A review of ADM1 extensions, applications, andanalysis: 20022005

D.J. Batstone*, J. Keller** and J.P. Steyer*

*Environment and Resources, Building 113, Technical University of Denmark Lyngby 2800, Denmark

(E-mail: djb@er.dtu.dk)

**Advanced Wastewater Management Centre, The University of Queensland, St Lucia, 4058, Australia

Abstract Since publication of the Scientific and Technical Report (STR) describing the ADM1, the model

has been extensively used, and analysed in both academic and practical applications. Adoption of the ADM1

in popular systems analysis tools such as the new wastewater benchmark (BSM2), and its use as a virtual

industrial system can stimulate modelling of anaerobic processes by researchers and practitioners outside

the core expertise of anaerobic processes. It has been used as a default structural element that allows

researchers to concentrate on new extensions such as sulfate reduction, and new applications such as

distributed parameter modelling of biofilms. The key limitations for anaerobic modelling originally identified in

the STR were: (i) regulation of products from glucose fermentation, (ii) parameter values, and variability, and

(iii) specific extensions. Parameter analysis has been widespread, and some detailed extensions have been

developed (e.g., sulfate reduction). A verified extension that describes regulation of products from glucose

fermentation is still limited, though there are promising fundamental approaches. This is a critical issue, given

the current interest in renewable hydrogen production from carbohydrate-type waste. Critical analysis of the

model has mainly focused on model structure reduction, hydrogen inhibition functions, and the default

parameter set recommended in the STR. This default parameter set has largely been verified as a

reasonable compromise, especially for wastewater sludge digestion. One criticism of note is that the ADM1

stoichiometry focuses on catabolism rather than anabolism. This means that inorganic carbon can be used

unrealistically as a carbon source during some anabolic reactions. Advances and novel applications have

also been made in the present issue, which focuses on the ADM1. These papers also explore a number of

novel areas not originally envisaged in this review.

Keywords ADM1; anaerobic; model; review

Introduction

It is undeniable that interest, and activity in academic and applied anaerobic digestion

simulation is rapidly developing. There have been some 750 publications regarding

anaerobic digestion modelling in the last 30 years, of which half have been in the last 5

years (Figure 1). Much of this work has been a driver for development of a standardised

anaerobic model.

The ADM1 was first presented at the 9th IWA Conference on Anaerobic Digestion in

2001 (AD2001) in Antwerp (Batstone et al., 2002a), and the related Scientific and Tech-

nical Report (STR) was published by IWA in early 2002 (Batstone et al., 2002b).

Between then, and mid-2005 there have been 30 ISI citations of the report. Additionally,

the model itself is available in popular aquatic modelling packages such as WEST, GPS-

X, Matlab Simulink, SIMBA, and Aquasim with cross-verification between the

implementations. The two most widely used implementations are the Aquasim 2.1

implementation, created by the ADM1 Taskgroup, and the Matlab implementation, in

Matlab C, and Matlab script (Rosen and Jeppsson, 2002; Rosen et al., 2006). These will

not be discussed widely here, but each implementation needed specific numerical tech-

niques to overcome limitations, and were cross-verified against each other. The

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availability of the code has helped considerably in distribution and use of the model, as

implementation of a complex bioprocess model such as the ADM1 is a daunting task and

can lead easily to errors that are difficult to identify and correct.

The original goals of publication of the ADM1, as stated in the STR were:

increased model application for full-scale plant design, operation and optimisation; further development work on process optimisation and control, aimed at direct

implementation in full-scale plants;

common basis for further model development and validation studies to make outcomesmore comparable and compatible;

assisting technology transfer from research to industry.The key objective of the ADM1 STR was to enable a shift in focus from development

of model fundamentals (e.g. basis, kinetics etc.) to investigation of specific aspects and

model application in industry situations. The Taskgroup identified, in the STR, a number

of key limitations in anaerobic digestion modeling (as of 2002). The main limitations

were: (i) models for regulation of VFA products from glucose are incomplete, and have

not been validated: (ii) uncertainty in parameter values, and parameter variation; and (iii)

lack of sufficient understanding of a number of related processes, such as sulfate

reduction, precipitation, etc.

The objective of the present paper is to review extensions, applications, and critical

analysis of the ADM1, especially in relation to whether the publication of a standardised

model has achieved these goals. In addition, we attempt to assess future requirements for

standardised anaerobic process modelling. This review is part of a special issue on the

ADM1, and is mainly intended to establish current knowledge. Therefore the other papers

in this issue are not specifically addressed, except where they address critical limitations.

