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EMHyTeC 2012 Hammamet (Tunisia) September 11
-
14, 2012




Single Phase Sequencing Batch Reactors (SBRs) for BioH2 production from
Biomass: Reactor Operation Criteria.


V. Piemonte
a*

, L. Di Paola
a

and Angelo Basile
b


a
)
Faculty of Engineering, University Campus Bio
-
Medico of Rome, via Alvaro del Portillo 21,
00128 Rome,
Italy
,
v.piemonte@unicampus.it
;
l.dipaola@unicampus.it



b
)
CNR
-
ITM, c/o University of Calabria, Via Pietro Bucci, Cubo 17/C, 87030 Rende (CS), Italy
;
a.basile@itm.cnr.it








Abstract


The application of biological processes for high pure hydrogen production, utilizable for fuel cells
purposes, is a promising alternative to conventional processes, such as steam reforming, limited by
equilibrium constraints.

In this framework, a promis
ing alternative technology is the employment of Sequential Batch Reactors
(SBRs) that, in the last years, were proposed and successfully experimented for xenobiotic biodegradation.
The high variability of the operating conditions in these systems could ind
uce in the biomass enzymes the
metabolic pathways required for biodegrading several compounds. The main limitation of SBR operation is
the high concentrations of substrates that the biomass can experience, leading to a significant reduction in
kinetic perf
ormance that is often not acceptable in practical applications. On the other hand, the SBR
application can improve the hydrogen productivity by removing xenobiotics that may inhibit largely the
metabolic conversion. This is a key point when the feedstocks
are agricultural or municipal wastes, that
exhibit large composition variation of the substrates and a variable concentration and quality of
xenobiotics eventually present in the influent.

The aim of this work is to formulate a dynamic model of a single ph
ase sequencing batch reactor applied to
the production of bio
-
hydrogen for fuel cells application from concentrated aqueous streams. In particular,
the effect of some operating parameters, such as the reactor loading time and the reaction time on the
react
or performance will be assessed in order to detect possible operational solutions to SBR limitations.


Keywords:

SBR, Dynamic Simulations, Bio
-
hydrogen production, Fuel Cells.


1

Introduction

The release of various toxic compounds into environment can often
result in considerable costs to human health
and the environment. The consequences of this release have included immediate toxicity to exposed biological
populations, accumulation and degeneration of local sites, and pollutant transport leading to contamin
ation of air,
soil and groundwater (Annadurai et al. 2000, Vrionis et al. 2002).

The conventional approach in industrial wastewater treatment is by chemical

physical processes: adsorption,
stripping, chemical oxidation (Dominquez et al. 2011, Cardoso et al
. 2011, Gustin et al. 2011, Ahmed et al.
2011, Shukla et al. 2011). All these processes can guarantee high removal efficiencies, but the first two have the
main disadvantage that they do not provide a real degradation of the compounds but only their transf
er from a
diluted to a concentrated stream to be ulterior treated or disposed of; on the other hand, chemical oxidation could
produce intermediates characterised by a toxicity level similar to the original substance (Tomei at al, 2003).

The application of
biological processes to xenobiotic removal is a promising alternative to conventional
chemical

physical treatment methods and Sequencing Batch Reactors (SBRs), characterised by a large variety of
operating conditions and high operational flexibility, appea
r to be a promising and suitable technological
solution in order to obtain a versatile microbial culture able to develop metabolic pathways required for the
degradation of bioresistant substances (Tomei at al. 2008, Ellis et al. 1986, Cruickshank et al. 20
00).


The conventional configuration of an SBR system consists of one or more tanks in series that after the initial
filling phase are operated in discontinuous mode (Chan et al. 2009). The essential difference between an SBR
and a conventional continuou
s
-
flow activated sludge system (Beltran et al. 2000) is that in each unit of the SBR
EMHyTeC 2012 Hammamet (Tunisia) September 11
-
14, 2012




system the series of operations (equalization, reaction, settling) is realized in a time rather than in space
sequence.

The duration of the whole operation sequence (work

cycle) is the reference parameter for the design of the
system and can be related to the total volume of a conventional continuous
-
flow facility. The fraction of time
devoted to a specific function in the SBR is equivalent to the volume of the correspondi
ng unit in the
continuous
-
flow system.

The work cycle for each tank in a typical SBR is divided into five time phases: Feed, Reaction, Settling, Draw,
and Idle, which can be realized under various operating conditions depending on the treatment objectives.

