MODELING OF DEGRADATION OF ORGANIC MICROPOLLUTANTS IN ACTIVATEDSLUDGE PROCESS FOCUSING ON PARTITION BETWEEN WATER AND SLUDGE PHASES

Student Number: 02M16079 Name: Tomoya KIKUTA Supervisor: Taro URASE

固液間の化学物質の分配に着目した微量有害物質の活性汚泥法での分解モデルの構築

菊田 友弥

　本研究では，活性汚泥処理におけるエストロジェン・医薬品などの微量有害物質の除去に

影響を及ぼす操作因子を特定するために，実験室内の反応器にて投与分解試験を行い，反応

器内での吸着・分解過程を反応速度論的に表現する二相モデルを構築した．pH の低い運転条件を選択し，活性汚泥側への溶質の移動を促進することにより，医薬品類の除去率が向上す

ることが明らかになった．

1. Introduction

Increasing evidences show that estrogens, whichare predominantly female hormones and originatefrom human urine, are more important in endocrinedisrupting activity than other artificial compounds likebisphenol A [1,2]. Since 1990s, pharmaceuticals havebeen detected in aquatic environments and they havebeen recognized as new unregulated contaminants[3–9]. Most of pharmaceuticals are by nature biologi-cally active, hydrophilic in order to be able to passbiological membranes easily, and persistent in order toavoid the degradation before having a curing effect [3].These human origin compounds are continually dis-charged to aquatic environments via a number ofroutes but primarily by treated wastewater [10–12].Thus it is very important to treat these compoundssuitably in wastewater treatment processes.

Several studies have been carried out as to influentand effluent concentrations of estrogens and estrogenconjugates in wastewater treatment plants [13–20].According to the survey on influent and effluentconcentrations of endocrine disrupting chemicalsincluding estrogens at 47 wastewater treatment plantsconducted by Japan Ministry of Land, Infrastructureand Transport, the removal ratio of 17β-estradiol (E2),estrone (E1) and benzophenone (BZP) were relativelylower than that of other EDCs, for E2 of 77%, for E1of 86% and for BZP of 71% [13]. C. Baronti et al.investigated in Roman wastewater treatment plantsthat the removal ratio of 17α-ethynilestradiol (EE2),which is one of the synthetic estrogens and used asoral contraceptive, were lower than that of naturalestrogens like E2 and E1 [15]. These lower removalratios were caused by persistent nature of the com-pounds or isolation of conjugates in sewerage.

There are a few studies measuring both influentand effluent concentrations of pharmaceuticals[8,21–25]. According to a survey in German waste-water treatment plants, clofibric acid (CA), which isone of the metabolite of lipid regulators, and carba-mazepine (CAZ), which is an antiepileptic agent, wereremoved poorly; the removal ratio of CA was 51%

and that of CAZ was 7% [8]. It is also reported thatCA and CAZ are persistent in the aquatic environment[8,25–29]. It is difficult to eliminate these persistentcompounds efficiently by conventional activatedsludge process.

Many models describing the fate of trace chemi-cals in wastewater treatment plant have been sug-gested so far. The target compounds are volatile or-ganic compounds (VOCs) [30–34], nitrilotriacteticacid (NTA) [35] and linear alkyl benzene sulfonate(LAS) [30,35], dioxin [32], PCBs [32] and PAHs[30,32] which have high hydrophobic property, and soon. The fate of pharmaceuticals was estimated by S.J.Khan et al. [36] using QSAR model for biodegrada-tion factor [37]. However there are no models usingthe parameters estimated by conducting biodegrada-tion experiments in an activated sludge bioreactor.

In this study, batch experiments were carried outin a laboratory scale activated sludge reactor to inves-tigate the behavior of estrogens and pharmaceuticalsby measuring the concentrations in water phase andsludge phase separately. Then a reaction kinetic modelwas introduced to determine the adsorption and bio-degradation characteristics of the target compoundsquantitatively. Thereafter the fate of the target com-pounds in wastewater treatment process was predictedby using numerical simulation and calculated pa-rameters. In addition, the model was extended topredict the effect of operational conditions of activat-ed sludge bioreactor on the removal of target com-pounds. By considering water phase and sludge phaseseparately, the advantage of complete solid-liquidseparation like membrane processes was evaluatedmore accurately.

