Bioresource Technology 100 (2009) 1539–1543

Contents lists available at ScienceDirect

Bioresource Technology

journal homepage: www.elsevier .com/locate /b ior tech

Application of the IWA ADM1 model to simulate anaerobic co-digestionof organic waste with waste activated sludge in mesophilic condition

K. Derbal a, M. Bencheikh-lehocine a,*, F. Cecchi b, A.-H. Meniai a, P. Pavan c

a Laboratoire de l’Ingénierie des Procédés de l’Environnement (LIPE), Département de Chimie Industrielle, Faculté des Sciences de l’Ingénieur, Université Mentouri, Constantine, Algeriab Department of Science and Technology, University of Verona, Verona, Italyc Department of Environmental Science, University of Venice, Venice, Italy

a r t i c l e i n f o a b s t r a c t

Article history:Received 29 April 2008Received in revised form 13 July 2008Accepted 16 July 2008Available online 26 October 2008

Keywords:Anaerobic co-digestionSimulationADM1Mesophilic temperatureSolid wastes

0960-8524/$ - see front matter � 2008 Published bydoi:10.1016/j.biortech.2008.07.064

* Corresponding author. Tel./fax: +213 31 81 88 80E-mail address: mossaabbb@yahoo.fr (M. Bencheik

Anaerobic digestion model no. 1 model of international water association was applied to a full scaleanaerobic co-digestion process for the treatment of the organic fraction of municipal solid wastes alongwith activated sludge wastes originating from a municipal wastewater treatment plant. This operationwas carried out in a digester of 2000 m3 in volume. It is operates at an average hydraulic retention timeof 26.9 days with an average organic loading rate of 1.01 kg TVS/m3 day, at a temperature of 37 �C with anaverage gas production rate of 0.296 m3/m3 day.

The aim of the present study is to compare the results obtained from the simulation with the experi-mental values. The simulated results showed a good fit for pH, methane and carbon dioxide percentages,biogas volume, chemical oxygen demand, total volatile fatty acids, inorganic nitrogen and inorganiccarbon.

� 2008 Published by Elsevier Ltd.

1. Introduction

Anaerobic digestion is worldwide used, particularly in Europefor the treatment of numerous types of biodegradable wastes. Thisis confirmed by the important number of treatment plants usingthis process on the industrial scale, during the past few years(Mata-Alvares et al., 2000).

In fact, anaerobic digestion of the organic fraction of the muni-cipal solid wastes alone or combined with organic sludge can con-tribute efficiently in solid waste reduction and biogas production(Jewell, 1979; Kayhanian and Tchobanoglus, 1992; Vallini et al.,1992; Cout et al., 1994). This process can be used for the solidwaste treatment under mesophilic or thermophilic conditions(Macé et al., 2003; Bolzonella et al., 2005a, 2003a), organic solidwastes with or without wastewater treatment plant sludge(Kayhanian and Rich, 1995; Bolzonella et al., 2005b), cheese whey(Erguder et al., 2001), agro-industrial wastewaters (Demirer et al.,2000), grey water from vacuum toilets (Feng et al., 2006), cowwastes (Igoud et al., 2002), olive mill waste (Fezzani and BenCheikh, 2007; Erguder et al., 2000), etc.

Due to the importance of anaerobic digestion as a treatmentprocess, different dynamic models exist, such as the AM2 whichwas developed jointly by researchers of the INRA of Narbonneand the INRIA of Sophia-Antipolis in 2001 (Olivier et al., 2001). It

Elsevier Ltd.

.h-lehocine).

is based on experimental results obtained on the fixed bed reactorof the INRA of Narbonne. This model is made of two steps: acido-genesis and methanogenesis corresponding to acido-acetogensand methanogens bacteria populations, respectively. As a more re-cent and elaborate model, the anaerobic digestion model no. 1(ADM1), was developed by an international water association(IWA) group (Batstone et al., 2002). Its main feature is the consid-eration of the principal steps of anaerobic digestion process thatare, respectively, substrate disintegration (non biological step),hydrolysis, acidogenesis, acetogenesis and finally the methanogen-esis with seven different bacteria groups.

