2745 IWA Publishing 2012 Water Science 8, Technology | 66.12 | 2012

Estimates of methane ioss and energy recovery potentiaiin anaerobic reactors treating domestic wastewaterL. C. S. Lobato, C. A. L. Chernicharo and C. L. Souza

ABSTRACT

This work aimed at developing a mathematical model that could estimate more precisely the fractionof chemical oxygen demand (COD) recovered as methane in the biogas and which, effectively,represented the potential for energy recovery in upflow anaerobic sludge blanket (UASB) reactorstreating domestic wastewater. The model sought to include all routes of conversion and losses inthe reactor, including the portion of COD used for the reduction of sulfates and the loss of methane inthe residual gas and dissolved in the effluent. Results from the production of biogas in small- andlarge-scale UASB reactors were used to validate the model. The results showed that the modelallowed a more realistic estimate of biogas production and of its energy potential.Key words | anaerobic reactors, biogas, COD balance, domestic wastewater, energy recovery, UASB

reactor

L. c. s. Lobato (corresponding author)C. A. L. ChernicharoC. L. SouzaFederal University of Minas Gerais.B. Horizonte.BrazilE-mail:/s/tofot)ato@ya/joo.co/n.r

INTRODUCTION

The mass balance of chemical oxygen demand (COD) toestimate the recovery of methane and energy in anaerobicreactors usually does not consider the portion of CODused in sulfate reduction, nor the portions lost as dissolvedmethane in the effluent or emitted to the atmosphere. It isknown that the portion of COD used in sulfate reductionis small due to the low concentration of sulfates in domesticwastewater, usually in the range of 20-100 mg SO^^ L"^(Singh & Viraraghavan 1998; Metcalf & Eddy 2003), but itis still important to consider it in the models that estimatethe production of methane. On the other hand, in relationto the COD converted to methane, a significant portioncould be dissolved in tbe liquid pbase and be lost witb tbefinal effluent (Agrawal et al 1997; Hartley & Lant 2006;Souza & Cbernicbaro 2on). Furthermore, methane losscan also occur due to emissions on the settler surface ofupflow anaerobic sludge blanket (UASB) reactors. Measure-ments taken by Souza & Cbernicbaro (2on) indicated tbat,of all the methane produced in UASB reactors treating dom-estic wastewater, tbe portion dissolved in tbe effluent variedfrom 36 to 40%, wbile tbe portion emitted on tbe surface ofthe settlers was in the order of 4%, constituting the wastegas. To explain these huge losses of dissolved methane.Hartley & Lant (2006) developed the hypothesis that themethane dissolved in tbe effluent of different types ofanaerobic reactors could be supersaturated in relation to

tbe saturation calculated according to Henry's law. There-fore, the measurements taken by Souza & Chernicharo(2on) in anaerobic reactors treating domestic (low concen-tration) wastewater and operated at a very low organicloading rate (around 1.5 kg COD m"^ d"^) are in accord-ance with tbis hypothesis.

The loss of methane dissolved in tbe effluent or in thewaste gas not only represents a loss of potential energy butalso contributes to the emission of greenhouse gases. Pierotti(2007) reports a mass balance that considers tbe portion ofCOD converted to metbane to be divided into methane inthe biogas and metbane dissolved in tbe effluent, in percen-tages from 20 to 25% of tbe influent COD, for both portions.The same mass balance sbows tbe percentage of 40-50% fortbe COD effluent and 10% for tbe COD that is convertedinto sludge. This mass balance takes into account the por-tion of COD converted to metbane and its division;however, it does not include tbe portion tbat is due tosulfidogenesis.

