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Journal of Hazardous Materials 162 (2009) 1563–1570

Contents lists available at ScienceDirect

Journal of Hazardous Materials

journa l homepage: www.e lsev ier .com/ locate / jhazmat

xtension of the anaerobic digestion model No. 1 (ADM1) to include phenolicompounds biodegradation processes for the simulation of anaerobico-digestion of olive mill wastes at thermophilic temperature

oubaker Fezzani ∗, Ridha Ben Cheikhiogas Laboratory, Industrial Engineering Department, URSAM - Ecole Nationale d’Ingénieurs de Tunis,niversité Tunis El Manar, BP. 37 Le Belvédère 1002 Tunis, Tunisia

r t i c l e i n f o

rticle history:eceived 14 November 2007eceived in revised form 22 June 2008ccepted 24 June 2008vailable online 10 July 2008

eywords:

a b s t r a c t

This paper describes for the first time the extension of the anaerobic digestion model No. 1 (ADM1) tohandle and simulate the anaerobic degradation processes of phenol compounds and homologues in olivemill wastewater (OMW) and olive mill solid waste (OMSW) at thermophilic temperature (55 ◦C). Thegeneral structure of the ADM1 was not changed except for the modifications related to the inclusion ofphenolic compounds degradation processes into acetate and further into methane and CO2. The effectof soluble phenolic compounds upon pH was taken into account in the pH simulation equations. Theinhibitory effect of phenolic compounds on the fermenting process and methanogenic sub-populations

athematical modellingDM1naerobic co-digestionhenol compoundslive mill wastewaterlive mill solid waste

was accounted for by the use of non-competitive inhibition functions. The most sensitive and new phenolicparameters were calibrated and validated using experimental data from our previous study dealing withthe thermophilic anaerobic co-digestion of OMW with OMSW in semi-continuous tubular digesters. Thesimulation results indicated that the extended ADM1 was able to predict with reasonable accuracy effluentphenol concentrations and gas flow rates and effluent pH of various influent concentrations digested at

(HRT

fishpmngaanaln

ubular digesterhermophilic temperature

hydraulic retention times

. Introduction

The anaerobic digestion model No. 1 (ADM1) developed recentlys a structured model that describes complex substrates byheir main components (carbohydrates, lipids, proteins, sugars,mino acids, long chain fatty acids (LCFAs), volatile fatty acidsVFAs), cations and anions) and includes multiple steps describ-ng biochemical and physicochemical processes encountered inhe anaerobic biodegradation of complex organic compounds [1].

any implementations of this powerful tool have been tested androved their success in simulating the anaerobic digestion of sev-ral industrial wastewaters [2–7]. Besides, many extensions andodifications of the ADM1 model have been established by several

esearchers to improve the outputs of the model and to enlarge its

apability to handle other main compounds in substrates submit-ed to fermentation and not included in the original ADM1 suchs the inclusion of lactate and ethanol into ADM1 for accurateio-hydrogen simulations [8]; the extension of ADM1 to include

∗ Corresponding author at: 28 Rue Larbi Zarrouk 9000 Beja - Tunisia.el.: +216 97 37 69 69.

E-mail addresses: bfezzani2007@yahoo.fr, b.fezzani@laposte.net (B. Fezzani).

wpi(

ttcc

304-3894/$ – see front matter © 2008 Elsevier B.V. All rights reserved.oi:10.1016/j.jhazmat.2008.06.127

s) of 36 and 24 days.© 2008 Elsevier B.V. All rights reserved.

