Na

La

b

a

ARRA

KACOD

1

1

ocmanfadpalp

1d

Chemical Engineering Journal 180 (2012) 32– 38

Contents lists available at SciVerse ScienceDirect

Chemical Engineering Journal

jo ur n al homep age: www.elsev ier .com/ locate /ce j

ew indirect parameters for interpreting a destabilization episode in annaerobic reactor

.A. Fdez-Güelfoa,∗, C. Álvarez-Gallegoa, D. Salesb, L.I. Romeroa

Department of Chemical Engineering and Food Technology, Faculty of Science, University of Cadiz, 11510 Puerto Real, Cadiz, SpainDepartment of Environmental Technologies, Faculty of Marine and Environmental Sciences, University of Cadiz, 11510 Puerto Real, Cadiz, Spain

r t i c l e i n f o

rticle history:eceived 23 July 2011eceived in revised form 25 October 2011ccepted 25 October 2011

eywords:naerobic digestionontrol parametersrganic fraction of municipal solid wastesestabilization episode

a b s t r a c t

The anaerobic digestion (AD) process for waste stabilization is a very attractive option in managing theorganic fraction of municipal solid waste (OFMSW); hence, many industrial OFMSW biomethanationplants are operating today all around the world. In general, the literature contains many operational andcontrol parameters to check the behavior of AD systems. However, in some cases, the classical param-eters are not enough to explain destabilization episodes and new parameters (based on combinationsand transformations among classical parameters) must be elucidated to understand the problem. Thus,this study’s objective is to establish new indirect parameters (non-solubilized carbon; non-acid carbon;acidogenic substrate such as carbon) based on classical control parameters such as VS, VFA and DOC toevaluate the performance/efficiency of the anaerobic digestion of the OFMSW during a destabilization

episode caused by overloading and washing-out phenomena.

Thus, a study was conducted in a continuous stirrer tank reactor (CSTR) in thermophilic-dry conditionsin order to determine the evolution of these new indirect parameters during a destabilization episode inorder to obtain more specific information about the imbalance among the different steps involved in theAD process. This additional information may help prevent and interpret destabilization episodes in ADsystems.

. Introduction

.1. Background

Nowadays, several alternatives are available for treating therganic fraction of municipal solid wastes: biological, physical andhemical processes [1]. However, the selection of any treatmentethod depends on many aspects [2]. Biological processes such

s anaerobic digestion (AD) provide advantages over other tech-ologies. Treating organic wastes by AD is an attractive method

or stabilizing organic wastes into biogas and digestate. Biogas is desirable energy source whose generation may be improved byifferent strategies: by applying physicochemical and biologicalretreatments [3–5], co-digestion or temperature phased AD. Inddition, the digestate is a stable waste that serves as an excel-ent compost with low levels of pathogenic bacteria for agriculturalurposes [6].

∗ Corresponding author. Tel.: +34 956016379; fax: +95 6016411.E-mail address: alberto.fdezguelfo@uca.es (L.A. Fdez-Güelfo).

385-8947/$ – see front matter © 2011 Elsevier B.V. All rights reserved.oi:10.1016/j.cej.2011.10.091

© 2011 Elsevier B.V. All rights reserved.

1.2. Problem statement

Several available AD options are now being taken into consid-eration. The great diversity of reactor designs is matched by thelarge variability of waste composition and choice of operationalparameters such as retention time (RT), solids content, mixing,recirculation, inoculation, single or multi-stages and temperature,etc. Depending on the number of stages, in one-stage systems, allreactions take place simultaneously in a single reactor, while in twoor multi-stage systems, the reactions take place sequentially in atleast two reactors [7]. Furthermore, industrialists prefer one-stagesystems because simpler designs have fewer technical failures,lower investment costs and a more easily controlled process.

