1-Identification of Activated Sludge And

7/28/2019 1-Identification of Activated Sludge And

1/15

IDENTIFICATION OF ACTIVATED SLUDGE AND

WASTEWATER CHARACTERISTICS USING

RESPIROMETRIC BATCH-EXPERIMENTS

H. BROUWER1*, A. KLAPWIJK1*M and K. J. KEESMAN2

1Department of Environmental Technology, Wageningen Agricultural University, Bomenweg 2,NL-6703 HD Wageningen, The Netherlands and 2Department of Agricultural Engineering and Physics,

Wageningen Agricultural University, Bomenweg 4, NL-6703 HD Wageningen,The Netherlands

(First received June 1996; accepted in revised form August 1997)

AbstractThis paper presents a procedure to obtain activated sludge kinetics and wastewater character-istics from respirometric batch-experiments. For identication of state variables and model parametersa modied version of the ASM no. 1 that describes the oxygen uptake rate of the nitrication processand organic matter elimination was used. It is demonstrated that the maximum nitrication rate of acti-vated sludge and the concentration nitriable nitrogen, and the rapid hydrolysis rate together with theconcentration slowly biodegradable organic compounds can be estimated accurately. Suggestions toimprove identiability problems are given. It is concluded that the proposed method oers possibilitiesto follow changes in sludge capacities, for both heterotrophic and autotrophic micro-organisms, andwastewater composition.# 1998 Elsevier Science Ltd. All rights reserved

Key wordsactivated sludge, identication, respirometry, batch-experiments, characterization, bio-kinetic parameters, wastewater composition

NOMENCLATURE

iXB mass N per mass COD in biomass (gN gCOD1)

kH rate of hydrolysis (h1)

K half-saturation coecient: for heterotrophicbiomass (mgCOD l1); for autotrophic biomass(mgN l

1)r respiration rate (mgO2 l1 h1)rend initial endogenous respiration rate (mgO2 l

1 h1)S soluble substrate concentration (mgCOD l1)X particulate substrate concentration (mgCOD l1)Y yield coecient (mgCOD mg

1 COD)mm maximum specic growth rate (h

1)

IndicesS1 and S2 index relative to readily biodegradable organic

compound 1 and 2S index relative to slowly biodegradable organic

compoundsi index relative to inert matterNH and NO index relative to ammonia or nitriteA1 and A2 index relative to autotrophic biomass

Nitrosomonas or NitrobacterH inde x rel at ive t o h eter ot ro phic bio ma ssma x inde x rel at ive t o max imum r at espec inde x rel at ive t o s pec ic ra te

INTRODUCTION

For modelling as well as control purposes of waste-

water treatment plants, information about the

wastewater composition and activated sludge

characteristics is essential.

The traditional way of analyzing wastewater

composition is based on relatively simple physical-

chemical methods. Filters are used to distinguish

the soluble, colloidal and suspended fractions. The

physical-chemical method is, however, not process-

related and therefore not able to fractionate the

readily and slowly biodegradable part. This makes

wastewater characterization by the physical-chemi-

cal method less suitable for model simulation or

control purposes.

Recent studies were done to gain knowledge

about activated sludge and wastewater character-

istics from a so-called respirogram (Kappeler and

Gujer, 1992; Spanjers and Keesman, 1994; Spanjers

and Vanrolleghem, 1995; Vanrolleghem and Van

Daele, 1994; Dochain et al., 1995; Vanrolleghem et

al., 1995). A respirogram is obtained in a batch

assay where a sample of wastewater, or a com-

pound which can be biologically oxidized, is added

to a batch-vessel which contains a volume of en-

dogenous respiring activated sludge. After addition

the respiration rate is measured over a period of

time. The collected data compose a dynamic respir-

ation rate prole which provides good means to

determine wastewater characteristics and activated

sludge kinetics.

This paper presents the evaluation of a series ofrespirograms gained from the municipal wastewater

treatment plant Nijmegen (The Netherlands). The

Wat. Res. Vol. 32, No. 4, pp. 12401254, 1998# 1998 Elsevier Science Ltd. All rights reserved

Printed in Great Britain0043-1354/98 $19.00 + 0.00PII: S0043-1354(97)00334-5

*Author to whom all correspondence should be addressed.

1240


2/15

primary goal was to investigate the identiability of

biokinetic model parameters and initial state

variables from a wastewater respirogram only.

Additionally, the obtained wastewater fractionswere compared with the measured analytical data:

Nkj-N, NH4-N, COD and BOD5.