2. Experimental section

2.1. Target compounds

The target compounds in this study are 17β-estradiol (E2), estrone (E1), 17α-ethynilestradiol(EE2), bisphenol A (BPA), benzophenone (BZP),clofibric acid (CA), gemfibrozil (GFZ), ibuprofen

(IBP), fenoprofen (FEP), ketoprofen (KEP), naproxen(NPX), diclofenac (DCF), indomethacin (IDM), pro-pyphenazone (PPZ) and carbamazepine (CAZ). E2 issaid to have the most significant contribution to theendocrine disruption potential in treated wastewater[2]. E1 is an intermediate compounds produced in thecourse of biodegradation of E2 [38,39]. EE2 is asynthetic estrogen included in oral contraceptives.BPA is one of the representative compounds whichhave endocrine disruption nature. BZP is also endo-crine disrupting chemical used as an ingredient ofdrugs and fixative of perfume. CA is one of the me-tabolite of lipid regulators which are clofibrate, etofi-brate and etofyllinclofibrate. GFZ is a lipid regulatingagent. IBP, FEP, KEP, NPX, DCF, IDM, PPZ arecommonly used non-steroidal anti-inflammatory drugs(NSAIDs). CAZ is an antiepileptic agent. Table 1shows the physical and chemical properties of thesecompounds.

2.2. Batch experiments

A series of experiments were carried out to inves-tigate the degradation of the target compounds byusing a laboratory scale activated sludge bioreactor.Activated sludge was collected at a wastewater treat-ment plant in Tokyo, Japan. The experimental set-upwas consisted of an activated sludge reactor with thevolume of 4 L at 20 °C as shown in figure 1. Theactivated sludge was fed with glucose, peptone andother nutrients at a certain time everyday and con-trolled with the MLSS around 2,500 mg/L. The pH ofthe reactor was adjusted in each experiment at 6.7(Run A-1), 5.6 (Run B-1) and 4.4 (Run B-2) respec-tively. At t=0, the target compounds dissolved inacetone or methanol and artificial wastewater wereadded to the reactor where the initial concentrations ofthe target compounds were 100 µg/L and time de-pendent change in the concentrations of the targetcompounds in both water phase and sludge phasewere analyzed. E1 was not added because E1 wasmeasured as an intermediate product of E2. During the

experiments, mixed liquor was collected with thesampling volume of 160 mL, subjected to immediateseparation by using centrifuge and grass-fiber-filters(GF/B) with retention diameter of 1µm into waterphase and sludge phase.

2.3. Analysis

The target estrogens and pharmaceuticals wereanalyzed separately. 17β-estradiol-d4 and 2,3-dichlorophenoxyacetic acid were used as surrogatestandards and chrysene-d12 as internal standard. Theconcentrations of E2, E1, EE2, BPA and BZP weremeasured by GC/MS analysis after solid phase ex-traction followed by dimethyl derivatization. Extrac-tion, derivatization and measurement procedures ofthese five compounds were based on a manual pub-lished by Japan Ministry of the Environment [40].Target pharmaceuticals like CA, GFZ, IBP, FEP, KEP,NPX, DCF, IDM, PPZ and CAZ were analyzed by themethod using GC/MS after solid phase extraction andpentafluorobenzyl derivatization suggested by V.Koutsouba et al. [41] and F. Sacher et al. [42]. Dis-solved organic carbon (DOC) and pH were measuredat every sampling time. MLSS were measured beforeeach experiment was carried out.

