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Page 1: Dry-thermophilic anaerobic digestion of simulated organic fraction of Municipal Solid Waste: Process modeling

Bioresource Technology 102 (2011) 606–611

Contents lists available at ScienceDirect

Bioresource Technology

journal homepage: www.elsevier .com/locate /bior tech

Dry-thermophilic anaerobic digestion of simulated organic fractionof Municipal Solid Waste: Process modeling

L.A. Fdez.-Güelfo a,*, C. Álvarez-Gallego a, D. Sales Márquez b, L.I. Romero García a

a Department of Chemical Engineering and Food Technology, Faculty of Science, University of Cádiz, 11510 Puerto Real, Cádiz, Spainb Department of Environmental Technologies, Faculty of Sea and Environmental Sciences, University of Cádiz, 11510 Puerto Real, Cádiz, Spain

a r t i c l e i n f o

Article history:Received 14 April 2010Received in revised form 16 July 2010Accepted 31 July 2010Available online 6 August 2010

Keywords:Anaerobic digestionOFMSWKineticsModeling

0960-8524/$ - see front matter � 2010 Elsevier Ltd. Adoi:10.1016/j.biortech.2010.07.124

* Corresponding author. Tel.: +34 956016379.E-mail address: [email protected] (L.A. Fd

a b s t r a c t

Solid retention time (SRT) is a very important operational variable in continuous and semicontinuouswaste treatment processes since the organic matter removal efficiency – expressed in terms of percent-age of Dissolved Organic Carbon (% DOC) or Volatile Solids (% VS) removed – and the biogas or methaneproduction are closely related with the SRT imposed. Optimum SRT is depending on the waste character-istics and the microorganisms involved in the process and, hence, it should be determined specifically ineach case.

In this work a series of experiments were carried out to determine the effect of SRT, from 40 to 8 days,on the performance of the dry (30% Total Solids) thermophilic (55 �C) anaerobic digestion of organic frac-tion of Municipal Solid Wastes (OFMSW) operating at semicontinuous regime of feeding.

The experimental results show than 15 days is the optimum SRT (the best between all proved) for thisprocess. Besides, data of organic matter concentration and methane production versus SRT have beenused to obtain the kinetic parameters of the kinetic model of Romero García (1991): the maximum spe-cific growth rate of the microorganisms (lmax = 0.580 days�1) and the fraction of substrate non-biode-gradable (a = 0.268).

� 2010 Elsevier Ltd. All rights reserved.

1. Introduction

The anaerobic digestion of OFMSW has attracted much interestin recent years. This technology offers great potential for fast andeffective degradation of organic matter to produce biogas with ahigh methane–hydrogen rate, but also contributes to save fossilenergy (Mata-Álvarez and Llabrés-Luengo, 1996).

There are three main tendencies in modeling of anaerobic pro-cesses to predict the reactor behavior (Garcia-Ocha et al., 1999):

1. Based model on kinetic equations such as Monod (1949) andContois (1959) or Romero et al. (1988, 1990, 1993) and RomeroGarcía (1991)).

2. An un-structured non-segregated model (Chen, 1983; Chen andHashimoto, 1980).

3. An un-structured segregated model (Hill, 1983).4. Structured kinetic models for dynamic simulation of the anaer-

obic degradation, as IWA anaerobic digestion models, are basedon a complex matrix with kinetic constants for different organicmatter degradation steps (Bagley and Brodkorb, 1999; Batstoneet al., 2002; Siegrist et al., 2002).

ll rights reserved.

ez.-Güelfo).

To calculate the size of the SSTR, the organic loading rate(OLR) and the SRT are the most used parameters in practice.The SRT is a fundamental operational variable of the processwhich determines its performance and the efficiency of theorganic matter removal and biogas productivity that can bereached (Wang et al., 1997; Kiyohara et al., 2000; Halalshehet al., 2001). When the SRT decreases in an anaerobic reactor,the consumed organic matter rate and, therefore, the specificmethane production increase (De la Rubia et al., 2006a). How-ever, this behavior presents an inflexion point from which theopposite effect is observed. Depending on the feeding character-istics, fundamentally size and organic content, every system pre-sents an optimum SRT below which the reactor destabilizes andthen an important reduction in the biogas generation and organ-ic matter removal takes place. In the present study, an analysisof evolution of the consumed organic loading rate (OLRC),removal efficiency (measured as DOC and VS removal percent-ages) and biogas production have been realized when the SRTis decreased.