MODEL PARAMETER IDENTIFICATION

Structural and practical identiability

In the calibration of model parameters identia-

bility analysis plays an important role.

The key question of the identiability analysis

was dened by Dochain et al. (1995) as follows:

``Can we expect, given a set of measured state vari-

ables, to give the model parameters a unique value,

via parameter estimation?''

Herein a distinction was made in identiability

on the basis of the model structure only (structural

identiability; Dochain et al., 1995) or on the type

and quality of available data (practical identiabil-

ity; Vanrolleghem et al., 1995). Dochain et al.

(1995) studied the structural identiability of kinetic

models describing the activated sludge process from

the assumption that only respiration data were

available. They concluded, for four types of models,

that only a smaller set of the combinations of the

original parameters were structurally identiable. In

the case of a parameter that is structurally identi-

able it is not ensured that this parameter is alsopractically identiable. Vanrolleghem et al. (1995)

showed that when a limited set of data is used for

parameter estimation, the problem of highly corre-

lated parameters was disturbing the uniqueness of

the parameter estimates. In that case, a change in

one parameter can be compensated by a pro-

portional shift in another parameter, still producing

a satisfying t between the experimental data and

model predictions. Due to correlation's the esti-

mated parameters may vary over a broad range and

little physical meaning can be given to the par-

ameters obtained.

Parameter uncertainty evaluation

Dochain et al. (1995) showed that from a

modied ASM no. 1 seven combinations of the

ve original parameters were structurally identi-

able. In their modied model no nitrication nor

denitrication were considered and the death-

regeneration concept was abandoned. The ques-

tion arises: ``can the parameters, with the avail-

able experimental data, be given unique values''.

A useful tool to analyze the precision of par-

ameter estimates is the eigenvalue decomposition

of the covariance matrix (Vanrolleghem et al.,

1995; Lukasse et al., 1996).

Let us recall very briey the theory to study thepractical identiability of model parameters. The

uncertainty in least-squares parameter estimates yN

E RP, from given single output data y E RN and in

this case the available OUR data, is given by the

covariance matrix of the estimates,

Cov yN s2e

XTX

11

where s2e is the residual error variance to be esti-

mated from 1aN pN

k1etkjy2 and X is the

Jacobian matrix de(tkvy)/dyj with k = 1,...,N andj= 1,...,p.

In this particular case: e(tkvy) = OUR(tk) OU R (tk,y), with OU R (tk,vy)

2 as the pre-

dicted OUR response at time instant tk as a func-

tion ofy.

Eigenvalue decomposition of the covariance

matrix is dened by:

VT Cov yNV L 2

Where V is an orthogonal matrix of eigenvectors

and L is a diagonal matrix with eigenvalues. The el-

ements of L indicate whether a parameter combi-

nation, given the weights of the associated

eigenvector, aects the sum of squares. A small

eigenvalue (li) corresponds with a relatively large

uncertainty in the direction of the associated (Vi)

vector. If, for instance, an element Vi,j is large as

compared to other elements in this column, the cor-

responding parameter value is dicult to estimate

accurately. In other words: for this parameter the

respirogram is non-informative and consequently a

wide range of parameter values can be used to

describe the experimental data. Notice that in

equation 1 the term s2e stems from the output data

and since it is a scalar it can be interpreted as a

scaling factor. Consequently, the analysis could also

have been performed with the Fisher Information

Matrix. XTX directly, as in Vanrolleghem et al.

(1995).

ACTIVATED SLUDGE MODEL

Modied IAWQ-model

In order to investigate the identiability of bio-kinetic parameters and biodegradable wastewater

components a modied version of the ASM no. 1

(Henze et al., 1987) was used. The following modi-

cations and assumptions were introduced:

. Nitrication was modelled as a two-step process;

ammonia was converted to nitrite by

Nitrosomonas and nitrite was converted to nitrate

by Nitrobacter.

. Readily biodegradable organic substrate was split

up into two fractions (SS1 and SS2) (Spanjers and

Vanrolleghem, 1994).

. Slowly biodegradable organic substrate (XS) was,

due to hydrolysis, converted to SS2.. Hydrolysis was modelled as rst-order kinetics

(Sollfrank and Gujer, 1991).

Use of respirometry to characterise sludge 1241


3/15

. Due to the short term of this specic batch-exper-

iment the endogenous respiration was assumed to

be constant.

