Population dynamics by methanol addition in denitrifying wastewater treatment plants

~

Pergamon

Waf. Sci. Tech. Vol. 39, No. I, pp. 43-50,1999. @1999IAWQ

Published by Elsevier Science Ltd Printed in OreatBritain. All rights reserved PH: S0273-1223(98)00774-4

0273-1223/99 S19'00 + 0'00

POPULATION DYNAMICS BY METHANOL ADDITION IN DENITRIFYING WASTEWATER TREATMENT PLANTS Irene Purtschert and Willi Gujer Swiss Federal Institutefor Environmental Scienceand Technology (EAWAG) and Swiss Federal InstituteofTechnology (EI'H). CH-8600Diibendorf, Switzerland

ABSTRACf The population dynamics were tracked in the system 'denitrification with methanol'. Experiments with both anoxic and aerobic cultivation were carried out in a lab plant comprising a sequencing batch reactor. Three cultivation periods were tracked: an anoxic lODe phase. which is not discussed here. then an anoxic 20°C phase and finally a mixed aerobic/anoxic 20°C phase. Batch tests were performed to characterise the adaptation period of the methanol degraders and to determine kinetic and stoichiometric parameters as well as the effects of temperature and of inhibitors. A mathematical model for denitrifying methanol degraders was developed and calibrated with the measured data. The verification was performed by full-scale experiments at the wastewater treatment plant of ZUrich-Werdhlilzli. The results show that it can be modelled by two types of microorganisms. mainly involved in the process of methanol degradation. Which type dominates in the system depends on the mode of cultivation. In order to optimise the process with respect to cost and performance, it is important to cultivate the beneficial population. This would be the one that produces less sludge and grows anoxically faster than others. A highly selective criterion is the available supply of soluble oxygen, So optimising nitrate elimination by denitrification with methanol means minimising the simultaneous exposure of the biomass to oxygen and methanol. ~ 1999IAWQ Published by Elsevier Science Ltd. All rights reserved

KEYWORDS denitrification; dynamic simulation; external carbon source; methanol; modeling; population dynamics. NOMENCLATURE b

= decay rate (T-I)

rden

= denitrification rate (M L-3 T-I)

D X = biomass dilution rate (d- I) rMeOH = methanol degradation rate (M L-3 T-I) KM half-saturation coefficient for MeOH (M L-3) SBR Sequencing Batch Reactor

= KiO =inhibition coefficient for 0i (M L-3)

Ko =half-saturation coefficient for 02 (M L-3) ~max

=maximum growth rate (T- )

= = =

SRT Solids Retention Time (T) X I' X 2 methanol degrading biomass (M L -3) Y COD biomass yield in COD units (M M-I)