Applications

Published applications can be divided into two classes: applications of the standard

model in a mixed tank, with the recommended approach given in the STR, often using

already implemented models, to assess specific systems and; applications of the ADM1

in new distributed parameter applications, often for theoretical analysis.

Mixed tank applications

Many of the papers cited in other sections of this review include mixed tank implemen-

tations in systems that include mixed sludge digesters, manure digesters, and UASB

Figure 1 ISI publications regarding anaerobic digestion modelling per year since 1972. Note that some

papers from 2004/2005 have not yet been indexed

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systems. However, there are two applications of the ADM1 in particular that are likely to

receive widespread use. The COST wastewater activated sludge benchmark (BSM1) was

produced by COST Action 624 and COST Action 682 for standardised comparison of

control and operating strategies. It describes a standardised wastewater treatment plant

with 2 anoxic tanks, 3 aerated tanks, and a secondary settler. The description included

the full model with all parameter values, and detailed input data. Reactions were

described using the IWA Activated Sludge Model Number 1 (ASM1; Henze et al.,

1987). The BSM1 was a success, resulting in 100 publications worldwide (Jeppsson et al.,

2006), with use not only in the core area of plant-wide control and optimisation, but also

as a teaching, training, and theoretical analysis tool.

A new benchmark (i.e. BSM2) has been proposed (Jeppsson et al., 2006) that also

considers a primary settler, thickener, and anaerobic digester, modelled using the ADM1

(Figure 2). This has been one of the drivers for cross-verification of the different versions

of the ADM1, as well as implementation of the reference versions in Matlab, WEST, For-

tran, GPS-X, and SIMBA. It has also resulted in detailed critical analysis of some con-

cepts proposed in the STR. These include discovery of an ammonia leak during the

disintegration process, and much improved interfacing of the ADM1, and ASM series

models (Copp et al., 2003; Vanrolleghem et al., 2005).

The ADM1 was also used within the TELEMAC project, a 5th Frame programme EU

project for improved remote monitoring, control, and operation of high-rate anaerobic

wastewater treatment plants. One interesting subproject is production of a model-based

operator training tool (Bernard et al., 2005). The ADM1 is sufficiently complex such that

it can predict complex overload behaviour, which is a necessary requirement for operator

training. Additionally, the ADM1 was used as a virtual plant to evaluate different control

strategies and software sensors for advanced monitoring of industrial anaerobic digesters.

The ADM1 has also been used to simulate and analyse the response and behaviour of an

anaerobic respirometer (Mosche and Meyer, 2003).

Distributed parameter modelling. The three key distributed parameter systems of interest

are biofilm systems, plug flow reactors (including UASB reactors), and municipal solid

waste reactors. Biofilm systems have been modelled using the ADM1 in one dimension (1D)

Figure 2 Plant layout for the proposed BSM2 from Jeppsson et al. (2006), used with permission

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(Batstone et al., 2004a), and 2/3D (Picioreanu et al., 2005). The second application

demonstrates the power of current computing, as the full ADM1, with pH solution can be

simulated in 105 discrete elements over several days, with single processor computers. An

image of the simulated granule from the 2D model is shown in Figure 3.

A plug flow ADM1 implementation was also used to simulate a laboratory-scale

UASB (Batstone et al., 2005), against experimental data. The model could effective

simulate acetate conversion rates against measured data, and demonstrated the higher

conversion efficiencies of a plug-flow system when compared to mixed reactors.

The ADM1 is not widely used for distributed parameter modelling of solid-phase

anaerobic digestion of solid waste. However, Vavilin and Angelidaki (2005) used a sim-

plified model to investigate the impact of separation in space of methanogenic and acido-

genic groups in solid phase batch digesters (VFA was assumed to inhibit methanogens)

and the same implementation can be readily applied to the ADM1.

Extensions

The ADM1 was designed to be readily extendible, and additional functions work very

well, and are easy to document. The most commonly requested extensions are sulfate

reduction, description of the behaviour of phosphorous, and mineral precipitation. A key

limitation in the existing model is regulation of products from glucose fermentation, as

recognised in the STR.