The effect of solid retention time (SRT) on organic matter con-centration in the effluent and its relation with the substrate con-centration in the influent (both measured as COD or VS) can beused to determine parameters of adequate kinetic models, as theproposed by Romero García (1991), for the prediction of the pro-cess behavior.

Page 2: Dry-thermophilic anaerobic digestion of simulated organic fraction of Municipal Solid Waste: Process modeling

Fig. 1. Anaerobic 5 l reactor.

L.A. Fdez.-Güelfo et al. / Bioresource Technology 102 (2011) 606–611 607

1.1. Kinetic model description

Process modeling, based in kinetic models, permits to predictthe effect of the most important process variables on system per-formance. In this sense, development of adequate models and itsparametrization by means the fit of model equations to experi-mental results, obtained in specific assays, is a very important task.

Besides, industrial plants for anaerobic treatment of organicfraction of Municipal Solid Waste are characterized for a wide var-iation in waste composition feeding to reactors and hence, processmodeling acquires a special significance to determine the optimumoperational conditions.

In this work, the substrate consumption model proposed byRomero García (1991) has been used. This model has been usedsuccessfully to fit experimental results of anaerobic digestion ofdifferent organic wastes: wine vinasses (Pérez et al., 2001a,b;Romero García, 1991), sludges from WWTP (De la Rubia et al.,2006b) and OFMSW (Fernández et al., 2010).

The model assumes that substrate consumption rate is given by

ð�rsÞ ¼ lmaxðh� SÞ � ðS� SNBÞðh� SNBÞ

ð1Þ

By including Eq. (1) in the mass balance for a completely mixedreactor and assuming steady state conditions, the model equationused in this work can be obtained

S ¼ SNB þS0 � SNB

lmaxhð2Þ

where:

SNB represents the non-biodegradable substrate concentration(g/L).S0 represents the initial substrate concentration (g/L).S represents the substrate concentration (g/L).h is the maximum substratum concentration that can beinvested in the biomass formation (g/L).lmax represents the specific grown rate of the microorganisms(days�1).h represents the SRT (days).

In Eq. (2), as postulated by the author (Romero García, 1991), itwas assume that parameter ‘‘h” is equivalent to the initial sub-strate concentration ‘‘S0” for continuous and semicontinuousoperation.

Besides, the above equation has been developed on the basisthan the activity of the overall microbial population can be repre-sented by the parameter lmax, which represents the rate of themicrobial group which is the rate-limiting of the process.

Eq. (2) can be modified by considering than the quantity of non-biodegradable substrate by the microorganisms involved in theprocess, is proportional to total substrate concentration in thefeeding. Thus, SNB can be expressed as the fraction of non-biode-gradable substrate (a) with respect to initial substrate concentra-tion S0 to obtain Eq. (3).

S ¼ a S0 þS0ð1� aÞlmaxh

ð3Þ

Obviously, the above equation could be easily linearized (Eq. (4)):

SS0¼ aþ 1� a

lmax

� �1h

� �ð4Þ

However, according to Leatherbarrow (1990), the linearization of anequation supposes a modification of the fitted variables becausethis procedure causes a modification of the random error distribu-tion, associated to the aforementioned values and thus, the hypoth-

eses of linear regression technique are invalidated. Whereas thenon-linear regression does not modify the error distribution, sinceit is not necessary to realize any transformation of the variables.

Therefore, in this work, the fitting of the model to experimentaldata has been performed by means of both linear and non-linearregression.

1.2. Computer support

Linear and non-linear regressions have been applied, to fit the-oretical equations to experimental data and to determine the ki-netic parameters of the model, using a statistical program(Software Statgraphics 5.0). The non-linear regression is based onthe minimization-square-residues algorithm of Marquardt (1963).

2. Methods

2.1. Experimental equipment

The reactor used for the semicontinuous process had a totalcapacity of 5 l and a working volume of 4.5 l (Fig. 1).

