investigation of the process stability of different
TRANSCRIPT
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Investigation of t
aSchool of Biological and Chemical Engine
Nanyang 473004, ChinabSchool of Environmental Science and E
250100, China. E-mail: [email protected] Bocent Advanced Ceramic Environ
337000, ChinadDepartment of Civil and Environmental Eng
Tohoku University, Miyagi 980-8579, Japan
† These authors contributed equally to th
Cite this: RSC Adv., 2020, 10, 39171
Received 7th August 2020Accepted 5th October 2020
DOI: 10.1039/d0ra06813f
rsc.li/rsc-advances
This journal is © The Royal Society o
he process stability of differentanammox configurations and assessment of thesimulation validity of various anammox-basedkinetic models
Chunyan Wang,ab Hanyang Wu,†c Bin Zhu,c Jianyang Song,a Tingjie Lu,c Yu-You Lid
and Qigui Niu *b
Over the last 30 years, the successful implementation of the anammox process has attracted research
interest from all over the world. Various reactor configurations were investigated for the anammox
process. However, the construction of the anammox process is a delicate topic in regards to the high
sensitivity of the biological reaction. To better understand the effects of configurations on the anammox
performance, process-kinetic models and activity kinetic models were critically overviewed, respectively.
A significant difference in the denitrification capabilities was observed even with similar dominated
functional species of anammox with different configurations. Although the kinetic analysis gained insight
into the feasibility of both batch and continuous processes, most models were often applied to match
the kinetic data in an unsuitable manner. The validity assessment illustrated that the Grau second-order
model and Stover–Kincannon model were the most appropriate and shareable reactor-kinetic models
for different anammox configurations. This review plays an important role in the anammox process
performance assessment and augmentation of the process control.
1. Introduction
With the development of the economy of the world, eutrophi-cation has spread fast and led to serious aquatic environmentalpollution, especially in the developing countries. The exces-sively discharged nitrogen can cause many negative impacts,such as eutrophication. Therefore, nitrogen removal shall beprocessed in a sustainable way, especially for wastewater treat-ment with a low C/N ratio. With the lower capital investment,less operational maintenance, no additional organic carbonsource, 90% reduction of sludge and the limited emission ofN2O, the anaerobic ammonia oxidation (anammox) process isa new nitrogen removal technology that has gained widespreadattention.1,2 However, despite the increasing interest in theanammox application, there were still many difficulties, such asthe low bacterial growth rate and the sensitivity to the envi-ronmental factors.3
ering, Nanyang Institute of Technology,
ngineering, Shandong University, Jinan
mental Technology Co., Ltd, Pingxiang
ineering, Graduate School of Engineering
is work.
f Chemistry 2020
Anammox processes can be conducted in many differentcongurations. Each process has its own optimized operationsand characteristics based on the design of the reactor. However,it is generally known that common reactors have certainshortcomings, and that appropriate operation conditionsshould be fully investigated to prevent the process from failurewithout optimized operation.4 Different reactors have differentcapabilities of nitrogen removal. Among the applied reactors,the Sequencing Batch Reactor (SBR), Up Flow Anaerobic SludgeBlanket (UASB) and Membrane Bio-Reactor (MBR) were themost popular congurations with different congurationstructures that benet the biomass enrichment in the form ofthe biolm or for avoiding sludge wash out.5–7 The aim ofoptimizing the operational conditions is to enhance the effi-ciency of nitrogen removal.8 The effects of environmentalfactors at various operational options on the anammox micro-bial community were also reported.9 Moreover, the microbialresidence time plays a critical role in the taxonomic composi-tion and functional description of the microbial communities.10
A large number of previous studies focused on experimentaland mathematical methods.11–13 The process-kinetic models arepowerful tools for investigating the performances of differentcongurations during the anammox process. Appropriatekinetic mathematical models are enabled to assess, control, andmitigate the process inhibition and process optimization.
RSC Adv., 2020, 10, 39171–39186 | 39171
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These models can be employed to achieve many key objectivesinvolving the optimization of the chemical processes, assessmentof the reaction hazards, and the design of emergency reliefsystems.14,15 Process-kinetic models enhance the comprehensionof the constructed system, and are conducive to the formulationand validation of a hypothesis. The prediction of the system'sbehaviour at a variety of conditions was developed to reduce theoperation risks. However, certain selection criteria and conditionsmust be obeyed when the proper evaluation and application of theprocess models were performed for understanding the process orpredicting the performance. In order to identify a suitable model,a correct model type shall be selected, and the parameters of themodel shall be estimated with the available data. To a great extent,the validity of the studies relies on the model, which is dened bythe proper preference of a mathematical model rst, and then thevalidity of the kinetics evaluation. Generally, an evaluation on theprocess performance is still characterized by the application of thesimple kineticsmodels andmethods for evaluating their reactions.
Kinetic models are proved to be a conventional way to estimateand prospect the performances and operations of differentprocesses. It is very important to choose a suitable model relatingto the kinetics evaluation of the anammox process assessment.Quantitative process-kinetics can gain insight into the underlyingoperational strategy with feasibility investigations in both batchand continuous processes. However, it is a pity that mostfrequently used models cannot t the kinetic data well. It isnecessary for us to know which model is better, and which isperfect in the simulated conditions. Moreover, the optimizedoperation conditions of the anammox process are also importantfor the lab scale and full-scale process design.
A majority of previous papers of different congurations(EGSB, UASB, SBR, MBR, and CSTR) were related to discussionsof the treatment performance or engineering application.However, only a limited number of articles are available forsolving the specic problems of the kinetics evaluation. So far,studies in investigating the anammox process-kinetics withdifferent congurations are relatively limited, and the assess-ment of anammox performance in different reactors is rare.Thus, the performance of the anammox system in differentreactors is reviewed in this paper with regards to validation ofthe commonly used process kinetic models.