Sulfate reduction is the most complex of these, as sulfate acts as electron acceptor for

oxidation of VFAs such as propionate, butyrate and acetate, but reacts preferably with

hydrogen (H2) formed in the fermentation. Additionally, the product, sulfide, is inhibi-

tory, is ionic (and hence affects pH), and is gaseous. Therefore to have a comprehensive

model of sulfate reduction, every part of the ADM1 needs modification. A very extensive

sulfate reduction extension was published by Fedorovich et al. (2003). This involves four

Figure 3 Granule simulated using the ADM1 in a 2D model after 31.25 days using 105 discrete elements.

From Picioreanu et al. (2005), used with permission. Subscribers to the online version of Water Science

and Technology can access the colour version of this figure from http://www.iwaponline.com/wst

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additional groups of microbes that can oxidise butyrate/valerate, propionate, acetate and

hydrogen respectively, with sulfate as electron acceptor to produce hydrogen sulfide.

Inhibition, acid-base chemistry, and gas stripping were also included. The new microbes

compete with those currently in the ADM1 for these substrates. The model was effective

in predicting the behaviour of a UASB fed with sulfate up to 6 gSL21. It is also possible

to use a reduced model, with a single group of sulfate reducers competing with

hydrogen utilisers, but this is effective only with influent S:COD ratios up to

0.1 gS gCOD21 (Batstone, 2006). Above this level, the sulfate reducers will oxidise

VFAs and the model will incorrectly predict sulfate in the effluent. Sulfide is an import-

ant contributor to odour, and a number of other anaerobic byproducts contribute to odour.

This has been further explored in this issue.

Phosphorous has been requested in order to close phosphorous balances in integrated

wastewater treatment plant modelling and particularly to account for the significant phos-

phorus retention and release in the biomass during digestion of activated sludge from

domestic wastewater treatment plants. Papers that have described an extension for this

have not been found, but it is a relatively simple extension. Soluble phosphorous can be

described by a single state, and organic (or inorganic) bound phosphorous can be

described by a separate state, as with nitrogen in the ASM1, or bound to complex particu-

lates (Xc), as with nitrogen in the ADM1. If required, acid-base chemistry for phosphor-

ous can be implemented and using this, precipitation of relevant complexes may also be

included (CaHPO4, struvite {MgNH4PO4} or others). The main difficulty in this regard is

not inclusion of individual processes, but the large number of processes. There are a huge

number of potential, (and maybe unknown) precipitants (Wild et al., 1996; Wild et al.,

1997), and release mechanisms are complex depending on upstream phosphorous removal

methods. Currently, there is likely insufficient fundamental knowledge available to enable

an ab initio prediction, but often data from existing, similar processes can be used to

approximate the expected solubilisation.

Single component precipitation extensions are relatively simple. The fully dissociated

anion needs to be modelled as a separate state (normally CO32), either by algebraic, or

differential equations, and the cation and precipitate need to be modelled as differential

states. Precipitation can be based either on equilibrium (using a KSO), or a first-order (or

more complicated) reaction. An extension for CaCO3 precipitation has been published

(Batstone and Keller, 2003), and can be used as a template for other precipitation

reactions.

Other extensions have focused on specific issues. For example, ethanol oxidation was

included to simulate the degradation of winery wastewater in an Anaerobic Sequencing

Batch Reactor (ASBR), and was found to have similar kinetic rates to propionate and

butyrate oxidation (Figure 4, Batstone et al., 2004b). Isovalerate was found to degrade to

acetate only, in comparison with normal-valerate, which degrades to propionate and acet-

ate, and an extension was written to address this (Batstone et al., 2003).

Despite strong interest, acidogenesis of glucose is still a key limitation in the existing

model. It is known that environmental factors, including pH and hydrogen concentration

regulate the production of products, including butyrate, propionate, acetate, ethanol, and

hydrogen (Mosey, 1983; Costello et al., 1991). However, there is still not a good model

available of this regulation as is becoming clearly evident from the results of many pro-

cesses aiming to achieve hydrogen production. Currently, the ADM1 has fixed stoichio-

metric parameters for glucose fermentation products, which is clearly not representative

of the actual acidogenic processes in most systems. This is especially critical, given the

rapidly raising interest in biohydrogen production where (mono)saccharides are the most

common source material, and the hydrogen production optimisation is the main focus of

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these processes. An interesting metabolic model has been proposed recently (Rodriguez

et al., 2004), but needs experimental validation. Further evaluation of this is presented in

Rodriguez et al. (2006).