Considering tbat the potential for production and recov-ery of biogas in UASB reactors tbat treat domestic waste isconsidered low (Noyola et al 2006), rarely resulting insome type of energy use (the biogas is usually burned), thedevelopment of models that permit more precise estimatesof the effective potential energy tbat may be recovered, aswell as the emission factors (losses), becomes important.

doi: 10.2166/wst.2012.514

2746 L. C. S. Lobato et al. Estimates of methane loss and energy in anaerobic reactors Water Science & Technology | 66.12 | 2012

Thus, the COD mass balance models must incorporate allthe main routes of conversion and of loss, that is: the portionused in sulfate reduction; the portion converted into sludge,which may be subdivided into the fraction remaining in thereactor and the portion that is lost with the effluent; the dis-solved portion not converted into methane and dischargedwith the effluent; the portion converted into methane thatis recovered as biogas (which can be used as energysource); as well as the portion converted into methanethat escapes dissolved in the effluent or as waste gas(losses). So, the aim of this study was to develop a math-ematical model that better represented the mass balance ofCOD and the potential for energy recovery in UASB reac-tors treating domestic wastewater.

MATERIAL AND METHODS

The mathematical model for calculating the mass balance ofCOD and the energy potential was structured with areduced number of input data, with the goal of facilitatingits use in a broader way. Conceptually, the model was struc-tured according to the COD conversion routes and methaneflow in UASB reactors shown in Figure 1.

The model was developed considering three scenariosthat lead to different methane recovery potential: (i) worstscenario; (ii) typical scenario; (iii) best scenario. The worstscenario, in which the energy potential is lower, involvessystems operating with more diluted waste, higher sulfateconcentrations, lower COD removal efficiencies, andhigher rates of methane loss. The best scenario involves sys-tems operating with more concentrated waste, lower sulfateconcentrations, higher COD removal efficiencies, and lower

rates of methane loss. The typical scenario uses intermedi-ary values for the input data.

Input data

The input data considered in the simulation are shown inTable 1. The variability of the input data (Pop, QPC,QPCcoD and T) was incorporated into the interpretationof the model results, through Analysis of Uncertainty,which is based on a large number of simulations (in thiscase, 250 simulations for each scenario), making the so-called Monte Carlo simulation. For each run of the model,a different set of values for the input data is chosen forwhich uncertainty exists. The input data were generated ran-domly following uniform distribution and within pre-established ranges.

Fractions of the mass baiance of COD and of potentiairecovery of CH4

Once the input data were defined, the portions of CODremoved from the system, converted into sludge and con-sumed in sulfate reduction, are firstly estimated. Based onthese portions, the total COD converted into CH4 andthe consequent volumetric production are calculated. Inorder to calculate the volume of CH4 actually availablefor energy use, the model considers the losses of CH4 dis-solved in the effluent and in the gaseous phase with thewaste gas, in addition to other eventual losses in the gas-eous phase (e.g. leaks). Finally, deducting these losses,the potential available energy is calculated. The equationsused to calculate all the portions of the mass balance ofCOD and the potential for energy recovery are shown inTable 2.

COD converted into CH4present in the biogas

* - . - . _ . i . J COD converted into CH4 and lost into the atmosphere

Load of infiuent COD tnr -tf

%

w * -

i,I 1

-=HL

i

1 -

COD converted into CH4 and lost with the waste gas

COD converted into CH and lost dissoived in the effluent

COD not converted into CH4, and lost with the effluent

COD used by the BRS in sulfate rduction

COD converted into sludge

Figure 1 I COD conversion routes and methane fiow in UASB reactors.

2747 L. C. S. Lobato e al. Estimates of methane loss and energy in anaerobic reactors Water Science & Technology | 66.12 | 2012

Table 1 Input data considered in the model

scenario

Unit worst Typical BestReference

Contributing population (Pop)Per-capita wastewater contribution

(QPC)Per-capita COD contribution

(QPCCOD)

Expected efficiency of COD removal

Dissolved CODCH4 lost with tbeeffluent (p^)

Percentage of CH4 in tbe biogas(CcH4)

inbab.