In addition, batch and continuous reactors are categorized onthe basis of operation mode. In batch reactors, the reactor vesselis loaded with raw feedstock and inoculated with digestate fromanother reactor. It is then sealed and left until it is thoroughlydigested. The digester is then emptied and a new batch of organicmixture is added. Nevertheless, in a continuous process, the reac-tor vessel is fed continuously with organic material and degraded

material is continuously removed from the bottom of the reactor[7]. However, there are some disadvantages to the batch process.Adhikari [8] has reported that a steady state is never achieved ina batch process. Moreover, the plant requires large spaces and is

Engin

nAft(

pttieAe(bm

ptcdgTtCiaaoTAtpt

ctnepTbaac

eopc

1

1

tNfaoc

rbwt

L.A. Fdez-Güelfo et al. / Chemical

ot practical due to the continuously increasing waste generation.dditional loading and unloading is another common issue. These

eatures have led many researchers to consider the aspects of con-inuous reactor design and thus, a continuous stirred tank reactorCSTR) on a laboratory scale has been used in this study.

The choice of parameters for monitoring and controlling the ADrocess will depend on several factors, such as origin of the waste,echnology of the digester used and knowledge available, etc. Inhe literature, several parameters have already been used for mon-toring and controlling the digesters. For example, Switzenbaumt al. [9] reviewed the parameters used for the characterization ofD processes in solid, liquid or gas phases. Generally, the param-ters used are exclusively based on liquid (pH, volatile fatty acidsVFA), alkalinity, redox potential, sulphide, dissolved organic car-on (DOC)) and gas (production, composition, hydrogen and carbononoxide monitoring) phases measurements.The chemical oxygen demand [10] and hydrogen in the liquid

hase [11] must be added to this description. The VFA concentra-ion has also long been recognized as an important parameter forontrolling anaerobic digesters. Indeed, when the pH is high, theigesters can work with high VFA concentrations of up to severalrams per liter. Yet, in this case, the treatment efficiency will be low.he use of bicarbonate alkalinity is another very popular parame-er since it decreases when VFA are accumulated. At least 1000 mgaCO3/L is needed for the process to operate successfully. Hydrogen

s also an important parameter. It has a very short relaxation timend the concentration in the gas phase may be between 20–30 ppmnd 400–600 ppm for the process to operate successfully. Theseperational values will depend on the organic loading rate (OLR).he OLR is a measure of the biological conversion capacity of theD system and is a particularly important control parameter in con-

inuous systems, since it is closely related to biogas yield and CH4roduction. In fact, many plants have reported system failures dueo overloading [7].

In general, in the literature there are many operational andontrol parameters to check the behavior of anaerobic diges-ion systems. However, in some cases, classical parameters areot enough to explain destabilization episodes and new param-ters based on combinations and transformations among classicalarameters must be elucidated in order to understand the problem.hus, this study aims to establish new indirect control parametersased on classical parameters such as VS, VFA and DOC to evalu-te the performance/efficiency of a CSTR for the thermophilic-drynaerobic digestion of the OFMSW during a destabilization episodeaused by overloading and washing-out phenomena.

Below, these new indirect parameters are introduced to the sci-ntific community as new tools for both scientists and operatorsf digesters and may help prevent a quick response to unwantedrocesses that lead to the inhibition of the anaerobic digestion pro-ess.

.3. New indirect parameters for the anaerobic digestion process

.3.1. Non-solubilized carbon (NSC)Organic matter determined as VS at 550 ◦C or 650 ◦C can be used

o estimate the amount of organic carbon that exists in the waste.avarro et al. [12] studied the “organic matter/organic carbon” ratio

or a wide range of solid wastes. Navarro tested 38 organic wastesnd obtained strong correlations between VS by calcination andrganic carbon by elemental microanalysis and oxidable organicarbon determined by Walkley and Black’s traditional method.

According to Navarro, it is very important to highlight that these

atios are characteristic of the waste and therefore, an error maye induced. However, these possible distortions are not importanthen following a temporal evolution. Navarro et al. [12] contrasted

his to the case of OFMSW, in which this relationship could be

eering Journal 180 (2012) 32– 38 33

between 2.03 and 1.87, which would mean between 49% and 53%carbon in organic matter. The average value of 51% has been con-sidered for estimations in this study.

