USAc Microbiology, Radboud University Nijmegen, Heyendaalseweg 135, 6525 AJ, Nijmegen, The Netherlands

a r t i c l e i n f o

Article history:

Received 27 August 2014

Received in revised form

27 January 2015

Accepted 28 January 2015

Available online 7 February 2015

Keywords:

Anammox

Anaerobic methane oxidation

Granular sludge

Modelling

Simulation

* Corresponding author. Department of BiosE-mail address: Eveline.Volcke@UGent.be

http://dx.doi.org/10.1016/j.watres.2015.01.0390043-1354/© 2015 Elsevier Ltd. All rights rese

a b s t r a c t

Anaerobic nitrogen removal technologies offer advantages in terms of energy and cost

savings over conventional nitrificationedenitrification systems. A mathematical model

was constructed to evaluate the influence of process operation on the coexistence of nitrite

dependent anaerobic methane oxidizing bacteria (n-damo) and anaerobic ammonium

oxidizing bacteria (anammox) in a single granule. The nitrite and methane affinity con-

stants of n-damo bacteria were measured experimentally. The biomass yield of n-damo

bacteria was derived from experimental data and a thermodynamic state analysis.

Through simulations, it was found that the possible survival of n-damo besides anammox

bacteria was sensitive to the nitrite/ammonium influent ratio. If ammonium was supplied

in excess, n-damo bacteria were outcompeted. At low biomass concentration, n-damo

bacteria lost the competition against anammox bacteria. When the biomass loading closely

matched the biomass concentration needed for full nutrient removal, strong substrate

competition occurred resulting in oscillating removal rates. The simulation results further

reveal that smaller granules enabled higher simultaneous ammonium and methane

removal efficiencies. The implementation of simultaneous anaerobic methane and

ammonium removal will decrease greenhouse gas emissions, but an economic analysis

showed that adding anaerobic methane removal to a partial nitritation/anammox process

may increase the aeration costs with over 20%. Finally, some considerations were given

regarding the practical implementation of the process.

© 2015 Elsevier Ltd. All rights reserved.

1. Introduction

Methane is the end product of anaerobic digestion and it can

be used for energy generation (van Lier et al., 2008). However,

some of the methane remains dissolved in the effluent of

ystems Engineering, Ghen(E.I.P. Volcke).

rved.

anaerobic digesters and potentially escapes to the atmosphere

during further downstream processing (Daelman et al., 2012).

Given the high global warming potential of methane, about 34

CO2 equivalents over a 100-year time scale, even small

quantities of methane emissions can largely affect the carbon

t University, Coupure Links 653, 9000 Gent, Belgium.

wat e r r e s e a r c h 7 3 ( 2 0 1 5 ) 3 2 3e3 3 1324

footprint of a wastewater treatment plant (wwtp) (IPCC et al.,

2013). Recently, a bacterial species capable of nitrite-

dependent anaerobic methane oxidation (n-damo), ‘Candida-

tus Methylomirabilis oxyfera’ was discovered (Raghoebarsing

et al., 2006; Ettwig et al., 2010). These microorganisms

oxidizemethane to carbon dioxide coupled to the reduction of

nitrite to dinitrogen gas (Ettwig et al., 2010).

Anaerobic nitrogen removal technologies offer clear ad-

vantages in terms of energy and cost savings over conven-

tional nitrificationedenitrification systems. The n-damo

process has so far not been applied in engineered systems, but

microorganisms related to Methylomirabilis oxyfera were

detected in nitrogen removal processes such as those treating

anaerobic digester effluents (Luesken et al., 2011a; Ho et al.,

2013), which contain high ammonium concentration and

dissolved methane (Bandara et al., 2011). Ammonium can be

conveniently removed from such reject waters with a com-

bined partial nitritation e anammox process, as demon-

strated at full-scale (van der Star et al., 2007). During partial

nitritation, typically half of the ammonium is converted to

nitrite, while nitrate formation is prevented. This is followed

by anaerobic oxidation of ammonium (anammox) to dini-

trogen gaswith nitrite as the electron acceptor. As rejectwater

contains high levels of ammonium in proportion to methane,

it is potentially interesting to combine anaerobic ammonium

and methane oxidizing bacteria to remove nitrogen and

methane simultaneously (Luesken et al., 2011a).