. iXB was assumed to be 0.086 gN gCOD1 (Henze

et al., 1987).

The modications were introduced because the

ASM no. 1, as such, was not able to produce a

satisfying t between modelled and measured respir-

ation data.

Not incorporated in the model were:

. Growth and decay processes of autotrophic and

heterotrophic biomass. These parameters were

left out of consideration because the experiments

performed didn't allow their estimation. Due to

the short term of the experiment and the low S0/

X0-ratio used (S0 and X0 were the initial substrate

and biomass concentration; expressed in COD),

decay respectively growth of biomass were di-cult to obtain.

. Hydrolysis of slowly hydrolysable organic matter

according to ASM no. 1.

. Denitrication, because dissolved oxygen was

non-limiting in the performed experiments.

. Ammonication, because this process was

assumed to be instantaneous (Henze et al., 1994).

From Table 1 it can be seen that the oxygen

uptake rate is composed of:

. oxidation of readily biodegradable organic com-

pound 1 (SS1) present in wastewater

. oxidation of readily biodegradable organic com-

pound 2 (SS2) present in wastewater and formedby hydrolysis of slowly biodegradable organic

compounds (XS)

. oxidation of ammonia (SNH, present in waste-

water) to nitrite

. oxidation of nitrite (SNO) to nitrate

. endogenous respiration

Parameter reduction

The model consisted of a large amount of par-

ameters and process variables. Some of the par-

ameters, like mm and XB (for both autotrophs and

heterotrophs) were structurally unidentiable fromrespiration data (Dochain et al., 1995). The amount

of parameters was therefore reduced by combining

non-identiable parameters to structurally identi-

able parameter combinations (Vanrolleghem and

Verstraete, 1993; Spanjers and Vanrolleghem, 1994;

Dochain et al., 1995). For instance, the maximum

nitrication rate (specic for Nitrosomonas) could

be measured with an excess of exogenous substrate

described by the following equation:

rNHmax

iXB

1

YA1

mm,A1XB,A1 3

In this equation iXB, YA1, mm,A1 and XB,A1 were

combined to one measurable parameter rNHmax.

EXPERIMENTAL PROCEDURE

The experimental set-up consisted of a batch-vessel (3 l)which was directly attached to a continuous respirometer(RA-1000; Manotherm). The respirometer is classied as a

continuous ow-through measurement which uses the DOconcentration in the liquid phase to calculate the respir-ation rate of the activated sludge (Spanjers et al., 1996).

Measuring principle. The peristaltic pump of the respi-rometer is continuously taking a sample of activatedsludge (24 l/h) from the batch vessel. After passing the res-piration vessel (0.75 l), where the dissolved oxygen at theinlet and outlet are measured, the sample is returning tothe batch vessel. Hereby the activated sludge is continu-ously recirculating. Due to the use of a single DO-elec-trode the measuring frequency is limited by the responserate of the DO-electrode (Spanjers and Klapwijk, 1990)and is xed at once a minute.

An important feature before the addition of substratecan take place is the state of respiration of the activatedsludge. Because one of the goals is to assess the biologicalcharacteristics of the wastewater, it is important that theactivated sludge is respiring in the absence of the exogen-ous substrate; also called the endogenous respiration(Spanjers and Klapwijk, 1990). The time period to aeratethe sludge before it reaches the endogenous state dependson the loading regime of the plant and the spot where thesludge was sampled. Roughly the sludge should be aeratedfor a period of 2 h without feed (Spanjers and Klapwijk,1990).

The experimental procedure was as follows:

1. Add a known volume of sludge to the batch-vessel.This may be sludge from the aeration tank or returnsludge.

2. Aerate the sludge for the time period until endogenousrespiration rate is reached. To detect this state, one canfollow the course of the measured respiration rate.

3. After the endogenous rate is reached a known volume

of pre-aerated wastewater can be added to the batchvessel containing the activated sludge. The sample ofwastewater has to be aerated rst to prevent a oxygen

Table 1. Model used for simulation wastewater respirogram

component -> i 1 2 3 4 5 6j process SS1 SS2 XS SO SNH SNO Process rate

1 growth heterotrophs on SS1 1

YH 1YH

YHiXB mm,H1

SS1KS1SS1

XBH

2 growth heterotrophs on SS2 1

YH 1YH

YHiXB mm,H2

SS2KS2SS2

XBH

3 growth N.somonas on SNH 3X43YA1

YA1iXB

1YA1

mm,A1SNH

KNHSNHXB,A1

4 growth N.bacter on SNO 1X14YA2

YA2iXB

1YA2

mm,A2SNO

KNOSNOXB,A2

5 endogenous respirationautotrophs and heterotrophs -1 rend

6 Hydrolysis XS 1 -1 kHXS

H. Brouwer et al.1242


4/15

drop in the batch-vessel which will aect the measuredrespiration rate.