2. Process-kinetics approaches
Different reactors used in the anammox process were summa-rized, and the performance comparison and kinetic simulationwere also evaluated. Currently, we are mainly focusing on theapplication of four kinds of substrate removal models,including the rst-order substrate removal model, the Grausecond-order substrate removal model, the modied Stover–Kincannon model and the Monod equation, to investigate theanammox process kinetics.
2.1 First-order substrate removal model
With regard to the application of the rst-order substrateremoval model to the bioreactor, the change rate of the
39172 | RSC Adv., 2020, 10, 39171–39186
substrate concentration in the completely mixed system may beexpressed as follows:12
� dS
dt¼ QSi
V� QSe
V� k1Se (1)
Because the change rate (�dS/dt) can be neglected undera pseudo-steady-state situation, the equation is derived as:
Si � Se
HRT¼ k1Se (2)
where Si and Se are the total nitrogen concentrations (g L�1) inthe inuent and effluent, HRT is the hydraulic retention time(day), k1 is the constant of the rst-order substrate removal rateconstant (1/d), Q is the inow rate (L/d) and V is the volume ofthe reactor (L).
2.2 Grau second-order substrate removal model
The general equation of a second-order model is described asshown below.16 By integration and linearization, the aboveequation can be expressed as eqn (3):
�dS
dt¼ k2
�Se
Si
�2
(3)
By integration and linearization, the above equation isexpressed as eqn (4):
SiHRT
Si � Se
¼ HRTþ Si
k2X(4)
If Si/(k2X) is considered as a constant (a) and (Si � Se)/Si isreplaced by the substrate removal efficiency (E), b is a constantfor the Grau second-order model, the above equation can berepresented as a simple one:
HRT
E¼ aþ bHRT:
2.3 Modied Stover–Kincannon model
As for the Stover–Kincannonmodel,16 initially, the equation wasapplied to predict the development of the attached-growthbiomass in a rotating biological contactor. Later, the modelwas further modied, and widely used to describe and predictthe performances of the bioreactor.17,18 The original model isexpressed, as shown below:
dS
dt¼
Umax
�QSi
A
�
KB þ�QSi
A
� (5)
where dS/dt is the substrate removal rate (kg m�3 d�1), Umax isthe constant of the maximum utilization rate (kg m�3 d�1), A isthe surface area of the disc (L), and KB is the constant of thesaturation value (kg m�3 d�1). If the volume of the reactor (V)takes the place of the surface area (A), the Stover–Kincannonmodel can be modied as below:18
This journal is © The Royal Society of Chemistry 2020
Fig. 1 Published papers in each year: (a) kinetic models used in theanammox process and (b) enrichment reactors. (Web of Scopus,access data: 2020.04.06).
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dS
dt¼
Umax
�QSi
V
�
KB þ�QSi
V
� (6)
where the Stover–Kincannon model takes dS/dt as a function ofthe loading rate of substrate at a steady state:dSdt
¼ QV� ðSi � SeÞ, so it can be further expressed as shown
below in eqn (7):
V
QðSi � SeÞ ¼KbV
Umax
QSi
þ 1
Umax
(7)
2.4 Monod model
The Monod model was extensively employed.19 The modiedversions of the Monod equation were developed concerning themodel anammox process in terms of the oxygen concentration,ammonia concentration and missing alkalinity:20
ds
dt¼ KSe
Ks þ Se
(8)
where K is the maximum substrate utilization rate (kg m�3 d�1),and Ks is the half saturation concentration (g L�1).
2.5 Other models used for the anammox-based process
Generally, the anammox bacteria cooperated with other func-tional bacteria to degrade the wastewater in the applied elds,such as SHARON and anammox process based on the continuitymodel.21 The ASM2, ASM2d and ASM3 models were also used tosimulate the anammox process, which is enriched frommunicipal activated sludge.22 The more complex microbialcommunities with AOB, NOB DHB and anammox were simu-lated with complex models, as reported.23
3. Anammox processes conducted indifferent reactors
In recent years, the interest in anammox has been increasedsignicantly with more and more articles being published astime has passed, as showed in Fig. 1a. Since 2005, an average of78 more papers has been published every year. In 2014, 300papers were published. Fig. 1b shows the number of anammoxprocesses conducted in different reactors, as previously re-ported. The sequencing batch reactor (SBR) was recognized asthe most dominantly employed bioreactor, which was the topicin one third of published papers, followed by the upowanaerobic sludge blanket (UASB), membrane bio-reactor (MBR),expanded granular sludge bed (EGSB), continuous stirred-tankreactor (CSTR), sequencing biolm batch reactor (SBBR) andupow anaerobic xed bed (UAFB), subsequently. While thenumber of applied UASBs was two-thirds of that of appliedSBRs, both SBRs and UASBs were the most popular reactorsconducted for the anammox process. Many advantages of thereactor are summarized in Table 1. The high NLR (nitrogen