In this study, the semicontinuous stirred tank reactor has beenconsidered as ideal completely mixed reactor without microorgan-ism retention. In this case the SRT is the same that the HRT.

The reactor was jacketed and thermostatically controlled usinga circulating 7L-bath. A ball valve was fitted to the lower part of thereactor in order to discharge the contents and in the cover therewere several ports: central hole for agitation system (mixing shaftat 13 rpm), a pH probe, a biogas collector, an opening for the addi-tion of feedstock and two further inputs for the pH-control. A strictpH-control was not necessary. The pH of the system was correctedonly when it was out of range 6.5–8. To this end, an on/off pH con-troller was used employing 5 N NaOH and 1 N H3PO4 solutions. Theinitial pH of the synthetic OFMSW (OFMSWSYNTH) – inoculum mix-ture was 7.2.

2.2. Sampling and analysis

For process monitoring and control, the following analyticaldeterminations have been used: Total Solids (TS), Volatile Solids(VS), alkalinity, pH, Dissolved Organic Carbon (DOC) and ammo-nium. All parameters were analyzed once a day and determina-tions were performed according to Standard Methods (APHA,AWWA, WEF, 1995).

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608 L.A. Fdez.-Güelfo et al. / Bioresource Technology 102 (2011) 606–611

The volume of gas produced in the reactor was directly mea-sured using a high precision flow gas meter – WET DRUM TG 0.1(mbar) – Ritter – through the Tedlar bag. The gas composition(hydrogen, methane and carbon dioxide) was determined by gaschromatography (SHIMADZU GC-14 B) with a stainless steel col-umn packed with Carbosive SII (diameter of 3.2 mm and lengthof 2 m) and a thermal conductivity detector (TCD). The injectedsample volume was 1 mL and the operational conditions were asfollows: 7 min at 55 �C; ramped at 27 �C min�1 until 150 �C; detec-tor temperature: 255 �C; injector temperature: 100 �C. The carrierwas helium and the flow rate used was 30 ml min�1. A standardgas (by Carburos Metálicos, S.A; composition: 4.65% H2; 5.33%N2; 69.92% CH4 and 20.10% CO2) was used for the systemcalibration.

Individual VFA (from C2 to C7, including iC4, iC5 and iC6) levelswere determined by gas chromatography (SHIMADZU GC-17 A) witha flame ionization detector and a capillary column filled with Nukol(polyethylene glycol modified by nitro-terephthalic acid). The tem-peratures of the injection port and detector were 200 and 250 �C,respectively. Helium was the carrier gas at 50 ml min�1. In addition,nitrogen gas was used as make up at 30 ml min�1 flow rate.

2.3. Methodology

In this work, eight experimental stages were used in a decreas-ing sequence of SRT. Test were run at 40, 35, 30, 25, 20, 15, 10 and8 days and the organic loading rates used in each SRT (expressed asmg DOC/L/d and mg VS/L/d) are shown in Table 1.

It is important to emphasize that OLR tested in this workexceeds limits established by Angelidaki et al. (2006) to reach asuccessful strategy of start-up. Concretely, in stages 7 and 8, theOLR – expressed in terms of Volatile Solids (VS) – is higher thanthe limit of 15 g VS/L/d established by the aforementioned authors.

In order to avoid the distortion in process performance causedby the changes in feed composition when real feeding are used, asimulated OFMSW was prepared following the indications ofMartin et al. (1997). This synthetic waste provides all nutritionalrequirements of the main microbial groups involved in anaerobicdigestion. It is very important to emphasize that the main objectiveof this work is to study the kinetics of the process in order to char-acterize the maximum specific growth rate of microorganisms.That is, the objective is not to obtain kinetic data that can beextrapolated to industrial scale. To this end, synthetic waste wasemployed to avoid the high heterogeneity of the real OFMSW.The real OFMSW shows a very heterogeneous composition thatcauses a great dispersion in the analytical parameters. This disper-sion in the analytical parameters complicates the kinetic studysince it is very difficult to adjust the models. A stable and homoge-neous composition along the time was necessary for that the ki-netic study was exhaustive. About the composition of the waste,the main constituents were potato (6.2% w/w), cabbage (5.3% w/

Table 1Organic loading rates (daily feeding).