Since its development in 2002 and up to now, the ADM1 hasbeen tested and used on different substrates where a great numberof research works are reported in this literature. As examples, onecan cite (Blumensaat and Keller, 2005) who modified the initialversion of ADM1 for the simulation of a dynamic behaviour of a pi-lot scale digester using sludge, in order to ensure a faultless modelimplementation. They obtained accurate results for the cases oflow to medium loading rates. However, the accuracy showed a de-cline with the increase of the loading rate.

Parker (2005) considered the application of the ADM1 to a vari-ety of anaerobic digestion configurations where the resultsshowed, in most of the considered cases, that the model was ableto reproduce the trends of the experimental results.

Feng et al. (2006) found that the ADM1 is not sensitive to thedistribution ratio of carbohydrates, proteins and lipids, whereasthe fraction of short chain fatty acids (SCFA) in the influent israther more important.

1540 K. Derbal et al. / Bioresource Technology 100 (2009) 1539–1543

Consequently, the great capabilities of ADM1 in modelling dif-ferent types of substrates and calculations have been the motivat-ing factor to use it in the present work to evaluate theperformances of a co-digestion process for the treatment of organicmunicipal solid waste and waste activated sludge in the abovementioned 2000 m3 reactor working at a temperature of 37 �C.

2. Methods

2.1. The anaerobic digestion model (ADM1)

As mentioned above the ADM1 was developed by the IWAgroup (Batstone et al., 2002) with the objective to build a fullmathematical model based intimately on the phenomenologicalmodel in order to simulate, at best, anaerobic reactors. It includes,as a first step, the disintegration of solid complexes (non biologi-cal step) into carbohydrates, lipids, proteins and inert material(soluble and particulate inert). The second step is the hydrolysisprocess of the disintegration products under an enzymatic actionto produce sugars, amino acids and long chain fatty acids (LCFA),successively. Then, amino acids and sugars are fermented to pro-duce VFA, hydrogen and carbon dioxide (acidogenesis). ThenLCFA, proprionic acid, butyric acid and valeric acid are anaerobi-cally oxided into acetate, carbon dioxide and hydrogen (acetogen-esis). Finally, methane can be produced through two paths: thefirst one is based on acetate whereas the second one is throughthe reduction of carbon dioxide by molecular hydrogen. The or-ganic species and molecular hydrogen, in this model, are ex-pressed as chemical oxygen demand (COD), whereas inorganicnitrogen and inorganic carbon species are expressed through theirmolecular concentrations.

Extensions and modifications were brought to ADM1 to enlargeits prediction capabilities by, taking into account other factors suchas, for instance, the sulfato-reductors or the degradation of certainsubstrates (Wolfsberger and Holubar, 2006; Batstone and Keller,2003). Moreover, Usama (2004–2005) considered the toxic effectsof cyanide as an inhibition process for acetate.

2.2. Reactor and monitoring

As mentioned previously, experimental data were obtainedfrom the monitoring of an anaerobic co-digestion of municipal so-lid waste mixed with wastewater treatment plant sludge, carriedout in the industrial digester which was operated under mesophilicconditions (37 �C). The substrate is introduced daily with an influ-ent mass loading of 1 kg TVS/m3/day and a hydraulic retentiontime (HRT) of around 27 days. Influent and effluent analysis weremade daily for pH, total solids (TS), volatile solids (VS), volatilefatty acids (VFA), biogas volume produced and its composition,partial alkalinity (TA) and total alkalinity (TAC), ammoniacal nitro-gen (NH3). Other analyses were made two or three times a week,like chemical oxygen demand (COD), Nitrogen djeldhal (TKN) andtotal phosphorous (Ptot). These parameters were determinedaccording to the standard methods for water and wastewaterexamination.

3. Results and discussion

3.1. Experimental monitoring of the full scale reactor

The full scale anaerobic digester was monitored for six months.Typical characteristics of influent feed are shown in Table 1. This isthe stream resulting from the blend of biowaste and waste acti-vated sludge. The typical solids concentration was some 3.9% whileTVS were 65% of TS.