ormation and emission of odorants [9]; the extension of ADM1 tonclude the effect of nitrate reduction processes [10] and the exten-ion of ADM1 to include cyanide compounds [11]. On the otherand, the extension of the ADM1 to include the biodegradation ofhenolic compounds and homologues present at high level in oliveill wastewaters (OMWs) and olive mill solid wastes (OMSWs) has

ever been done by any researcher. In fact, OMWs and OMSWs areenerated by the industries of olive oil, in the Mediterranean region,nd contain (in addition to carbohydrates, lipids, proteins, sugars,mino acids, LCFA, VFA, cations and anions) phenols and polyphe-olic compounds. The concentration of phenols reaches up to 15 g/lnd contributes in inhibiting the methanogenic process at highevel [12,13]. The objective of this work was to incorporate the phe-olic compounds and phenol degradation processes into the ADM1ith emphasize placed on the simulation of gas flow rates, pH andhenol concentrations in effluents generated from digesters treat-

ng in co-digestion OMW and OMSW at thermophilic temperature55 ◦C).

The results of the extended ADM1 model were comparedo some experimental results obtained from the study of thehermophilic anaerobic co-digestion of OMW with OMSW in semi-ontinuous tubular digesters fed with various initial substrateoncentrations at different HRTs.

1564 B. Fezzani, R.B. Cheikh / Journal of Hazardo

Nomenclature

COD chemical oxygen demandDE differential equationsHRT hydraulic retention time (days)Ka,ph phenolic acid equilibrium constant (mol/l)kB,ph kinetic rate constant of phenol acid–base reaction

(mol/l/day)NH4

+–N total ammonium nitrogen (mg/l) or (mg/kg TS)OMW olive mill wastewaterOMSW olive mill solid wasteQ influent and effluent flow rate (m3/day)SCOD soluble chemical oxygen demand (g COD/l)Sph soluble phenol concentration (g COD/l)Sph− phenol ion concentration (mol/l)TCOD total chemical oxygen demand (g COD/l)TKN total Kjeldahl nitrogen (g/l) or (g/kg TS)TS total solids (g/l)Vliq liquid reactor volume (m3)VS volatile solids (g/l)Xph particulate phenol concentration (g COD/l)XBph concentration of phenol biomass (g COD/l)

Greek symbols�j kinetic rate equation for process j of ADM1 model

2

2

a[mdcdtb(ppedbmic

2

[wmppaias

iOlptia

C

Braw

2

ivpchdworaerm

dm

2

ttifatnwactda

2

tptemperature are given below:

(kg COD m3/day)�i,j Stoichiometric coefficients of ADM1 model

. Suggested modifications to ADM1

.1. Degradation of phenol under methanogenic conditions

Phenol anaerobic degradation is a complex process and requiresconsortium of various microorganisms. In 1985, Young and Rivera

14] and other authors suggested that phenol could be stoichio-etrically converted to methane and carbon dioxide by anaerobic

igestion. More recently it was found that under methanogeniconditions, the degradation process of phenol can proceed throughifferent pathways. So far, two possible pathways for mineraliza-ion of phenol have been reported; either via benzoate into theenzoyl-CoA pathway (mesophilic temperature) or via caproatethermophilic temperature). At ambient and mesophilic tem-eratures, it was confirmed by many authors that phenol wasresumably degraded through benzoate pathway [15–18]. How-ver, at thermophilic temperature phenol was assumed to beegraded through caproate pathway which is further convertedy acetogens to acetate but caproate was not confirmed experi-entally as an intermediate [19]. In fact, neither caproate has been

dentified as an intermediate, nor the bacteria responsible for theaproate production has been identified [19].

.2. Modification of the basic structure

The original ADM1 basic structure designed by Batstone et al.1] to help in understanding the degradation processes of complexastewater by their main compounds is not suitable for realisticodelling wastewaters containing, in addition to the main com-

ounds predefined by the original ADM1, other compounds like

articulate and soluble phenol compounds such as wastewatersnd solid wastes from olive oil industries (OMW and OMSW). Fig. 1llustrates the new ADM1 basic structure modified to take intoccount phenol compounds as composite, particulate and solubleubstrates. As can be seen, original ADM1 structure is modified to

us Materials 162 (2009) 1563–1570

nclude the following steps: disintegration of composite solids (likeMSW) into particulate phenol compounds; hydrolysis of particu-

ate phenols to produce soluble phenols; finally and to simplify thehenol degradation process discussed above we suppose that, athermophilic temperature, soluble phenol compounds (expressedn terms of phenol equivalent) are converted into acetate, hydrogennd carbon dioxide according to the following reaction:

6H6O + 0.025NH3 + 5.302H2O → 0.025C5H7NO2 + 2.75C2H4O2

+ 2.75H2 + 0.375CO2 (1)

ased on the these modifications the ADM1 model will be moreealistic in phenol process monitoring, data analysis and to begood starting point to model phenol degradation in olive millastes submitted to thermophilic anaerobic digestion.

.3. Additional growth kinetics

The inclusion of phenol compounds (soluble and particulate)nto the ADM1 model requires the addition of three extra stateariables described in terms of COD (two for soluble and particulatehenols and one for phenol degrading organisms) and four phenolsonversion processes: one for phenol disintegration, one for phenolydrolysis, one for uptake of phenol and one for decay of phenolegrading organisms. Phenolic compounds conversion processesere described by a number of kinetic expressions. The hydrolysis

f particulate phenols compounds (Xph) was described by first orderate expression. The conversion of soluble phenol compounds tocetate was expressed by Haldane growth kinetic equation. Finally,ndogenous decay process of phenol degrading biomass was rep-esented by first order kinetic expression and dead biomass wasaintained in the system as composite particulate material.The new kinetic equations, new yield coefficients and new

erived stoichiometry for all steps included in the extended ADM1odel are presented in Table 1.

.4. Additional and modified equations

The liquid phase differential equations (DE) that were added tohe original ADM1 model updated by Rosen and Jeppsson [20] toake into account phenol compounds degradation were as follow-ng: one (DE) for particulate phenol degradation process, one (DE)or soluble phenol degradation into acetate at thermophilic temper-ture and one (DE) for phenol biomass concentration modelling. Onhe other hand, acetate, hydrogen, inorganic carbon and inorganicitrogen liquid phase concentration (Sac, Sh2, SIC and SIN) equationsere modified to include the contributions of phenol compounds

ccording to the reaction Eq. (1) suggested in Section 2.2. Also,omposite substrate (Xc) concentration equation was modified toake into account composite substrate issued from phenol biomassecay. Finally, pH simulation equations were modified to take intoccount the effect of soluble phenolic compounds on effluent pH.

.4.1. Additional phenol liquid phase equationsThe mass balance equations added to ADM1 model to describe

he dynamic degradation of phenol substrates and the behavior ofhenol biomass concentration in the liquid phase at thermophilic

dXph

dt= Q

Vliq(Xph, in − Xph) + fXph, Xc �1 − �4a (2)

dSph

dt= Q

Vliq(Sph, in − Sph) + fSph, Xph

�4a − �7a (3)

B. Fezzani, R.B. Cheikh / Journal of Hazardous Materials 162 (2009) 1563–1570 1565

1 mo

wpau

S

TB

O

Fig. 1. Biochemical conversion processes according to IWA ADM

dXBph = Q(X − X ) + Y � − � (4)

dt VliqBph, in Bph ph 7a 20

here Sph represents the concentration of soluble phenol com-ounds, Xph is the concentration of particulate phenol compoundsnd XBph is the concentration of phenol biomass, Vliq is the liq-id reactor volume, Q is the flow rate into and out of the reactor,

Xn�c(

able 1iochemical rate coefficients (�i,j) and kinetic rate equations (�j) for particulate compone

nly additional processes and components to ADM1 are shown.

del [1] extended for phenols compounds degradation pathway.

ph,in is the input concentration of the soluble phenol components,

ph,in is the input concentration of the particulate phenol compo-ents, XBph,in is the input concentration of the phenol biomass andj (j = 4a, 7a and 20) are the new specific kinetic rates for phenolompounds degradation processes in the extended ADM1 modelsee Table 1).