Lab-scale studies have demonstrated that anammox and

n-damo bacteria can coexist in a bioreactor and perform

simultaneous removal of methane and ammonium (Luesken

et al., 2011b; Zhu et al., 2011). Since both bacteria have a

doubling time ofmore than ten days (Strous et al., 1998; Ettwig

et al., 2009), proper biomass retention is needed to handle

large volumetric flows and loading capacities such as

encountered in a wwtp. Granular sludge consists of biofilm

aggregates in the form of dense, fast-settling granules,

resulting in compact systems, which allows a high loading

rate due to a large biofilm surface area in the reactor (Beun

et al., 2002). Therefore, granules offer a good option for

simultaneous growth of both n-damo and anammox bacteria.

One of the experiments with simultaneous methane and

ammonium removal mentioned above (Zhu et al., 2011) was

conducted with an inoculum from a granular sludge system,

indicating that n-damo grew on granule surfaces already. In

these systems, the sludge retention time is uncoupled from

the hydraulic retention time. If n-damo would grow in flocs

only, they would be washed out due to their slow growth rate.

Due to the slow growth rates of both bacteria, experimental

work aiming at process optimization can be very time

consuming. Mathematical models are useful tools to study

new unknown processes as it was demonstrated previously

(Picioreanu et al., 1997; Hao et al., 2002; Volcke and van

Loosdrecht, 2010). For the construction of a reliable model,

realistic parameter values are essential. Therefore, in this

study, the nitrite and methane affinity constant of n-damo

bacteria were experimentally determined, and the yield co-

efficient of ndamo was calculated based on thermodynamic

state calculations combined with experimental data. A

mathematical model was constructed and applied in a simu-

lation study to evaluate the influence of process operation on

the coexistence of anaerobic methane and ammonium

oxidizing bacteria in a single granule.

2. Material and methods

2.1. Thermodynamic state analysis and experimentaldetermination of the biomass yield of n-damo bacteria

Since no direct measurements are available for the biomass

yield of n-damo it was calculated based on experimental batch

tests with M. oxyfera (Raghoebarsing et al., 2006; Ettwig et al.,

2009) and thermodynamic state analysis. Thermodynamic

calculations for the stoichiometric reactions of n-damo bac-

teria were performed according to the method of

(Kleerebezem and Van Loosdrecht, 2010). First the mass and

electron balances and reaction stoichiometry are set up, fol-

lowed by a vector-based calculation method to derive the re-

action stoichiometry of the metabolic redox reactions. The

calculation combines the anabolic metabolism, which is

defined per C-mole of formed biomass with the catabolic re-

action, which is calculated by the Gibbs energy needed to

produce one C-mole of biomass, to obtain the overall meta-

bolic reaction. All calculations are available as Supplementary

material S1.

2.2. Biological conversions e experimentaldetermination of methane and nitrite affinity constants

A mathematical model was set up and the stoichiometric

matrix, kinetic expressions are detailed in Supplementary

material (S2, S3) and parameter values are listed in

Supplementary material S4. It is important to note that, while

ammonium (SNH4) is the nitrogen source for biomass growth of

anammox bacteria (Strous et al., 1998), n-damo bacteria, are

bound to use nitrite (SNO2) e in absence of other nitrogen

sources e for incorporation in biomass (Ettwig et al., 2008,

2009; Rasigraf et al., 2012). In principle n-damo bacteria can

also grow on ammonium but at high ammonium removal

efficiencies and hence low ammonium concentrations they

are forced to utilize nitrite for growth. Defining the n-damo

yield coefficient as the biomass production on methane sub-

strate, the following n-damo reaction stoichiometry is ob-

tained by closing the COD and N balances:

� 1Yn�damo

CH4 þ�� 11:71

�1

Yn�damo

�þ iNXB

�

NO2�/

�1

1:711

Yn�damo� 1

�� 2iNXB

�N2 þ Xn�damo

(1)

Note that this reaction involves a net nitrite consumption,

despite of the positive value of iNXB, which is resolved from the

definition of the yield coefficient on methane. The use of ni-

trite also for assimilation into biomass leads to a lower overall

dinitrogen production than the anabolic n-damo reaction

alone. The corresponding reaction rate is given by Eq. (2),

which describes substrate dependency of growth of n-damo

bacteria by Monod kinetics and also considers nitrite

inhibition.