This journal is © The Royal Society of Chemistry 2020
loading rate) and NRR (nitrogen removal ratio), enrichmentgranular sludge, fast start up and high settleability can be ob-tained when the UASB or EGSB is applied. However, the MBR(with a long sludge retention time (SRT)) brought a fast startupof the process and a high accumulation rate for anammoxenrichment, which was commonly evaluated with specialpurposes (Table 1). The general comparison of the anammoxprocess conducted in different processes is shown in Table 2.The contents regarding the general process descriptions,applications, advantages and disadvantages, and design criteriaare given for each technology based on previous researchstudies as the referenced applications. The advantages anddisadvantages of each reactor constructed for anammox arelisted in Table 2. Biolm, granule and occulent were the threemain kinds of anammox conducted in different reactors, amongwhich the biolm and granule were the most popular ones. Aprevious investigation showed that UASB and SBR were themost popular bioreactors that can make granules or keep highanammox biomass. The long retention time of the active sludgeis the key factor to inuence the successful development ofa high-rate anaerobic wastewater treatment. The long retentiontime of sludge can be realized due to the specic reactorconguration design and xed biomass in the form of staticbiolms, particle-supported biolms or granule sludge. It wasobserved that the UASB with upow can easily change thesludge into granules. The high loading rate of UASB with highremoval efficiency was oen reported.7 In contrast, the engi-neering applications of anammox included more than 100 full-scale partial nitridation/anammox installations worldwide by
RSC Adv., 2020, 10, 39171–39186 | 39173
Tab
le1
Anam
moxproce
ssesco
nductedin
differentco
nfigurations(m
ost
popularreac
tors)a
UASB
EGSB
CST
RSG
BR/SASB
R(G
/F)MBR
Nov-BFR
UAFB
MBBR/SBR
Adv
antage
HighNLR
andNRR;
enrich
men
tgran
ular
slud
ge;
highsettleab
ility
HighNLR
andNRR;
enrich
men
tgran
ular
sludg
e;fast
startup
;high
settleab
ility
Intensive
mixing;
idealmod
elfor
simulation
Highstab
ilityof
processen
rich
men
tgran
ular
slud
ge;fast
startup
;high
subs
tratecon.;
adjust
process
timingviaPL
C,
conventop
eration
Highstab
ilityof
process;
fast
start
up/enrich
men
t;highslud
geconcentration;h
igh
NRRwithfree
cell
or/granular
slud
ge;
higheffl
uent
quality;
highde
gree
ofau
tomation
High
stab
ility;
fast
enrich
men
t;bio
lmcu
lturing;
highde
gree
of automation
Highstab
ilityof
process;
fast
startup
/en
rich
men
t;highslud
geconcentration;
highNRRwith
free
cellor/
gran
ular
slud
ge
High
stab
ility;
fast
enrich
men
t;bio
lmcu
lturing
Disad
vantage
Deadzoneareasan
dsu
bstrateinhibition;
inue
nthierarchy;
slud
gewashou
t;sludg
eoa
tation
withlayer
distribution
Costlyto
operate;
slud
gewashou
t;slud
geoa
tation
consu
meen
ergy
LowSR
T;c
onsu
me
energy
Costlyto
operate;
slud
gewashou
t;negativeeff
ecton
downstream
processes;highpe
akow
may
disrup
tpe
rforman
ce
Costlyto
operate;
mem
bran
ecleaning
andreplacem
ent;
processsensitive
tosu
stained
peak
hou
row
;sop
histicated
operation
Costlyto
operate
Costlyto
operate;
mem
bran
ecleaning;
ligh
ter,
uffier
slud
geocs
Costlyto
operate;
bio
lmfall
off
aSG
BR:s
taticgran
ular
bedreactor;SA
SBR:s
tatican
aerobicslud
gebe
dreactor;Nov-BFR
:Noven
bio
lmreactor;MBBR:m
ovingbe
dbio
lmreactor.
39174 | RSC Adv., 2020, 10, 39171–39186 This journal is © The Royal Society of Chemistry 2020
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Tab
le2
Perform
ance
ofan
ammoxproce
ssco
nductedin
differentreac
tors
a
Reactor
type
Inoculum
slud
geOpe
ration
day(d)
T(�C)
pHAmmon
ium
removal
(%)
NLR
(kgN
m�3
d�1)
NH
4+–N
inue
nt(m
gL�
1)
NO2�–N
inue
nt(m
gL�
1)
Slud
geconcentration
(VSL�
1)or
anam
mox
purity
(%)
Referen
ce
UASB
Anaerobic
gran
ules
400
35�
17.0
86.5–92.3
6.4
1027
1409
—46
UASB
Aerob
icgran
ules
300
307.0
900.5
200
220
—26
UASB
Nitrifying+
anam
mox
>140
0Normal
6.3–7.3
<90
9.5
400–55
057
5–17
550
–60
47
UASB
Nitrifying
220
30–33
7.5–8.0
970.16
115
130
—48
UASB
Anam
mox
gran
ules
235
357.8–8.0
99.29(TN)
1.03
458
575
91.2–92.4
49
UASB
AN-GSA-AS
320
�35
7.3–7.9
951.25
——
—50
UASB
Anaerobic
gran
ular
slud
gean
ammox
slud
ge
214/45
035
�1
6.8–7
70–99.9
74.3–76.7
�200
240
42–57gVSL�
17
1LUASB
Synthetic
med
ium
7035
�1
6.8–7.0
93.2
�7.1
30–70
30–7
0—
51
SBR
ASbiom
ass
200–60
025
8.0
——
——
—52
SBR
Anam
mox
320
337.0–8.0
99–100
0.43
180
250
—53
SBR
Activated
slud
ge36
536
�0.3
7.5–8.2
99.9
1.6
1268
166.14
85.0
6SB
RAnam
mox
400
35�
16.7–7.0
60(TN)
1.0
700
0—
54SB
RAnam
mox
400
35�
17.5
78(TN)
0.36
200–25
00
<35
25SB
RAnam
mox
gran
ules
218
30�
17.5–8.0
980.3
150
150
—55
2LSB
RNitritation
–an
ammox
synthetic
wastewater
180
33�
185
–94
0.18
gN
perg
VSS
perd
500
—1.8gVSS
perL
18–19%
Ca.
