Application of the ADM1 model to advanced anaerobic digestion

Bioresource Technology 96 (2005) 1832–1842

Application of the ADM1 model to advanced anaerobic digestion

Wayne J. Parker *

Department of Civil Engineering, University of Waterloo, Waterloo, Ont., Canada N2L 3G1

Received 20 November 2003; received in revised form 3 January 2005; accepted 5 January 2005

Available online 8 March 2005

Abstract

In this paper the ADM1 model that has been developed by the IWA Task Group for Mathematical Modelling of Anaerobic

Digestion Processes is summarized. The model was applied to a variety of anaerobic digestion scenarios that are presented in the

literature and for each data set the model predictions were compared to experimental values. Based upon the model applications

it was apparent that for accurate model simulations the influent sludge should be well characterized in terms of biodegradable

and recalcitrant COD and also nitrogenous compounds. In almost all cases the model was able to reflect the trends that were

observed in the experimental data however the concentrations of VFAs were consistently over-predicted in digesters with short

SRTs. It would appear that the inhibition functions associated with low pH values tend to overestimate the impact of pH on bioki-

netic rates for the acid-consuming bacteria. Application of the model with flow through of active biomass between digesters in series

in temperature-phased systems needs to be further evaluated in the future.

� 2005 Elsevier Ltd. All rights reserved.

Keywords: Anaerobic digestion; Two-phase; Temperature-phased; Mesophilic; Thermophilic; Model; Sludge

1. Introduction

Owners and operators of wastewater treatmentplants are increasingly considering the use of advanced

digestion technologies for producing pathogen-free bio-

solids and for enhancing sludge stabilization. Some

examples of such technologies include staged thermo-

philic (Krugel et al., 1998), temperature-phased (TPAD)

(Han et al., 1997), two-phase (Ghosh, 1987) and three-

phase digestion (Drury et al., 2002). With the increasing

complexity of these processes it is difficult to evaluatethe impact of all process variables on the performance

of the digesters. Hence, it is difficult to optimize the

design and operation of these processes. Pilot testing

for the purposes of optimization is challenging due to

the extended time periods that are required to operate

0960-8524/$ - see front matter � 2005 Elsevier Ltd. All rights reserved.

doi:10.1016/j.biortech.2005.01.022

* Tel.: +1 519 888 4567x6324; fax: +1 519 888 4349.

E-mail address: [email protected]

these processes. Given these factors, the use of models

for predicting process performance over a range of

design and operating conditions becomes attractive.Over the years a range of models have been develo-

ped for modeling anaerobic digestion processes. Early

models were steady state and assumed a rate-limiting

step (Lawrence, 1971). However, the increasing com-

plexity of the advanced digestion technologies requires

more complex models that can represent the impacts

of changing environments on chemical and microbial

species. Based on reports in the literature there is evi-dence of a number of multi-species models that are

based upon differing assumptions and have differing

configurations (Angelidaki et al., 1999; Pavlostathis

and Gossett, 1986; Siegrist et al., 1993). Relatively re-

cently there has been a move by the International Water

Association�s (IWA) Task Group for Mathematical

Modelling of Anaerobic Digestion Processes to develop

a common model that can be used by researchers andpractitioners (IWA, 2002). This model (ADM1) has a

mailto:[email protected]

W.J. Parker / Bioresource Technology 96 (2005) 1832–1842 1833

structure that is similar to the IWA activated sludge

models that have received acceptance by practitioners

over the last 10 years. The application of a version of

the model to municipal sludge digestion has been de-

scribed by Siegrist et al. (2002).

The objective of this study was to examine the appli-cation of the ADM1 model to advanced digestion tech-

nologies. This paper presents an overview of the model

structure and assumptions and defines important model

inputs. A description of the model application to exist-

ing data sets for a variety of anaerobic digester configu-

rations will be presented. The impact of modifying

process parameters on process performance, as pre-

dicted by the model, will be summarized. Difficultiesencountered in model use and recommendations for

modifications will be presented.