wat e r r e s e a r c h 7 3 ( 2 0 1 5 ) 3 2 3e3 3 1 325

r1¼rNdamoG;NO2 ¼mDdamo

max

SCH4

Ndamo

SNO2

Ndamo

KNdamoi;NO2

NdamoXNdamo

KCH4 þSCH4 KNO2 þSNO2 Ki;NO2 þSNO2

(2)

The inhibition constant for n-damo ðKNdamoi;NO2 Þ was set to

40 g NO2��Ngm�3 (He et al., 2013) and for anammox bac-

teria ðKANi;NO2Þ to 400 g NO2

��Nm�3 (Lotti et al., 2012) and

these inhibition values were considered equal to 50% ac-

tivity inhibition (IC50) for nitrite (Cheng and Prusoff, 1973).

The ammonium and nitrite affinity constants for anammox

bacteria were based on literature values (Strous et al., 1999).

N-damo bacteria were only recently discovered and not

all parameters relevant for this microorganism have been

experimentally determined so far. For this reason, several

parameters were estimated based on available experi-

mental data. Bacterial growth can be described with a first

order system with a time constant 1/m, which is related to

the observed doubling time by m ¼ ln2/tdoubling time. For n-

damo bacteria, a doubling time as long as 14 days has been

reported (Ettwig et al., 2009). As this value was observed

during near-optimal growth conditions (no substrate limi-

tation, no nitrite inhibition), the corresponding growth rate

m can be considered as the maximum growth rate and is

thus calculated as mmax ¼ ln2/14 ¼ 0.0495 d�1. The methane

affinity constant ðKNdamoCH4 Þ of n-damo bacteria was estimated

as 0.19 g COD m�3 based on reanalysis of published data

(Ettwig et al., 2008; Rasigraf et al., 2012) and unpublished

results. The nitrite affinity constant ðKNdamoNO2 Þ was estimated

from nitrite depletion in an enrichment culture under

methane saturation (duplicate experiments) similar to the

setup of previous research (Ettwig et al., 2008) and

was found to be 0.6 g NO2� �N m�3 (Supplementary mat

erial S5).

2.3. Model implementation: reactor configuration andinfluent characteristics

A one-dimensional biofilm model was set up to describe the

growth and decay of anaerobic methane oxidizers (n-damo)

and anaerobic ammonium oxidizers (anammox) in a granular

sludge reactor. The Aquasim model can be downloaded as

Supplementary material S6. Spherical biomass particles

(granules) were modelled to grow from an initial radius of

0.01 mm to a granule radius of 0.75 mm such that the reactor

eventually contained 100 m3 of biomass, comprising both

active biomass as well as inerts. The reactor volumewas set to

400 m3. Nitrite was assumed to be supplied by partial nitrita-

tion in a separate compartment, which was not further

addressed in this study. The influent was considered to be fed

at a flow rate of 2500 m3 d�1 at a total nitrogen concentration

of 1000 g Nm�3 and ~100 g CODm�3 ofmethane (1.5mM, close

to saturation), respectively. The values are based on mea-

surements from reject water (Hartley and Lant, 2006; Bandara

et al., 2011) (Supplementary material S7). A schematic view of

the biofilm reaction model describing the combined methane

and ammonium removal process in a granule is depicted in

Fig. 1. The model was implemented in the Aquasim software

(Reichert, 1994). The model was applied in a simulation study

to determine the influence of the influent nitrite: total nitro-

gen ratio, the substrate loading rate, and the granule size on

substrate removal and granule composition. This was

accomplished by varying one parameter at a time, while

keeping all others constant.

2.4. Stoichiometric calculations and economic feasibility

An optimal supply of nitrite, ammonium and methane for n-

damo and anammox was calculated based on the stoichio-

metric coefficients (Supplementary material S4) and previ-

ously set values for the yield coefficients. The stoichiometric

nitrite concentration needed for the n-damo bacteria for the

given methane concentration (100 g COD m�3) was then

calculated as SNO2=SCH4 ¼ 1=1:71ð1=YNdamo � 1Þþ iNxB=1=YNdamo.

The nitrogen concentration (1000 g Nm�3) was assumed to be

a mixture of nitrite and ammonium in a stoichiometric

optimal ratio for anammox bacteria being SNO2=SNH4 ¼ 1=YAnþ1=1:14=1=YAn þ iNXB. This results in an overall stoichiometric-

optimal influent composition in terms of nitrite (555 g

NO2� �Nm�3), ammonium (445 g NH4

þ �Nm�3), and

methane (100 g CODm�3), allowing for completemethane and

ammonium removal. To evaluate the economic feasibility of

simultaneous methane and ammonium removal in respect to

the partial nitritation/anammoxprocess a value of 0.5V per kg

nitrogen oxidized (to nitrite) was used to estimate the aeration

costs for both processes (van Dongen et al., 2001).