Jettenia
(16.8%
)an
dNitrosomon
as(20.1%
)
56
18LSB
RPa
+AN
Raw
optoelectron
icindu
strial
wastewater
9437
7.8–8.0
10–33gm
�3d�
118
3–20
0—
—57
3LSB
R0.6kg
Nm
�3d�1
pigg
erywaste
prod
uction/no
dilution
50dstartup
308.1�
191
�10
970.5–0.6gNpe
rL
perd
—NO2–N
removed
/NH
4–N
removed
molar
ratio
was
1.28
�14
%
274�
45%
2.3g
TSS
perLan
d79
%VSS
/TSS
58
3LSB
RCANON
Trace
N2H
4
(4mgL�
1)was
adde
dinto
the
inuen
t
8031
�1
—70
�7(TN)
0.33
�0.06
kgN
perLpe
rd
150mgN
per
L—
Ca.
Scalindu
a,3.14
�10
9to
5.86
�10
10
copies
perg(dry
slud
ge)
59
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Tab
le2
(Contd.)
Reactor
type
Inoculum
sludg
eOpe
ration
day(d)
T(�C)
pHAmmon
ium
removal
(%)
NLR
(kgN
m�3
d�1)
NH
4+–N
inue
nt(m
gL�
1)
NO2�–N
inue
nt(m
gL�
1)
Slud
geconcentration
(VSL�
1)or
anam
mox
purity
(%)
Referen
ce
MBBR
Synthetic
wastewater
2Lof
virgin
carrier
med
ia
86–121
33.4–35
7.5�
0.1
0.57
–0.64�
0.17
0.03
–0.22
348.36
–507
0.48
–0.77
Ca.
Brocadia
fulgidash
ito
Ca.
Kuenenia
stuttgartiensis
AOB1.83
–1.4
NOB
60
10LMBR
Synthetic
wastewater
306.8–7.5
85%
(TN)
1gN
perLpe
rd
12.9
mM
3.4mM
(1.21)
Growth
rate
of0.21
d�1
5
15L/8L
MBR
Synthetic
wastewater
250
377.1–7.5
1680
1680
0.23
dayas
free
cells
61
1.6LMBR
Synthetic
med
ium
6330
�1
7.0�
0.2
82.14
293/16
8084
084
0Ca.Brocadia60
%62
1.8L
GSB
FEffluen
tof
theA-
stag
eof
the
WWTP
20� C
/1–5
215
� C/60–12
710
� C/134
–285
20an
d10
7–7.5
—50
�7mgN
pergVSS
perd
0.4gN
perL
perd
50�
7mgN
pergVSS
per
d
Ca.
Brocadia
0.35
gTSS
/12g
TSS
63
6LSB
BR
Synthetic
ammon
ium-rich
wastewater
3035
�1
74—
470
——
64
SBBRs
Synthetic
med
ium
9035
�1
7.0–7.8
881.62
kgN
m�3
d�1
—Ca.
Anam
moxoglobu
s(D
Q31
7601
.1)
40.1%
65
2.6LFB
RSynthetic
wastewater
6535
�0.2
8�
0.2
0.05
–0.06kg
Nm
�3d�
10.25
kgN
m�3d�1
50mgL�
150
mgL�
1Ca.
Kuenenia
stuttgartiensis
66
EMBRs
—50
33�
18.0�
0.3
0.8
——
—67
5LAnR
Synthetic
med
ium
102
327.8�
0.3
900.30
gN
L�1d�
112
30�
61mgL�
1—
—68
aNLR
:nitrogenload
ingrate;a
nam
mox
purity:thepe
rcen
tage
ofan
ammox
inthebiom
ass;MBBR:m
ovingbe
dbio
lmreactor;EMBRs:external
MBR;F
BR:
xedbe
dreactor;PA
N-AnR:p
artial
nitrication
andan
ammox
reactor;GSB
F:gran
ular
uidized
bedreactor;SG
SR:s
tirred
gassolidreactor.
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2014. Most of them were conducted in the one-stage congu-ration, and the most commonly applied reactors were SBRs,followed by granular systems and MBBRs.24
4. Characteristic and stability analysisof the anammox process in differentreactor setups
Different reactors used for the anammox process are summa-rized in Table 2. The performance such as the startup time,nitrogen-loading rate, removal efficiency, substrate concentra-tion, and the purication of sludge is described and comparedin detail. Themost commonly used SBR reactor has an NLR thatvaried from 0.3 kg m�3 d�1 to 1.6 kg m�3 d�1 with the highestremoval efficiency over 99%.6 The comparison of the mostcommonly used UASB and SBR processes with the maximumNRR and startup time is shown in Fig. 2. Generally, the UASBprocess can obtain a high NRR over 2 kg m�3 d�1. However, thatof the SBR reactor was lower than 2 kg m�3 d�1 with a shortertime for startup. By comparing the anammox sludge with anorganic C content lower than 35%25 and a content higher than99%,6 it was found that the anammox sludge with higher puritycan obtain a higher nitrogen removal efficiency. Similarly, theUASB reactors with different purities and operation conditionshad relatively large differences in the NRRs, which might varyfrom 0.5 kg m�3 d�1 (ref. 26) to 76 kg m�3 d�1. To data, thehighest NRR obtained was 76 kg m�3 d�1 when the UASBreactor was fed with substrate of low concentration under shortHRT.7 Other reactors for the anammox process were reported tohave different NRRs varying from 0.3 kg m�3 d�1 to 1.62 kg m�3
d�1 (Table 2).
Fig. 2 The start up time and maximum NRR comparison of theanammox process of the most used reactors (a) UASB and (b) SBR.