Sulfate concentration in the influent kg SO4 m(Cso,)

Efficiency of sulfate reduction {Eso) "/oOperational temperature of tbe C

reactor (T)CODcH4 lost as waste gas (pw) %Otber CODcH4 losses (e.g. biogas %

leaks) (po)kg m"^

0/0

1,000-1,000,000

0.12-0.22 von Sperling & Chernicharo (2005)

0.09-0.11 von Sperling & Chernicharo (2005)

60 65 70 von Sperling & Chernicharo (2005)0.08 0.06 0.04 Singb&Viraraghavan (1998); Metcalf& Eddy (2003);

Gloria et al (2008)80 75 70 Souza (2010)20-30 von Sperling & Cbernicbaro (2005)

7.5 5.0 2.5 Souza & Cbernicbaro (2on)

7.5 5.0 2.5 Souza & Cbernicharo (2on)

0.025 0.020 0.015 Souza & Cbernicharo (2on)

70 75 80 von Sperling & Cbernicbaro (2005)

Validation of the mathematical modei

Following the simulations, the validation of the model wascarried out based on measured biogas production and com-position in small- and large-scale UASB reactors, accordingto the main characteristics shown in Table 3, and thedescriptions given below.

RESULTS AND DISCUSSION

Simulations

Figure 2 shows the average values obtained from the simu-lations performed, in which the contribution of eachportion of the mass balance of COD may be observed forthe three simulations analyzed (worst, typical and best).

The analysis of Figure 2 supports the followingcomments:

13-15% of the COD applied to the system was convertedinto biomass. In relation to simulations of sulfate concen-tration in the influent (varying between 40 and 80 mg L~^),the percentage COD use in sulfate reduction variedbetween 3 and 7%.

For the simulated rates of methane loss in the effiuent(varying between 15 and 25mgL"^), 11-17% (average)of the COD load applied to the system was convertedinto non-recovered methane in the biogas, but lost dis-solved in the effluent.The portion of influent COD effectively converted into CH4present in the biogas, which represents the effective poten-tial of energy recovery, varied from 19% in the worstscenario to 39% in the best scenario. As it involves domesticwaste, in which the relationship COD/SO4" is high, metha-nogenesis (the sum of the portions of COD converted intoCH4) is greater in relation to suldogenesis (39-52% con-trasted to 3-7% of the influent COD, respectively).In the worst scenario, of all the COD converted into CH4,on average 39%, only 19% refers to the portion of CH4collected in the three-phase separator and available foruse. This represents a loss of about 50% of energy poten-tial. In the best scenario, an average of 52% of COD isconverted into CH4, with 39% related to the portion ofCH4 available for use, which characterizes only a 25%loss of energy potential. Thus, for a given concentrationof influent COD and removal efficiency in the reactor,the loss of dissolved methane in the effluent becomesan extremely important factor in the energy balance ofthe system.

2748 L. C. S. Lobato et al. \ Estimates of methane loss and energy in anaerobic reactors Water Science & Technology | 66.12 | 2012

Table 2 I Equations for calculating the portions of the mass balance of COD and energy recovery potential

Portions Equations Notes

Estimate of meaninfluent fiowrate

an = Pop X QPC

Estimate of daily COD CODremoved = Pop x QPCCODmass removed fromthe system

= CODremoved xEstimate of daily CODmass used by the i'coD =biomass

Estimate of sulfate load COSO4 convened = ^mean X Cso, X so,converted intosulfide

Estimate of daily COD CODso, = COso, convertemass used in sulfate S^" + 2O2 => SO4"reduction (32g) + (64g) ^ (96g)

Estimate of daily COD CODCH, = gmass converted into _ CODm, x K x (275-F T)

QCH, - px/methane production

Estimate of available PEavaUabIe-CH4 = QN-actual-CH, X CH4energy potential

mcan = mean influent flowrate (m^ d '); Pop =population (inhab.); QPC = per-cupte wastewatercontribution (m'' inhab "^ d"')

oved = daily COD mass removed from thesystem (kg COD d^'); Pop = population (inhab.);QPCCOD = per-capita COD contribution (kgCOD inhab"' d"'); BCOD = efficiency of CODremoval (%)