2. Model description

The ADM1 model is described in considerable detail

in the report prepared by the IWA Task Group forMathematical Modeling of Anaerobic Digestion Pro-

cesses (IWA, 2002). The following provides a brief over-

view of the model for the purposes of this discussion.

The ADM1 model is a structured model that reflects

Complex ParticulateOrganic Matter (Xc

Carbohydrates (Xch) Proteins (Xpr)

AminoAcids(Saa)

Methane (Sch4)

Sugars(Ssu)

Propionate (Spro)

Acetate (Sac)

Fig. 1. Conceptual mode

the major processes that are involved in the conversion

of complex organic substrates into methane and carbon

dioxide and inert byproducts. In Fig. 1 an overview of

the substrates and conversion processes that are ad-

dressed by the model is presented. From Fig. 1 it can

be seen that the model includes disintegration of com-plex solids into inert substances, carbohydrates, proteins

and fats. The products of disintegration are hydrolyzed

to sugars, amino acids and long chain fatty acids

(LCFA) respectively. Carbohydrates and proteins are

fermented to produce volatile organic acids (acido-

genesis) and molecular hydrogen. LCFA are oxidized

anaerobically to produce acetate and molecular hydro-

gen. Propionate, butyrate and valerate are convertedto acetate (acetogenesis) and molecular hydrogen. Meth-

ane is produced by both cleavage of acetate to methane

(aceticlastic methanogenesis) and reduction of carbon

dioxide by molecular hydrogen to produce methane

(hydrogenotrophic methanogenesis).

To address these mechanisms, the model employs

state variables to describe the behaviour of soluble and

particulate components. All organic species and molecu-lar hydrogen are described in terms of chemical oxygen

demand (COD). Nitrogenous species and inorganic car-

bon species are described in terms of their molar concen-

trations. Soluble components are those that can pass

)

Fats (Xli)

Long Chain Fatty Acids

(Sfa)

Butyrate (Sbu) Valerate (Sva)

Hydrogen (Sh2)

InertParticulates

(XI)

InertSoluble

(SI)

l for ADM1 model.

Table 1

Data sets referenced in this study

Digester configuration Sludge source References

Single stage

mesophilic digestion

Mixed PS and WAS Cacho Rivero et al.

(2002)

Acid phase digestion PS Eastman and

Ferguson (1981)

Temperature-phased

anaerobic digestion

PS Han and Dague

(1995)

Mixed PS and WAS Han et al. (1997)

Two-phase digestion Mixed PS and WAS Ghosh (1987)

1834 W.J. Parker / Bioresource Technology 96 (2005) 1832–1842

through microbial cellular walls and include the mono-

mers of complex polymers (sugars, amino acids, long

chain fatty acids), volatile organic acids (propionate,

butyrate, valerate, acetate), hydrogen, and methane. In

Fig. 1, soluble species are represented with a capital

‘‘S’’. In addition to the organic species, the model ad-dresses inorganic carbon (carbon dioxide and bicar-

bonate) and nitrogenous species (ammonia and

ammonium). All of the species that dissociate as a func-

tion of pH (VFAs and ammonia) have variables defined

for both the protonated and non-protonated species.

The model maintains a charge balance among ionic spe-

cies and hence there are variables for inorganic anions

and cations including the hydrogen ion. The modelsolves for the hydrogen ion concentration, and thereby

the pH, by ensuring chemical neutrality in solution.

Particulate species consist of either active biomass

species or particulate substances that are incapable of

directly passing through bacterial cell walls. In Fig. 1

particulate species are those with a capital ‘‘X’’. The

microbial species that are considered in the model in-

clude sugar fermenters, amino acid fermenters, LCFAoxidizers, butyrate and valerate oxidizers, propionate

oxidizers, aceticlastic methanogens and hydrogeno-

trophic methanogens. Non-microbial particulate species

include complex organics that either enter the process in

the influent or that result from the death and decay of

microbial species and the products of disintegration of

the complex organics. This latter group consists of car-

bohydrates, proteins and LCFAs.Substrate conversion processes are described by a

number of kinetic expressions that describe the conver-

sion rates in terms of substrate concentrations and rate

constants. The disintegration of Xc and hydrolysis of

Xch, Xpr and Xli are described by first order rate expres-

sions. Substrate conversion processes have Monod-type

kinetic expressions while endogenous decay processes

are first order in biomass concentration. It should benoted that the ADM1 model differs from the ASM mod-