=

43

44

I. PURTSCHERT and W. GUIER

INTRODUCTION Issues of population dynamics are complex and show a large variety on a macroscopic as well as on a microscopic scale. Regarding an ecosystem, small changes of the environmental conditions might cause a sudden increase of certain species, while others might drastically decrease. With regard to wastewater treatment, bulking and foaming problems with activated sludge are well-known examples of these effects . If methanol is added to sludge in order to provide an efficient denitrification, this also induces a shift in the population composition that can be tracked by measuring the degradation rates of methanol. In the future, many of the larger wastewater treatment plants will have to include a denitrification step. Since the biological elimination of nitrate is usually controlled by the availability of organic carbon, an effective solution will require the addition of an external carbon source or to enlarge existing tank volumes. Comparing possible carbon substrates, methanol turns out to be relatively cost effective and causes a lower sludge production than acetate. On the other hand. methanol as a Cj-compound is not accessible for all microorganisms but gives a selective advantage to a specialised group: Hyphomicrobium sp, a denitrifying, methylotrophic bacteria, that has to be enriched in the activated sludge before being able to effectively remove nitrate from wastewater. GOAL The goal of this investigation is to understand effects of population dynamics for ~he activated sludge system 'denitrification with methanol'. This system has been chosen as a suitable environment because of its highly selective impact on bacteria populations and because it exclusively favors specialised groups of organisms. If the activity of these groups is monitored over an extended period of time, the dynamics of methanol degrading organisms depending on operating conditions can be assessed. Since mixed cultures are present and no isolation of the specific bacteria is performed. their natural habitat remains unchanged and the findings are applicable to an optimal design and operation of treatment plants. MATERIALS AND METHODS The experiments were performed in a Sequencing Batch Reactor (SBR) of 81 volume and a total SRT of 10 days. Denitrifying activated sludge was cultivated under different conditions, e.g. temperature and electron acceptor. Parallel batch tests served to determine stoichiometric and kinetic parameters . Full-scale experiments at the wastewater treatment plant of Zurich-Werdholzl! are used to discuss a possible application of methanol to denitrifying wastewater treatment plants in Switzerland. The acquired results from laboratory experiments are implemented in a mathematical model and verified by full-scale data series. The dissolved ionic compounds nitrate. nitrite, ammonia and phosphate were determined colorimetrically by Flow Injection Analysis (FIA) after filtration (0.45 um). Total nitrogen as well as total phosphorus content were measured in the same way after digestion with K2S20 S' To analyse methanol in the batch tests, a gas chromatograph (Carlo Erba Vega 6000) with a Flame Ionisation Detector (FlO) was used. It was operated with a capillary column and H2 as carrier gas. The dissolved and the total COD were measured colorimetrically by the HACH method (DR/2000). The model calculations were performed with the simulation programs AQUASIM (Reichert, 1994) and ASIM (Gujer, 1990). The model 'Aerobic and Anoxic Methanol Degradation' is presented in the way of 'Activated Sludge Model No. I' (Henze et al., 1987). CULTIVATION EXPERIMENTS Three long-term experiments with different conditions (temperature. aerobic or anoxic cultivation mode) were used to characterise issues of population dynamics in the system 'denitrification with methanol'. In order to provide the background for mathematical modeling several stoichiometric and kinetic parameters were determined in separate batch tests.

Population dynam ics by methanol addition

4S

Anoxic cultiyation The SBR was operated with a 30% predenitrification period with methanol addition. Two different Cultivation periods were investigated. one at lDoC and the other one at 20°C. Methanol dose at 20°C was twice the one at 10°C. The results indicate that the methanol degraders at 20°C had reached their maximum level after about 7-8 days (Figure I). At lDoC a very slow enrichment could be observed. In the mathematical model this can be described by implementing a process inhibiting the enzyme synthesis. which is not discussed here (see Purtschert, 1997). ...1000 r - - - - - - - - - . , . - - - - ,

•

~ 800 ' e Q 600 o

U400

S

i

200

~

O+--;----;-+--+---t-+'--+----J

o

5

10

15 20 25 30 35 time [d)

40

Figure I. Methanol degradation rates during the anoxic cultivations at 20·C. After 31 days. methanol addition was stopped (rMeOH =saturated methanol degradation in separate batch tests) .

.. • ••

6000

Aerobic perIod

;"'5000 og

•

e 4000

'1

Q

30% Anoxic period

• •

•• •• Aerobic Activities••

03000

u

CII

';'2000

'i •• ~ 1000 " · ~ III ..... ••

• •

•••• • • Anoxic Actlvltl..

O~-+--+---t--+-:"':":":";'-:"':"'-':"':;""":":';':~

o

10

20

30

40 50 time [d)

60

70

80

Figure 2. Methanol degradation activities during tho aerobic cultivation at 20°; Aerobic and anoxic max imum (saturated) rates during the aerobic CUltivation. After 40 days a 30% anoxic period was introduced. Whereas the aerobic activities clearly react to the change. the anoxic ones increase only slightly.

Aerobjc cUltjyation The third period was a fully aerobic 20°C cultivation. After 40 days the SBR was changed to 30% predenitrification. The shift from an aerobic cultivation to an anoxic one resulted in a response of the methanol consumer activities (Figure 2). The bacteria were able to denitrify with methanol in the fully aerobically operated SBR as well as during the predenitrification period. During the fully aerobic phase the aerobic activity was much higher than the anoxic one. The cultivation shift resulted in the aerobic rates strongly decreasing wheare the anoxic ones increased only slightly. The reason could be that mainly two populationsof methanol degraders were present in this system. Dependingon the mode of cultivation one of the two had a selective advantage and outgrew the other.