3. Results and discussion

3.1. Yield determination of n-damo bacteria bymeasurements and thermodynamic calculations

N-damo bacteria grow autotrophically, and thus fix carbon

dioxide by the Calvin-Benson-Bassham cycle (Rasigraf et al.,

2014). In principle, they are able to assimilate ammonium as

nitrogen source, but were grown without ammonium in the

medium, and are hence bound to assimilate nitrite (Ettwig

et al., 2008, 2009). In the presence of ammonium, as in the

simulated case, anammox bacteria are co-enriched, and

consume all ammonium supplied, so that most likely no

ammonium is left for assimilation by M. oxyfera (Luesken

et al., 2011b). Therefore, unlike to the study of Chen et al.

(2014), nitrite and not ammonium was assumed to be

assimilated into biomass. Assuming an optimal energy

usage of methane and nitrite yielded a stoichiometric

equation of:

1NO2� þ 0:434CH4 þ 1Hþ/0:49N2 þ 1:28H2Oþ 0:335CO2

þ 0:099C1H1:8O0:5N0:2 (A)

However, the stoichiometric nitrite: methane ratio of 2.3

(1/0.43) did not fit the measured ratio from experimental

data exactly. Kinetic measurements from previous research

reported a nitrite over methane ratio of 1/0.415 ¼ 2.4

(Raghoebarsing et al., 2006; Ettwig et al., 2009). The stoi-

chiometric Equation (A) was hence fitted by changing the

biomass yield such that the reported nitrite over methane

ratio of 2.4 was met, resulting in the following equation:

Fig. 1 e A) schematic view as well as B) simulation result of a distribution of (A) anammox and (-) ndamo bacteria as well

as (C) inerts as a function of granular diameter. Simulations were conducted at stoichiometric-optimal nitrite (555 mg

NO2� �N=m3) ammonium (445 mg NH4

� �Nm�3) and methane (100 g COD m¡3) concentrations for complete methane and

ammonium removal.

wat e r r e s e a r c h 7 3 ( 2 0 1 5 ) 3 2 3e3 3 1326

1NO2� þ 0:415CH4 þ 1Hþ/0:493N2 þ 1:27H2Oþ 0:348CO2

þ 0:066C1H1:8O0:5N0:2 (B)

A sensitivity analysis was conducted in which the optimal

stoichiometric media composition was used. The yield of

Anammox bacteria was kept constant (0.17 g COD g�1 N)

whereas the yield of n-damo bacteria was varied beyond its

default value of 0.16 g COD g�1 N (corresponding with

0.066 mol biomass per mol�1 nitrite) to determine its effect on

the competition. N-damo bacteria could compete for substrate

as long as their yield coefficient was higher than

0.13 g COD g�1 N; at smaller values n-damo bacteria were

washed out (Supplementary material S9).

3.2. Granule structure and influence of nitrite: totalnitrogen ratios

The model in this study showed that anammox bacteria

mostly grew on outer layers whereas n-damo bacteria mainly

grew underneath the layer of anammox bacteria, which can

be explained by slower growth rates of n-damo bacteria with

respect to anammox bacteria. The most inner part of the

granules consisted of inert compounds (Fig. 1).

In themodel, different NO2� �N: total N ratios (total N was

kept at 1000 g N m�3) were tested at a fixed methane con-

centration (100 g COD m�3) to study at which influent

composition both bacteria could coexist. At lower ratios

(ammonium in excess), n-damo bacteria were outcompeted

by anammox bacteria. However, at ratios close to the stoi-

chiometric equilibrium, needed to completely remove

methane and ammonium, n-damo bacteria remained in the

system. At high ratios (nitrite in excess), anammox bacteria

got limited by ammonium, leading to an accumulation of ni-

trite while methane was completely removed, until an inhib-

itory concentration of nitrite was reached (Fig. 2). N-damo

bacteria can accordingly only grow in a narrow range close to

the stoichiometric optimum influent composition.