3. Model structure

3.1. Two-phase fate model

A two-phase fate model was proposed in order toclarify the transfer of the target compounds betweenwater phase and sludge phase. The model containsadsorption and desorption of target compounds be-tween water phase and activated sludge phase anddeformation kinetics in activated sludge phase asshown in figure 2. This model assumed first orderreaction inside sludge and the reaction in water phasewas neglected based on our experimental observation.The transfer of the compounds between water phaseand sludge phase was assumed to follow linear ad-

Table 1. The chemical and physical properties of the target compoundsWater Solu-

bilityHenry’s Law Con-

stantS/N Chemical Name Abbrev.Mol.

Weight[mg/L] [atm-m3/mol]

LogKow pKa

1 17β-estradiol E2 272.39 3.60 3.64×10-11 4.012 Estrone E1 270.39 30 3.80×10-10 3.133 17α-ethynylestradiol EE2 296.41 11.3 7.94×10-12 3.674 Bisphenol A BPA 228.29 120 1.00×10-11 3.325 Benzophenone BZP 182.22 137 1.94×10-6 3.186 Clofibric acid CA 214.65 583 2.19×10-8 2.577 Gemfibrozil GFZ 250.34 N/A N/A 4.778 Ibuprofen IBP 206.29 21 1.50×10-7 3.97 4.919 Fenoprofen FEP 242.28 N/A N/A 3.9 7.310 Ketoprofen KEP 254.29 51 2.12×10-11 3.12 4.4511 Naproxen NPX 230.27 15.9 3.39×10-10 3.18 4.1512 Diclofenac DCF 296.16 2.37 4.73×10-12 4.51 4.1513 Indomethacin IDM 357.80 0.94 3.13×10-14 4.27 4.5014 Propyphenazone PPZ 230.31 3×106 1.84×10-9 1.9415 Carbamazepine CAZ 236.28 17.7 1.08×10-10 2.45

sorption isotherm with finite transfer rate becauselinear adsorption of estrogens was suggested bySchäfer et al. [43]. The transfer of the compounds toair phase was neglected because Henry’s low constantof the target compounds are less than 1.0 × 10-3 atm-m3/mol [31]. Two differential equations were drawnfor changes in water phase and sludge phase respec-tively.

€

d βCW( )dt

= −kb k pCW −CS( )X (1)

€

d CS X( )dt

= kb k pCW −CS( )X − k1CS X (2)

where CW is concentration in water phase [µg/L], CS isconcentration in activated sludge phase [µg/gMLSS],X is mixed liquor suspended solid (MLSS)[gMLSS/L], kp is water-sludge partition coefficient[L/gMLSS], kb is water-sludge mass-transfer rateconstant [hr-1], k1 is first order biodegradation rateconstant [hr-1]. β is volume correction factor becauseCW is defined as concentration in water phase and notas that in mixed liquor. In the case of the degradationof E2, the changes in both E2 and E1 were considered.In the proposed two-phase model, two paths wereconsidered for the degradation of E2. One path is thedegradation of E2 to unknown compounds other thanE1 with the rate constant of k1, and the other is thedegradation of E2 to E1 with the rate constant of k2.

€

d βCWE2( )

dt= −kb

E2 k pE2CW

E2 −CSE2( ) X (3)

€

d CSE2 X( )

dt= kb

E2 k pE2CW

E2 −CSE2( ) X − k1

E2CSE2 X − k2

E2CSE2 X (4)

€

d βCWE1( )

dt= −kb

E1 k pE1CW

E1 −CSE1( ) X (5)

€

d CSE1X( )

dt= kb

E1 k pE1CW

E1 −CSE1( ) X − k1

E1CSE1X + k2

E2CSE2 X (6)

where equation 3 is the change of E2 in water phase,equation 4 is the change of E2 in sludge phase, equa-tion 5 is the change of E1 in water phase, and equation6 is the change of E1 in sludge phase.

3.2. The extension of the model to wastewater treat-ment process

The two-phase fate model is necessary to be ex-tended to calculate effluent concentration in a waste-water treatment process. It is not obviously true thatthe parameters obtained in a laboratory batch experi-ments can be used exactly in the same way in thesimulation for real wastewater treatment. However,such extension will give rough estimation of the per-formance of real wastewater to a certain extent for theremoval of trace contaminants.