nts

1566 B. Fezzani, R.B. Cheikh / Journal of Hazardous Materials 162 (2009) 1563–1570

Table 2Characteristics of the OMW and the sludge used in the extended ADM1

Parameters Units OMW Initial composition Sludge

Initial composition Composition after batch mode fermentation

pH – 7.5 ± 0.3 7.5 ± 0.2 7.5TCOD g COD/l 130 ± 3.5 37.5 ± 0.5 20.56SCOD g COD/l 80 ± 2.5 0.04 ± 0.005 1.72Total carbohydrates g COD/l 35 ± 1.5 10.05 ± 0.3 0.7Total proteins g COD/l 14 ± 1.5 8.4 ± 0.2 0.5Total lipids g COD/l 25 ± 1.5 2.03 ± 0.005 0.3Total phenols g COD/l 31 ± 1.6 0.00 0.0Total inerts g COD/l 25 ± 1.5 17 ± 0.25 19Sugars g COD/l 18 ± 1.5 0.015 ± 0.01 0.08Amino acids g COD/l 6.5 ± 1.5 0.0015 ± 0.001 0.05LCFA g COD/l 10 ± 1.5 0.0 0.03Soluble phenols g COD/l 16 ± 1.25 0.0 0.0Soluble inerts g COD/l 11.55 ± 1.5 0.0 1.5Acetic acid g COD/l 7.5 ± 0.5 0.0 0.02Propionate acid g COD/l 3.75 ± 0.5 0.0 0.01Butyrate acid g COD/l 4.85 ± 0.5 0.01 ± 0.002 0.01Valerate acid g COD/l 1.85 ± 0.5 0.01 ± 0.008 0.02Alkalinity g CaCO3/l 3.8 ± 0.3 3.8 ± 0.35 3.4 ± 1.2Inorganic nitrogen (IN) g N/l 750 ± 55 1.3 ± 0.05 1.6 ± 0.15Inorganic carbon (IC) mol/l 0.074 ± 0.006 0.062 ± 0.006 0.054AC

E licate

2

bapr

wc(

wp

wo

2

tp

S

we

w

�

wkr

2

t

I

I

I

wi

nions mol/l 0.073 ± 0.003ations mol/l 0.464 ± 0.018

ach value is an average of three replicates. ± Shows standard deviations among rep

.4.2. Modified liquid phase equationsAt thermophilic temperature acetate, hydrogen, inorganic car-

on and inorganic nitrogen liquid phase concentration (Sac, Sh2, SICnd SIN) equations were modified to include the contributions ofhenol compounds according to the suggested phenol degradationeaction (1) as follows:

dSac

dt= Q

Vliq(Sac, in − Sac) +

∑

j=1−19

�ac, j�j + (1 − Yph)fac, ph�7a (5)

dSh2

dt= Q

Vliq(Sh2, in − Sh2) +

∑

j=1−19

�h2, j�j

+(1 − Yph)fh2, ph�7a − �T, h2 (6)

dSIC

dt= Q

Vliq(SIC, in − SIC) +

∑

j=1−19

�IC, j�j − fph, Xc CXph�1

+(CXph− Cph)�4a + (Cph − (1 − Yph)Cac − YphCbiom)�7a

+(Cbiom − CXc )�20 − �T, co2 (7)

dSIN

dt= Q

Vliq(SIN, in − SIN) +

∑

j=1−19

�IN,j�j − YphNbiom�7a

+(Nbiom − NXc )�20 (8)

here∑

i=1−19�i�j (i = ac, h2, IC and IN) are the sums of the stoi-hiometric coefficients (�i) multiplied by the specific kinetic rates�j) for process j of the original ADM1 model [1,20].