This journal is © The Royal Society of Chemistry 2020
Over the past twenty years, many studies carried out havefocused on the optimization of the anammox process parame-ters. The relative issues involving the substrate inhibition,temperature effect, organic matter and salinity have beenextensively investigated.27 The drawback of the anammoxprocess with quite low bacteria growth rate can be overcome byMBR, which is more effective than most other reactors forenrichment.5 A reactor conguration with a high capacity ofbiomass retention is essential for the anammox process.Recently, a novel process conducted in an MBR with pure free-cell suspension of highly active anammox was successful, witha higher growth rate than the specic maximum growth rateever reported for the biomass, 0.21–0.23 d�1.5 This strategy hasa number of potential capacities in the cultivation of seedinganammox in terms of practical engineering projects.2 MBR orMBBR and Nov-BFR with carriers can accumulate a certainamount of anammox to keep the process stable. Additionally,inherent with each technology are the advantages and disad-vantages of the process, and/or operation and maintenance.Discharging standards are oen the primary consideration inselecting a treatment technology.
Anammox processes conducted in different reactors canaccumulate different kinds of anammox bacteria following thesubstrata and operation conditions. Because of its potentials innitrogen removal during the biological process, the high treat-ment performance and stability of the anammox process havebeen constantly studied for engineering application. Most of thelab-scale enrichment anammox bacteria were ‘Ca. Brocadia’ and‘Ca. Kuenenia’, which are almost mono-species in the anammoxprocess, illustrating a competition relationship of the anammoxspecies owing to their different substrate affinities. It should beworth noting that under specic physiological conditions, Ca.Kuenenia outgrows ‘Ca Brocadia’, resulting in overgrowth whenthe substrate concentration is low.28,29 Meanwhile, the ecologicalroles of the functional microbe and their potentials should beextensively explored in order to attain new perspectives for furtherdesign, operation, and maintenance of the process.
Generally, a large number of gas bubbles will be generated ingas tunnels and gas pockets in some high-loading bioreactorsinoculated with anammox bacteria of high activity. It is specu-lated that the gas bubbles entrapped in the gas pockets mightbe a pivotal factor to cause sludge oatation, especially in theupow reactor, such as a UASB or an EGSB. Aer the hollows arelled with gas bubbles, the anammox granules will unavoidablyoat and be washed out of the reactor, leading to a failure of theanammox process. The granule oatation can be undoubtedlyresponsible for instability, or even failure of the anammoxreactor.30,31 The existence of this washout obstacle compels theimplementation of a large number of studies in pursuit ofa feasible way to overcome this obstacle.
5. Process-kinetic analysis ofdifferent anammox processes
Bibliometric analysis showed that the investigation on thereactor-kinetic models in the published paper was only one-
RSC Adv., 2020, 10, 39171–39186 | 39177
Tab
le3
Comparisonofthekinetics
usedforthean
ammoxreac
tora
Reactor
V(L)
T (�C)
Subs
trate
Inoculum
NLR
(gL�
1d�
1)
First-orde
rGrausecond-orde
rMod
ied
Stover–
Kincannon
Mon
od
Ref.
HRT
(d)
k 1 (1/d)
R2
a (1/d)b
k 2 (1/d)R2
Rm
KB
R2
Ks
(gL�
1)
Mmax
(1/d)
Kd
(1/d)
Y (mgVSS
permg
N)
R2
ILAB
24/20
30�
1Synthetic
wastewater
PN-anam
mox
gran
ular
420�
30NH
3–
NmgL�
1:
1.0–
0.06
666
.90.61
021.09
0.02
2.06
40.99
5422
.2927
.250.98
10.00
2446
0.00
7408
0.00
590.35
110.71
–0.94
34
Up
owlter
35Cultured
activated
sludg
e
0.93
–7.34
0.08
–0.6
0.44
0.17
21.4
0.96
—0.98
512
.412
0.97
9—
——
——
69
ANMR
35Floccu
lent
anam
mox
slud
ge
0.10
7–0.74
60.6–3.0
5.31
0.70
70.11
1.11
—0.99
57.89
8.98
0.99
90.19
20.16
9—
—0.59
935
ANMR
35Floccu
lent
anam
mox
slud
ge
115–29
7/15
3–31
30.6–2.9
5.30
50.70
60.11
1.11
0.99
548.98
7.89
0.99
860.19
20.16
930.59
949
MAR
0.8/
0.65
25Sa
ltysynthetic
Cultured
anam
mox
slud
ge
0.08
–1.94
0.25
–1.0
7.44
0.75
60.06
1.14
—0.99
16.41
7.37
0.99
30.10
70.95
2—
0.95
20.99
311
AUF
35Cultured
activated
slud
ge
270–30
50.08
–0.6
1.4
0.96
0.98
5512
12.4
0.97
9212
288–30
7UABF
35Anam
mox
gran
ules
360–70
01–0.25
h0.04
1.06
0.99
935
.738
.10.99
936
475–92
4UABF
35Anam
mox
gran
ules
400/52
81–0.25
h0.05
1.04
0.99
820
.721
.60.99
837
UASB
125
Synthetic
wastewater
Preservation
treatm
ents-
4+distille
dwater
50–300
/60
–300
3–9.62
h55
.556
.60.99
38
UASB
125
Synthetic
wastewater
Preservation
treatm
ents–40+
dimethyl
sulfoxide
50–300
/60
–300
3–9.65
h0.99
91.16
50.99
1666
.767
.90.99
238
UASB
5037
Synthetic
wastewater
Anam
mox
gran
ules
167–27
8/19
1–41
10.2–3.2
11.64
0.80
430.09
1.03
—0.99
8527
.827
.50.99
949
SUASB
8.6
35�
1Synthetic
wastewater
Nitrifying
slud
gean
dmature
anam
mox
gran
ule
5.63
2.5–24
h14
.814
.50.98
970
39178 | RSC Adv., 2020, 10, 39171–39186 This journal is © The Royal Society of Chemistry 2020
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Tab
le3
(Contd.)