The estimate of total organic carbon (TOC) from the experimen-tal data of organic matter (VS) allows the elucidation of a newparameter for monitoring the degradation of organic matter. Anew parameter can be estimated by subtracting the instrumentallydetermined DOC from the total organic carbon (estimated from thedata of VS using the ratio “Organic matter/organic Carbon”). Thismay be called “Non-Solubilized Carbon (NSC)” and would representthe organic carbon fraction that has not been solubilized in thehydrolysis stage. The expected behavior for this variable is a con-tinuous decrease along the organic matter solubilization during thehydrolysis step.

The above information may be summarized in the followingequations:

NSC(

M

L3

)= TOC

(M

L3

)− DOC

(M

L3

)(1)

where

TOC(

M

L3

)= VS

(M

L3

)0.51 (2)

1.3.2. Non-acid carbon (NAC)Solubilized organic matter from the hydrolysis and acidogenic

stages is composed of acid compounds (VFA) and non-acid com-pounds. Dissolved acid carbon (DAC) can be easily obtained fromthe contributions of the different VFA (C2–C7, including iC4, iC5 andiC6), determined by gas chromatography in the medium consider-ing the “carbon/molecular weight” ratios of each VFA independently.The difference between the estimated data of TOC (from VS data)and the DAC data allows for the estimation of the “Non-Acid Carbon(NAC)”. The NAC includes the non-solubilized carbon (biodegrad-able or not) and the soluble carbon that is not in acid form.

Considering the absolute amount of NAC, this variable’sbehavior should correspond to a continuously decreasing trend,especially in the initial o hydrolysis and acidogenesis phases. Later,during the methanogenesis step, the decline should be less abrupt.

However, the percentage of NAC may experience phases ofgrowth due to the consumption of acids. Although the absoluteamount of NAC decreases, the NAC percentage will rise if theacid carbon disappears by gasification. Ultimately, the result ofthe degradable carbon depletion is that most carbon will be in anon-acidic and non-biodegradable form.

Based on the above information, the DAC may be estimatedusing the following expression:

NAC(

M

L3

)= TOC

(M

L3

)− DAC

(M

L3

)(3)

DAC(

M

L3

)=

i=7∑i=2

[AiH(M/L3)ni12

MWi

](4)

where:

• AiH represents the concentration of every individual VFA.• ni, is the number of carbons of AiH.• MWi, is the molecular weight of AiH.

1.3.3. Acidogenic substrate such as carbon (ASC)The total VFA, determined by gas chromatography, and the DOC

determination by the TOC analyzer are highly reliable data, which

allow another derived parameter to be obtained.

The total VFA determined as the weighted sum over the molec-ular weight of C2–C7 acids expressed as mg/L of DAC can besubtracted from the DOC, also expressed in mg/L of carbon, to

34 L.A. Fdez-Güelfo et al. / Chemical Engineering Journal 180 (2012) 32– 38

as(bt

ccadyr

e

A

Aa

2

2

omsbri

tpm

sR

Table 1Operational procedure: initial organic loading rate (OLR0) and retention time (RT)for each stage.

Stage RT (day) OLR0 (kgVS/m3 day) Operation time (day)

1 15 11.82 452 10 17.72 50

(4.9%, w/w), bread (3.5%, w/w) and paper (55.8%, w/w), as wasreported by Martin et al. [16].

Table 2Characterization of the synthetic OFMSW.

Parameter Data

pH 7.78Density (kg/m3) 750Alkalinity (g CaCO3/L) 4.29Ammonia (g NH3–N/L) 1.68Total Nitrogen (g NH3–N/kg) 207.2TS (g/g sample) 0.90VS (g/g sample) 0.71FTS (g/g sample) 0.19

Fig. 1. Diagram of the laboratory-scale CSTR.

ccount for the fraction of non-acid soluble carbon. This non-acidoluble carbon may be called “Acidogenic Substrate such as CarbonASC)” and is the fraction of solubilized organic matter that has noteen transformed into volatile fatty acids and therefore, can be usedo study the behavior of the acidogenesis phase.

This variable’s expected evolution would be an initial increaseoinciding with the start of hydrolysis until a peak is reached thatoincides with the compensation of its generation by hydrolysisnd its consumption by acidogenesis. From that time on, its valueecreases, due to a greater extent of acidogenesis over the hydrol-sis, stabilizing at values that would be representative of the mostefractory soluble substrate.