The effluent characteristics are shown in Table 2. Total and vol-atile solids were clearly reduced around 30% with respect to theinfluent parameters shown in Table 1, Values of alkalinity, pHand VFA were similar to typical results of literature (Bolzonellaet al., 2003b) and stable enough, with low fluctuations. Finallythe gas production characteristics are presented in Table 3.

3.2. Implementation of ADM1

The substrate (solid waste + sludge) was characterized accord-ing to the original version of ADM1 (Batstone et al., 2002). There-fore, the input data were calculated on the basis of the influentsubstrate characteristics mentioned in Table 1. Thereafter, theADM1 model was calibrated, using experimental data, throughthe optimisation of the different parameters, mainly the disinte-gration and hydrolysis ones, with a constraint on their valueswhich should be within the physical range. The experimental andsimulated results are discussed in the following paragraph.

3.2.1. Estimation of kinetic parameter valuesBefore starting the simulation step, the kinetics parameters

concerning the disintegration and hydrolysis phases were firstestimated. These were evaluated considering both experimentalbatch runs; i.e., for biowaste and sludge hydrolysis (batch testsin serum bottles) and the modelling of experimental data chang-ing the values of the kinetic parameters. In particular, the ADM1was first used to simulate experimental data obtained during thetrials of anaerobic co-digestion runs. It was found that the con-stants for disintegration and hydrolysis suitable for this studywere equal to typical values reported in literature for biowaste(Mata-Alvarez, 2003) as presented in Table 4. All the values ofkinetics and stoichiometry constants were then maintained as inthe ADM1 model.

3.3. Simulation of the process and comparison with experimental data

After estimating the parameters of disintegration and hydroly-sis of the substrate, the obtained results concerning the chemicaloxygen demand, both total and dissolved (TCOD and SCOD) as wellas the total volatile fatty acid (TVFA), are represented in Fig. 1. Itcan be noticed that the simulated results are in good agreementwith the experimental values up to the 15th day. Thereafter, adeviation is shown between the two sets of values, i.e., experimen-tal and simulated, for the total COD. However if the soluble resultsare considered this deviation is probably due to the particulatefraction of COD.

Moreover, the substrate distribution between proteins, carbo-hydrates and lipids was not measured but default model valueswere adopted for this parameter. This can be justified by the factthat the used experimental rig is housed in the Treviso wastewatertreatment plant and influent characteristics are daily varying. Thereported values in the literature are specified to particular types ofwastes, hence may not be safely used in this work. For the resultsof TVFA it can be seen that they show a kind of a good stability inthe digester operations and they fit reasonably well the experi-mental values.

Fig. 2 shows the variation of total gas volume produced withtime, which clearly depends on the nature, composition and biode-gradability of the waste. In fact, even though the mass loading inthe digester is maintained almost constant (3% variation), theamount of sludge and biowaste can be different at any day, andhence leading to different biogas production. Moreover, the struc-tural limitations of the ADM1 imply that the simulated gas produc-tion follows an average path; therefore simulated data are onlypartially confounded with experimental values.

Table 1Influent characteristics

Parameters Middle Minimum Maximum Standard deviation Number of samples

pH 6.5 5.9 6.9 0.28 48NH3 (mg N/l) 18. 8 46.5 10 38TKN (mg N/l) 47.9 40 52.5 3.54 23TCOD (mg COD/l) 691.9 591.1 822.1 69.4 27Ptot (mg P/g TS) 24.0 669.2 1183 172.4 23TS (g/l) 39.1 29 48.1 3.28 47TVS (g/l) 25.8 23.2 29.5 1.43 47TVS (% TS) 65 57.1 70 2.57 47VFA (mg COD/l) 225.8 22.6 1358.7 364.7 47TA at pH 6 (mg CaCO3/l) 201.6 39 400 92.4 49TA at pH 4 (mg CaCO3/l) 590.5 380 1268.8 201.4 48