Reactor
V(L)
T (�C)
Subs
trate
Inoculum
NLR
(gL�
1d�1)
First-orde
rGrausecond-orde
rMod
ied
Stover–
Kincannon
Mon
od
Ref.
HRT
(d)
k 1 (1/d)
R2
a (1/d)b
k 2 (1/d)R2
Rm
KB
R2
Ks
(gL�
1)
Mmax
(1/d)
Kd
(1/d)
Y (mgVSS
permg
N)
R2
UASB
135
�1
Synthetic
wastewater
0.16
�10
0.24
kgSm
3
d1wou
ld
14.6
95.2984
.030.97
5871
UASB
135
�1
Synthetic
wastewater
Cop
per(II)
recovery
0.4–2.4
h15
1.515
7.90.73
72
UASB
135
�1
Synthetic
wastewater
OTCrecovery
0.4–2.4
h21
2.822
8.40.74
672
UASB
1.5
35�
1Synthetic
wastewater
Re-startup
49.5
56.8
0.98
541
UASB
1.5
35�
1Synthetic
wastewater
Re-startup
454.552
80.99
541
UASB
1.5
35�
1Synthetic
wastewater
Re-startup
384.644
7.70.99
41
UASB
1.5
35�
1Synthetic
wastewater
Re-startup
476.255
30.99
641
UASB
1.5
35�
1Synthetic
wastewater
Re-startup
144.915
3.70.99
41
UASB
135
�1
Synthetic
wastewater
Singlefeed
70–2
661.52
–2.06
h15
17.5
0.93
442
UASB
135
�1
Synthetic
wastewater
Multifeed
70–2
671.52
–2.06
h27
.537
.50.93
242
UASB
Activated
slud
ge0.15
–2.8
0.2–3.2
11.6
0.80
40.09
1.03
—0.99
912
.111
.40.99
90.09
20.22
5—
—0.77
316
UASB
recycled
5037
Synthetic
wastewater
Anam
mox
gran
ular
0.28
–1<1
27.8
27.5
0.99
949
PNreactor5
28�
2Rejectwater
wtp
Lab-scale
ll-draw
reactor
13.9
300.96
73
UAF
2.5
36Rejectwater
wtp
Mesop
hilic
digester
ofamun
icipal
31.2
42.1
0.97
73
UAF
230
Synthetic
wastewater
Wastewater
treatm
ent
plan
t
0.93
–7.34
gL�
12–14
.40.43
950.17
51.39
70.96
40.98
612
.412
0.97
912
ILAR
3.8
30�
1Synthetic
wastewater
Mun
icipal
wastewater
treatm
ent
plan
t
(NH
4)2SO
4
0.39
–6.96g
L�1
12–21h
5.77
5.39
0.95
7274
aILAB:internal-lo
opairli
bio-pa
rticle
reactor;ANMR:non
-woven
mem
bran
ereactor;MAR:marinean
ammox
reactor;VAF:
upow
anaerobiclter;R2:correlationcoeffi
cien
t;k 1
andk 2
isthe
subs
trateremoval
rate
constan
t(1/d)of
each
equa
tion
.
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tenth of the total. Meanwhile, the Stover–Kincannon model wasthe most commonly used one, which was followed by theMonod model and the Grau-second model (Fig. 1b). It wasconrmed by many studies that the anammox bacteria werevery sensitive to operational conditions, such as dissolvedoxygen, temperature, pH and composition of organic matters.Unfavorable conditions will largely reduce the activity of theanammox bacteria, and eventually cause a failure in bioreactorperformance. Therefore, it is of practical signicance to effec-tively augment the activity of the anammox bacteria in order toachieve a high-rate process under the mainstream conditions,which might cause a large decrease in the specic activity ofanammox. Most of the literature reached a consensus in thatthe process control for anammox is a prerequisite to practicallyensure the successful performance under unstable inuentconditions.32
The common bioreactors have certain shortcomings sincedifferent reactors have different optimal operating conditions.For instance, the UASB reactor oen encounters unsatisfactorysubstrate removal efficiency, severe sludge washout, and largedead zone areas. An EGSB is costly in term of the hugeconsumption of energy and operation cost. In addition, a bio-lm reactor has a long sludge age and sporadic sludge otation.The main objectives of process modeling are to control andevaluate the performance of the process, as well as to optimizethe system design and scale up the pilot plant investigations.33
For example, the concentrations and activities of anammoxmeasured in different reactors could be used in conjunctionwith models to control the process parameters, involving theinuent loading rate and hydraulic residence time in order to
Fig. 3 Reactor-kinetic validation assessment. (a), N2 gas production (b),
39180 | RSC Adv., 2020, 10, 39171–39186
maximize nitrogen removal. To date, process control is widelyconsidered in the literature as an essential factor to guaranteegood performance in various bioreactors.