Therefore, the ASC may be calculated by means of the followingxpression:

SC(

M

L3

)= DOC

(M

L3

)− DAC

(M

L3

)(5)

s can be seen, ASC is equivalent to the difference between the NACnd the NSC.

. Materials and methods

.1. Continuous stirred tank reactor

A 5 L reactor without biomass recycling with a working volumef 4.5 L was used (Fig. 1). The thermophilic conditions (55 ◦C) wereaintained by circulating water through the jacket from a thermo-

tatic water bath (7 L). The reactor was equipped with a dischargeall valve and several input/output ports located at the top: a stir-ing paddle (stirring rate of 13 rpm), pH probe, biogas outlet, feednlet and two extra pH controllers.

The pH was adjusted using an on/off controller and correc-ions were performed by adding 5 N NaOH and 1 N H3PO4. TheH was maintained stable in the 6.5–8 range, which is suitable for

ethanogenic microorganisms.In this type of reactor, the hydraulic retention time (HRT) and t

olid retention time (SRT) are equal. The reactor was operated withT in the range of 15–8 days. Three different organic loading rates

3 8 22.16 45

were used from 11.82 to 22.16 kgVS/m3 day. Each RT was main-tained for at least three periods in order to reach stable operation.The operation time of each RT is detailed in Table 1.

The destabilization episode was induced by operating the sys-tem above its optimal RT, 15 days according to Fdez-Güelfo et al.[13]. In stages 2 and 3, the OLR fed to the system was higher than thecritical rate (15 kgVS/m3 day) in order to maintain system stability,as established by Angelidaki et al. [14].

2.2. Inoculum and feed solution

The CSTR reactor was initially loaded with 1.5 kg of dry-milled(90% total solids – TS) synthetic OFMSW (OFMSWSYN) producedartificially in the laboratory. A total of 4 L of inoculum (i.e., 2 L ofsludge and 2 L of leachate) from the modified SEBAC (SequentialBatch Anaerobic Composting) reactors was necessary to hydrate thedry waste and adjust the moisture level of the waste to 30% in totalsolid (TS). The inoculation procedure and process stabilization havebeen previously published by Fdez-Güelfo et al. [15]. In that publi-cation, the objective was to study the start-up and stabilization ofthe CSTR. The goal of the present study is to examine a destabiliza-tion episode based on the same CSTR that was stabilized at 15 daysRT.

2.2.1. Feeding the CSTRAfter being started up with the inoculum, the CSTR reactor was

subsequently fed on a daily basis with an amount of OFMSWSYNthat was produced artificially in the laboratory and based on thenutritional requirements of the main populations of microorgan-isms involved in the anaerobic digestion [16]. This type of feedavoids the problem of large variations in the composition of theindustrial OFMSW. Constancy in the composition of the OFMSWis an important factor in ensuring an accurate determination ofthe efficiency of the process. The characterization of the syntheticOFMSW (OFMSWSYN) used is given in Table 2.

As for the composition of the waste, the main constituents werepotato (6.2%, w/w), cabbage (5.3%, w/w), orange (4.9%, w/w), apple

TC (mg/g) 112.6TIC (mg/g) 0.29DOC (mg/g) 112.3Total VFA (mgAcH/L) 1440

L.A. Fdez-Güelfo et al. / Chemical Engineering Journal 180 (2012) 32– 38 35

Table 3Average concentration of the main VFAs (expressed as mg/L) and total VFA (expressed as mgAcH/L).

Stage RT (day) mg/L

Acetic(C2)

Propionic(C3)

Isobutyric(iC4)

Butyric(C4)

Isovaleric(iC5)

Valeric(C5)

Isocaproic(iC6)

Caproic(C6)

Heptanoic(C7)

Total VFA(mgAcH/L)

1 15 4178 95 30 2018 57 n/d n/d n/d n/d 7.282 × 103

2 10 2612 90 27 2737 47 n/d n/d n/d 21 6.017 × 103

42

n

2

pthisopvs

cT

2

cssaodwl2f

dTtgcosftwg6

vaoopT(indrus

3 8 4250 66 22 1798

/d: non detected.