Furthermore, composite substrate concentration (Xc) equationas modified, to take into account composite substrate issued from

henol biomass decay, as follows:

dXc

dt= Q

Vliq(Xc,in − Xc) +

∑

j=13−19

�j + �20 − �1 (9)

aa

I

0.091 ± 0.002 0.0910.027 ± 0.004 0.027

s.

here∑

i=13−19�j is the sum of the specific kinetic rates (�j) of theriginal ADM1 model.

.4.3. Modified pH simulation equationsThe charge balance equation of the original ADM1 was modified

o take into account the contribution of soluble phenolic com-ounds into acid–base reactions as follows:

H+ − SOH− = SHCO−3

+ Sac−

64+ Spro−

112+ Sbu−

160+ Sva−

208+

Sph−

220

+SAn− − SCat+ − SNH+4

(10)

here Sph− is the phenol ion concentration implemented in thextended ADM1 model as kinetic rate equation as following:

dSph−

dt= −�A, ph (11)

here

A, ph = kB, ph(Sph− (Ka, ph + SH+ ) − Ka, phSph) (12)

here Ka,ph (mol/l) is the phenolic acid equilibrium constant andB,ph (mol/l/day) is the kinetic rate constant of phenol acid–baseeaction.

.5. Modification of the acetogenic inhibitory factor

The inhibition factor I5 applied to the rate of acetate uptake ofhe original ADM1 was modified as follows:

5 = IpH, acIIN,limINH3 ITVFAIphenol (13)

nstead of:

5 = IpH, acIIN, limINH3 (in the original ADM1) (14)

here ITVFA and Iphenol are non-competitive functions added to takento account the inhibition of methanogenic steps by high total VFA

nd high phenol concentrations, respectively. Their expressions ares follows:

TVFA = 11 + STVFA/KITVFA

(15)

B. Fezzani, R.B. Cheikh / Journal of Hazardo

Table 3Characteristics of OMSW used as co-substrate

Parameters Units Average value OMSW

TS % 97 ± 2VS g/kg TS 970 ± 0.5TCOD g COD/kg TS 1180 ± 2Carbohydrates g/kg TS 362 ± 10Total lignins g/kg TS 350 ± 10Total proteins g/kg TS 125 ± 5Total lipids g/kg TS 110 ± 5Total polyphenols g/kg TS 23 ± 5T

Er

I

3

Htwmcdwvg

4

4

Ibpppalpsoi

vo

4

iO

4

4

uA[thieos

4

tcswtprstafiWcaA

e

TI

S

ffffff

f

ffNNC

CKk

KN g N/kg TS 20 ± 1.5

ach value is an average of three replicates. ± Shows standard deviations amongeplicates.

phenol = 1

1 + (Sphenol)2/KIphenol

(16)

. Lab-scale experiments data

Experimental data of three reactors R1, R2 and R3 operated atRTs of 36 and 24 days (from our previous work dealing with the

hermophilic anaerobic co-digestion of OMW with OMSW [12])ere used to compare the simulations of the extended ADM1 toeasurements. Each reactor was fed with an influent substrate con-

entration of 43, 67 and 130 g COD/l, respectively. The amount of thery OMSW was 56 g TS/l of OMW. Alkalinity in the form of Ca(OH)2as added to all OMW concentrations (5–25 g/l of OMW) to pro-

ide a neutral medium (pH: 7.0–8.0) for the methanogens Archaearowth.