Modeling and parameter identication are subjects withwide ranges, offering a realm of approaches and methods. Inmany practical industrial projects, most knowledge is availablein the form of heuristic rules achieved from rich experience ina variety of processes. Until now, the successful application ofanammox in practical projects is still facing huge challenges.The kinetics involves operational and environmental factors,affecting the utilization rates of the substrates. By means of thekinetics evaluation, the optimization on the plant design andprediction of the performance of treatment plants can be con-ducted,14,33 and the process models relating to the anammoxprocess can be further discussed (Table 3).11,14,34–38 Furthermore,the anammox enrichment culture can be signicantly promotedbecause the kinetics can provide a convincing basic recipe fordealing with the operational and environmental factorsaffecting the performance of substrate removal.11 It is wellknown that many mathematical models, such as rst-ordersubstrate removal models, Grau second-order substrateremoval models, Stovere–Kincannon models, and Monodmodels are widely adopted in the eld of wastewater treatment(Table 3). For example, the rst-order and second-ordersubstrate removal models are effective for estimating thekinetic constants in anammox processes.14,39,40 In addition, theMonod model was initially applied to represent the growth ofmicroorganisms, and widely employed to express the degrada-tion kinetics. Moreover, the Stovere–Kincannon model is one ofthe most expensively developed mathematical models for
13 substrate consumption (c),45 and the model comparison (d).15,45
This journal is © The Royal Society of Chemistry 2020
Tab
le4
Comparisonofkineticmodelsap
plie
dto
anam
moxreac
tors
Mod
els
Reactor
Inoculum
NLR
(gL�
1d�1)
HRT(d)
Con
stan
tsof
mod
els
R2
Referen
ce
First-order
mod
elUp
owlter
Culturedactivatedslud
ge0.93
–7.34
0.08
–0.6
0.44
0.17
269
ANMR
Floccu
lentan
ammox
slud
ge0.10
7–0.74
60.6–3.0
5.31
0.70
735
UASB
Activated
sludg
e0.15
–2.8
0.2–3.2
11.6
0.80
416
MAR
Culturedan
ammox
slud
ge0.08
–1.94
0.25
–1.0
7.44
0.75
611
UASB
Anam
mox
gran
ules
167–27
80.2–3.2
11.64
0.80
4349
191–41
1UASB
Activated
sludg
e0.93
–7.34
1.5–12
0.45
80.43
13UASB
Anaerobicdigestionslud
ge0.93
–7.34
1.5–12
0.56
10.04
13UASB
0.93
–7.34
1.5–12
0.79
80.18
13a
bGrausecond-orde
rmod
elUp
owlter
Culturedactivatedslud
ge0.93
–7.34
0.08
–0.6
1.4
0.96
40.98
569
ANMR
Floccu
lentan
ammox
slud
ge0.10
7–0.74
60.6–3.0
0.10
51.11
0.99
535
UASB
Activated
sludg
e0.15
–2.8
0.2–3.2
0.09
361.03
0.99
916
MAR
Culturedan
ammox
slud
ge0.08
–1.94
0.25
–1.0
0.05
541.13
60.99
111
AUF
Synthetic
med
ium
10.1–1.99
1.39
70.96
412
ANMR
Floccu
lentan
ammox
slud
ge11
5–29
70.6–2.9
0.10
541.11
010.99
5414
153–31
3UASB
Anam
mox
gran
ules
167–27
80.2–3.2
0.09
361
1.02
870.99
8515
191–41
1Activated
slud
ge0.93
–7.34
1.5–12
0.08
71.13
0.93
13UASB
Anaerobicdigestionslud
ge0.93
– 7.34
1.5–12
0.05
11.14
0.98
130.93
–7.34
1.5–12
0.09
11.20
0.97
13Rm
KB
Mod
ied
stover–
Kincannon
mod
elUp
owlter
Culturedactivatedslud
ge0.93
–7.34
0.08
–0.6
12.4
120.97
969
ANMR
Floccu
lentan
ammox
slud
ge0.10
7–0.74
60.6–3.0
7.89
8.98
0.99
935
UASB
Activated
slud
ge0.15
–2.8
0.2–3.2
11.4
12.1
0.99
916
MAR
Culturedan
ammox
slud
ge0.08
–1.94
0.25
–1.0
6.41
7.37
0.99
311
AUF
Anam
mox
slud
ge10
.1–1.99
1212
.40.97
912
ANMR
Floccu
lentan
ammox
slud
ge11
5–29
70.6–2.9
8.98
7.89
0.99
8614
UASB
Anam
mox
gran
ules
167–27
80.2–3.2
12.1
11.4
0.99
915
191–41
1Activated
slud
ge0.93
–7.34
1.5–12
0.89
21.01
90.94
13UASB
Anaerobicdigestionslud
ge0.93
–7.34
1.5–12
11.11
00.98
130.93
–7.34
1.5–12
3.33
4.03
70.98
13Rm
Ks
Mon
odmod
elANMR
Floccu
lentan
ammox
slud
ge0.10
7–0.74
60.6–3.0
0.16
90.19
20.59
935
EGSB
Anam
mox
gran
ules
0.76
–22.87
0.06
–0.33
0.63
20.20
80.98
675
UASB
Activated
slud
ge0.15
–2.8
0.2–3.2
0.22
50.09
20.77
316
MAR
Culturedan
ammox
slud
ge0.08
–1.94
0.25
–1.0
0.95
20.10
70.99
311
UASB
Anam
mox
gran
ules
167–27
80.2–3.2
0.22
460.09
240.77
2515
191–41
1UASB
Activated
sludg
e0.93
–7.34
1.5–12
——
—13
Anaerobicdigestion
slud
ge
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Table 5 Most popular kinetic models used for the activity simulationa
Simulation equations Reference
q ¼ Sqmax
Ks þ S þ S2
KI
76
q ¼ qmax
�exp
�� S
KI
�� exp
�� S
KS
��77
q ¼ qmax
�1� exp
�� S
KS
��78
r ¼ Srmax
Ks þ S þ S2
KIH
79
r ¼ Srmaxð1� S=SmÞnKs þ S
80
r ¼ Srmaxð1� S=SmÞnS þ KsðS=SmÞm
81
r ¼ Srmax
Ks þ Sexp
�� S
kip
�82
a Where q is the specic substrate conversion rate constant (d�1); qmax isthe maximum specic substrate conversion rate constant (d�1); KS is thehalf saturation constant (mg N L�1); KI is the inhibition constant (mg Nper L); KIH is the inhibition constant of Haldane (mg N per L); kip is theinhibition constant of Aiba; rmax is the maximum specic activity (mgL�1); Sm is the maximum removal efficiency (mg L�1 d�1).