3.3. Influence of substrate loading rate

Previous simulation studies have evaluated the effect of

inflow variations on a partial nitrificationeanammox biofilm

process even though at that time it was not known whether

AOB and anammox bacteria could grow in a biofilm (Hao et al.,

2002). A similar approach was chosen here to assess the effect

of the total biomass volume on the bulk liquid concentrations

(Fig. 3A) as well as on the biomass fractions of n-damo and

anammox bacteria (Fig. 3B). The competition of both bacteria

was evaluated for influent containing the stoichiometric ra-

tios needed for complete ammoniumandmethane removal at

a fixed biomass volume retained in the system. In a waste-

water treatment reactor (such as in an aerobic granular sludge

reactor), the sludge retention time is controlled by selectively

removing sludge from the system. Considering a fixed

biomass volume is therefore a reasonable assumption. Since

Fig. 2 e (A) Influence of influent nitrite fraction at fixed methane concentration (100 g COD m¡3) on reactor performance in

terms of (C) ammonium, (-) methane, (:) nitrate, (A) nitrite, and (£) nitrogen gas as well as (B) biomass fraction of (◊)

inerts, (◌) anammox, and (D) ndamo bacteria at different influent nitrite: total nitrogen ratios [%] and at a fixed influent

methane concentration of 100 g COD m¡3. The influent total nitrogen concentration was kept at 1000 g N m¡3. At the

intersection (denoted by grey line) the media contained the ideal stoichiometric ratio for simultaneous removal of

ammonium and methane (A) enabling coexistence of anammox and ndamo (B).

wat e r r e s e a r c h 7 3 ( 2 0 1 5 ) 3 2 3e3 3 1 327

the substrate loading was kept constant in the model, the

biomass specific substrate loading was higher at lower sludge

volumes.

For a low amount of biomass, the biomass specific sub-

strate loading of all substrates was too high for a complete

Fig. 3 e Influence of biomass volume (A) on reactor performanc

specific removal capacity, (B) nitrogen removal efficiency, and (▵

of (:) anammox bacteria, (C) ndamo bacteria, and (-) inerts at

volume of the reactor was considered to be 400 m3. In operating

present. In operating zone II methane was removed (A) and ndam

and 100 m3 oscillations occurred (grey area; (A, B, C)). Graph C w

is NH4þ (black -), NO2

� (black –), CH4 (grey–) effluent concentrati

substrate removal. This was leading to high ammonium and

(inhibitory) nitrite concentrations and consequently to low

removal efficiencies (Fig. 3A and B operating zone I). When the

biomass volume was increased stepwise from 10 to 50 m3,

anammox bacteria consumed nitrite to levels at which nitrite

e in terms of (▫) biomass specific loading rate, (þ) biomass

) methane removal efficiency as well as (B) biomass profiles

different biomass volume fractions in the reactor. The total

zone I (A) no methane was removed and (B) no ndamowere

o grew in the system (B). For biomass volumes between 50

as obtained for a biomass volume of 80 m3. The denotation

ons (gN m3 and g COD m3).

wat e r r e s e a r c h 7 3 ( 2 0 1 5 ) 3 2 3e3 3 1328

inhibition was lower, leading to a stepwise increase in their

biomass activity (and growth rate). In this operating zone

(10e50 m3) ammonium was in excess and despite stoichio-

metric ratios of substrates in the influent (555 g NO2 m�3;

445 g NH4 m�3; 100 g COD m�3 (CH4)) n-damo bacteria lost the

competition for nitrite to anammox bacteria, which domi-

nated the system (Fig. 3B). At these conditions did the low

methane affinity constant of n-damo bacteria not give any

competitive advantage and was overruled by the high nitrite

affinity of anammox bacteria compared to n-damo bacteria

(Figs. 2A and 3 operating zone I).

Only when the biomass volume was set high enough

(>50 m3), corresponding to a sufficiently low biomass loading

rate (<1gN/gVSS/d) such that anammox could consume

almost all ammonium, n-damo bacteria were able to grow

(Luesken et al., 2011b). Under these conditions the biomass

specific removal capacity got close to what is needed to

completely remove all nitrogen and methane. However, only

from a biomass volume of 100 m3 and higher, the biomass

specific removal rate coincidedwith the nitrogen loading rate,

corresponding with complete and stable methane and

ammonium removal. The results showed that even if the

influent contained the ideal stoichiometric ratios for complete

ammonium and methane removal, the biomass concentra-

tion needed to be sufficiently high (or the biomass specific

substrate loading sufficiently low) to allow simultaneous

methane and ammonium removal. At lower biomass con-

centrations (too high biomass loading rate), n-damo bacteria

were outcompeted by anammox bacteria. Note that the same

results in terms of the biomass loading rate were obtained

when varying the influent flow rate instead of the biomass

concentration.