Figure 3 illustrates the conventional activatedsludge process and membrane separation activatedsludge process considered in this study. By takingmass balance in an ideal completely mixed flow re-actor, the following equations were obtained for asteady state condition.

€

QCW,inf − kb k pCW −CS( ) XV = QCW (7)

€

QCS,inf X inf + kb k pCW −CS( ) XV

= k1CS XV +VXSRTCS + QCS X eff (8)

where Q is flow rate of wastewater, V is reactor vol-ume, CW,inf is influent concentration of target com-pounds in dissolved fraction, CS,infXinf is influent con-centration of target compounds in particulate associat-ed fraction. Equation 7 is the mass balance equationfor the water phase where the difference in the influ-ent flux and effluent flux was attributed to the ex-change to the sludge phase. Equation 8 is the massbalance for the sludge phase where the difference inthe influent flux and effluent flux was attributed to theexchange to the water phase, biodegradation anddisappearance by excess sludge removal. In this study,the influent concentration of target compounds inparticulate associated fraction was assumed to be zerobecause the target compounds are more or less water-soluble compounds.

In this simulation, hydraulic retention time (HRT)was applied to determine the characteristics of an

Thermostat

Blower

Temperature sensor

Heater

PAir

Activated sludge phase

Water phase kb

k1

kp

CW

others

Adsorption

Deformation

CS

Partition

Figure 1. A schematic diagram of the activatedsludge reactor

Figure 2. A conceptual diagram of the two-phase fate model

Bioreactor

Return sludge

QCW

€

VX

SRTCS

V, X

QCSXeff

InfluentQCW,inf

QCS,infXinf

Excess sludge

Effluent

Sedimentationtank(a)

Influent

Effluent

Excess sludge

QCW,inf

V, XQCW

€

VX

SRTCS

Membrane Bioreactor

QCS,infXinf

(b)

Figure 3. Schematic representation of (a) conventional activated sludge process and (b) membrane separa-tion activated sludge process used in this study

ideal wastewater treatment plant as HRT=V/Q. In realwastewater treatment plant, HRT, sludge retentiontime (SRT) and MLSS concentration are the importantparameter for the operation of activated sludge proc-ess. However, two of them can be independent param-eters and the other is the dependent parameter of thetwo independent parameters. HRT and MLSS con-centration were selected to be the independent param-eters in this study and SRT was calculated by thefollowing equation.

€

1SRT =

YS0

X ⋅HRT − kd (9)

where Y is the yield and assumed to be 0.6mg/mgBOD5 in this study, S0 is the influent BOD5 andassumed to be 150 mg/L in this study, and kd is thedeath coefficient and assumed to be 0.06 day-1 [44].

4. Results and discussion

4.1. Experimental results and identification of themodel parameters

Typical results are shown in figure 4. The targetcompounds in the water phase were rapidly adsorbedto the sludge phase. Then both concentrations in waterphase and sludge phase were gradually decreased dueto biodegradation. Model parameters (kb, kp, k1) wereestimated in each Run by using the least-squaremethod. Simultaneous numerical solutions for differ-ential equations 1 and 2 were used to fit curves infigure 4 obtained by using the calculated parameters.The calculated parameters with experimental condi-tions are shown in table 2.

From the results of neutral pH condition (Run A-1), water-sludge partition coefficients (kp) of the targetpharmaceuticals were less than 0.1 L/gMLSS andthese values were lower than target estrogens and

EDCs which are E2, E1, EE2, BPA and BZP. kp of E2is the highest in the target compounds and nine timeslarger than that of E1. In addition, E2 was rapidlybiodegraded 60 times as fast as E1 comparing thevalue of k1. EE2, which is a synthetic estrogen, waseasily adsorbed to the sludge but difficult to biode-grade. The kp value of BZP was lower than that ofBPA while the k1 value of BZP was 13 times higherthan that of BPA. CA, NPX and DCF have high po-tential that discharge to the aquatic environment withoriginal form because biodegradability of these threecompounds were lower than that of BPA and theamount of sorption to sludge were quite small. The k1

value of IDM was the highest among those of thetarget compounds except for E2 and consequently it isa easily biodegradable compound. It is clear that IDM,BZP, IBP and FEP, which are synthetic chemicals,were more biodegradable than E1, which is a humanorigin compound.