4. After the addition of wastewater the respiration ratewill increase due to the oxidation of organic and nitro-gen compounds.

5. When the respiration rate has returned to the initialrate, i.e. the rate before adding wastewater (taking di-lution with wastewater into account), the completerespirogram is acquired.

At the municipal wastewater treatment plant ofNijmegen, a series of respirometric batch-experiments wereperformed on 6 dierent days. The Nijmegen plant has aplug-ow conguration and is mainly treating domesticwastewater. The batch-experiments were commenced bytransferring 0.9 l of pre-settled wastewater to 1.5 l ofreturn sludge in a batch-vessel of 3 l. The applied S0/X0-ratio equals the ratio as it enters the rst compartment ofthe full-scale installation. The experimental conditions arepresented in Table 2.

RESULTS AND DISCUSSION

Figure 1 shows the six respiration rate curves

gained after the addition of wastewater to thebatch-vessel containing endogenously respiring

sludge. Directly after the addition of wastewater to

the activated sludge the respiration rate increases

and within two minutes the maximum respiration

rate is reached. The gures contains rough data.

Observe that Fig. 1(af) shows a respirogram

with a double nitrogen tailing. A double tailing is

created when the conversion rate of nitrite into

nitrate (Nitrobacter) is lower than ammonia into

nitrite (Nitrosomonas) and consequently nitrite is

accumulated. A double nitrogen tailing is previously

recognized by Ossenbruggen et al. (1996).

For all six respirograms the model is used to esti-

mate the model parameters and state variables. In

Fig. 2 the measured and modelled total respiration

rate (16 June 1996) and the estimated respiration

rates for the ve wastewater components are

shown. The modelled respiration rate matches the

measured respiration rate.

Identiability analysis

The model contains 9 biokinetic parameters and

4 initial state variables, listed in Table 3.

Results of an eigenvalue decomposition of the co-

variance matrix of the estimated parameters are

given in Appendix A. From the matrix of eigenvec-

tors (Appendix A) we see that the vectors with thesmallest eigenvalues (column 10, 11, 12 and 13)

contains the following dominant weights on the

parameters and initial state variables: (1-YH)Ss1,

rSs1max and the saturation coecients (3.43-

YA1)KNH and (1.14-YA2)KNO (roughly, elements

>0.3). Consequently, these parameters/states are

dicult to obtain with the given experimental data

set. The poor identiability is conrmed by the sen-

sitivity plot (d/dy*y) of the parameters concerned.

From Fig. 3(ad) the derivatives of the residualsto the parameters and state variables become visible

and it is shown that for some parameters only a

small part of the curve is sensitive for a change of

the residual of the estimate. When only a very few

data points are related to the substrate induced res-

piration rate, for instance rSs1 (Fig. 1) and more-

over, as no saturation behaviour can be observed,

no information is retained to dierentiate between

rSs1max and (1-YH)KS1. In this case only the rst

order constant rSs1max/(1-YH)KS1 can be estimated.

Notice, furthermore, from Fig. 3(d) that the high

sensitive peaks of (1-YH)XS and kH coincides and

thus these parameters cannot be identied sepe-

rately in this particular experimental setup. A simi-

lar eect can also be seen from Fig. 3(b) for rNHmaxand (3.43-YA1) KNH.

Results of the identiability analysis are summar-

ized in Table 4.

The parameter combination (1-YH)XS and kHcan be estimated very precisely in combination.

However, this will not guarantee both parameters

can be separately estimated with the same accuracy.

To improve the reliability of estimation Lukasse

et al. (1996) suggested to reduce the amount of

model parameters by giving them xed values.

Those parameters which were not sensitive to the

model output were given a xed value and conse-quently the remaining model parameters could be

obtained with higher accuracy. Another approach

was suggested by Vanrolleghem et al. (1995). They

suggested the use of an optimal experimental de-

sign. Their results indicate that the parameter var-

iances could be decreased by a factor of 2 when an

amount of substrate is injected at an optimally cho-

sen time instant during the experiment.