.2.2. Conditioning of the feedstock solutionThe control TS concentration in the daily feed is necessary for the

roper operation of the dry anaerobic digestion process. To achievehis, the OFMSWSYN must be conditioned in order to ensure theomogeneity of the samples and their TS content. The condition-

ng of the waste involves drying the feedstock at 55 ◦C for 24 h andubsequently at room temperature for 72 h until a final moisturef 10% is obtained. The dry waste is then milled by means of a higherformance mill (brand and model Retsch SM 2000-Retsch) to pro-ide an average particle size of around 1 mm. Thus, homogeneousamples can be obtained from originally heterogeneous waste.

Lastly, the TS concentration was adjusted to 30% (which is aharacteristic of dry anaerobic digestion) by adding tap water [17].his final solution was employed as a daily feed for the digester.

.3. Analytical techniques

The following analytical determinations were used for wasteharacterizations and process monitoring and control: TS, volatileolids (VS), alkalinity, pH, DOC, ammonium and VFA. To verify theystem’s performance, all the parameters were analyzed once a daynd determinations were performed according to Standard Meth-ds [18]. TS, VS, pH, alkalinity and ammonium were determinedirectly from digested OFMSWSYN samples. The DOC concentrationas analyzed from the filtrate supernatant obtained by means of a

ixiviation (10 g of digested waste in 100 mL of Milli-Q water during0 min) of the effluent samples. Samples for the DOC analysis wereurther filtered through a 0.47 �m glass fiber filter.

The volume of gas produced in the reactor was measuredirectly by using a high precision flow gas meter – WET DRUMG 0.1 (mbar) – Ritter – through the Tedlar bag. The gas composi-ion (hydrogen, methane and carbon dioxide) was determined byas chromatography (SHIMADZU GC-14 B) with a stainless steelolumn packed with Carbosive SII (diameter of 3.2 mm and lengthf 2 m) and a thermal conductivity detector (TCD). The injectedample volume was 1 mL and the operational conditions were asollows: 7 min at 55 ◦C; ramped at 27 ◦C min−1 until 150 ◦C; detec-or temperature: 255 ◦C; injector temperature: 100 ◦C. The carrieras helium and the flow rate used was 30 mL min−1. A standard

as (by Carburos Metálicos, S.A; composition: 4.65% H2; 5.33% N2;9.92% CH4 and 20.10% CO2) was used for the system calibration.

Individual VFA (acetic, propionic, iso-butyric, butyric, iso-aleric, valeric, iso-caproic, caproic and heptanoic) levels werenalyzed, as in the case of the DOC, from the filtrate supernatantbtained by means of a lixiviation (10 g of digested waste in 100 mLf Milli-Q water during 20 min) of the effluent samples. The sam-les for the VFA analysis were further filtered through a 0.22 �meflon filter. VFA levels were determined by gas chromatographySHIMADZU GC-17 A) with a flame ionization detector and a cap-llary column filled with Nukol (polyethylene glycol modified byitro-terephthalic acid). The temperatures of the injection port and

etector were 200 ◦C and 250 ◦C, respectively. Helium was the car-ier gas at 50 mL min−1. In addition, nitrogen gas was used as makep at 30 mL min−1 flow rate. The total VFA was calculated as theum of individual VFA levels.

n/d n/d n/d n/d 3.233 × 103

3. Result and discussion

New indicators to verify the behavior of AD systems are definedin Section 1 to develop the discussion of the results. These newparameters have been defined in order to obtain more specificinformation about the balance among the different steps involvedin the AD process. This additional information may help interpretand prevent destabilization episodes in cases in which classicalcontrol parameters are not enough to understand the problem.

3.1. System performance

As has been indicated previously, three different RT were testedin this study. At stage 1 (RT of 15 days), the system was oper-ated in the optimum conditions for the thermophilic-dry anaerobicdigestion of industrial and synthetic OFMSW [13].