46

I. PURTSCHERT and W. GUIER

Discussion The results of the long-term experiments indicate that two types of methanol degraders exist. The dominant population of methanol consumers depends on the mode of cultivation (see also Table 3). In a pragmatic approach two types of methylotrophic denitrifiers can be distinguished: X I with a high aerobic growth rate and, as will be shown later, a high yield coefficient. This organism is expected to dominate if substantial methanol degradation occurs under aerobic conditions . X2 with a smaller yield coefficient, a higher anoxic and probably a smaller aerobic growth rate than XI ' This organism will dominate if all methanol degradation takes place under anoxic conditions. THE MODEL 'AEROBIC AND ANOXIC METHANOL DEGRADATION' Deyelopment of the model In developping a model, which should be as simple as possible and still be able to describe the presented system 'Aerobic and Anoxic Methanol Degradation' in a suitable way, several questions have to be answered: r: Is the readily biodegradable influent COD to be considered by modeling the methanol degradation'? Does methanol induce the build up of storage products as does e.g. acetate'? How do the bacteria enter into the activated sludge system, by continuous inoculation or only by chance'? Which types of organisms dominate the system and which conditions favor which type'? Which soluble and particulate substances have to be implemented in the model'? These questions are here discussed in a very short way, for details see Purtschert (1997). Batch tests were carried out first with methanol only and subsequently with supplementary acetate addition. They show that the methanol degradation was not influenced by the acetate consumption . This allows us to neglect the heterotrophic biomass and its connected processes, which makes the model much simpler. In contrast to acetate, batch tests indicate that no methanol has been converted into storage products. Graezer-Lampart et al. (1986) and Duchars and Attwood (1989) confirm this result. Schmider and Ottow (1986) and Gliesche et al. (1996) found Hyphomicrobium sp populations in both the influent and the activated sludge tank of WWTP's without methanol addition. The bacteria were present throughout the year but only at low concentrations. Our batch tests with wastewater confirm these statements. Two groups of dominating bacteria are distinguished in the model, X I and X 2. According to the experiments, they have different yield coefficients and anoxic as well as aerobic maximum growth rates. Both of them are able to denitrify with methanol and therefore an anoxic growth process is needed for each population. From Figure 4 it can be seen that in all the experimental phases the organisms were able to denitrify. But Figure 5 shows that during the fully aerobic cultivation phase the 'aerobic' population X I was dominant. Besides, the two populations concept is not a differentiation of genetic types, but only of phenomenoJogic ones. The main selective factor will be the available oxygen, as controlled by the kinetic parameters of the microorganisms (Table 3). In a mathematical model only the really essential substances should be implemented. These would be: oxygen, nitrate and methanol as soluble, biomass XI and X2 as particulate substances. A process called 'respiration' is introduced in order to represent the oxygen uptake of nitrifiers and heterotrophs.

47

Population dynamics by methanol addition

Stoichiometry and kinetics Tables I and 2 represent the stoichiometric matrix and the process rate equations of the model. The stoichiometric and the kinetic parameters are shown in Table 3. Table I. Stoichiometric matrix of the model 'Aerobic and Anoxic Methanol Degradation' . Only the population XI is shown, but X2 has the analogous stoichiometry Process

XI

Aerobic Growth

Xt

Anoxic Growth

XI

Decay

O2

Respiration

Oxygen

Nitrate

Methanol

Xt

g02 m')

gNm')

gCODMem')

gCODm')

1 YI

_I-Y, YI

1

-_.2.:2L 2.86·YI

1 -Y I

-1 -1

Table 2. Process rates of the model 'Aerobic and Anoxic Methanol Degradation'. Only the population X I is shown, but X2 has the analogous process rates Process