A sensitivity analysis was conducted under conditions

with excess ammonium to evaluate the effect of a range of

realistic nitrite affinity constants of n-damo bacteria on their

competition with anammox bacteria. This test was conducted

to evaluate to which extent the model outcome relied on a

very accurate experimental determination of the nitrite af-

finity constant (Supplementary material S4, S8). The results

confirmed that under the entire range of currently known

realistic nitrite affinity constants, n-damo bacteria would

suffer washout at high ammonium concentrations, as previ-

ously observed (Luesken et al., 2011b). Hence, n-damo bacteria

can only survive if nitrite is in excess of ammonium, so that

additional nitrite cannot be utilized by anammox bacteria.

Under high ammonium concentrations, n-damo bacteria

cannot be favoured through elevatedmethane concentrations

because the competition depends on nitrite and not on

methane.

3.4. Oscillatory reactor behaviour

During the transition period fromnear-complete (50m3) to full

substrate removal (80 m3), the removal efficiency was not

stable and resulted in oscillating substrate removal effi-

ciencies, similar to a competition behaviour known from

general ecology (Berryman, 1992) (Fig. 3A, B and C grey area).

The oscillating pattern (Fig. 3C, Supplementary material S10)

can be explained by the affinity constants of both bacteria. In

microbiology the competition of two species for one substrate

is driven by their substrate affinity (Andrews and Harris, 1986)

and their doubling time. A good example is the competition

between two common genera of nitrite oxidizing bacteria:

Nitrospira (K-strategist winning at low substrate concentra-

tions) and Nitrobacter (R-strategist winning at high substrate

concentration). Nitrospira possess a low maximum specific

growth rate (in this case like n-damo), but is well adapted to

low nitrite concentrations (unlike n-damo), whereas Nitro-

bacter is known to be a relatively fast-growing NOB (like

anammox) with low affinities to nitrite (unlike anammox)

(Schramm et al., 1999; Kim and Kim, 2006). According to the r-

K selection theory, n-damo bacteria cannot compete with

anammox for nitrite in the presence of excess ammoniumdue

to their lower affinity constant and growth rate. This means

that, n-damo and anammox bacteria can only grow together if

enough nitrite remains for methane oxidation. At a biomass

volume of 50 m3 the amount of anammox bacteria was suffi-

cient to oxidize ammonium almost completely (Fig. 3 oper-

ating zone I). At biomass volumes from 50 to 80 m3 (Fig. 3 grey

area), the biomass specific loading (loading rate per VSS)

closely (but not fully) matched the biomass specific removal

capacity (removal rate per VSS). Since the reactorwas fed in all

scenarios with a medium fulfilling the stoichiometric influent

conditions needed for complete methane and ammonium

removal, low effluent ammonium concentration and lower

maximum specific growth rates of anammox bacteria corre-

sponded to elevated methane and incomplete nitrite effluent

concentrations. Consequently, n-damo bacteria had a high

maximum specific growth rate and a high nitrite reducing

activity. This in turn resulted in the collapse of the growth of

anammox bacteria and a peak in ammonium and nitrite

effluent concentrations. At higher ammonium and nitrite

concentrations anammox bacteria started to grow again,

leading to decreasing nitrite concentrations, an increase in

growth rate of anammox bacteria, a decrease in methane

removal and a lower n-damo growth rate thereby starting a

new oscillation cycle (Fig. 3C). It should be stressed that n-

damo bacteria did not actively compete for nitrite. If in the

presented scenario (Fig. 3C) the influent nitrite concentrations

would be lowered such that anammox bacteria could

consume all nitrite with ammonium, n-damo bacteria would

be washed out.