The main limitation of SBR operation is the high concentrations of xenobiotic substrates that the biomass can
experience, leading to a significant reduction in kinetic performance that is often not acceptable in practical
applications (Tomei et al. 2010).

AGGIUNGEREI QUALCOSA SULLE CRITICITA’ CHE SPIEGHI
MEGLIO...

The aim of this work is to formulate a dynamic model of a single phase sequencing batch reactor applied to the
removal of xenobiotic compounds from concentrated aqueous streams. In particular, th
e effect of some operating
parameters, such as the reactor loading time, the reaction time and the reactor hold
-
up on the reactor
performance will be assessed in order to detect possible operational solutions to SBR limitations.


2

Mathematical modeling

The mathematical model proposed here refers to a sequencing batch reactor where one substrate is degraded by
aerobic microorganisms. Work cycle in this system includes four phases: feed, reaction, settling and effluent
discharge (see Figure 1). During the
feed phase the reactor is loaded with the water stream to be treated.
Simultaneously, the biomass starts to degrade the xenobiotic compounds present in the liquid solution. Then, the
reaction phase is characterized by the only biomass activity devoted to t
he xenobiotic degradation. Finally, the
reactor is settled and the liquid suspension is discharged. Biomass concentration is adjusted to the fixed
operating value at the start of a new cycle by assuming that the produced biomass is completely drawn out fro
m
the reactor in the wastage phase.


In particular, in this work the model is focused on the feed and reaction phases where the biodegradation process
takes place. Substrate degradation rate was modelled by the Haldane equation which is commonly utiliz
ed for
substrate inhibited kinetics.

In order to have an equation with more representative parameters in relation to the process kinetics, the equation
was rearranged in a different form as suggested by Tomei and Annesini (2007):








(



)











(






)

(






)










(1)


In equation (1)
,

X is the biomass concentration,













is the substrate concentration at which the
maximum removal rate occurs, k
max

is the maximum removal rate observed at C
W

= C
W
* and


Errore.
Non si
possono creare oggetti dalla modifica di codici di campo.

is a parameter that accounts for the extent of the
inhibitory effects.

By considering a completely mixed tank reactor the mass balance equations for the feed phase are given by:



(




)













(



)











(






)

(






)








(2)


(



)
























(3)





















(4)





























(first cycle)




(5)


































(next cycles)


(6)


where
C
in

is the inlet substrate concentration (mg/l);
C
w,n
-
1
RP

the substrate concentration in the liquid phase at the
end of the (n
-
1) cycle (mg/l);
F
in

the inlet flow rate (l/h);
k
e

the endogenous respiration coefficient (1/h);
Y

the
growth yield coefficient (mg biomass /mg substrate);
k
max

the maximum removal rate in the Haldane equation
observed at
C
w

=
C
w
*

(1/h);
V
w

the liquid volume inside the SBR (l);
V
max

the reactor volume at the end of the
feed phase (l);
V
w0

the residual volume (l),
X

the biomass concentration (mg/l),
X
0

the initial value of the biomass
concentration (mg/l);
X
opt

the work value of the biomass concentration (mg/l).

On the same way, the m
ass balance equation for the reaction phase (
F
in
=0) can be written as


EMHyTeC 2012 Hammamet (Tunisia) September 11
-
14, 2012














(



)











(






)

(






)










(7)
























(8)




































(9)


where
C
w
FP

and
X
FP


stand for the substrate and biomass concentration in the liquid phase at the end of the feed
phase (mg/l), respectively.

The set of differential Eqs. (1)
-
(8) was integrated numerically with the gPROMS

package (Process System
Enterprises, London, UK).


3

Results and discussion

In Table 1 are reported the parameter values used during the computer simulations in order to asses the effect on
the SBR performance of some important operative
parameters
.

To c
larify the interpretation of the data, in Figure 2 is reported a magnified part (referring to a low number of
cycles) of the typical “sawtooth” concentration profiles referring to the liquid phase. This representation
modality allows a rapid evaluation of
the stability of the operating conditions. Furthermore, the Figure clearly
highlights the two different operating phases: the first one (loading phase) characterized by a rapid increase of
the xenobiotic concentration in the liquid phase (xenobiotic accumu
lation rate higher than xenobiotic removal
rate), and the reaction phase, where the substrate is progressively degraded by the biomass up to a zero
concentration value.

The model was applied for a sensitivity analysis on some significant operating pa
rameters. The first series of
simulations was performed by varying the reaction time, t
reaction
, in the range of 3
-
5.5 h.