CODsiudge = daily COD mass converted intobiomass (kg CODsiudge d"'); ycoD = sludge yield,as COD (kg COD.iudge kg COD I^noved); Y= sludgeyield, as TVS (kg TVS kg COD^ e^ nioved);TVS-COD = conversion factor (1 kg TVS =1.42 kg CODsiudge); TVS = total volatile solids

COSO4 ^j = load of SO4 converted into sulfide(kg SO4 d~'); Cso, = average influent SO4concentration (kg SO4 m"''); 30, = efficiency ofsulfate reduction (%)

CODso^ = COD used by the BRS for sulfatereduction (kg CODgo, d"^); KCOD-SO^ = CODconsumed in sulfate reduction (0.667 kg CODSO4

CODcH4 = daily COD mass converted into methane(kg CODcH4 d"^); QCH4 = theoretical volumetricproduction of methane (m'' d"'); i? = gas constant(0.08206 atm L m o r ' K"'); T= operationaltemperature of the reactor ( C); P = atmosphericpressure (1 atm); KCOD = COD of one mole ofCH4 (0.064 kg CODcH4 mor ' )

Qw-cH4 = methane loss as waste gas (m^ d"'); p =percentage of methane in the gaseous phase lostas waste gas (%); QO-CH4 = other methane lossesin the gaseous phase (m^ d"'); po = percentage ofmethane in the gaseous phase considered as otherlosses (%); QL-CH4 = loss of dissolved methane inthe liquid effluent (m^ d"'); pt = concentration ofdissolved methane in the liquid effluent (kg m"');/cH4 = conversion factor of methane mass intoCOD mass (4 kg COD kg CHj')

Qactuai-cH4 = actual producton of methaneavailable for energy recovery (m'' d"')

PEactuai-CH4 = available energy potential (MJ d~');QN-actuai-cH4 = normalized methane production(Nm' d"'); CH4 = calorific energy of methane(35.9 MJ Nm-')

The mass balance carried out by Souza (2010) throughmeasurements in reactors, in both pilot- and demon-stration-scale, indicated the following ranges in relation tothe global COD: soluble in the effluent (14-24%), sludgein the effluent (10-20%), sludge retained in the reactor

(8-10%), methane in the biogas (24-30%), dissolvedmethane (16-18%), and sulfate reduction (4.5-5%). It isobserved that these values are close to the ones obtainedfrom the simulations using the mathematical modeldeveloped.

2749 L. C. S. Lobato et al. \ Estimates of methane ioss and energy in anaerobic reactors Water Science & Technology | 66.12 | 2012

Table 3 Main characteristics of the UASB reactors used to validate the model

Characteristic

LocationPopulation (inhab.)Mean influent owrate (L s"^)Number of unitsDimensions (m)Useful depth (m)Useful volume (m'^ )

Pilot-scale

CePTS*80.021D = 0.34.00.36

Demo-scale

CePTS*1400.321D = 2.04.514.0

Full-scale

Ona - Belo Horizonte - Brazil330,0006602438.4x6.44.52,211.9

Full-scale

Laboreaux - Itabira - Brazil30,00070821.7x6.24.51,210.9

(*) Centre for Research and Training on Sanitation - Belo Horizonte - Brazil.

(a)

COD usedin Sulfatereduction

7%

(b)COD

conveftedlntosludge ' ' ^

COO notconerted intoCH4, and lost COD used in ^^

witiithe sulfate \ " ieffluent reductionm 5%

OttierC0DCH4

losses3%

(c)COD

converted intoconverted into COD used in f^ngCH4, and lost sulfate 1504

with the reductioneffluent 3%

35%

COD notconverted intoCH4, and lost

30%

Figure 2 I Result of the simulations of COD mass balance in UASB reactors treating domestic waste, in relation to the infiuent COD for the three scenarios: (a) worst; (b) typical; (c) best.