Critical analysis and modifications

Model structure and basis. Most of the criticisms of the ADM1 have been that it is too

simple, or too complex. Simplicity can be addressed by adding relevant extensions to the

model (where feasible), and on the other hand researchers have also used the ADM1 as a

basis for more simplified models. Model reduction usually aims to decrease simulation

time (especially in integrated systems modelling), decrease parameter estimation

requirements, or decrease implementation workload. The Siegrist model (Siegrist et al.,

2002) is a slight simplification of the ADM1, orientated towards primary sludge

digestion. It removes the butyrate and valerate components but has a good basis for both

thermophilic and mesophilic sludge digestion. Elmitwalli et al. (2003) used the ADM1 as

a basis for a two-step model to assess the impact of temperature on anaerobic treatment

of domestic sewage. Batstone (2006) has recommended a two-step model similar to that

of Elmitwalli et al. (2003) for simulation of hydraulics in UASB reactors.

Copp et al. (2004) reduced the ADM1 substantially for an alternative implementation

in GPS-X. The changes included lumping all soluble components more complex than

acetate as soluble COD, and separating nitrogen states from COD states, in a similar way

to the ASM1. The changes improved simulation speed by a factor of 5. However, while

model reduction is valid, and often recommended, it should be recognised that it

decreases specific capabilities. For example, the reduced GPS-X model will not effec-

tively simulate hydrogen inhibition of propionate or butyrate oxidation, and will incor-

rectly predict pH during propionate or butyrate accumulation.

Another important limitation was recognised by Kleerebezem and van Loosdrecht

(2006), in that stoichiometry is based only on catabolic reactions. Anabolic reactions

source COD from the substrate, but in cases of carbon limitation, they source excess car-

bon from carbon dioxide. This is unrealistic for most organisms (except hydrogen utili-

sers), especially those that do not produce bicarbonate (e.g. butyrate oxidisers). Because

biomass yields in general are relatively small, and because most reactions produce carbon

dioxide during catabolism, the overall impact is small. However, when the ADM1 is used

Figure 4 Measured values for propionate ( ), acetate (S) and residual COD (soluble COD-approximateinert COD-organic acid COD) (o), and simulated data (solid lines as marked?) for ethanol, propionate, and

acetate over a single cycle fed with winery wastewater in an ASBR (Batstone et al., 2004b), used with

permission

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as a basis for assessing metabolic products, the updated basis proposed by Kleerebezem

and van Loosdrecht (2006) should be used.

Kinetics. Critical analysis of kinetics has largely focused on hydrogen inhibition. The

STR recognised that thermodynamics played a critical role in inhibition, but that

diffusion limitations within biofilms may allow reactions to occur, that seem

thermodynamically impossible from concentrations in the bulk liquid. Therefore a simple

non-competitive function was chosen. Zheng and Bagley (2006) recommended

replacement of the non-competitive function with a function dependent on the actual free

energy (rate is negative if free energy is positive or zero). The results were verified using

data from an anaerobic sequencing batch reactor (ASBR). Kleerebezem and van

Loosdrecht (2006) recommended also using the hydrogen ion as a driver for the reaction.

Both papers are essentially based on the work of Hoh and CordRuwisch (1996). While

the inhibition function is certainly valid when the model observes in-situ hydrogen

concentrations, and elegant (no inhibition constant is required), the original limitations

identified in the STR relating to diffusion in biofilm or floccular systems remain.

Additionally, the thermodynamic functions are discontinuous at DG0 0, which cancause considerable problems when using implicit differential equation (stiff) solvers.

Continuous approximations of this function also cause integration problems.

Parameter values. The recommended parameter set in the ADM1 is based on low

decay rates (0.010.02 d21). This reflects the consensus of previously published decay

rates. However, decay, and uptake (and hence growth) rates are heavily correlated

(Batstone et al. 2003), and it is possible to increase the decay rate while simultaneously

increasing the uptake rate to have zero net impact on outputs. In parallel to the

publication of the ADM1, the Siegrist model was also presented (Siegrist et al., 2002).