. Results and discussion

.1. Substrates definitions

OMW and OMSW were represented by their main components.n fact, OMW (primary organic substrate) was represented as solu-le substrates (sugars, amino acids, long chain fatty acids, solublehenols, soluble inert, volatiles fatty acids, anions and cations) andarticulate substrates (carbohydrates, proteins, lipids, particulatehenols and particulate inert). Also, all phenol compounds (solublend particulate) are expressed in terms of phenolic acid equiva-

ent. The dry OMSW was represented as composites substrates (orolymers) and the phenolic fraction of the composite Xc was repre-ented by coefficient fXph,Xc . Tables 2 and 3 show the characteristicsf OMW, OMSW and the sludge used to determine the values ofnput steady-state variables and the initials values of steady-state

narat

able 4nitial and estimated values of stoichiometric parameters

toichiometric parameters Names

SI, Xc Soluble inert fraction in OMSW

SI, Xc Particulate inert fraction in OMSW

ch, Xc Carbohydrates fraction in OMSW

pr, Xc Proteins fraction in OMSW

li, Xc Lipids fraction in OMSW

Xph,Xc Particulate phenol fraction in OMSW

Sph,XphSoluble phenol fraction issued from particulate phenol de

ac,ph Acetate fraction issued from soluble phenol degradation

h2,ph Hydrogen fraction issued from soluble phenol degradation

Xc Nitrogen content in OMSWI Nitrogen content in inert substrates of OMSW

XphCarbon content in particulate phenol compounds

ph Carbon content in soluble phenol compounds

a,ph Phenolic acid equilibrium constant

B,ph Kinetic rate constant of phenol acid–base reaction

us Materials 162 (2009) 1563–1570 1567

ariables of the extended ADM1 to run the simulations of the anaer-bic co-digestion of OMW with OMSW.

.2. Model implementation

The set of ordinary differential equations of the ADM1 weremplemented using Matlab 7.0 software and integrated with theDE15s solvers as recommended by Rosen et al. [21].

.3. Model calibration

.3.1. Initial conditionsThe data set from the reactor R2 operated at a HRT of 36 days was

sed to assist the model calibration. Initial values of the originalDM1 parameters were those suggested by Rosen and Jeppsson

20]. Initial values of parameters related to phenolic compounds ofhe extended ADM1 (phenol maximum specific uptake rate; phenolalf-saturation constant; decay phenol biomass constant, phenol

nhibition constant for uptake and phenol yield coefficient) werextracted from standards values in literatures [22]. Initial valuesf all the model state variables were obtained by simulating theludge in batch mode during 10 days as shown in Table 2.

.3.2. Parameters estimationThe estimation procedure to identify the new phenolic parame-

ers and other sensitive parameters (disintegration and hydrolysisonstants; maximum specific uptake rates; half-saturation con-tants; inhibition constant for uptake and decay biomass constants)as as following: disintegration rate constant was set initially

o 0.115 d−1 and the hydrolysis rate constants for carbohydrates,roteins and lipids were set initially to 0.35, 0.2 and 0.063 d−1,espectively, as determined previously by Stamatelatou et al. whotudied the anaerobic digestion of OMSW under mesophilic andhermophilic conditions [7]. Then an iterative procedure waspplied in adjusting especially disintegration rate constant throughtting the predicted gas flow rate to measured gas flow rate.hereas the hydrolysis rate constants were let without change. The

orrelated parameters such as: maximum specific uptake rates (Km)nd half-saturation constants (Ks) of VFA were adjusted throughDM1 fitting to effluent measured data.

Ammonia and TVFA inhibition parameters for acetate utilis-rs were adjusted to avoid the digester failure at each HRT. The

ew sensitive phenolic parameters (of the extended ADM1) weredjusted by fitting the simulation model outputs to experimentalesults. The modified stoichiometric parameters were determinedccording to the OMSW chemical composition. The other parame-ers with low sensitivity on phenol model outputs were applied

Units Original suggested values Estimated values

– 0.1 0– 0.2 0.36– 0.2 0.37– 0.2 0.13– 0.3 0.11– – 0.03

gradation – – 1– – 2.75– – 2.75Kmol N/kg COD 0.0376/14 0.0167/14Kmol N/kg COD 0.06/14 0.00Kmol C/kg COD – 0.033Kmol C/kg COD – 0.0319mol/l – 3.16e−10mol/l/day – 1e+10