Figure 3 shows the results from the simulations and therespective adjusted lines for the production of biogas and forthe energy recovery potential in UASB reactors treatingdomestic wastewater. The simulations considered the vari-ation in the contributing population from 0 to 1 millioninhabitants (corresponding to influent flowrates from 0 to2.5 m'' s"^). The input data for the model are shown in

Table 1, for the three scenarios considered (worst, typicaland best), while the determination coefficients of theadjusted lines are presented in Table 4.

A wide range of biogas production and potential forenergy generation may be obtained, depending on the inputvariables. Considering, for example, a wastewater flowrateof 2,000 L s \ the expected biogas production and potential

(b)

Typicali Best

0 500 1,000 1,500 2,000

Wastewater flowrate (L.s-' )2,500

ergy

c

'SI r

gene

n(M

J.la

len

l

s.

400,000 -

300,000

200,000 -

i 00,000

0"Wonl Typical

500 1,000 1,500 2,000 2,500

Wastewater flow rate (L.s' ' )

Figure 3 I Expected ranges of biogas production (a) and potentiai generation of energy (b) in UASB reactors treating domestic wastewater.

2750 L. C. S. Lobato et al. \ Estimates of methane loss and energy in anaerobic reactors Water Science & Technology | 66.12 { 2012

Tabie 4 I Regression equations and determination coefficients of the adjusted data

Scenario

Best

Typical

Worst

Linear regression equation"

y =

y =

8.95X

7.52*

5.16

MJd H s ^

y = 235.92X

y = 185.46

y = 118.86

Determinationcoefficient (/?')

0.83

0.75

0.64

"Regression equations were obtained for a set of simulated data during a certain run of themodel.

of energy recovery may vary from 10,000 to 18,000 m^ d ^and from 240,000 to 480,000 MJ d'\ respectively.

Based on the simulations performed, tbe following uni-tary relationships were also obtained for methane, biogasand energy production in UASB reactors treating typicallydomestic wastewater (Table 5).

The UASB reactors show an estimated volumetric biogasproduction of 14 L.inbab"^ d"^ (mean for tbe typical scenario);tbis production is lower tban tbat found in tbe sludge digesters.In the best scenario, tbe mean value of tbe volumetric biogasproduction was 17L.inhab"^ d^^ The potential for energyrecovery in tbe UASB reactors varied from 1.5 to 2.9 MJ perm^ of treated wastewater, depending on the characteristics oftbe influent wastewater and tbe efficiency of tbe system.

Finally, it is important to mention tbat tbe range ofmean metbane yield predicted by tbe model (0.113-0.196 Nm^ CH4 kg CODremoved - Table 5) is in close agree-ment witb tbe expected range reported by Noyola et al(1988), of 0.08-0.18 Nm^ kg CODremoved-'.

reactors used to validate tbe model (Table 3), were plottedon tbe same grapb sbowing tbe tendency lines for the resultsobtained in tbe simulations (Figures 4-7).

The mean values obtained for tbe pilot-scale UASB reac-tor were 0.12 m^ d"' for biogas production (Figure 4(a)), and2.7 MJd"' for the energy recovery potential (Figure 4(b)),considering the mean influent flowrate of 0.02 L s"^ For thedemonstration-scale UASB reactor, considering the meaninfluent flowrate of 0.32 L s "\ 2.1 m^ d"' and 55.8 MJ d"'were obtained for biogas production (Figure 5 (a)) andenergy recovery potential (Figure 5(b)), respectively.

Biogas production in tbe UASB reactors of LaboreauxWWTP was in tbe order of 390 m^ d"^ (Figure 6(a)), result-ing in an energy recovery potential of around 11,000 MJ d"^(Figure 6(b)). For tbe UASB reactors of Ona WWTP, tbemean observed values were 3,900 m^d~^ for biogas pro-duction (Figure 7(a)) and 105,000MJd"' for energyrecovery potential (Figure 7(b)).