Stage OLR0 SRT (days) Operation time (days)

mg DOC/L/d mg VS/L/d

1 702 4431 40 142 803 5069 35 173 938 5920 30 254 1120 7090 25 505 1404 8862 20 606 1872 11,817 15 457 2808 17,725 10 308 3509 22,156 8 24

w), orange (4.9% w/w), apple (4.9% w/w), bread (3.5% w/w) and pa-per (55.8% w/w). Table 2 shows the physicochemical characteriza-tion of the feeding.

3. Results and discussion

3.1. Organic loading rate (OLRC) removed

The system was operated at SRT from 40 to 8 days. The SRT of40, 35, 30 and 25 days, correspond to the start-up and stabilizationperiod, whereas the SRT of 20, 15, 10 and 8 days describe the fol-lowed sequence to analyze the optimum SRT.

The removal efficiency (based on the DOC and VS) and the OLRC

depends on the OLR0 and the imposed SRT. The relation betweenthese parameters, suggesting the following two aspects:

1. For SRTs lower than 15 days, the contact time between the bio-mass and the substrate begins to be insufficient and therefore,the organic matter removal efficiency decreases notably, espe-cially if it is taken into account the removal efficiency in termsof VS.

2. Besides, SRTs higher than 20 days cause a gradual decrease inthe removal yields. This fact suggests that there are lacks ofsubstrate in the system and, therefore, the growth of microor-ganisms is being limited.

As a consequence, 15 days can be considered the optimum SRTfor the dry-thermophilic anaerobic digestion of synthetic OFMSWand, in these conditions, the system reaches the maximum organicmatter removal yield, 89% in VS. Table 3 shows the results obtainedfor the different SRT tested in this study.

As can be seen in Table 3 the methane production, expressed asLCH4 /LREACTOR/day, increases continuously from 40 to 15 dayswhereas a diminishing of methane productivity is detected forSRT lesser than 15 days (10 and 8 days SRT). This behavior is thesame than that observed for organic matter removal efficiencyand, hence, it confirms that 15 days is the optimum SRT for theprocess. Data for biogas and methane production, as well as for or-ganic matter degradation, indicate than 10 days SRT could be con-sidered useful since only a slight decreasing with respect to15 days SRT efficiency is produced. However, for 8 days SRT a dras-tic decreasing in methane production and total acidity concentra-tion, expressed as mgAcH/L, can be observed (Fig. 2).

At the lower SRTs (10 days and, especially, 8 days) the destabi-lization of the system takes place and the wash out of the micro-organisms with lower specific growth rate (MethanogenicAcetate-utilizing) occurs. For this reason the methane productiondecreases in these low SRTs. Others research works as Smith andMah (1966) or McCarty (1981) indicate that methane percentagecoming from Methanogenic H2-utilizing population is, approxi-mately, the 30% of total methane production. This fact suggests

Table 2Features of the simulated OFMSW.

Analytical parameter Values

pH 7.78Density (kg/m3) 750Alkalinity (g CaCO3/L) 4.29Ammonium (g NH3–N/L) 1.68Total nitrogen (g NH3–N/kg) 23.0Total Solids (g/g sample) 0.90Total Volatile Solids (g/g sample) 0.71Suspended Fixed Solids (g/g sample) 0.19DOC (mg/g) 112.3Acidity (mg AcH/L) 1440

Page 4: Dry-thermophilic anaerobic digestion of simulated organic fraction of Municipal Solid Waste: Process modeling

Table 3Operation values for the different applied SRT.

SRT (days) OLR0 (g DOC/LR d) OLRc (gD OC/LR d) DOCc (%) OLR0 (g VS/LR d) OLRc (g VS/LR d) VSc (%) Biogas (L/LR d) CH4 (L/LR d) pH

40 0.702 0.235 33.52 4.431 2.980 67.26 0.638 0.007 8.1935 0.802 0.419 52.19 5.064 3.823 75.48 1.944 0.465 7.8730 0.936 0.547 58.44 5.908 4.830 81.76 1.160 0.499 7.8625 1.123 0.717 63.87 7.090 6.237 87.98 1.396 0.582 7.9720 1.404 0.944 67.26 8.862 7.851 88.59 2.258 0.933 7.8815 1.872 1.228 65.59 11.817 10.516 89.00 3.244 1.149 7.7410 2.808 1.716 61.12 17.725 15.213 85.83 3.783 0.929 7.808 3.509 2.000 56.98 22.156 15.959 72.03 1.615 0.132 7.83

L.A. Fdez.-Güelfo et al. / Bioresource Technology 102 (2011) 606–611 609

that, if the best methane production for this simulated waste isaround 40% (Martin et al., 1997), the methane percentage whenMethanogenic H2-utilizing microorganisms are acting, maydiminished until 10–12%.