Reduction of unknown model parameters also

can be achieved by the performance of isolated sub-

strate respirograms. With a sequential addition of

synthetic substrates of nitrite and ammonia the bio-

kinetic parameters of autotrophic bacteria can bededuced seperately. In this approach the calibrated

biokinetic parameters for autotrophic bacteria can

Table 2. Experimental conditions

Date MLSS pH Temp COD BOD5 S0/X0*

(June 1993) (g/l) () (8C) (mgCOD/ l) ( mgCO D/ l) (g COD/g COD)

16 1.6 6.58 20.5 311 160 0.08818 1.95 7.62 21 247 160 0.05721 1.69 7.69 21 363 170 0.09723 1.59 7.23 20.5 364 185 0.10324 1.7 6.9 19.5 344 180 0.09125 1.76 7.39 20 387 210 0.099



5/15

Fig 1. (a)(c).



6/15

Fig. 1. Wastewater respirograms obtained at 6 dierent days.



7/15

be used as default settings. The only model par-

ameters left to estimate are kH, rSmax and (1-YH)KS(in the case of one readily biodegradable organic

compound) and the wastewater components: (1-

YH)XS, (1-YH)SS and (3.43-YA1)SNH. This signi-

cantly reduces the number of unknown parameters

for parameter calibration of a wastewater respiro-

gram.

Biokinetic parameters

With the objective to obtain biokinetic constants

from batch cultivated biodegradation experiments it

is demonstrated that the applied S0/X0 is extremely

important (Chudoba et al., 1992; Novak et al.,

1994; Spanjers and Vanrolleghem, 1994). The S0/X0ratio determines whether catabolism or anabolism

prevails. When anabolism prevails, organisms have

sucient substrate for their growth and cell multi-

plication dominates above storage and accumu-

lation phenomena. In order to nd representative

kinetic parameters it is important to work at low

S0/X0 ratios. The threshold between low and highratios of S0/X0 is not strictly dened but may be

considered between an interval of 2 and 4 as a cor-

rect estimation (Chudoba et al., 1992).

The wastewater treatment plants generally work

at very low actual S0/X0 ratios. The applied actual

S0/X0 ratio varied between 0.057 and 0.103

(Table 2). Therefore it is expected that the observed

biokinetic parameters will represent true values. The

estimated biokinetic heterotrophic parameters aregiven in Fig. 4 and Fig. 5. The parameter values

found are readily in agreement with values reported

in literature using similar calibration techniques

(Spanjers and Vanrolleghem, 1994). However, half-

saturation coecients found by other research

groups show signicantly higher values: 2.5 to

4 mgCOD/l (Kappeler and Gujer, 1992), 5 mgCOD/

l (Sollfrank and Gujer, 1991) and 20 mgCOD/l

(Henze et al., 1987). Dierences found can be

explained by the applied experimental conditions.

Kappeler and Gujer worked at a very high S0/X0ratio which resulted in a considerable population

shift among the fast-growing/low-anity organisms(Grady et al., 1996).

Fig. 2. Wastewater respirogram (16 September 1993) with measured and modelled respiration rates.

Table 3. Model parameters, parameter combinations and state variables

parameterparameter

combination unit state variableparameter

combination unit

rSs1max1

YH1mmYH1XBH (mgCOD/l.h) SS1* (1-YH) SS1 (mgCOD/l)

rSs2max1

YH2mmYH2XBH (mgCOD/l.h) SS2* (1-YH) SS2 (mgCOD/l)

rNHmax iXB 1

YA1mmYA1XBYA1 (mgNH4-N/l.h) XS* (1-YH) XS (mgCOD/l)

rNOmax iXB 1

YA2mmYA2XBYA2 (mgNO2-N/l.h) SNH* (3.43-YA1) SNH (mgNH4-N/l)

KS1* (1-YH) KS1 (mgCOD/l)

KS2* (1-YH) KS2 (mgCOD/l)KNH* (3.43-YA1) KNH (mgNH4-N/l)

KNO* (1.14-YA2) KNO (mgNO2-N/l)kH - (1/h)

* Under the assumption of known biomass yield (YH, YA1 and YA2).



8/15

Figure 6 and Fig. 7 graphically show the time

variation in the specic maximum substrate elimin-

ation rate for Nitrosomonas and Nitrobacter.

Taking into account the poor identiability of

rNOmax (Appendix A), special care should be paid

to these values. On June 23 and 24 the observed

respirogram shows only one tailing. From this

type of respirogram it is obvious that no infor-mation regarding the conversion of nitrite can be

obtained.