els in that microbially mediated processes are defined in

terms of substrate conversion as opposed to microbial

growth. For each of the above-mentioned processes

the rate of generation of products is related to the pro-

cess rate through stoichiometric coefficients. For exam-

ple the rate of growth of an organism is related to the

rate of substrate consumption through the yield coeffi-cient for the organism on the substrate. This format is

consistent with the approach that is employed in the

ASM models.

It is recognized that a number of the conversion pro-

cesses that are active in anaerobic digestion of municipal

sludges can be inhibited by the accumulation of interme-

diate products such as molecular hydrogen, ammonia or

by extremes of pH. In the model, all microbially medi-ated substrate conversion processes are subject to inhibi-

tion by extremes of pH. All anaerobic oxidation

processes are subject to inhibition by accumulation of

molecular hydrogen and aceticlastic methanogenesis is

inhibited at elevated free ammonia concentrations. Inhi-

bition that is caused by molecular hydrogen and free

ammonia is implemented in the model by employing

rate multipliers that reflect non-competitive inhibition.An empirical correlation is employed as a process rate

multiplier to reflect the effects of extreme pH.

Liquid–gas mass transfer of gaseous components

(methane, carbon dioxide and molecular hydrogen) is de-

scribed by mass transfer relationships. Hence the appli-

cation of the model equations requires separate mass

balances for the liquid and gas phases of the components.

3. Model application

In this study a selected number of data sets were

chosen from previously published reports on anaerobic

digestion of municipal wastewater sludges. Data sets

were selected to encompass a range of digester configu-

rations and on the basis of the completeness of the datasets that would be employed for model inputs and for

comparison with model predictions. In all cases, studies

that employed actual sludges from municipal waste-

water treatment plants were selected. The data sets that

were employed in this study are described in Table 1.

The ADM1 model employs a large number of con-

stants and coefficients. Given the model complexity it

was impossible to calibrate the model parameters withany of the data sets that were available. In the report

describing the ADM1 model the authors reviewed the

previously published reports on anaerobic digestion pro-

cesses and presented recommended values for model

parameters. For the purposes of this study the recom-

mended model parameters were employed unless addi-

tional information was provided by the original

researchers that allowed for an improved estimate ofthe model parameters.

In order to achieve accurate model predictions it

is important to define the properties of the sludge stream

entering the digester. For organic substances, the

ADM1 model defines these inputs in terms of soluble

and particulate COD. For municipal sludges a majority


of the organic loading is associated with the particulate

COD. The particulate COD entering the digester is de-

fined in terms of biodegradable (Xc) and non-biodegrad-

able components. Estimation of these parameters is

often challenging for many data sets as in many cases

the sludge COD is not reported and in almost all casesthe biodegradable fraction is not independently mea-

sured. In most cases the sludge is characterized in terms

of its volatile solids content.

The relationship between volatile solids content and

COD will depend upon the relative contribution of pri-

mary (PS) and waste activated sludge (WAS) to the

sludge composition (Parkin and Owen, 1986). Primary

sludges typically contain approximately 2.0 kg COD/kgVS while WAS typically has a value of 1.4 kg COD/kg

VS for this parameter. The inlet COD can therefore be

estimated on the basis of these typical values if the rela-

tive contributions of PS and WAS are known.

The biodegradable fraction of the sludge particulate

COD will also be a function of the sludge make-up.

Primary sludges have been estimated to have a COD

‘‘ultimate’’ biodegradability of 69% (Parkin and Owen,1986). The biodegradable fraction of WAS is dependent

upon the sludge age that is employed in the aeration

process (Gossett and Belser, 1982). Sludges that have ex-

tended solids residence times (SRT) in the aeration basin

will have been highly oxidized and hence will be rela-

tively recalcitrant to biodegradation in anaerobic diges-

tion. The ultimate biodegradability of WAS has been

found to range from 30% to 50% over the range of SRTstypically employed in wastewater treatment processes.