In Figure 3 it can be observed that the increasing of the operative reaction time results in a substantial
modification of the reacto
r performance: for t
reaction
= 3 the reactor outlet stream is characterized by a high
xenobiotic content, that is the reactor work at “low removal” efficiency, while for t
reaction
= 5.5, the xenobiotic
concentration in the reactor outlet stream is almost z
ero. This behaviour is representative of a “high removal”
efficiency. On the other hand, for a value of the reaction time slightly lower than 5.5, the reactor seems to arrive
at a periodic working condition with high efficiency, but subsequently the remov
al efficiency deteriorates toward
a very low removal condition. This finding suggests the presence of two reactor steady state points. The first one
at high removal efficiency (low xenobiotic concentration in the effluent stream) and the second one at low
removal efficiency (high xenobiotic concentration in the effluent stream).

The same reactor behavior can be obtained by varying the xenobiotic feed flow rate, F
in
, that is by varying the
reactor loading time, t
load
. Indeed, by assuming an operative
reaction time for which we have a bad reactor
performance (t
reaction
=3) and by decreasing the reactor loading time from 0.2 to 0.1 h, the reactor reach again a
good operation functioning (see Figure 4). By acting on the loading time it is possible to reduc
e the whole work
cycle time (t
reaction

+ t
load
), but this way a reduction of the total solution volume to be treated is also obtained. It is
evident that, based on the specific case, both the loading and reaction phases time must be optimized.

Table
1
. Model parameters used in the simulations.

Parameter

Value

β
=
O.RT
=
=
u
0
=X
opt

1000 mgVSS/l

C
in

350 mg/l

C
w
*

19.24
g/l

F
in

10 l/h

k
max

0.093 mg/(mgVSS h)

t
load

From 0.1 to 0.2 h

t
reaction

From 3 to 5.5 h

V
max

4.0 l

V
min

2.0 l

Y

0.
30

K
e

0.0034 h
-
1

n
cycles

50

It is worth noting that both in the Figures 3 and 4, for the “low removal” condition, the
substrate concentration
inside the reactor is slightly lower than the inlet substrate concentration to be treated. This behaviour is due to
the residual degradation capacity of the biomass inside the reactor that for all the conditions tested in this work
does not reach a zero value. Therefore, the steady state point at low removal efficiency is characterized by a low
EMHyTeC 2012 Hammamet (Tunisia) September 11
-
14, 2012




degradation rate due to a high biomass inhibition: cycle by cycle the xenobiotic uptake is much higher than the
xenobiotic removal by the bio
mass activity.

To conclude, figure 5 shows….




4

Conclusion

In this work the dynamic modeling of a sequencing

batch reactor (SBR) for the xenobiotic removal from
wastewater has been provided. The influence of important operative parameters on the SBR performance has
been assessed. By varying the operative reaction and loading times or the reactor maximum hold
-
up
the reactor
changes from a bad working cycle characterized by low removal efficiency to a good working cycle
characterized by high removal efficiency. Therefore, the evaluation of the reaction and loading time is extremely
important for a right reactor des
ign: a non correct choose of these operative parameters would lead to an
extremely sensitive reactor, which would easily jump to a working point corresponding to ineffective reactor
performance that does not provide a significant substrate removal.



5

Pa
per preparation


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Write up to 5 keywords (upper and lower cases, italic face, 12 pt).

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References

Ahmed, S., Rasul, M.G., Brown, R., Hashib
, M.A. 2011, Influence of parameters on the heterogeneous
photocatalytic degradation of pesticides and phenolic contaminants in wastewater: A short review, Journal of
Environmental Management 92 (3), 311
-
330.


Annadurai G., Rajesh Babu S., Mahesh K., Murug
esan T., 2000, Adsorption and biodegradation of phenol by
chitosan
-
immobilized Pseudomonas Putida (NICM 2174), Bioprocess Engineering, 22, 493
-
501.


eltr n, F. ., Garc a
-
Araya, .F., lvare , P. ., , Continuous flow integrated chemical o one)
-
a
ctivated
sludge system treating combined agroindustrial
-
domestic wastewater, Environmental Progress 19 (1), 28
-
35.


Cardoso, N.F., Pinto, R.B., Lima, E.C., Calvete, T., Amavisca, C.V., Royer, B., Cunha, M.L., Pinto, I.S. 2011,
Removal of remazol black B te
xtile dye from aqueous solution by adsorption, Desalination 269, 92
-
103.