4.2. Comparison of the model parameters in differentpH condition

The kp values of the target compounds except forE2, IBP and CAZ were increased with decrease in pHof the reactor as shown in figure 5a. Especially in thecase of the pharmaceuticals with one carboxyl group,the kp values at pH=5.6 (Run B-1) were 2.5 to 30times higher than those at pH=6.7 (Run A-1). In addi-tion, the kp value of IDM at pH=4.4 (Run B-2) was 72times as large as that at pH=6.7 (Run A-1). The kp

values of the compounds having one carboxyl grouplike CA, GFZ, IBP, FEP, KEP, NPX, DCF and IDMincreased with the decrease in pH while the increasein the kp values of those having hydroxyl groups likeE1, EE2 and BPA were small. The increases of kp ofthe compounds having no hydrophilic groups like

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BZP water est.

BZP water exp.

Time [hr]

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IBP water est.

IBP water exp.

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KEP water exp.

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IDM water exp.

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BZP sludge est.

BZP sludge exp.

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IBP sludge est.

IBP sludge exp.

Time [hr]

Conc. [µg/gMLSS]

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KEP sludge est.

KEP sludge exp.

Time [hr]

Conc. [µg/gMLSS]

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IDM sludge est.

IDM sludge exp.

Time [hr]

Conc. [µg/gMLSS]

Figure 4. The plots show experimental results on time dependent change in concentrations. Solid linesrepresent most probable fitting-curves. Upper figures show concentrations in water phase. Bottom figuresshow concentrations in sludge phase.

BZP, PPZ and CAZ were not observed with the de-crease of pH.

The k1 values of E1, EE2, BPA, GFZ, FEP, KEP,NPX and DCF at pH=5.6 (Run B-1) were highestamong the series of the experiments as shown infigure 6b. There is a possibility to stimulate the biode-gradation of these compounds at the reactor pH be-tween 6.7 and 4.4. On the other hand, the k1 values ofBZP, IDM and CAZ were decreased with decrease ofpH.

4.3. Relationship between Kow and kp

kp was in the order of E2 > EE2 > BPA > E1 whichhave hydroxyl groups at Run A-1. This relationshipwas consistent with the order of LogKow values, for E2of 4.01, for EE2 of 3.67, for BPA of 3.32, and for E1of 3.13. The partition between water and sludgenaturally correlated with Kow, which is widely used forthe prediction of the fate of organic compounds[31,32,45]. In the case of PPZ, CAZ and BZP whichhave no hydrophilic groups, linear relationship be-tween kp and Kow was observed while in the case ofpharmaceuticals which have one carboxyl group, this

Table 2. The operational conditions and calculatedmodel parameters

Run A-1 Run B-1 Run B-2Run D(Mean)