Table 2Effluent characteristics

Parameters Middle Minimum Maximum Standard deviation Number of samples

pH 7.4 7.2 7.7 0.14 50NH3 (mg N/l) 593.1 440 720 66 38TKN (mg N/l) 41.1 35.1 44.1 2.48 21COD (mg COD/l) 625.5 565.39 702.2 42.1 25Ptot (mg P/g TS) 28.4 7 125 15 23TS (g/l) 31.8 27.7 38.2 1.6 48TVS (g/l) 18 15.4 20.8 1 47TVS (% TS) 56.9 49.9 63.2 2.4 47VFA (mg COD/l) 12.1 2.1 30.6 7.6 41TA at pH 6 (mg CaCO3/l) 2342.3 1100 2163 163.1 50TA at pH 4 (mg CaCO3/l) 1469.3 2040 2982 175.2 50

Table 3Characteristics and biogas production

Parameters Middle Minimum Maximum Standard deviation Number of samples

Biogas volume (m3/day) 606.4 375 860 129.3 46SGP (m3 biogas/kg TVS) 0.31 0.118 0.45 0.09 39Gas production rate (GPR) (m3 biogas/m3 day) 0.4 0.183 0.42 0.06 48% CH4 (%) 65.8 60.3 68.1 1.3 49% CO2 (%) 34.2 31.9 39.7 1.3 49V-CH4 (m3/day) 399.7 246 559.9 83.7 46V-CO2 (m3/day) 206.7 129 300 46.6 46H2S (ppm) 622.7 321 778 125.1 43

Table 4Initial and estimated values of kinetic parameters

Kinetic parameters Names Units Initial values used in ADM1 Initial values Estimated values

Kdis Disintegration constant Day�1 0.5b 0.7 0.5Khyd.Ch Carbohydrate hydrolysis constant Day�1 10b 1.25a 1.017Khyd.Pr Proteins hydrolysis constant Day�1 10b 0.5a 0.3842Khyd.Li Lipids hydrolysis constant Day�1 10b 0.4a 0.999

a Middle values obtained from Mata-Alvarez (2003).b Values obtained from Batstone and Keller (2003).

K. Derbal et al. / Bioresource Technology 100 (2009) 1539–1543 1541

In order to have an insight on the biogas production the inputorganic loading rate was calculated and plotted as shown inFig. 2 where it can be seen that dynamic conditions are prevailing.

Fig. 3 shows the experimental and simulated results of gas pro-duction which is composed of methane gas, carbon dioxide andhydrogen. However, since the hydrogen volume is not importantit was not analysed in the total volume and it was assumed thatthe gas is only made of methane gas and carbon dioxide. Eventhough, this assumption could influence the errors, the obtainedresults are satisfactory. It can be noticed that at the beginning ofthe simulation, the results are overestimated for methane gasand underestimated for the carbon dioxide. However, these results

show that the reactor presents a good stability from the point ofview of gas composition.

To see better what is happening in the system, inorganic carbon(IC), inorganic nitrogen (IN) and pH were represented in the sameFig. 4 and hence the alkalinity is implicit.

IC should be regarded as bicarbonate alkalinity (BA), since thevariation of BA is due to the neutralisation of VFA in the solution.BA or IC are more sensitive to VFA accumulation than pH, andare correlated empirically to VFA accumulation (Bolzonella et al.,2003a). However, the variation of BA could not be converted intoVFA units. From the simulation point of view ADM1 does not rep-resent fluctuations but shows an average trend at the beginning of

0 5 10 15 20 25 30-10

0

10

20

30

40

50

(simulated TCOD)(simulated SCOD)(simulated TVFA)(measured TCOD)(measured SCOD)(measured TVFA)

Efflu

ent T

CO

D, S

CO

D a

nd T

VFA

(KgC

OD

/m3 )

Time (days)

Fig. 1. Comparison between the simulation and the experimental total and solubleCOD and TVFA.

0 5 10 15 20 25 300

200

400

600

800

1000

simulated gas flowmeasured gas flow

calculated OLR

Time (days)

Gas

flow

(m3 /d

)

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

Org

anic

load

ing

rate

(OLR

) (Kg

TVS/

m3 *d

)

Fig. 2. Comparison between the simulated and the experimental biogas productionrate and the variation of the organic loading rate (OLR) with time.

0 5 10 15 20 25 300

20

40

60

80

100

CH

4 an

d C

O2 (

%)

Time (days)

simulated CH4simulated CO2measured CH4measured CO2

Fig. 3. Comparison between the simulation and the experimental % of CO2 and CH4.