Similar behavior was described by Linke (2006), who found adecrease in the removal percentages, as well as methane and bio-gas yield, when the organic loading rate was increased from 0.8 to3.4 g VS/L/d.

As can be seen in Table 3, when the SRT correspond to 20 and15 days, the OLRC in terms of VS is very close to the OLR0, showingremoval efficiency above 88%. On the contrary, SRTs higher than20 days and lower than 15 days present a reverse effect, more ac-cused for lower SRTs.

Some authors have observed an increase in biogas production andVS removal efficiency when the SRT is decreased (Alatiqi et al., 1998).The same behavior has been observed in this work: for SRT among 20and 15 days, the organic matter elimination (expressed as % DOCC

and as % VSC) is higher than for SRT higher than 25 days.On the other hand, the methane production rate is directly re-

lated to DOCC and, therefore, with the OLRC. Hence, when theSRT ranged from 40 to 15 days, the methane production is directlyproportional to the OLRC. In Table 3, the evolution of biogas andmethane production is also shown.

In summary, the methane and biogas productions present anincreasing trend when the SRT is decreased except for 10–8 daysstages. In fact, an almost proportional relation between the appliedSRT and the biogas and methane productions was observed. Thesame behavior was described by Sánchez et al. (2000). On the otherhand, for high SRT ranged from 40 to 20 days, when the feed organ-ic loading rate (OLR0) is increased, the consumed organic loadingrate and removal efficiency are increased. For low SRT, ranged from15 to 8 days, the effect is the opposite.

3.2. Substrate consumption model of Romero García (1991)

The fit of the expressions (Eqs. (3) and (4)) of substrate con-sumption model to determine the kinetic parameters of the model

Fig. 2. Evolution of total concentration, ex

requires the values of biodegradable substrate concentration thatcan be evaluated as DOC or VS. In Table 4, the values of S and S0

(expressed as DOC and VS) for the different SRT are shown.It is noticeable than SRT from 40 to 25 days were not main-

tained for enough time to reach pseudo stationary state conditions.In this sense, it is admitted usually than the minimum period oftime required to assure that the system is near to stability is equiv-alent to three times the SRT used. For hence, only SRT from 20 to8 days have been used in the model fitting.

Linear fit for Romero García (1991) model is only valid for theDOC data (Table 5). For VS data, intercept is negative and, hence,lack of physical significance. However, non-linear fit is adequatefor both, DOC and VS data. Nevertheless, as can be seen in Table5, the best results were obtained when the DOC data are used(r2 = 0.983; lmax = 0.581 days�1; a = 0.268).

The lmax value obtained from the fit of organic matter (DOC)represents the global maximum specific growth rate for the overallof microbial populations involved in the process and consideringthat the system operates in semicontinuous regime it will be rep-resentative of the microbial group rate-limiting.

In Table 6 the values obtained are compared with the usual val-ues in literature. Kinetic modeling studies of the dry-thermophilicanaerobic digestion of OFMSW (Álvarez Gallego, 2005) indicatethat the maximum specific growth rate of the populations involvedin the hydrolytic and acidogenic stages ranged between 0.08 and0.18 days�1; for the methanogenic acetoclastic Archaeas lmax ran-ged 0.23–0.28 days�1; whereas for the hydrogen utilizing Archaeasthe values were 0.33–0.40 days�1.

Equally, this results can be compared with results obtained inthe research group. Thus, kinetic modeling studies of the anaerobicdigestion of wine vinasses in wet conditions indicate that the lmax

of the Acetoclastic Archaeas was 0.3 days�1 in mesophilic range(Sales et al., 1989) and 0.6 days�1 in thermophilic range, both whenusing the Chen and Hashimoto model (Romero et al., 1988, 1990,1993) as when using the model of Romero García (1991). The lastvalue is very similar to the result presented in this paper(0.518 days�1).

pressed as mgAcH/L, in the effluent.