Hence, it is apparent that accurate application of the

model requires a detailed characterization of the inlet

sludge composition. The sludge composition should be

determined in terms of COD and the biodegradable

fraction should be determined. This latter parameter

could be determined through the use of a long term

batch digestion test to identify the maximum biodegrad-ability of the sludge. While there are no standard proto-

cols for such a test, existing anaerobic biodegradability

protocols could presumably be adapted for this purpose.

If the contribution of PS and WAS to the digester feed

were to vary substantially with time, then this testing

should be performed on the PS and WAS streams sepa-

rately. The properties of the composite sludge as a func-

tion of time could subsequently be estimated.The ADM1 model also estimates the behaviour of

nitrogen compounds in anaerobic digestion. In the cases

of municipal sludges the presence of ammonia nitrogen

in the inlet and the release of ammonia from decay of

solids has a substantial influence on the buffering of

pH. As will be demonstrated later in this paper the con-

centration of ammonia/ammonium in the inlet can have

a substantial impact upon the pH of acid-phase digestersthat have a relatively short SRT. In addition, the diges-

tion of highly concentrated sludges can result in the re-

lease of elevated concentrations of ammonia that can be

inhibitory to aceticlastic methanogens (IWA, 2002). It is

therefore important to characterize the concentration of

ammonia/ammonium in the digester inlet as well as the

nitrogen content of the sludges. It should be noted that

the ADM1 model does not maintain a perfect massbalance on nitrogen (Blumensaat and Keller, 2005).

Ammonium that is taken up by microbial growth is

not completely released during subsequent decay.

Hence, it can be expected that the model will underesti-

mate the concentrations of ammonium.

The data sets employed in this study did not contain

all of the information that was previously described.

Where necessary, typical values were assumed. The im-pact of these assumptions on model predictions will be

subsequently discussed.

3.1. Single stage mesophilic digestion

Cacho Rivero et al. (2002) reported a study that as-

sessed the impact of digester SRT on mesophilic an-

aerobic digestion of mixed PS and WAS. A series ofdigesters were operated over SRTs ranging from 5 to

40 days. In their paper the sludge COD, ammonia and

TKN content and VFA composition were detailed.

For this study, the biodegradable COD was estimated

by extrapolating the results that were obtained for ex-

tended SRTs. In their study COD removal, ammonia

and TKN content as well as VFA concentrations in

the digested sludges were reported and were employedfor comparison with the model predictions.

The comparison of the model predictions for effluent

COD, NH4/NH3-N, and VFAs is summarized in Fig. 2.

The error bars in Fig. 2 represent 1 standard deviation

of the experimental data. From Fig. 2 it can be seen that

the model was able to predict the effluent COD with

considerable accuracy. Nitrogen concentrations were

accurately predicted for the shorter SRTs and whilethe trend of increasing concentrations with increasing

SRT was reproduced, the absolute values that were pre-

dicted at longer SRTs were somewhat lower that the ob-

served values. The differences in nitrogen concentrations

may have been due to the lack of mass balance on nitro-

gen in the ADM1 model. It would be expected that

under conditions where there is substantial solids

destruction that the model would underestimate the con-centrations of ammonium-nitrogen.

The differences between the model predictions and the

observed results may also have resulted from differences

between the assumed and the actual protein content of

the sludge. The reference did not provide any informa-

tion on the distribution of carbohydrates, proteins and

lipids in the sludge and hence the default model values

were employed for this parameter.The model predictions for VFA concentrations were

relatively accurate for SRTs greater than or equal to

0

5

10

15

20

25

30

5 10 20 40

SRT (d)

CO

D (g

/L)

ModelExperimental

0

500

1000

1500

2000

2500

5 10 20 40

SRT (d)

NH

4/NH

3-N

(mg/

L)

ModelExperimental

0

200

400

600

800

1000

1200

1400

1600

1800

5 10 20 40

SRT (d)