Stages 2 and 3 (RT of 10 and 8 days) correspond to a desta-bilization episode, since the OLR feeding of the system is higherthan the critical rate (15 kgVS/m3 day) to maintain reactor stabil-ity, as established by Angelidaki et al. [14]. Hence, in these stages,new indicators will be used to explain the imbalance between thedifferent microbial populations involved in the process.

3.2. Interpretation of classical monitoring parameters

3.2.1. Stage one: 15 day-RTIn general, the total VFA evolution is determined by two fac-

tors: the VFA generation rate (which depends on the transformationrate of NSC and NAC to DAC during the hydrolysis and acidogen-esis stages) and the VFA degradation rate to methane productionin the acetoclastic methanogenic stage. During this RT, both rateswere coupled and then the total VFA concentration remains rel-atively stable in the interval 7000–7500 mgAcH/L. As can be seenin Table 3, the average total VFA is 7.282 mgAcH/L. This is lowerthan the limit established by Ghosh et al. [19]. According to theseauthors, the methanogenesis is not affected if the total VFA con-centration is lower than 13,000 mgAcH/L. In fact, as can be seen inTable 4, during this period there is no hydrogen in the biogas andthe proportion CH4/CO2 was 50:50, approximately, which is char-acteristic of the stable operation of CSTR treating this type of waste[20].

3.2.2. Stage two: 10 day-RTAs can be seen in Table 3, the average total VFA concentra-

tion decreases from 7282 to 6017 mgAcH/L in comparison withstage 1. Although the total VFA concentration decreases, this doesnot induce an increase in biogas and methane generation. Hence,this RT (higher than the optimum RT of 15 days) starts to affectthe system’s stability. Hydrogen appears in the biogas and theapproximately 35/60 proportion of CH4/CO2 is slight imbalanced

in comparison with a stable system (Table 4).

As can be seen in Fig. 2, the methanogenesis seems to be affected.Methane generation decreases, hydrogen appears (and disappears)twice in this period and CO2 generation increases greatly. This fact

36 L.A. Fdez-Güelfo et al. / Chemical Engineering Journal 180 (2012) 32– 38

Table 4Production and average composition of biogas [13].

Stage RT (day) LBIOGAS/LRd LCH4 /gVSc LBIOGAS/gVSc LCH4 /LRd H2 (%) CH4 (%) CO2 (%)

1 15 3.56 ± 1.35 0.13 ± 0.05 0.34 ± 0.14 1.64 ± 0.50 n/d 46.1 ± 8.03 53.9 ± 8.032 10 1.72 ± 1.12 0.06 ± 0.02 0.11 ± 0.08 0.61 ± 0.30 3.49 ± 6.62 35.4 ± 22.9 61.1 ± 19.23 8 0.08 ± 0.12 <0.01 <0.01 <0.01 30.6 ± 8.18 3.19 ± 2.16 48.8 ± 28.2

n/d: non detected.

0 10 20 30 40 50 60 70 80 90 10 0 11 0 12 0 13 0 14 00

3

6

9

12

15

18

0

10

20

30

40

50

Alk

alin

ity (g

CaC

O3/ L

)

H2 CH4 CO2

8-day RT10-day RT15-day RT

Vol

ume

(L)

Time (d

Alkalin ity

Fig. 2. Evolution of the da

Table 5Average values of alkalinity, ammonia and (total VFA/alkalinity) ratio.

Stage RT (day) Alkalinity(g CaCO3/L)

Ammonia(g NH3–N/L)

Ratio (totalVFA/alkalinity)

1 15 36.6 2.96 0.20

st

a(l(a

faisssc

methanogenesis is clearly affected in stages 2 and 3. This is another

2 10 31.5 3.05 0.193 8 18.3 2.74 0.17

uggests that the methane generation may be associated basicallyo the H2-utilizing methanogens bacteria [21].

The high CO2 generation may be linked to an imbalance in thecetoclastic methanogenesis and a gradual decrease in alkalinityTable 5) that causes the partial liberation of CO2 dissolved in theiquid phase [22]. With classical control parameters such as gasCO2), generation is very imprecise and establishes whether thecetoclastic methanogenesis is truly affected.