Page 5: Dry-thermophilic anaerobic digestion of simulated organic fraction of Municipal Solid Waste: Process modeling

Table 4Used values of h, S y S0 for kinetic modeling.

h (days) DOCInfluent (g/L) DOCEfluent (g/L) VSInfluent (g/L) VSEfluent (g/L) cV (LCH4/LR d)

40 28.075 18.664 177.25 58.035 0.00735 28.075 13.422 177.25 43.461 0.46530 28.075 11.668 177.25 32.336 0.49925 28.075 10.131 177.25 21.313 0.58220 28.075 9.512 177.25 20.229 0.93315 28.075 9.662 177.25 19.506 1.14910 28.075 10.913 177.25 21.021 0.9298 28.075 12.094 177.25 49.580 0.132

Table 5Kinetic for substrate consumption model of Romero García (1991).

Kinetic models Model fitting for DOCC Model fitting for VS

Model parameters r2 Model parameters r2

Lineal regressionSS0¼ aþ 1� a

lmax

� �1h

� �y = 1.2607x + 0.2679a = 0.268lmax = 0.580 days�1

0.968 y = 1.978x � 0.0133a = 0.013lmax = 0.498 days�1

0.643

Non-linear regression S ¼ aS0 þS0ð1� aÞ

lmax

a = 0.268lmax = 0.581 days�1

0.983 a = �0.013lmax = 0.512 days�1

0.644

Table 6Comparison of the maximum specific growth rates obtained in different studies.

Population of microorganisms Range of temperature Waste lmax (days�1) Reference

Overall Thermophilic Simulated OFMSW 0.58 Present studyHydrolytic–acidogenic Thermophilic Industrial OFMSW 0.08–0.18 Álvarez Gallego (2005)Methanogenic Acetate-utilizing Thermophilic Industrial OFMSW 0.23–0.28 Álvarez Gallego (2005)Methanogenic H2-utilizing Thermophilic Industrial OFMSW 0.33–0.40 Álvarez Gallego (2005)Methanogenic Acetate-utilizing Mesophilic Industrial OFMSW 0.11–0.19 Fernández et al. (2010)Methanogenic H2-utilizing Mesophilic Industrial OFMSW 0.18–0.24 Fernández et al. (2010)Overall Thermophilic Sludge from WWTP 0.195 De la Rubia et al. (2006b)Overall Mesophilic Organic solid waste 0.29 Mata-Álvarez and Llabrés-Luengo (1996)Methanogenic Acetate-utilizing Thermophilic Wine-Distillery Wastewaters 0.60 Romero et al. (1988, 1990, 1993)

and Romero García (1991)Acidogenic Thermophilic Sludge from WWTP 0.72 Van Lier et al. (1993)Methanogenic Acetate-utilizing Thermophilic Sludge from WWTP 0.72–1.44 Van Lier et al. (1993)Methanogenic Acetate-utilizing Mesophilic Wine-Distillery Wastewaters 0.30 Sales et al. (1989)

610 L.A. Fdez.-Güelfo et al. / Bioresource Technology 102 (2011) 606–611

4. Conclusions

For the SRTs ranged from 20 to 15 days, the higher removal per-centages of DOC and VS are obtained. The DOC removal yield isaround 66% for both periods. In the case of VS, the removal yieldis around 89%. For SRT of 10 and 8 days the removal efficiency de-creases with respect to aforementioned. Therefore, 15 days may beconsidered the optimal SRT. Applying the substrate consumptionmodel of Romero García (1991), the global maximum specificgrowth rate and the non-biodegradable substrate fraction in thefeeding were estimated with the following values: 0.581 days�1

and 0.268, respectively.

Acknowledgements

This work was supported by the Spanish Ministry of Scienceand Innovation (Project CTM2007-62164/TECNO), by the Innova-tion, Science and Enterprise Department of the Andalusian Govern-ment (Project P07-TEP-02472) and by the European RegionalDevelopment Fund (ERDF).

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