Ace

tic A

cid

(mg/

L)

ModelExperimental

0

50

100

150

200

250

300

5 10 20 40

SRT (d)

Prop

ioni

c A

cid

(mg/

L)ModelExperimental

-20

0

20

40

60

80

100

5 10 20 40

SRT (d)

But

yric

Aci

d (m

g/L)

ModelExperimental

-60

-40

-20

0

20

40

60

80

100

5 10 20 40

SRT (d)

Vale

ric A

cid

(mg/

L)

ModelExperimental

Fig. 2. Comparison of model predictions with data of Cacho Rivero et al. (2002).


10 days. However the model clearly overpredicted theconcentration of acetate while underpredicting the con-

centrations of propionate, butyrate and valerate. These

results suggest that the rates of oxidation of propionate,

butyrate and valerate were somewhat overestimated by

the model and this would partially, but not completely,

explain the elevated acetate concentrations. It would

appear that the rate at which acetate was converted to

methane at the lower SRT was somewhat under-estimated. This may have resulted from either underesti-

mation of the substrate consumption coefficients for

aceticlastic methanogenesis or an overestimation of the

inhibition of this activity by ammonia. The model pre-dicted a 40% reduction in the activity of these organisms

due to the presence of ammonia. The impact of reduced

rates of aceticlastic activity on model predictions would

be greatest at the lower SRTs.

3.2. Acid phase digestion

Eastman and Ferguson (1981) performed one of thefirst detailed studies on the acid-phase digestion of mu-

nicipal sludges. In their study, the impact of HRT was

assessed over a range from 9 to 36 h. The impact of seed


culture was also evaluated. The model does not have the

capability to address this parameter and hence only the

tests that were conducted with raw sludge as the seed

were employed for this analysis. The model predictions

for ammonia/ammonium-N, pH and total volatile acids

(as acetate) were compared with the observed values inFig. 3.

From Fig. 3 it can be seen that the model somewhat

underpredicted the organic acid concentrations at the

lowest SRT of 9 h and overpredicted these values for

the longest SRT of 72 h. The underprediction of acid

0

2

4

6

8

10

12

9 18 36 72

SRT (hrs)

VFA

(g C

OD

/L)

ModelExperimental

0

1

2

3

4

5

6

7

9 18 36 72

SRT (hrs)

pH

ModelExperimental

0

100

200

300

400

500

600

700

800

9 18 36 72

SRT (hrs)

NH

4-N

(mg/

L)

ModelExperimental

Fig. 3. Comparison of model predictions with data of Eastman and

Ferguson (1981).

concentrations at 9 h is in agreement with the overesti-

mation of the effluent pH in this test. It would appear

that the model underestimated the rates of disintegra-

tion, hydrolysis and acidification under these relatively

extreme conditions of SRT and pH. It should be noted

that the model does not correct any of the disintegrationor hydrolysis rates for pH. Ghosh (1987) has demon-

strated that the rate of hydrolysis is influenced by pH.

An improvement of the model for addressing acid phase

digesters would be to include a rate correction term for

hydrolysis processes.

While not presented in Fig. 3 it must be noted that

although Eastman and Ferguson (1981) observed meth-

ane production at the longer SRTs the model did not pre-dict the generation of appreciable quantities of methane

under these conditions. The conversion of VFAs tometh-

ane in the experimental datamay explain the highermodel-

predicted VFA concentrations relative to the observed

values. The results suggest that methanogens are less sen-

sitive to pH than the pH inhibition functions suggest.

The ammonia-nitrogen concentrations were under-

predicted at the lowest SRTs and overpredicted at thehighest SRTs. These results tend to confirm the model

predictions of VFA concentrations since an underpre-

diction of solids destruction and hydrolysis, as indicated

by reduced VFAs, would also result in a reduced release

of ammonium.