For biomass volumes of 80 m3, oscillations in bulk liquid

concentrations stopped and the biomass specific removal

capacity fully matched the biomass loading rate leading to a

complete, stable and simultaneous methane and ammonium

removal and an equal distribution between anammox and n-

damo bacteria (Fig. 3B). At high biomass volumes, the system

operated below the maximal substrate oxidizing capacity as

indicated by the lower biomass specific removal capacity and

hence activity, respectively (Fig. 3 operating zone II). However,

in this operation zone the removal capacity turned out to be

robust. A system designed for simultaneous methane and

ammonium removal should hence not be operated close to its

maximum biomass specific substrate removal capacity (Fig. 3

intersection operating zone I and II). These insights into the

possible oscillatory process operation are of vital importance

for a successful implementation of stable and reliable simul-

taneous ammonium and methane removal in wastewater

treatment systems.

wat e r r e s e a r c h 7 3 ( 2 0 1 5 ) 3 2 3e3 3 1 329

3.5. Influence of granule size on the reactor performance

An influence of the granule size on bacterial fractions occu-

pying the granule can be expected from the increasing sub-

strate surface loading for increasing granule diameter (lower

surface: volume ratio) and diffusion limitations of different

substrates (Winkler et al., 2011; Volcke and van Loosdrecht,

2012). For relatively small granules (<0.3 mm), the granule

consisted entirely out of active biomass and therefore there

was no accumulation of inerts. Under these conditions, the

nitrogen and methane removal efficiencies remained quite

constant with increasing granule size, similar to other simu-

lation studies (Ni et al., 2009), while the fraction of n-damo

bacteria increased at the expense of anammox bacteria. The

reason for this is that n-damo bacteria were located more in

the inner part of the granule and thus were faced with lower

substrate concentrations for increasing granule size, leading

to a decreased activity and thus implying the need for more

biomass to perform the same conversion.

As the granule size increases, substrate diffusion into the

centre of the granules becomes more difficult, which resulted

in the accumulation of inert material (Fig. 4B) thus implying

less space for active biomass growth at the given constant

total biomass volume. As a result, the anammox conversion

efficiency decreasedwith increasing granule size (Fig. 4A). The

methane removal efficiency also decreased for larger granules

andwasmore pronounced than the decrease in the anammox

conversion (Fig. 4A). Anammox bacteria grow faster and have

a higher affinity for nitrite than n-damo bacteria, which con-

stitutes an advantage for the former in the competition for

space on the surface of the granule. This effect is more severe

on larger granules which have a smaller specific surface.

Overall, it is recommended to keep the granule size small

enough to maintain high ammonium and methane removal

efficiencies, but not too small to still ensure good settling

properties and a high biomass retention capacity. A proper

biomass wasting should hence be applied to select for a

certain granule size.

3.6. Cost estimation and implications for practice

Aeration costs account for approximately half of the costs

created during wastewater treatment. Aeration is therefore a

sensitive parameter for the economic feasibility of new

Fig. 4 e Influence of granule size on steady state (A) reactor per

ammonium removal efficiency (:) and nitrate effluent concentr

anammox, (◌) ndamo, and (D) inerts. Simulations were conduct

(100 g COD m¡3) and nitrogen components (1000 g total N m¡3,

treatment processes. Anammox-based treatment systems are

economically interesting because ammonium only needs to be

partly oxidized to nitrite (not to nitrate) compared with con-

ventional nitrificationedenitrification systems,hence reducing

aeration costs by approximately two-fold (van Dongen et al.,

2001). The theoretical cost estimation for the simultaneous

removal of ammonium (1000 g N m�3) and methane

(100 g CODm�3) from reject water (scenario B) showed that the

costs are increased by 23% compared to a partial nitritation

anammox two-stage treatment system (scenario A) (Table 1).

The reason is that more ammonium needs to be oxidized to

nitrite to remove both ammonium andmethane present in the

reject water than for anammox-based ammonium removal

only. Currently there are no penalties for high greenhouse gas

emissions from wastewater treatment, but it is highly likely

that future regulations for threshold values of emitted green-

house gases fromwastewater may justify the application ofM.

oxyfera for the treatment of reject water or other streams con-

taining high ammonium andmethane concentrations.

A challenge in the application of n-damo bacteria (scenario

B) is that methane needs to be kept in the liquid phase. A

preceding partial nitritation step to yield the desired nitrite:

ammonium mixture would strip all methane from the liquid

phase. An alternative option could be to split the reject water

in two streams: one for the oxidation of all ammonium to

nitrite and another stream containing methane and ammo-

nium. However, in this option, half of the methane would still

be stripped in the aerated tank. In addition, the required

complete oxidation of ammonium to nitrite will entail addi-

tional costs, for caustic addition, in the typical case that the

wastewater does not contain enough alkalinity to buffer the

acidifying nitrification.