Xt

Aerobic Growth

XI

Anoxic Growth

XI

Decay

Oz

Respiration

Process rate

Table 3. Stoichiometric and kinetic parameters of the model 'Aerobic and Anoxic Methanol Degradation', The parameters were determined by batch tests, except the numbers in italics, which were identified by AQUAS1M from SBR data. From batch tests and literature the half-saturation and inhibition coefficients, Kj , are assumed to be small. « I g m,3. According to the sensitivity analysis with AQUAS1M they seem to have no important influence on the system. Therefore, they are all estimated to be 0.1 g m,3. The biomass concentration in the influent is based on different experiments with wastewater, where the ratio of aerobic to anoxic methanol degradation was determined

y

XI Xz

"'.n..•

~m..,..rob

~....no.

b

gCOD x g.ICODMeOH

d· 1

d·1

d·1

20°C

20·C

20·C

ro'influent

0.58

3 .88

0.81

0.178

0.5

0.44

1.72

1.30

0.25

2

1

~CODx

4R

I. PURTSCHERT and W. GUJER

Simulation of the SBR experiments Figures 3-5 represent the results of the dynamic calculations of the three long -term experiments. As the parameters were obtained from the batch tests of these periods. the simulations fit well. In Table 3 all the parameters used in the simulation are shown. _ 1000

;

•

BOO

E

c

o

Anox ic Acti v ities

600

U 400

S ~ 200 ~

30% Ano x ic Cu lt ivation

I

o o

5

10

15 20 25 ti mo [d]

30

35

40

Figure 3. Anoxic Cultivation: Methanol degradation activities from the hatch experiments and their simulntion. After 31 day s of the 20°C phase the methanol additi on was stopped. 6000

30% A n o x i c po r lo d I

",~5000

'tl

., 4000

E

C

0 3000 u - 2000

'" ~

i! 1ooo

o ...-------~--------' o 10 20 30 40 50 60 70 80 li mo (d] Figure 4. Simulation of the aerobic 20°C period . The aerobic and the anoxic rates from hatch ex periments are shown. For the first 40 da ys the SBR was operated aerobic ally afler then with pred enitrification .

700 ... 600

60

an ox ic .,~

'E 500

50 1, - - - - ---1

E 40

z

g 400 ~ 300 9200 ';' 100

.' ---- - - -

..

~ 30

~ z

o o

10

20

30 40 50 lim o [d]

60

70

80

Nlt r at o t.

Nlt r at o t ...

20 10

M ct h dll o l t ,

10

20

;J

•

30 40 50 lim o [d )

60

70

80

Figure 5. The same situati on as in Figure 4 is shown . Calculated biomass concentrations X I and X2 (left ) as we iI as nitrate and methanol concentrations during the 1.5 h 'denitrification' cycle (right ) are represe nted .

The shift from an aerobic to an anoxic methanol consumer cultivation effected the situation as show n in Figure 5: First . X 2. of which the inoculation is higher. dominated the syste m. After starting meth anol addition . it soon was outgrown by XI' which profited from the full y aerobic environment. Finall y. the

49

Population dynamics by methanol addition

cultivation shift benefited X 2 again, because of its higher anoxic growth rate. It has to be noted that X I and X2 are not two identified different species, but rather they are groups of organisms with related properties. Verification of the model The developed model was verified with the full-scale experiments performed at the wastewater treatment plant of Zurich-Werdholzli, which are described by Purtschert et at. (1996). The results indicate that the nitrate removal performance was improved by 20% due to the addition of methanol after an adaptation period of about IO days. However, the capacity to manage peak loads was low and part of the methanol was always lost to aerobic degradation due to the reactor configuration and the mode of dosage. According to extraordinary strong rainfalls between day 30 and 35, the biomass dilution rate Ox dramatically increased and caused a substantial biomass washout (Figures 6 and 7). This gave X I a selective advantage because more methanol got into the aerobic zone. Figure 7 clearly indicates that in the full-scale plant there was continuous competition between the two groups of organisms. Improved operating conditions could help to favor group X 2, which has more desirable stoichiometry and kinetics for full-scale denitrification. 0.5

----

600 500

0.4

'c '1

e

400 0.3 ;-

c

:!:!.