The results for biogas production and tbe resultantpotential for energy recovery in both the pilot- and demo-scale UASB reactors (Figures 4 and 5), obtained using exper-imental data, were observed to be witbin tbe simulatedranges (between worst and best scenarios), with no dataobserved below tbe worst scenario line. For tbe full-scalereactors (Figures 6 and 7), most of the results for biogas pro-duction and energy recovery potential were verified to beconcentrated between tbe simulated ranges. However,some data from botb full-scale plants were situated belowtbe worst scenario line.

Validation of the mathematical model

Tbe predicted results of biogas production and the corre-sponding potential for energy recovery, for tbe four UASB

Model adjustment to the measured data

To better evaluate tbe model adjustment to the measureddata of biogas production, tbese data were grouped in

Table 5 I Unitary relationships for the production of methane, biogas and energy production In UASB reactors treating domestic wastewater

unitary relationsiiip

Unitary metbaneyield

Unitary biogas yield

Unitary energypotential

unit

NLCH4 inbab"' day"'NLCH4 m"^wastewater

NLCH4kgCOD-eUved

NLbiogas inbab"' day"'NLbiogas m"^wastewater

NLbiogas kg CODremoved

MJ m^'^wastewater

MJ kg CODr'movedMJ Nm"^biogas

MJ inbab"' year"'

Worst scenario

iVIaximun'

9.9

81.7

154.1

14.1

116.7220.1

2.95.5

25.1

129.5

1 Minimum

3.616.766.0

5.2

23.8

94.3

0.6

2.4

25.1

47.7

Mean

6.8

42.2

113.4

9.860.3

162.0

1.5

4.1

25.1

89.7

Typicai scenario

iVlaximum

13.3

103.7

185.8

17.7

138.3247.8

3.7

6.7

26.9

173.8

1 Minimum

7.4

34.8124.2

9.946.4

165.6

1.2

4.5

26.9

96.8

iVIean

10.2

64.2

158.3

13.685.6

211.1

2.3

5.7

26.9

133.8

Best scenario

iVlaximum

16.7

134.6

219.1

20.8

168.3

273.9

4.8

7.9

28.7

218.4

1 Minimum

11.1

51.8

173.9

13.9

64.8

217.4

1.96.2

28.7

145.7

Mean

13.7

81.3

196.0

17.1

101.6

245.0

2.9

7.0

28.7

179.3

2751 L, C. S. Lobato et ai. \ Estimates of methane loss and energy in anaerobic reactors Water Science & Teciinoiogy | 66.12 | 2012

1 0.02 0.03* measured data (pilot sea le)

Wastewater flowrate (L.s"')

I 0.02 0.03measured da ta (pilolseale)

Wastewater fiowrate (L.s-')

Figure 4 I Validation of the modei using the monitoring data from the pilot-scale UASB reactor: (a) biogas production; (b) potential ot energy recovery.

.1 0.2 0.3

* measured data (demonstration scale)

Wastewater flowrate fL.s-')

0.1 0.2 0.3 measured data (demonstration seak)Wastewater flowrate {L.s'' )

Figure 5 I Validation of the model using the monitoring data from the demonstration-scale UASB reactor: (a) biogas production; (b) potential of energy recovery.

20 40 60 80 measured data (Laboreaux WWTP)Wastewater flowrate (L.S"')

20 40 60 80 meastjreddata (Labotcaux WWTP)Wastewater flowrate (L.s-')

Figure 6 I Validation of the model using the monitoring data from the Laboreaux WWTP: (a) biogas production; (b) potentiai of energy recovery.

two sets of results, as follows: (i) measured results of biogasproduction in the pilot- and demo-scale reactors (Figure 8(a));and (ii) measured results of biogas production in the full-

scale plants (Figure 8(b)). It can be seem from Figure 8(a)that the linear adjustment of the biogas production datafrom the pilot- and demo-scale UASB reactors was very

2752 L. C. S. Lobato et al. | Estimates of methane loss and energy in anaerobic reactors Water Science & Technology | 66.12 | 2012

(a) (b)7.000

6.000 5,000g3 4,0001 3.000 a.

a 2.000

1.000

0

CQ

.