The maximum conversion rate shows a high vari-

ation for both nitrifying organisms. Spanjers and

Vanrolleghem (1995) observed, at the applied S0/X0ratio of 0.05, the wastewater appeared to be inhibi-

tory to nitrication. Inhibition of nitrication was

not veried. However, due to a low pH on June 16

and 24 (Table 2) inhibition of the nitrication rate

could have been occurred. In the case of inhibitionof nitrication due to a decreasing pH, the maxi-

mum nitrication rate for both organisms are

Fig 3(a)(b) caption overleaf.

Table 4. Identiability classication of a combination of biokinetic model parameters and initial state variables for this specic exper-imental design (Fig. 1)

IdentiabilityGood Bad

(1-YH)XS and kH (1-YH)Ks1 and rSs1maxrNHmax; (3.43-YA1)SNH and (1-YH)XS; (1.14-YA2)KNO(1-YH)XS; rNHmax and rSs2max (1-YH)Ss1 and (3.43-YA1)KNHrSs2max and (1-YH)Ss2



9/15

Fig. 3. Sensitivity plot of the model parameters and state variables.

Fig. 4. Estimated specic maximum substrate elimination rates for heterotrophic organisms (95% errorbounds).



10/15

underestimated. Consequently, the area of the curve

which is attributed to oxidation of XS is estimated

larger and a smaller area is attributed to the oxi-

dation of SNH which results in an overestimation of

XS and underestimation of SNH.

According to the ASM no. 1 the hydrolysis

constant kH slightly depends on the biomass con-centration but mainly relies on temperature.

Hence, in many activated sludge models hydroly-

sis of slowly biodegradable organic substrate is

simplied to a rst order conversion. Because it

is not possible to deduce the hydrolysis rate of

slowly biodegradable COD from a 2-h exper-

iment it is suggested to characterize the hydroly-

sis process as fast hydrolysis (Sollfrank and

Gujer, 1991; Spanjers and Vanrolleghem, 1995).

The hydrolysis rate of slowly biodegradable organic

substrate is given in Fig. 8.

The hydrolysis shows a rather constant rate,except on June 24. The estimated values are in the

range of previous works. Dierences can be

explained by the medium or temperature which is

used to obtain the hydrolysis rate. In some cases a

dierent time scale is used.

Fig. 5. Estimated half-saturation coecients readily biodegradable compounds SS1 and SS2 (assumedYH=0.67); (95% error bounds).

Fig. 6. Estimated specic maximum substrate elimination rate for Nitrosomonas and Nitrobacter(assumed YA1=0.18 and YA2=0.06); (95% error bounds).



11/15


12/15

Table 5 lists the values of hydrolysis rates which

are reported by several authors and their exper-

imental designs used.

Wastewater composition

A basic problem of the experimental set-up used

is the fact that addition of wastewater in the batchvessel led to a delayed increase of the respiration

rate in the attached respirometer. The assumption

that the initial substrate concentration could be cal-

culated from the injection at time zero was incor-

rect. This phenomenon could be corrected by

injecting the sample of wastewater in both batch

and respiration vessel in appropriate amounts

(equal dilutions), or by applying mass balances for

both vessels as done by Spanjers and Vanrolleghem

(1994). Because the maximum respiration rate was

reached within 2 min after the addition we think

the possible error made was almost negleglible.

The estimated and analytical measured waste-water composition are given in Fig. 9. For the esti-

mation of dierent wastewater fractions the

heterotrophic yield (YH) determines the absolute

concentration of COD and, indirectly, via N-incor-

poration into biomass, the concentration nitriable

nitrogen. With the assumption of YH=0.67, and

Fig. 9. Estimated organic wastewater fractions: XS, Ss1, Ss2; assumed XBH and measured total COD,euent COD (Xi + Si) and BOD5 (assumed YH=0.67).

Fig. 10. Cumulated total COD calculatedfor YH=0.5 and 0.67, compared to measured total COD.



13/15

taking into account that 20% of the inuent COD

exist of biomass (Henze, 1992), the estimated cumu-

lated organic fractions SS1, SS2, XS, Xi+Si (inert

COD) and XBH are somewhat higher than the ana-

lytical measured total COD (Fig. 10). From Fig. 10

it can be seen that an applied YH of 0.5 corre-

sponds more reasonable to the measured values.