0 10 20 300.00

0.02

0.04

0.06

0.08

0.10simulated ICsimulated INmeasured ICmeasured IN

measured pH

Time (days)

Efflu

ent I

C a

nd IN

(Km

ol/m

3 )

0

2

4

6

8

10

12

14

simulated pH

Efflu

ent p

H

Fig. 4. Comparison between the simulation and the experimental IC, IN and pH.

1542 K. Derbal et al. / Bioresource Technology 100 (2009) 1539–1543

the experiment. The differences between experimental and simu-lated results are damped after the first 10 days, similarly to theother results (Fig. 4).

The simulated results of inorganic nitrogen do not present theaverage experimental trend and seem to be underestimated com-pared to the experimental values (Fig. 4) contrarily to the hydroly-sis and ammonification of disintegrated particulate matter whichwas underestimated by the model. This also may be due to the le-vel of the kinetic constant values.

The results of pH are well simulated by ADM1 and are stable, incomparison to BA variations (Fig. 4). As a monitoring variable, BA ismore sensitive than pH, and therefore it can be used as a controlparameter for the operation of anaerobic digesters.

4. Conclusion

The ADM1 model was tested to simulate the behaviour of a bio-reactor for the anaerobic co-digestion of waste activated sludgeand biowaste.

ADM1 showed acceptable simulating results, regarding thenumber of parameters involved and processes considered. How-ever, it is important to note, according to the findings of this studythat the ADM1 model is relatively limited in simulating complexprocesses such as anaerobic digestion. In fact it cannot reproducethe intimate variations of the different parameters, but an averagetrend is exhibited. This can be explained, as mentioned previously,by the fact that not all the input kinetic parameters were obtainedvia analyses but extracted from this literature.

For the present case, the obtained results can be tested for theprediction of the different operating parameters. ADM1 can, there-fore, be used as a managing tool of anaerobic digestion.

The simulated results show an acceptable fit. However, at thestart of the experiment, where a transient state prevails, the simu-lated results do not show a good fit.

It was confirmed that inorganic carbon or bicarbonate alkalinityis a very sensitive parameter to volatile fatty acids accumulationthan pH or VFA variations and hence it can be used as a monitoringparameter for VFA accumulation.

References

Batstone, D.J., Keller, J., 2003. Industrial applications of the IWA anaerobic digestionmodel No. 1 (ADM1). Water Sci. Technol. 47 (12), 199–206.

Batstone, D.J., Keller, J., Angelidaki, I., Kalyuzhnyi, S.V., Pavlostathis, S.G., Rozzi, A.,Sanders, W.T.M., Siegrist, H., Vavilin, V.A., 2002. Anaerobic Digestion Model No.1. International Water Association (IWA), Publishing, London, UK.

Blumensaat, F., Keller, J., 2005. Modelling of two-stage anaerobic digestion using theIWA anaerobic digestion model no. 1 (ADM1). Water Res. 39, 171–183.

Bolzonella, D., Innocenti, L., Pavan, P., Traverso, P., Cecchi, F., 2003a. Semi-drythermophilic digestion of the organic fraction of municipal solid wastes:focusing on the start-up phase. Bioresour. Technol. 86, 123–129.

K. Derbal et al. / Bioresource Technology 100 (2009) 1539–1543 1543

Bolzonella, D., Battistoni, P., Mata-Alvarez, J., Cecchi, F., 2003b. Anaerobic digestionof organic solid wastes: process behaviour in transient conditions. Water Sci.Technol. 48 (4), 1–8.

Bolzonella, D., Francesco, Fatone, Pavan, P., Cecchi, F., 2005a. Anaerobicfermentation of organic municipal solid wastes for the production of solubleorganic compounds. Ind. Eng. Chem. Res. 44, 3412–3418.

Bolzonella, D., Pavan, P., Battistoni, P., Cecchi, F., 2005b. Mesophilic anaerobicdigestion of waste activated sludge, influence of the solid retention time in thewastewater treatment process. Process Biochem. 40, 1453–1460.