3.3. Temperature-phased anaerobic digestion (TPAD)

TPAD processes consist of reactors operating at ther-

mophilic and mesophilic temperatures in series. While

either process may be first, the most common orientation

has the thermophilic digester ahead of the mesophilic di-

gester. For the purposes of this study two papers on

TPAD digestion were referenced; one that studied diges-

tion of PS alone (Han and Dague, 1995) and one that

studied a mix of PS and WAS (Han et al., 1997). In theformer paper the ratio of the volumes of the first and sec-

ond digesters was 1:2. In the latter paper two systems

were operated with system A having a ratio of volumes

of 1:2.5 while system B had a ratio of volumes of 1:5.

In all of the systems the mesophilic temperature was

35 �C while the thermophilic temperature was 55 �C. Acomparison of the model predictions with the data pre-

sented in the paper of Han and Dague (1995) is summa-rized in Fig. 4. The comparison of model predictions

with the results of Han et al. (1997) are presented for sys-

tems A and B in Figs. 5 and 6 respectively.

It should be noted that the model does not explicitly

predict volatile solids removal (VSR). For the purposes

of this paper it was assumed that the removal of volatile

solids was proportional to the removal of overall

COD. This assumes that all of the COD remainingafter digestion have the same ratio of volatile solids

concentration:COD. This undoubtedly introduces some

0

2

4

6

8

10

12

14

16

10 11.5 12.5 13.6 15

SRT (d)

CH

4 Pr

oduc

tion

(L/d

)

ModelExperimental

0

10

20

30

40

50

60

10 11.5 12.5 13.6 15

SRT (d)

VSR

(%)

ModelExperimental

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

10 11.5 12.5 13.6 15

SRT (d)

VFA

(mg/

L)

ModelExperimental

0

500

1000

1500

2000

2500

10 11.5 12.5 13.6 15

SRT (d)

VFA

(mg/

L)ModelExperimental

1st Stage2nd Stage

Fig. 4. Comparison of model predictions with data of Han and Dague (1995).


error in the estimates however, there was generally insuf-

ficient data on the composition of the digester effluent to

perform a more refined conversion of COD to solids

concentrations.

The patterns with respect to the model predictions

and observed data that are presented in Figs. 4–6 are

consistent. In all three cases, the model overpredicted

the production of methane by the temperature-phasedprocesses. It should be noted that in the papers only

total methane production was reported and hence it

was not possible to compare methane production from

the two reactors separately. In all cases the extent of

overprediction was greatest for the lower SRTs and pre-

dictions improved for the longer SRTs. The predictions

for VSR were best for the results presented in Fig. 4

while in Figs. 5 and 6 the model consistently overpre-dicted the VSR. The overprediction of VSR was consis-

tent with the overprediction of methane generation. In

all three cases the model substantially overpredicted

the concentrations of VFAs in the thermophilic reactor.

The greatest overprediction was associated with the

shortest SRTs and the predictions improved at longer

SRTs. With the exception of the 10 day SRT in Fig. 4

the model tended to underpredict the concentrationsof VFAs in the mesophilic second stage digester.

The results suggest that for thermophilic conditions

the model overpredicts the generation of volatile fatty

acids and that this is accentuated at shorted SRTs. It

should be noted that at low SRTs the model predicted

substantial inhibition of the acetoclastic methanogens

due to low pH (IWA, 2002). It may be that the inhibi-

tion functions for this process were too severe.

Although the model predicted high VFA concentra-tions in the thermophilic phase reactor, it predicted that

essentially all of the VFAs could be converted in the sec-

ond phase mesophilic reactor. The predicted effluent

concentrations were actually lower than those that were

observed. It should be noted that in this modeling effort

the biomass that was present in the first phase reactor

was allowed to flow into the second phase reactor and

remain active at the new temperature. This may have re-sulted in the overprediction of activity in the latter reac-

tor as it is unlikely that all of the thermophilic biomass

leaving the first digester would remain viable in the sec-

ond stage digester. It may be more appropriate to as-

sume that the biomass entering the second digester

should be considered as biodegradable particulate or-

ganic matter.