/y

- /y

A

fi

200 400 600 800 measured dala (Ona WWTP)

Wastewater flowrate (L.s-')

1,000 )0 400 600 800 measured data (Ona WWTP)

Wastewater flowrate (L.S"')

1,000

Figure 7 I validation of ttie model using the monitoring data from the Ona WWTP; (a) biogas production; (b) potential of energy recovery.

y=5.70xR"=0.81

measured data (pilot and dei|- - linear adjustment of measured data

Wastewater flowrate (L . s ' )

250 500 750 measured data (WWTP Laboreaun and Ona)

linear adjustment of the measureddataWaslewater flowrate (L.s"')

Figure 8 I Model adjustment to the measured biogas production data; (a) pilot- and demonstration-scale UASB reactors; (b) full-scale UASB reactors.

close to tbe tendency line predicted by the model in typicalscenario, confirming great adberence to the model. Tbedetermination coefficient {R^) for this set of data was0.92. On the other hand, the linear adjustment of thedata from the two full-scale plants stayed close to the ten-dency line of the worst scenario (Figure 8(b)). The R^coefficient for this set of data was 0.81.

The greater adherence of the results from the pilot-and demonstration-scale reactors to the model may beexplained by the fewer variations in the concentration ofthe infiuent wastewater, and also by the greater precisionof the biogas meters used in the CePTS. In the case of thetwo full-scale plants, the excessive dilution of the influentwastewater is a recurring problem, owing to the contri-butions of rainwater and fiood on the river banks,which result in the reduction of biogas production.Moreover, the lack of calibration of biogas metersduring some periods may have prompted erroneousmeasurements.

It is worth mentioning that the model was developedand validated for the COD balance in UASB reactors treat-ing domestic (low concentration) wastewater. Its use forother situations should therefore considrer the review ofthe input data presented in Table 1.

CONCLUSION

The mathematical model developed enabled better represen-tation of the mass balance of COD and of the potential forenergy recovery in UASB reactors treating domestic waste-water. The results of the simulations performed showedthat the model enables a more realistic estimate of theamount of biogas that can be recovered from the interiorof the three-phase separators, which effectively representthe portion available for energy recovery.

The incorporation into the model of the losses ofmethane dissolved in the effiuent and in the gaseous phase.

2753 L. C. S. Lobato et al. \ Estimates of methane loss and energy in anaerobic reactors Water Science & Technology | 66.12 | 2012

as well as the portion of COD used for sulfate reduction, maybe considered an advance as the available models usuallyoverestimate biogas production and the potential for energyrecovery in anaerobic reactors used in the treatment of dom-estic wastewater. The results of the simulations indicate thatsignificant portions of the influent COD may not be recov-ered as methane in the biogas, depending primarily on theloss of methane dissolved in the effluent and the concen-tration of sulfate in the influent. In worst scenario (seeTable 2), only 19% of the influent COD was recovered asmethane in the biogas. In the best scenario, the percentageof methane recovered in the biogas reached 39% of the influ-ent COD. Of all the COD converted into methane, theportion recovered in the biogas varied from 49 to 75%,depending on the losses mentioned above.

When all COD fractions are considered in the mass bal-ance, as well as the possible losses in the liquid and gasphases, the values obtained for the theoretical amount ofmethane available for energy recovery are much closer tothe actual values measured in the field. This can be con-firmed by the validation of the mathematical model usingthe results for biogas production and percentage of CH4obtained in pilot, demo- and full-scale UASB reactors.

ACKNOWLEDGEMENTS

The authors wish to acknowledge the support obtained fromthe following institutions: Companhia de Saneamento deMinas Gerais - COPASA; Conselho Nacional de Desenvol-vimento Cientfico e Tecnolgico - CNPq; Fundaao deAmparo Pesquisa do Estado de Minas Gerais - FAPEMIG;Sistema Autnomo de Agua e Esgoto de Itabira - SAAEItabira.

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First received 28 March 2012; accepted in revised form 19 July 2012

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