The estimated nitriable nitrogen concentration

shows some inconsistency with the nitrogen found

from chemical analysis (Fig. 11). Spanjers and

Vanrolleghem (1995) found values in good agree-

ment with the ammonia concentration found by

analysis. They rst calculated YA1 from a dosage of

known amount of ammonia and used this value to

obtain the ammonia concentration from the waste-

water experiment. YA1 values of 0.36 and 0.56 were

found. Dierences could be explained by a poorly

controlled pH during the experiment (Table 2),

which is aecting the estimated maximum oxidation

rates and consequently the inuent composition.

Therefore we would like to stress that it is very im-portant to keep the pH constant at a non-inhibiting

level.

CONCLUSIONS

From identiability analysis it is found that from

a wastewater respirogram the maximum nitrication

rate of activated sludge and the concentration nitri-

able nitrogen, and the hydrolysis rate in combi-

nation with the concentration slowly biodegradable

organic compounds can be estimated accurately for

the given system and experiment.

The reliability of estimation of model parametersand state variables depends on the respiration pro-

le and chosen model structure. It is recommended

that the results of an eigenvalue decomposition of

the covariance matrix related to given respirograms

be evaluated.

To improve the identiability of wastewater com-

position the number of unknown model parameters

should be reduced. In this paper it is suggested that

the biokinetic parameters be obtained separately,

with the addition of a sequence or mixture of syn-

thetic substrates. The assessed biokinetic parameters

can then be used as default values which favour the

estimation of the remaining unknown model par-

ameters.

Finally, it is demonstrated that respirometric

batch-experiments are a useful tool in obtaining

some activated sludge and wastewater character-

istics. Automation of the procedure could make it

possible to follow changes of activated sludge as

well as wastewater characteristics in time and is

therefore recommended.

AcknowledgementsThe authors wish to thank AnnekeRinia and Ron Blokzijl for their assistance in the researchcarried out. Jacques Segers and Dennis Piron from``Zuiveringsschap Rivierenland'' are thanked for their co-operation during the research.

REFERENCES

Chudoba P., Capdeville B. and Chudoba J. (1992)Explanation of biological meaning of the S0/X0 ratio inbatch cultivation. Wat. Sci. Techn. 26, 743751.

Dochain D., Vanrolleghem P. and Daele van D. (1995)Structural identiability of biokinetic models of acti-vated sludge respiration. Wat. Res. 29, 25712578.

Grady C. P. Jr., Smets B. F. and Barbeau D. S. (1996)

Variability in kinetic parameter estimates: a review ofpossible causes and a proposed terminology. Wat. Res.30(3), 742748.

Fig. 11. Estimated and analyzed nitrogen wastewater fractions: SNH (nitriable nitrogen) and NH4-Nand Nkj-N (assumed YA1=0.18 and YA2=0.06).



14/15

Henze M., Grady C.P.L., Gujer W., Marais G.v.R. andMatsuo T. (1987). Activated sludge Model No.1.IAWPRC Scientic and Technical Report No.1,IAWPRC, Londen.

Henze M. (1992) Characterization of wastewater for mod-elling of activated sludge processes. Wat. Sci. Tech. 25,115.

Henze M., Gujer W., Mino T., Matsuo T., Wentzel M. C.and Marais G. v. R. (1994). Activated Sludge ModelNo. 2. IAWQ Scientic and Technical Reports. Preprintfor IAWQ Specialised Seminar on Modelling and Controlof Activated Sludge Processes, Copenhagen.

Kappeler J. and Gujer W. (1992) Estimation of kineticparameters of heterotrophic parameters under aerobicconditions and characterization of wastewater foractivated sludge modelling. Wat. Sci. Tech. 25, 1992,125139.

Lukasse L. J. S., Keesman K. J. and Straten van G.(1996) Grey-box identication of dissolved oxygendynamics in activated sludge processes. Proc. 13th IFAC

World Congress, July 1996.Novak N., Larrea L. and Wanner J. (1994) Estimatiom ofmaximum specic growth rate of heterotrophic andautotrophic biomass: a combined technique of math-ematical modeling and batch cultivations. Wat. Sci.Tech. 30, 171180.

Ossenbruggen P. J., Spanjers H. and Klapwijk A. (1996)Assesment of a two-step nitrication model for activatedsludge. Wat. Res. 30, 939953.

San Pedro D. C., Mino T. and Matsuo T. (1994)Evaluation of the rate of hydrolysis of slowly biode-gradable COD (SBCOD) using starch as substrateunder anaerobic, anoxic and aerobic conditions. Wat.Sci. Tech. 30, 191199.