The differences between the model predictions andthe observed values of the VFA concentrations may also

0

2

4

6

8

10

12

14 20 28

SRT (d)

CH

4 Pr

oduc

tion

(L/d

)

ModelExperimental

0

10

20

30

40

50

60

14 20 28

SRT (d)

VSR

(%)

ModelExperimental

0

1000

2000

3000

4000

5000

6000

14 20 28SRT (d)

VFA

(mg/

L)

ModelExperimental

0

50

100

150

200

250

14 20 28SRT (d)

VFA

(mg/

L)ModelExperimental

1st Stage 2nd Stage

Fig. 5. Comparison of system a model predictions with data of Han et al. (1997).


have been due to the procedure used to adjust the bioki-

netic coefficients for temperature. In the model docu-

mentation (IWA, 2002) it is suggested that a constant

correction factor be employed for all of the microbial

species. Implementing this strategy tends to result in

an accumulation of VFAs at the higher temperatures.

It may be that differing temperature correction factorsshould be employed for the different microbial

species.

3.4. Two-phase anaerobic digestion

In two-phase anaerobic digestion the first digester is

operated at a short SRT to wash out methanogenic bac-

teria and promote the establishment of an acidic envi-ronment. In the second stage digester the VFAs that

are generated in the first stage are converted to methane.

In the study reported by Ghosh (1987) a number of

experiments were performed with digesters operating

at both mesophilic and thermophilic conditions. For

the purposes of this paper only the tests that were per-

formed under mesophilic conditions were examined.

Testing was conducted with total SRTs of 3 days and7 days and an influent TS concentration of 7%. With

the 3 day SRT the first stage had an SRT of 0.9 days

while the second stage had an SRT of 2.1 days.

With the 7 day SRT the first stage had an SRT of

2 days and the second stage had an SRT of 5 days. In

Tables 2 and 3 a comparison of some of the model

predictions and the reported experimental values are

presented.From Table 2 it can be see that with the exception of

the first stage of the 7 day SRT digesters the model pre-

dictions for VFAs were relatively close to the observed

values and the pH values for the second stage digesters

were also well predicted. The paper did not report the

first stage pHs and hence it was not possible to use this

parameter to evaluate the predictions for VFAs. The

overprediction of VFAs for the short SRT reactorswas consistent with that observed in the previously de-

scribed temperature phased digestion studies.

The model significantly under-predicted the NH4-N

concentrations for the 3 day SRT system while this re-

sponse was relatively well predicted for the 7 day SRT

system. It should be noted that there appeared to be

an inconsistency in the data for this response since the

observed values for the 3 day SRT system were substan-tially higher than the 7 day system. This seems to be

inconsistent with the VSR data that will be subsequently

0

1

2

3

4

5

6

7

8

9

10

12 17 24

SRT (d)

CH

4 Pr

oduc

tion

(L/d

)

ModelExperimental

0

10

20

30

40

50

60

12 17 24

SRT (d)

VSR

(%)

ModelExperimental

0

1000

2000

3000

4000

5000

6000

7000

12 17 24

SRT (d)

VFA

(mg/

L)

ModelExperimental

0

50

100

150

200

250

10 11.5 12.5

SRT (d)

VFA

(mg/

L)

ModelExperimental

1st Stage 2nd Stage

Fig. 6. Comparison of system B model predictions with data of Han et al. (1997).

Table 2

Comparison of volatile acids, pH And NH4-N for two phase digestion

Response SRT = 3 days SRT = 7 days

Stage 1 Stage 2 Stage 1 Stage 2

Vol. acids (mg/l)

Exper. NA 1680 1610–1810 109

Model 3811 1393 6711 180

pH

Exper. NA 7.2 NA 7.3

Model 5.8 7.0 5.2 7.3

NH4-N (mg/l)

Exper. NA 1820 NA 1049

Model 472 899 766 961

Table 3

Comparison of VSR for two phase digestion

Response VSR (%)

SRT = 3 days SRT = 7 days

Model 34.0 42.0

Experimental

MOPa 26.5 33.6

Weight of gasb 35.5 51.5

Theor. gas yieldc 28.3 43.4

a VS reduction was calculated as: VSR = 100 * (VS1 � VS0)/

[VS1 � (VS1 * VS0)].b VS reduction was calculated as VSR = 100 * (weight of gas/weight

of VS fed).c VS reduction was calculated as VSR = 100 * (observed gas yield/

theoretical gas yield of 1.078 SCFM/kg VS added).


described which indicated higher solids reduction for the

longer SRT system.