Exp. period [hr] 96 96 48 22

Water temp [°C] 20 20 20 15

MLSS [gMLSS/L] 2.663 2.774 2.189 --Influent DOC [mg/L] 144 145 138 400

Initial pH 6.7 5.6 4.4 N/A

kb [hr-1] >10 >10 >10 --

kp [L/gMLSS] 1.506 0.713 0.426 0.491

k1 [hr-1] 0.000 0.000 0.000 1.495E2

k2 [hr-1] 6.839 8.390 13.329 4.675

kb [hr-1] >10 >10 >10 --

kp [L/gMLSS] 0.170 0.218 0.303 0.302E1

k1 [hr-1] 0.109 0.263 0.167 0.657

kb [hr-1] 2.000 1.684 4.968 --

kp [L/gMLSS] 0.438 0.547 0.554 0.450EE2

k1 [hr-1] 0.013 0.105 0.088 0.020

kb [hr-1] 2.278 2.934 6.027 --

kp [L/gMLSS] 0.217 0.304 0.378 0.589BPA

k1 [hr-1] 0.028 0.225 0.130 0.567

kb [hr-1] 3.542 >10 3.965 --

kp [L/gMLSS] 0.161 0.168 0.177 --BZP

k1 [hr-1] 0.363 0.091 0.081 --

kb [hr-1] >10 >10 >10 --

kp [L/gMLSS] 0.029 0.162 0.554 --CA

k1 [hr-1] 0.017 0.000 0.025 --

kb [hr-1] 0.448 0.401 0.403 --

kp [L/gMLSS] 0.100 0.327 1.106 --GFZ

k1 [hr-1] 0.052 0.434 0.210 --

kb [hr-1] 0.199 0.054 1.061 --

kp [L/gMLSS] 0.080 1.265 0.470 --IBP

k1 [hr-1] 0.201 0.186 0.352 --

kb [hr-1] 0.178 0.296 1.311 --

kp [L/gMLSS] 0.057 0.306 0.515 --FEP

k1 [hr-1] 0.160 0.400 0.141 --

kb [hr-1] 0.337 2.271 >10 --

kp [L/gMLSS] 0.029 0.072 0.429 --KEP

k1 [hr-1] 0.061 0.078 0.028 --

kb [hr-1] 0.464 1.184 1.916 --

kp [L/gMLSS] 0.024 0.093 0.444 --NPX

k1 [hr-1] 0.013 0.079 0.041 --

kb [hr-1] 3.795 >10 >10 --

kp [L/gMLSS] 0.032 0.159 0.701 --DCF

k1 [hr-1] 0.000 0.260 0.052 --

kb [hr-1] 7.225 0.125 1.540 --

kp [L/gMLSS] 0.039 1.158 2.851 --IDM

k1 [hr-1] 0.541 0.253 0.112 --

kb [hr-1] 4.098 1.003 6.216 --

kp [L/gMLSS] 0.015 0.015 0.019 --PPZ

k1 [hr-1] 0.030 0.000 0.090 --

kb [hr-1] >10 >10 3.281 --

kp [L/gMLSS] 0.066 0.028 0.035 --CAZ

k1 [hr-1] 0.030 0.000 0.000 --

0

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0.8

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1.6

E2 E1 EE2 BPA BZP CA GFZ IBP FEP KEP NPX DCF IDM PPZ CAZ

pH=6.7 (Run A-1)pH=5.6 (Run B-1)pH=4.4 (Run B-2)

kp [L/gMLSS]2.85

(a)

0

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E1 EE2 BPA BZP CA GFZ IBP FEP KEP NPX DCF IDM PPZ CAZ

pH=6.7 (Run A-1)pH=5.6 (Run B-1)pH=4.4 (Run B-2)

k1 [hr-1]

(b)

Figure 5. Comparison of (a) kp and (b) k1

PPZ

CA

E1

EE2

BPA

BZPGFZIBP

FEP

NPX

KEPDCF

IDM

CAZ

E2

-2

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-1

-0.5

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1 2 3 4 5 6Log Kow

Log kp

(a)

CAZ

IDM

DCF

KEP

NPX

FEP

IBP

GFZ

BZP

BPAEE2

E1CA

PPZ

E2

-2

-1.5

-1

-0.5

0

0.5

1 2 3 4 5 6Log Kow

Log kp

(b)

Figure 6. Correlation between Kow and kp at(a) pH=6.7 and (b) pH=5.6

relationship was not obvious in the neutral pH condi-tion (Run A-1) as shown in figure 6a. However in thelower pH condition (Run B-1), linear relationshipbetween kp and Kow was observed even in the case ofpharmaceuticals which have a carboxyl group due tothe increase of kp (figure 6b).