The VFA/alkalinity ratio is another classical control parameteror checking the system’s stability. If the ratio ranges between 0.1nd 0.5, the stability of the process starts to be affected by a decreasen alkalinity. If the ratio is higher than 0.5, this is indicative of aystem failure [23]. In this study, the ratio remains practically con-

tant in stages 1 and 2 (0.20 and 2.19 respectively). However, intage 2, the microbial populations involved in methanogenesis arelearly affected. This is an example of a classical control parameter

0 10 20 30 40 50 60 0

100020003000400050006000700080009000

Acetic (C2) But yri c (C4) 10-d15-day RT

mg/

L

Tim

Fig. 3. Evolution of the acetic, butyric and propio

ays)

ily gas generations.

that does not provide relevant bidirectional information about thesystem status and ratio values.

Furthermore, as can be seen in Fig. 3, the acetic acid (andtotal VFA) decreases and the butyric acid is accumulated withoutincreasing biogas generation. All these facts suggest that the aceto-genesis step is also affected. These results corroborate that methanegeneration comes mainly from H2-utilizing methanogens bacteria.Even the homoacetogenesis is discarded as a possible pathway forgenerating acetate and therefore, methane.

According to Marchain and Krause [24], the propionic/aceticratio is an important indicator in preventing system failure by over-loading. Following an overloading process, the propionic/aceticratio increases immediately before changes in other parameters(such as biogas production and composition, pH and VFA) wereobserved. Pullammanappallil et al. [25] reported that propionic acidconcentrations lower than 2750 mg/L at pH values of 6.5 do notnegatively affect methane production. McCarty and Brosseau [26]established that propionic/acetic ratios higher than 1.4 are negativefor system stability. In this study, the propionic acid concentrationis lower than 100 mg/L in all stages and the propionic/acetic ratioranged between 0.02 and 0.16 from stage 1 to stage 3. However, the

example in which classical control parameters are unclear or arenot enough to explain destabilization episodes in some cases. Inaddition, inhibition phenomena by ammonia are not present in the

70 80 90 100 110 120 13 0 14 0

Propioni c (C3 ) Total VFA (mgAcH/L)8-day RTay RT

e (days)

nic acids and the total VFA in the effluent.

L.A. Fdez-Güelfo et al. / Chemical Engineering Journal 180 (2012) 32– 38 37

Table 6Average values of the different control parameters (direct and indirect).

Stage RT (day) g/L

TOC DOC DAC aNSC = TOC − DOC aNAC = TOC − DAC aASC = DOC − DAC

1 15 41.83 3.909 2.846 37.92 38.98 1.0632 10 48.14 4.470 2.428 43.67 45.71 2.0423 8 59.89 4.855 1.301 55.03 58.59 3.554

a Indirect parameters not determined analytically.

0 10 20 30 40 50 60 70 80 90 100 110 120 130 1400

100 0

200 0

300 0

400 0

500 0

600 0 DOC DAC AS C

8-day RT10-day RT15-d ay RT

mg

/ L

Time (days)

carbo

set

3

ddgiAtsita

3

iabt

Fig. 4. Evolution of dissolved organic carbon (DOC), dissolved acid

ystem. The ammonia concentration is lower than the 4 g/L limitstablished by Ahring [27] to prevent destabilization episodes inhe thermophilic anaerobic digestion process.

.2.3. Stage three: 8 day-RTThis RT was imposed on the system in order to accelerate the

estabilization process. The 10-day RT was maintained during 50ays and despite the changes in the system’s behavior was veryradual and slow. The evolution of classical control parametersndicates that this stage corresponds to a wash-out of the reactor.s can be seen in Figs. 2 and 3, biogas generation drops drastically

o zero and the total VFA and butiric acid concentrations decreaseharply in the effluent from approximately 5000 to 2000 mgAcH/Ln the first case, and from 3000 to 1000 mg/L in the last one. In addi-ion, the concentration of acetic acid in the effluent also falls to zerond alkalinity drops from 31.5 to 18.3 g CaCO3/L (Table 5).