0 300

)(

0

0.2

S

c

F OO

~

0.1

100

o

0

o

5

10 15 20 25 30 35 40 45 50 55 60 65 time [d)

Figure 6. Verification with the full-scale experiments at WWTP of ZUrich-Werdhiilzli: The aerobic and the anoxic activities are represented as well as the methanol addition rate and the biomass dilution rate. 70

,-----------~

0.25

~~ 60

'e 50

0.20

~ 30

0.15 !!.

g 40 ~

)(

C"

20

0.10

10

O L-- - - - - - - - --' 0.05

o

10

20

30 40 time [d]

50

60

I

I

I I

------'

Figure 7. The same situation as in Figure 6 is shown. The biomass concentrations are represented and the biomass dilution rate to illustrate its dramatic effect.

50

I.

PURTSCHERT and W. GUIER

CONCLUSIONS Based on the laboratory study a mathematical model was formulated describing two different populations of methanol consumers XI and X2. Both groups are capable of degrading methanol aerobically and anoxically, while their different growth kinetics selectively favors the dominant population. Both organisms are inoculated by the influent wastewater and are therefore found all the year round at low concentrations in activated sludge. The verification of the model was performed by analysing datasets from full-scale experiments. The population group X I growing faster aerobically shows a higher yield coefficient than their competitors X2. Since a low sludge production is desired an optimised operation should favor the second group of organisms. As a consequence. the crucial criteria for the selection is the simultaneous availability of dissolved oxygen and methanol. Therefore, overdosing of methanol must be avoided. This is independent of the anoxic volume in the range of 10% to 60% of activated sludge reactor. In order to maintain an efficient denitrification. the anoxic zone should consist of at least 20% of the total tank volume and is preferably separated into two compartments, where the methanol dosage is directed to the first. At startup. a stepwise increase in methanol addition is advised in order to avoid excess methanol loss during the adaptation period. The full-scale denitrification performance leads to an overaIl consumption of 3.4 kg MeOH kg-INeliminated' which causes total operation costs of about 3.20 Sfr. kg-IN. If operating conditions favor group XI' the overall consumption will exceed 4.5 kg MeOH kg-INehminated' REFERENCES Duchars, M. G. and Attwood, M. M. (1989). The influence of C:N ratio in the growth medium on the cellular composition and regulation of enzyme activity in Hyphomicrobium X. J. Gen. Microbiol.• 135,787-793. Gliesche, C. G., Hirsch. P. and Holm. N. C. (1996). Hyphomicrobium sp im KI1Irwerk und im abwasserbelasteten Gewasser, Lemmer/GriebelFlemming(Hrsg.), Okologie der Abwasserorganismen. Springer-Verlag Berlin Heidelberg. Graezer-Lampart, D.• Egti, T. and Hamer G. (1986). Growth of Hyphomicrobium ZV620 in the Chemostat: Regulation of NH4assimilating enzymes and cellular composition, J. Gen. Microbiol., 132, 3337-3347. Gujer, W. (1990). Activated Sludge SIMulation Program - ASIM, MS-DOS, public domain. Henze, M., Grady, C.. Gujer, W., Marais. G. and Matsuo. T. (1987). Activated Sludge Model No. I, IAWPRC Task Group on Mathematical Modeling for Design and Operation of Biological Wastewater Treatment. IAWPRC Scientific and Technical Report No. I. Purtschert, I.. Siegrist. H. and Gujer, W. (1996). Enhanced denitrification with methanol at WWTP Zurich-Werdholzh. Waf. Sci. Tech.• 33(12), 177-126 Purtschert, I. (1997). Populationsdynamik bei Methanoleinsatz indenitrifizierenden Klaranlagen, Diu. ETII ZUrich. Nr. 12492. Reichert, P. (1994). AQUASIM - A tool for simulation and data analysis of aquaticsystems, Waf.Sci. Tech., 30,21 -30. Schmider, F. and Ouow, J. C. G. (1986). Charakterisierung der denitrifizierenden Mikroflora in den verschiedenen Reinigungsstufen einer bioJogischen KlllranJage. Archiv Hydrobiol., 106.497-512