The predicted VSR values along with three different

measures of VSR for the experimental data that were re-

ported in the original paper are presented in Table 3.From Table 3 it can be seen that the model predictions

were within the range of values that were reported in

the papers. It should however be noted that the range of

values reported in the paper was quite wide and hence

the assessment of the model predictions could not be very

rigorous.

4. Discussion

In this paper the predictions of the ADM1 model

using the default values for most of the model coeffi-cients were able to reflect most of the trends that were

reported for a variety of digester configurations. There

were however consistent deviations between the model

predictions and observed values for VFAs when the


model was employed to predict the behaviour of low

SRT systems. In the two phase systems the model was

often able to perform reasonably in predicting second

stage concentrations of VFAs as with the longer SRTs

in these stages the rates of VFA conversion were able

to compensate for the high inlet concentrations ofVFAs. It would appear that there could be improve-

ments made to the model in the estimation of VFA con-

centrations under these conditions. It may be necessary

to more closely examine the relationship between pH

and rate coefficients in this regard.

For the purposes of this study it was often necessary

to estimate the values that were input into the model for

sludge characteristics such as COD, biodegradable frac-tion of the COD, TKN and NH4-N. These have a sub-

stantial influence on model predictions. If the model is

to be used as an analysis and design tool it would benefit

from more careful characterization of these parameters.

A standardized protocol for determining the anaerobi-

cally biodegradable fraction of the sludge COD would

assist in this regard.

The model predictions for VSR that were reported inthis paper assumed that the reductions in volatile solids

are proportional to the reductions in COD. However, it

is known that the COD content of volatile solids de-

pends upon the sludge source and its degree of stabiliza-

tion. Hence, the estimated values for VSR likely contain

error. The extent of this error has not been quantified

for this paper. For more accurate predictions of VSR

the COD contents of volatile solids in the feed sludgeshould be accurately characterized. In addition, the

use of typical values for the COD content of digested

sludge should be employed to convert predicted COD

concentrations to VS concentrations.

In this implementation of the model it was assumed

that for digesters in series the biomass which moved from

one digester to another would be active in the down-

stream reactor. This assumption should be valid fortwo-phase systems where the digester temperatures are

the same in both digesters. Implementation of the model

in this manner for temperature-phased configurations

requires more analysis as it is likely that the biomass

entering the second stage digester will be somewhat less

active than the model predicts.

5. Conclusions

The ADM1 model is a powerful tool for predicting

the behaviour of anaerobic digesters treating municipal

sludges. However, for successful simulation the feed

stream should be well characterized with respect to it�sCOD content and the biodegradable fraction of this

material. A standardized protocol for measuring thelatter parameter would further use of the model by the

industry. The ammonia and TKN concentrations

present in the feed need to be well characterized because

of their impact on pH buffering and inhibition func-

tions.

The model tended to overpredict VFA concentrations

for reactors that were operated at reduced SRTs. Thiswas observed for both mesophilic and thermophilic

digesters. The results suggest that the inhibition function

for pH may over emphasize the impact of reduced pH

on biological activity. In addition, the model does not

incorporate a pH function for the disintegration and

hydrolysis processes. This will have some impact on

low SRT systems that tend to operate at reduced pHs.

The relationship between COD and VS concentra-tions for digested sludges should be established. This

would improve the estimates of VSR since the model

only predicts COD concentrations.

Implementation of the model for temperature-phased

systems should be further examined since the current

implementation assumes that the biomass leaving the

upstream digesters can become active in the downstream

digesters at the downstream temperature. It does notseem that this would be likely for thermophiles entering

a mesophilic digester. The contribution of the incoming

biomass to the activity of the digesters should be further

quantified.

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Application of the ADM1 model to advanced anaerobic digestion

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