A more plausible solution could be to implement methane

and ammonium removal in a single reactor system, in which

the oxygen level is controlled to ensure simultaneous oxida-

tion of part of the ammonium on the one hand and anaerobic

methane and ammonium oxidation on the other hand.

Methane stripping might be remedied to a certain extent by

recirculation of the aeration gas, which might allow re-

dissolution of stripped methane into the liquid phase. The

feasibility of such an operation needs further investigation,

e.g. with respect to the competition of n-damo with aerobic

methane oxidizing bacteria. Another challenge in practicewill

be the control of the produced nitrite: ammonium ratios to

formance in terms of (C) methane removal and (A)

ations as well as (B) biomass concentrations of (þ)

ed at stoichiometric influent concentrations of methane

namely 555 g NO2� �Nm�3 and 445 g NH4

þ �Nm�3).

Table 1 e Cost estimation of an A: partial nitritatione anammox based and B; partial nitritatione anammox based processcoupled to methane oxidation assuming a COD concentration of 100 COD m¡3. Both scenarios consider a nitrogenconcentration of 1000 g N m¡3. A ratio of 0.5 Euro per kg N (van Dongen et al., 2001) oxidized was used to calculate thecosts per m3.

Parameter Unit Scenario A Partialnitritation e anammox

Scenario B Partialnitritation e anammox þ ndamo

Ammonium oxidized g NH4þ �Nm�3 430 555

Aeration costs V m�3 0.21 0.28

Additional costs of scenario B % 23%

wat e r r e s e a r c h 7 3 ( 2 0 1 5 ) 3 2 3e3 3 1330

stoichiometric-optimum levels for both anammox and n-

damo bacteria, despite varying methane concentrations. Too

low nitrite concentrations will disfavour n-damo bacteria and

too high nitrite concentrations will lead to nitrite in the

effluent as well as to inhibition effects, which are both highly

undesirable. This demonstrates the need for adequate online

sensors and control strategies. N-damo bacteria may also be

applied without anammox bacteria, such as for the treatment

of wastewater which is lacking organic carbon and for which

the expensive addition of organic electron donor (presently

mostlymethanol) would be required (Peng et al., 2007). In such

a case, methane originating from anaerobic digestion could be

used for denitrification purposes in a dedicated reactor for

anaerobic methane oxidizing bacteria only. However, a com-

plete and more elaborated economic feasibility study is

needed to evaluate the profit of such a solution.

4. Conclusions

- The nitrite and methane affinity constant of anaerobic

methane oxidizing (dnamo) bacteria was determined

experimentally and the yield coefficient of n-damo bacteria

was calculated from experimental data combined with

thermodynamic state analysis.

- Simultaneous anaerobic methane and ammonium

removal in a granular sludge reactor is feasible through the

coexistence of anammox and n-damo bacteria, provided

that nitrite, ammonium and methane are supplied in

optimal stoichiometric amounts, and that the biomass

loading rate is sufficiently low (i.e., high biomass concen-

tration in reactor or low influent flow rate).

- A system designed for simultaneous methane and

ammonium removal should not be operated close to its

maximumbiomass specific substrate removal capacity due

to the risks of oscillating removal efficiency.

- Smaller granules resulted in higher ammonium and

methane removal efficiencies due to lower diffusion

limitations.

- Theadditional removal ofmethanebesides ammoniummay

increase the aeration requirements by over 20% compared to

partial nitritation e anammox treatment systems.

Acknowledgements

The authors thank R. Kleerebezem for help with the thermo-

dynamic calculations and Huub op den Camp and MCM van

Loosdrecht for discussions as well as Katinka van de Pas-

Schoonen for technical support. Mari Winkler was funded by

a Marie Curie Intra-European Fellowship (PIEF-GA-2012-

329328). Katharina Ettwig and Boran Kartal were funded by

veni grants (Projects 863.13.007 and 863.11.003, respectively)

from the Dutch Science Foundation (NWO). Karin Stultiens

was supported by an ERC Advanced grant on anaerobic

ammonium oxidation (No. 2322937). Thomas Vannecke is

supported by the Research Foundation-Flanders (FWO)

through a Ph.D. fellowship.

Appendix A. Supplementary data

Supplementary data related to this article can be found at

http://dx.doi.org/10.1016/j.watres.2015.01.039.

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