.3. Interpretation of the new indirect monitoring parameters

In order to clarify the questions that arose in this study about the

nterpretation of the results with classical control parameters, andditional interpretation based on the new indirect parameter haseen realized in order to verify the postulated hypotesis and explainhe causes of the destabilization episode. Table 6 summarizes the

0 10 20 30 40 50 60 7030

35

40

45

50

55

60

65 10-da15-d ay RT

Non

-Sol

ubili

zed

Car

bon

(g /

L)

Time

Fig. 5. Non-solubilized carbon (NS

n (DAC) and acidogenic substrate like carbon (ASC) in the effluent.

averages values of the different direct (TOC, DOC and DAC) andindirect (NSC, NAC and ASC) control parameters for each RT.

Fig. 4 is presented to verify the hypothesis about the acidogenicstep inhibition. At the start of the 10-day RT, the DAC decreased andthe DOC increased in the effluent. This indicates that the system hasexperienced a shock from overloading. From day 45 to day 50, theDOC concentration increases and the DAC concentration decreasesgradually in the effluent. This behavior is logical, since the aceticacid and total VFA concentrations decrease sharply in this period.Between day 50 and 60, the system is able to punctually absorbthe excess or organic load, since the DAC increases and the DOCdecreases in this period. On the other hand, from day 60 to day 95,the ASC increases gradually in the effluent. This corroborates thatthe acidogenic step is affected, since the solubilized organic carbonis not transformed to soluble acid carbon.

Lastly, as can be seen in Fig. 5, the NSC concentration increasesin the effluent when the 10-day RT is imposed on the system.This suggests that the hydrolysis step is also affected and conse-quently, as has been previously postulated, the acidogenesis stepis also affected. This sequential failure of the hydrolysis and acido-

genesis steps causes the methane generation by methanogenesisacetoclastic pathway to be also affected.

Along the 8-day RT, the evolution of the new control parametersis analogous to the previous RT. As can be seen in Table 6, there are

80 90 100 110 120 13 0 140

8-day RTy RT

(days)

C) evolution in the effluent.

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8 L.A. Fdez-Güelfo et al. / Chemical

ncrements in all the new parameters that are logical if the fact thathis RT is a wash-out period of the reactor is taken into account.

As can be seen in Fig. 4, the ASC increases continuously duringhe 8-day RT and approaches the DOC concentrations. Acidogenesiss halted. If the 8-day RT is observed in Fig. 5, a similar trend is showny NSC and hydrolysis must also be affected. These two facts takenogether only admit one possibility: the global failure of the processnd hence, a wash out as a consequence.

. Conclusions

The following conclusion may be drawn from the above discus-ion:

. Classical control parameters (such as biogas generation, ammo-nia concentration, total VFA, ratio acidity/alkalinity and ratiopropionic/acetic) are not enough to interpret in depth a destabi-lization episode in anaerobic digestion processes of solid wastes.

. The definition of new indirect control parameters (NSC, NAC,ASC) based on classical control parameters such as VS, VFA andDOC allows for the interpretation of destabilization episodesbased on the main stages of the anaerobic digestion process.

. The interpretation of the destabilization process based on theanalysis of the new control parameters establishes that thehydrolysis stage is affected when 10-day RT is imposed on thesystem. This induces a sequential failure in the acidogenesis stepand therefore, the methane generation by the methanogene-sis acetoclastic pathway is also partially affected. In addition,the data indicate that hydrogen is generated, but is not used toform methane and hence, it can be concluded that H2-utilizingmethanogens bacteria are also partially affected.

. At the 8-day RT, the different microbial populations involved inthe anaerobic digestion process are washed-out with the efflu-ent and even methane generation by H2-utilizing methanogensbacteria disappears completely.

cknowledgements

This work was supported by the “Ministerio de Ciencia Inovación” of Spain (projects CTM2007-62164/TECNO andTM2010-17654), the “Consejería de Innovación, Ciencia y Empresa”f the “Junta de Andalucía, Spain” (project P07-TEP-02472), theuropean Regional Development Fund (ERDF) and the “Ministe-io de Educación y Ciencia” of Spain (project NovEDAR ConsoliderSD2007-00055).

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