Fig. 4 SAA kinetic simulation of the EGSB-anammox biomass (a–f)13 and(h), and NF-nitrifying system (i).43
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determining the kinetic constants in immobilized bioreactors.Also, it was reported that the Stovere–Kincannon model hasbeen investigated in continuously operated mesophilic andthermophilic upow anaerobic lters for the treatment ofsoybean wastewater, paper pulp liquors, and simulated starchwastewater, and the determination of kinetic constants ina packed bed reactor for decolonization.11
A detailed comparison of different substrate removal kineticmodels for anammox reactors is listed in Table 4. Comparedwith the various processes conducted in the UASB, MAR, ANMRand up-lters, the result of the rst-order simulation showedthat the UASB had the highest K1 of 11.64 (d�1) with R2 being0.80, and the up-lter had the lowest K1 of 0.43 (d�1) with R2
being 0.439.12,15 All of the rst-order simulations proved that R2
was low, indicating the poor tting of the data. While these datasimulated by second-order simulation proved a higher R2,which was 0.99 or 0.98, respectively. Meanwhile, the modiedStover–Kincannon also gave a high R2 of 0.98 in a UAF system.12
In the UASB system, among the most commonly used modiedStover–Kincannon model, Rmax varied from 15 to 476, as re-ported due to the different operational conditions.41,42 Thedifference in the Umax values was probably due to the differentadopted reactor congurations, different treated wastewatercharacteristics and developed microorganisms in variousstudies. The Stover–Kincannon model was suitable for thekinetic analysis of a complicated anaerobic process. This ispartially due to the simplication of this model without diffu-sion of the modeling substrate, hydraulic dynamics and other
the different systems of anammox (g), DMX-deammonification system
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parameters, which might be key factors for the reactor perfor-mance, but were difficult to measure. The methods of validityassessment between the experiment and prospect can be con-ducted by the linear regression equation, y ¼ x (Fig. 3). Themodied Stover–Kincannon model and the Grau second-ordermodel are both practical because in the case that Umax isequal to kB, the Grau second-order model can be transformed tothe modied Stover–Kincannon model. Thus, the total nitrogenconcentration in the effluent predicted by the Grau second-order and modied Stover–Kincannon models may displayhigh correlation with actual measured data. Conversely, theMonod model and the rst-order model were proven to be notfeasible in many cases. The Grau second-order model and themodied Stover–Kincannon model were both acceptable topredict the total nitrogen concentration in the effluent sincetheir plot lines nearly coincided with the actual line (Fig. 3). Theprocess kinetic models also illustrated that the substrateconcentration and granule size should be carefully controlled asthe main process parameters. Different types of kinetic modelsshould be used to obtain the appropriate model. For the activitytest simulations, most popular kinetic models used for theactivity simulation are shown in Table 5. The specic anammoxactivity (SAA) kinetic simulation of the EGSB-anammox biomass(a–f)13 and the differences between the anammox (g), DMX-deammonication system (h), and the NF-nitrifying system(i)43 were compared and veried (Fig. 4). Other simple kineticASM1 models for granular biomass oatation were also inves-tigated.44 Among the kinetic models, the basic Monod equationfor the DMX process, the extended Edwards and Luong equa-tion for the AMX process, and the Andrews equation for the NFprocess were used and validated to be the most appropriateequations for the process.
A simplied kinetic model lacks the capacity of expressingthe detailed mechanism, but it can be used to properly describethe main characteristics of a reaction. A good model not onlyprovides a better understanding of the complex biological andchemical fundamentals, but is also fundamental for the processdesign, start-up, dynamics predictions, and process control andoptimization. Obviously, the simplied models with limitedvariables, which are conrmed suitable for practical engi-neering applications, were proved to be powerful tools foranammox at low growth rates. Although different kineticmodels were investigated to describe the anammox processcarried out in different reactors, the modied Stover–Kincan-non and Grau second-order models seemed to be the mostsuitable for describing nitrogen removal.4,12,37 However, thesemodels still had problems since the limitations of these kineticmodels cannot describe cellular metabolism and regulation.Moreover, these models did not give any insight to the variablesthat could inuence cell growth. In addition, these models shallbe further modied when the special phase of the process wassimulated to get the actual kinetics. More analysis methods andtechnologies for a more in-depth study shall be extensivelycarried out with the purpose of improving the understanding ofthe reaction mechanisms and microbial community dynamics.
This journal is © The Royal Society of Chemistry 2020
6. Conclusions
In the review, the process-kinetics of different anammoxcongurations with process performance was investigated.Among the congurations, SBR, UASB and MBR were the mostcommonly used and favored for bacterial accumulation. Thesimulation models of the kinetics were proved as valuableinformation for process construction and rector operation. Thekinetic model validation proved that the modied Stover–Kin-cannon model and Graus second-order model could be appro-priate for different reactor anammox processes. Rather than thecorrelation coefficient, the validation revealed that the modiedStover–Kincannon model was more appropriate for nitrogenremoval kinetics in most congurations. Based on the simula-tion of correlated indexes, the activity kinetic models illustratedthat the modied Han–levenspiel, Luong and Andrews modelswere the most appropriate kinetic models for the activitysimulation in the anammox process. The appreciate congu-rations could improve the denitrication efficiency, andcontribute to the biomass enrichment in the projects of engi-neering application.
Conflicts of interest
There are no conicts of interest to declare.
Acknowledgements
This work was supported by the National Natural ScienceFoundation of China (Grant No. 51608304) and the Scienticand Technological Projects of Henan Province (Grant No.172102210420).
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