Cout, D., Genon, G., Ranzini, M., Romano, P., 1994. Anaerobic co-digestion ofmunicipal sludge and industrial organic waste. In: Proceedings of the SeventhInternational Symposium on Anaerobic Digestion, Johannesburg, South Africa.

Demirer, G.N., Duran, M., Erguder, T.H., Guven, E., Ugurlu, O., Tezel, U., 2000.Anaerobic treatability and biogas production potential studies of different agro-industrial wastewater in Turkey. Biodegradation 11, 401–405.

Erguder, T.H., Guven, E., Demirer, G.N., 2000. Anaerobic digestion of olive millwastes in batch reactors. Process Biochem. 36, 243–248.

Erguder, T.H., Tezel, U., Guven, E., Demirer, G.N., 2001. Anaerobic biotransformationand methane generation potential of cheese whey in batch and UASB reactors.Waste Manage. 21, 643–650.

Feng, Y., Behrendt, J., Wendland, C., Otterpohl, R., 2006. Parameters analysis anddiscussion of the anaerobic digestion model no. 1 (ADM1). Water Sci. Technol.54 (4), 139–147.

Fezzani, Boubaker, Ben Cheikh, Ridha, 2007. Anaerobic co-digestion of olive millwastewater with olive mill solid waste in a tubular digester at mesophilictemperature. Bioresour. Technol. 98, 769–774.

Igoud, S., Tou, I., Kehal, S., Mansouri, N., Touzi, A., 2002. Première approche delacaractérisation du biogaz produit à partir des déjections bovines.Énergierenouvelable 5, 123–128.

Jewell, W.J., 1979. Future trends in digester region. In: Proceedings of the FirstInternational Symposium on Anaerobic Digestion, Cardiff, Wales. AppliedScience Publishers, London, pp. 17–21.

Kayhanian, M., Rich, D., 1995. Pilot-scale high solids thermophilicanaerobicdigestion of municipal solid waste with an emphasis on nutrimentrequirements. Biomass Bioenergy 8 (6), 433–444.

Kayhanian, M., Tchobanoglus, G., 1992. Pilot investigation of an innovativetow-stage anaerobic digestion and aerobic composting process for therecovery of energy and compost from the organic fraction of MSW. In:Proceedings of the First International Symposium on Anaerobic Digestion,Venice, Italy.

Macé, S., Bolzonella, D., Cecchi, F., Mata-Alvarez, J., 2003. Comparison of thebiodegradability of the grey fraction of municipal solid waste of Barcelona inmesophilic and thermophilic conditions. Water Sci. Technol. 48 (4), 21–28.

Mata-Alvarez, J., 2003. Biomethanization of the Organic Fraction of Municipal SolidWastes. IWA Publishing, London, UK, pp. 42.

Mata-Alvares, J., Macé, S., Libres, P., 2000. Anaerobic digestion of organic solidwastes. An overview of research achievements and perspectives. Bioresour.Technol. 74, 3–16.

Olivier, Bernard, Zakaria, Hadj-Sadok, Denis, Dochain, Antoine, Genovisi, Steyer,Jean-Philipe, 2001. Dynamical model development and parameter identificationfor an anaerobic wastewater treatment process. Biotechnol. Bioenergy 75 (4),424–438.

Parker, Wayne J., 2005. Application of the ADM1 model to advanced anaerobicdigestion. Bioresour. Technol. 96, 1832–1842.

Vallini, G., Cecchi, F., Pavan, P., Alvarez, M., Basseti, A., 1992. Recovery and disposalof the organic fraction of MSW by means of combined anaerobic and aerobicbiotreatments. In: Proceedings of the Fifth International Symposium onAnaerobic Digestion of Solid Wastes, Venice, Italy.

Wolfsberger, A., Holubar, P., 2006. WP7 Biokinetic Data. Modelling and ControlSecond Year CROPGEN Meeting, Vienne.

Zaher Usama El-Sayed, 2004–2005. Modelling and monitoring the anaerobicdigestion process in view of optimisation and smooth operation of WWTP’s.PhD Thesis in Appl. Biol. Sci.: Environ. Technol. Academic Year 2004–2005,Universiteit Gent, Faculty of Bioscience Engineering.