1568 B. Fezzani, R.B. Cheikh / Journal of Hazardous Materials 162 (2009) 1563–1570

Table 5Estimated kinetic parameters of the implemented extended ADM1

Kinetic parameters Names Units Estimated values

kdis Disintegration constant d−1 0.015khyd,ph Phenol hydrolysis constant d−1 0.001km,ph Monod maximum specific rate for phenol uptake d−1 2.25kSph

Half-saturation constant for phenol uptake kg COD m−3 10.5KIph

Inhibition constant for phenol uptake kg COD m−3 50kdec,Bph Phenol biomass decline constant d−1 0.02Yph Phenol yield coefficient kg CODX/kg CODs 0.018k skk ersk utilise

w(rTrt

4

bcqs

FT

pp0ntt(

m,ac Maximum uptake rate for acetate utiliserm,su Maximum uptake rate for sugar utilisers

ITVFATVFA inhibition constant for acetate utilis

INH3Ammonia inhibition constant for acetate

ithout any modification such as physicochemical parametersequilibrium coefficients and constants). Modified stoichiomet-ic coefficients implied in the extended ADM1 were presented inable 4. Estimated parameter values that better fit the experimentalesults of gas flow rates, pH and effluent soluble phenol concentra-ions are given in Table 5.

.3.3. Calibration results

Fig. 2 shows measured and simulated results of effluent solu-

le phenol concentration, gas flow rate and effluent pH after modelalibration. Effluent soluble phenol concentrations were predicteduite well with some deviations within 0.1–0.5 g COD/l betweenimulations and experimental results. Gas flow rate and effluent

ig. 2. Simulation results in comparison with experimental data for an influentCOD concentration of 67 g COD/l at a HRT of 36 days after parameters calibration.

4

rdts

4

c

Fed

d−1 15d−1 1.7kg COD m−3 7.5

rs Kmol m−3 3.21e−3

H were predicted quite well by the extended model at steady-stateeriod but they revealed some discrepancies within 5–10 l/day and.2–0.6, for the first fifteen and thirty days respectively. Also, weoticed that the deviations between measurements and simula-ion of effluent pH given by the extended model were greater thanhose given by the original model as presented in our previous workFezzani and Ben Cheikh [24]).

.4. Model validation

The calibrated model was validated with the experimentalesults of the reactors R1 and R3 operated at HRTs of 36 and 24ays applying the same pervious calibrated parameters. Most ofhe simulation results were comparable to the measurements as

hown below.

.4.1. Phenol simulation resultsFig. 3 shows measured and simulated results of soluble phenol

oncentrations in effluents rejected from digester R1 treating influ-

ig. 3. Validation results of soluble phenol concentration simulations with efflu-nt phenol experimental data of an influent TCOD concentration of 43 g COD/l atifferent HRTs: 36 days (A) and 24 days (B).

B. Fezzani, R.B. Cheikh / Journal of Hazardous Materials 162 (2009) 1563–1570 1569

Fed

ecaw

nandtmot2ea

4

rtmpcsdgot(cwgctw

Ff2

4

the reactor R1 at HRTs of 36 and 24 days. Effluent pH was simulatedquite well by the extended model at steady-state period of bothHRTs but it revealed some deviations within 0.3–0.5 at transientperiods of both HRTs.

ig. 4. Validation results of soluble phenol concentration simulations with efflu-nt phenol experimental data of an influent TCOD concentration of 130 g COD/l atifferent HRTs: 36 days (A) and 24 days (B).

nt substrate concentration of 43 g COD/l. Effluent soluble phenoloncentrations were predicted accurately by the extended modelnd the deviations between the simulations and measurementsere less than 2 g COD/l.