Siegrist et al. (2002) based parameter values on batch experiments, with decay rates on

the order of 0.05 d-1. An example of the two models is shown in Figure 5, with km(kgCODS kgCODX21 d21) and KS (kgCODm

23) of the ADM1 set to 6.6, 0.030 (acetate

utilisers), and 9.0, 0.029 (propionate utilisers), respectively. In this case, the higher decay

rates used by Siegrist et al. (2002) offset the higher KS values. Indeed, there is

independent indication from biofilm modelling (Batstone et al., 2004a) that higher decay

rates may be more valid.

There has been extended analysis of the applicability of the recommended parameter

set for digestion of sludge from domestic sewage treatment plants. Blumensaat and Keller

(2005) applied the ADM1 to simulation of mixed primary and secondary sludge in a two-

stage thermophilic/mesophilic digester. Parameters were optimised, with small (2050%)

increases in uptake and half-saturation coefficients for acetate and propionate compared

Figure 5 A comparison of the ADM1 (solid line), with optimised km, KS for acetate and propionate, with the

Siegrist model (Siegrist et al., 2002), with published parameters

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to the recommended parameter set. They also found that the hydrolysis rate under meso-

philic conditions was double that under thermophilic conditions, the opposite to that rec-

ommended in the STR. Parker (2005) applied steady-state predictions to a range of

sewage sludge digesters operating at different retention time. It was found that at short

retention times, the model overpredicted acetate, and underpredicted butyrate and propio-

nate. This could be corrected by two modifications: (i) decrease in acetate KS, and

increase in propionate/butyrate KS, (ii) increasing ammonia inhibition constant, and

decreasing hydrogen inhibition constant. Shang et al. (2005) simulated the steady state of

mixed primary and secondary sludge digesters, and found very good agreement between

model and measured data, but with a 10% overprediction of biogas production. This was

related to overprediction of solids destruction, and is probably related to either the disin-

tegration parameter, or inert fraction in the sludge. In summary, out of the four studies,

two studies (Siegrist et al., 2002; Parker, 2005) found KS values effectively lower than

the ADM1 set, one study (Blumensaat and Keller, 2005) found KS values effectively

higher than the ADM1 set, and the other did not assess organic acids, but found good

overall prediction. This indicates that the recommended parameter set in the STR is a

reasonable compromise but there may be case-specific adaptations necessary in some

situations.

Parameters for the ADM1 have also been applied in a range of other systems, includ-

ing an ASBR treating winery wastewater (Batstone et al., 2004b), and a thermophilic

manure digester (Batstone et al., 2003). Generally modifications to kinetic parameters

have been on the order of 2050%, which is relatively small compared to the large vari-

ations found in some parameters used for activated sludge systems.

Conclusions

Publication of the ADM1 has largely addressed its primary objective of reducing dupli-

cate published model structures. Indeed, no references to new, complex structural models

were found. There has been a considerable amount of effort in producing extensions to

the ADM1, and extensive critical analysis. The most serious criticism is that of Kleerebe-

zem and van Loosdrecht (2006), relating to inorganic carbon use during anabolism. How-

ever, its impact is relatively small in environmental systems, and probably does not

warrant an overhaul of the current model structure and stoichiometry.

Among the goals, most relate to increased model application in full scale, and by tech-

nology developers and users. This has also been achieved, and several of the papers cited

in this review are from these users and we are aware of several other applications in prac-

tice that have not been published or presented in conferences. Application is primarily in

sewage sludge digesters, and hopefully, future use will also involve analysis and optimis-

ation of industrial high-rate digesters, as in this context, modelling can provide real

gains. Publication of the ADM1, and its adoption into the BSM2 has also introduced the

field of anaerobic modelling to a variety of researchers working in control and optimis-

ation of activated sludge treatment plants, and in the future, the end-users of this

benchmark.

Of the three core limitations regulation of glucose fermentation products; parameter

values; and key extensions the last two are being well addressed by subsequent publi-

cations. Additional work is needed on parameter variability across industries, and specific

extensions. However, the key limitation of glucose fermentation products needs model

development and verification, given the high level of interest in carbohydrate fermenta-

tion technologies for hydrogen production. This should have a fundamental, metabolic

basis, as has been proposed. Such research would be invaluable for interpretation and

optimisation of renewable hydrogen production processes.

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Acknowledgements

We thank the ADM1WS1 scientific committee for reading and commenting on this

manuscript.

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A review of ADM1 extensions, applications, and analysis: 2002-2005IntroductionApplicationsMixed tank applications

ExtensionsCritical analysis and modificationsConclusionsAcknowledgementsReferences