Chan, Y.J., Chong, M.F., Law, C.L., Hassell, D.G. 2009, A review on anaerobic
-
aerobic treatment of industrial
and municipal wastewater, Chemical Engineering Journal 155 (1
-
2), 1
-
18.


Cruickshank S.M., Daugulis A.J., McLellan P.J. 2000, Dynamic modeling and optimal fed
-
batch feeding
strategies for a two
-
phase partitioning bioreactor, Biotechnology and Bioingineering, 67, 224
-
233.


EMHyTeC 2012 Hammamet (Tunisia) September 11
-
14, 2012




Domínguez, J.R., González, T., Palo, P., Cuerda
-
Correa,

E.M. 2011, Removal of common pharmaceuticals
present in surface waters by Amberlite XAD
-
7 acrylic
-
ester
-
resin: Influence of pH and presence of other drugs,
Desalination 269, 231
-
238.


Ellis TG, Smets BF, Magbanua BS Jr., Grady CPL Jr. 1996, Changes in mea
sured biodegradation kinetics during
the long
-
term operation of completely mixed activated sludge (CMAS) bioreactors, Water Science &
Technology 34, 35

42.


Guštin, S., arinšek
-
Logar, R. 2011, Effect of pH, temperature and air flow rate on the continuous
ammonia
stripping of the anaerobic digestion effluent, Process Safety and Environmental Protection 89 (1), 61
-
66.


Shukla, P., Sun, H., Wang, S., Ang, H.M., Tadé, M.O. 2011, Nanosized Co3O4/SiO2 for heterogeneous
oxidation of phenolic contaminants in waste

water, Separation and Purification Technology 77 (2), 230
-
236.


Tomei M.C., Annesini M.C., Luberti R., Cento G., Senia A. 2003, Kinetics of 4
-
nitrophenol biodegradation in a
sequencing batch reactor, Water Research, 37, 3803

3814.


Tomei M.C., Annesini M.
C., Rita S., Daugulis A.J. 2008, Biodegradation of 4
-
nitrophenol in a two
-
phase
sequencing batch reactor: concept demonstration, kinetics and modelling, Applied Microbiology and
Biotechnology, 80, 1105
-
1112.


Tomei, M.C., Annesini, M.C., Piemonte, V., Prp
ich, G.P., Daugulis, A.J. 2010, Two
-
phase reactors applied to
the removal of substituted phenols: Comparison between liquid
-
liquid and liquid
-
solid systems, Water Science
and Technology 62 (4), 776
-
782.


Vrionis H.A., Kropinski A.M., Daugulis A.J. 2002, En
hancement of a two phase partinoning bioreactor system
by modification of the microbial catalyst: demonstration of concept, Biotechnology and Bioengineering, 79, 587
-
594.



List of Symbols

C
w

=Substrate concentration (mg/l)

C
w
* = Substrate concentration
at which the maximum removal rate occurs in the rearranged form of Haldane equation
(mg/l)

C
in

= Inlet substrate concentration (mg/l)

C
w,n
-
1
RP

= Substrate concentration in the liquid phase at the end of the (n
-
1) cycle (mg/l)

C
w
FP

= Substrate concentrat
ion in the liquid phase at the end of the feed phase (mg/l)

F
in

= Inlet flow rate (l/h)

k
e

= Endogenous respiration coefficient (1/h)

K
I

= Inhibition constant in the Haldane equation (mg/l)

k
max

= Maximum removal rate in the rearranged form of Haldane
equation observed at C = C* (1/h)

K
S

= Saturation constant in the Haldane equation (mg/l)

r
S

= Substrate degradation rate (mg/lh)

t
load

= Feed phase time (h)

EMHyTeC 2012 Hammamet (Tunisia) September 11
-
14, 2012




t
reaction

= Reaction phase time (h)

V
w

= Liquid volume (l)

V
max

= Reactor volume at the end of the feed phase (l)

X = Biomass concentration (mg/l)

X
0

= Initial value of the biomass concentration (mg/l)

X
FP

= Biomass concentration in the liquid phase at the end of the feed phase (mg/l)

X
opt

= Work value of the biom
ass concentration (mg/l)

Y = Growth yield coefficient (mg biomass /mg substrate)

β = Inhibition parameter in the rearranged form of Haldane equation


[1] Authors initials and surnames) “Title”, name of the ournal
,
volume (
issue
)
, year, pages.

[ ] Authors initials and surnames) “Title”, name of the conference, place, country, dates.