Fig. 4 shows measured and simulated results of soluble phe-ol concentrations in effluents rejected from digester R3 treatingn influent substrate concentration of 130 g COD/l. Effluent phe-ol concentrations were replicated reasonably well at a HRT of 36ays. But, some deviations within 1–2 g COD/l were observed just athe end of the steady-state period. Also, great deviations between

easurements and model simulations (within 2–5 g COD/l) werebserved at HRT of 24 days. These inconsistencies between simula-ions and effluent soluble phenol experimental results at a HRT of4 days may be due to the correlation of the most sensitive param-ters such as hydrolysis constants with feed concentration and HRTs mentioned by Gavala et al. [23].

.4.2. Gas flow simulation resultsFigs. 5 and 6 show measured and simulated results of gas flow

ates in the reactors R1 and R3, respectively. For low feed concen-ration gas flow rate was simulated quite well by the extended

odel and the deviations were within 2–5 l/day at steady-stateeriod and within 5–10 l/day at transient period. For high feedoncentration gas flow rate was predicted with high accuracy atteady-state period of the HRT of 36 days but it presented someeviations at transient state period. Also, some deviations betweenas flow rate and measurements, in the range of 1–10 l/day, werebserved at a HRT of 24 days. These inconsistencies may be dueo the correlation of some parameters with reactor configurationsuch as gas–liquid mass transfer coefficient) and others with feedoncentration and HRTs such as hydrolysis constants [23]. Besides,

e noticed that, for high feed concentration, gas flow predictions

iven by the extended model were enhanced by reducing the dis-repancies between experimental results and simulation comparedo those given by the original model as presented in our previousork [24].

Fo2

ig. 5. Validation of gas flow rate simulations with gas flow rate experimental resultsor an influent TCOD concentration of 43 g COD/l at different HRTs: 36 days (A) and4 days (B).

.4.3. pH Simulation resultsFig. 7 shows simulated and measured results of effluent pH from

ig. 6. Validation of gas flow rate simulations with gas flow rate experimental resultsf an influent TCOD concentration of 130 g COD/l at different HRTs: 36 days (A) and4 days (B).

1570 B. Fezzani, R.B. Cheikh / Journal of Hazardo

Fe

mOBpptpti

5

ccetasawfsc1miatct

R

[

[

[

[

[

[

[

[

[

[

[

[

[

[

[

ig. 7. Validation results of pH simulations with measurements values for an influ-nt TCOD concentration of 43 g COD/l at HRTs of: 36 days (A) and 24 days (B).

These discrepancies may be due to cumulative errors in esti-ating initials anions and cations concentrations of the sludge andMW as mentioned by other authors such as Zaher et al. [25].esides, they may be due to the assumptions done on phenolic com-ounds present in OMW and OMSW that could affect the modifiedH equation. Furthermore, we noticed that the modified pH equa-ion of the extended model was less accurate in predicting effluentH at transient period compared to what given by the pH equa-ion of the original model in our previous work [24] for the samenfluent.

. Conclusions

This study has demonstrated that the extended ADM1 modelould simulate with reasonable accuracy effluent soluble phenoloncentrations and the steady-state values of gas flow rates andffluent pH in three reactors operated at thermophilic tempera-ure (55 ◦C) and fed with influent substrate concentration of 43, 67nd 130 g COD/l, respectively, at HRTs of 36 and 24 days. Steady-tate of gas flow rates and effluent pH were replicated with highccuracy at different HRTs. Also, effluent phenol concentrationsere predicted quite well at HRTs of 36 and 24 days with low

eed concentrations. Nevertheless, some deviations between mea-urements and model simulations were observed for high feedoncentration within 2–5 g COD/l at a HRT of 24 days and within–2 g COD/l at a HRT of 36 days. At the end, the fundamentals of theodel are generally valid, although more studies are still needed to

mprove this extended model to predict more precisely gas flowsnd effluents pH at transient periods for different feed concentra-ions and to take into account the biodegradation process of phenolompounds via benzoate pathway at ambient and mesophilicemperatures.

[

us Materials 162 (2009) 1563–1570

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