Sollfrank U. and Gujer W. (1991) Characterization ofdomestic wastewater for mathematical modelling of theactivated sludge process. Wat. Sci. Tech. 23, 10571066.

Spanjers H. and Klapwijk A. (1990). On-line meter for

respiration rate and short-term biochemical oxygendemand in the control of the activated sludge process.In Advances in Water Pollution Control, Proc. 5thIAWPRC Workshop, 26 July3 August, Yokohama andKyoto, Japan.

Spanjers H. and Vanrolleghem P. A. (1994). 50th PurdueIndustrial Waste Conference, Lewis, pp. 611118, 1995.

Spanjers H. and Keesman K. J. (1994). Identication ofwastewater biodegradation kinetics. Proceedings 3thIEEE. Conference on Control Applications, 2426August, Glasgow, Scotland, pp. 10111016.

Spanjers H. and Vanrolleghem P. A. (1995) Respirometryas a tool for rapid characterization of wastewater andactivated sludge. Wat. Sci. Tech. 31(2), 105114.

Spanjers H., Vanrolleghem P. A., Gustaf O. and DoldP. (1996) Respirometry in control of the activated

sludge process. Wat. Sci. Tech. 34(2), 117126.Vanrolleghem P. A. and Verstraete W. (1993)Simultaneous biokinetic characterization of hetero-trophic and nitrifying populations of activated sludgewith an on-line respirographic biosensor. Wat. Sci.Tech. 28, 377387.

Vanrolleghem P. A. and Van Daele M. (1994) Optimalexperimental design for structure characterization ofbiodegradation models: on-line implementation in arespirographic biosensor. Wat. Sci. Tech. 30, 243253.

Vanrolleghem P. A., Van Daele M. and Dochain D.(1995) Practical identiability of a biokinetic modelof activated sludge respiration. Wat. Res. 29, 25612570.

Appendix overleaf.



15/15

APPENDIX

A

EigenvalueDecompositio

noftheCovarianceMatrix

(1-YH)S

s1

0.00

0.01

0.02

0.05

0.07

0.00

0.39

0.29

0.13

0.64

0.57

0.06

0.04

(1-YH)S

s2

0.18

0.14

0.30

0.21

0.84

0.21

0.18

0.00

0.06

0.13

0.06

0.01

0.01

(1-YH)X

s

0.34

0.35

0.70

0.30

0.07

0.08

0.11

0.24

0.25

0.12

0.13

0.01

0.00

kH

0.91

0.08

0.21

0.30

0.16

0.09

0.03

0.05

0.03

0.00

0.00

0.00

0.00

rNHmax

0.12

0.66

0.43

0.26

0.13

0.08

0.07

0.23

0.24

0.26

0.29

0.02

0.00

rNOmax

0.02

0.02

0.05

0.09

0.21

0.91

0.01

0.06

0.14

0.06

0.10

0.29

0.01

(3.43-YA

1)SNH

0.02

0.61

0.22

0.19

0.01

0.16

0.14

0.42

0.45

0.23

0.25

0.04

0.00

rSs2max

0.13

0.17

0.36

0.75

0.30

0.02

0.27

0.02

0.23

0.02

0.22

0.05

0.00

(3.43-YA

1)KNH

0.01

0.11

0.08

0.07

0.04

0.02

0.02

0.27

0.51

0.55

0.59

0.03

0.01

(1.14-YA

2)KNO

0.01

0.01

0.01

0.04

0.06

0.28

0.03

0.02

0.04

0.06

0.03

0.95

0.04

(1-YH)Ks1

0.01

0.01

0.02

0.02

0.08

0.04

0.14

0.47

0.34

0.25

0.17

0.03

0.74

(1-YH)Ks2

0.01

0.03

0.05

0.30

0.28

0.01

0.81

0.22

0.26

0.08

0.23

0.05

0.00

rSs1max

0.01

0.01

0.03

0.03

0.08

0.04

0.18

0.53

0.37

0.24

0.15

0.02

0.67

Eigenvalues

8.20E+

05

9.80E+

04

4.53E

+

04

3.10E+

04

1.46E+

04

7.22E+

03

2.98E+

03

1.60E+

03

1.35E+

03

1.74E+

02

1.48E+

02

3.07E+

01

2.59E+

00


Documents

1-Identification of Activated Sludge And