4.4. Effect of operating condition on removal

By using the three parameters obtained in Run D,the simulations to estimate the removal of the targetcompounds for various HRT and MLSS were carriedout. The effect of operating condition on the removalwas shown in figure 7. Higher MLSS and higher HRTconditions were shown to be effective for higherremoval because the removal was attributed to thebiodegradation. In the case of E2, the removal wascalculated to be more than 90% with MLSS concen-tration of more than 1,000 mg/L while EE2 removalwas shown to be low. In the case of EE2, the maxi-mum removal was calculated to be 24% even at in-finite SRT condition.

4.5. Predicted fate of target compounds in real waste-water treatment plant

MLSS of 1,000 mg/L and HRT of 8 hrs were se-lected as the operating conditions considering typicalwastewater treatment facilities. Effluent SS concen-tration was assumed to be 10mg/L. Figure 8 shows thefate of target compounds when their influent concen-trations are assumed to be 100. The influent concen-tration does not affect the ratios of their fate in thismodel calculation because all the equations are linearequations. In the case of E2 and BPA, more than 60%

biodegradation was estimated, while the biodegrada-tion of EE2 was very slow. The contribution of excesssludge removal to the overall removal was very smallbecause the target compounds have relatively hydro-philic nature. The calculation also showed that E1concentration is higher than that of E2 in treatedwastewater.

4.6. Comparison of treatment processes

Membrane separation activated sludge process canremove suspended matters completely in the effluent.The model calculation predicted that the contributionof the sludge fraction, associated with the 10mg/L SSin the effluent, is negligible. For example, E2 in thetreated water is calculated to be 6.3 in figure 8. If wesubtract the particle-associated fraction from thisvalue by introducing membrane separation process,the E2 concentration is 6.2 which is almost the samevalue in the calculation of the conventional activatedsludge process as shown in table 3. This result sug-gests that the removal of these target compounds willnot be enhanced only with the improvement of solid-liquid separation such as with the introduction ofmembrane technology.

However membrane separation activated sludgeprocess has the advantage of higher MLSS operation.In order to compare final effluent concentrations indifferent treatment processes, a numerical simulationwas applied for three cases. The first case is the typi-cal conventional activated sludge process operatedwith MLSS of 1,000 mg/L and HRT of 8 hrs. Thesecond case is pure oxygen activated sludge processoperated with higher MLSS of 2,000 mg/L and shorterHRT of 3 hrs. The third case is the membrane separa-

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E2

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AS

EE2 (Influent)

100Biodegradation

EE2 (Excess Sludge)

EE2 (Treated Water)90.7

2.8

6.5

AS

BPA (Influent)

100Biodegradation

BPA (Excess Sludge)

BPA (Treated Water)28.2

1.1

70.7

AS

E2 (Influent)

100Biodegradation

E2 0.1

65.3

E1 0.6

E1

E2 6.3

26.6Treated Water

Excess SludgeMLSS = 1,000 mg/LHRT = 8 hours

Figure 7. Effect of operating condition on the re-moval of target compounds in conventional acti-vated sludge process

Figure 8. The simulated fate of target compoundsin conventional activated sludge process

Table 3. Effect of residual SS on the concentrations of treated waterInfluent Bioreactor R-SS Final effluent

CW,inf CW CS CSXeff

[–] [–] [gMLSS-1] [–]

ConventionalAS

Membraneseparation AS

E2 100 6.2 1.9 0.02 6.3 6.2E1 0 26.5 8.3 0.08 26.6 26.5

EE2 100 90.3 40.5 0.41 90.7 90.3BPA 100 28.0 15.6 0.16 28.2 28.0

It was assumed that MLSS=1,000 mg/L, HRT=8 hrs, Effluent SS in conventional AS=10 mg/L.

tion activated sludge process operated with higherMLSS of 10,000 mg/L and shorter HRT of 3 hrs. Theresults are shown in table 4. The effluent concentra-tions of the target compounds in the pure oxygenprocess were calculated to be slightly higher than thatin the conventional process. It was calculated thatremoval in the membrane separation process washigher than that in the conventional process and pureoxygen process. This high removal in the membraneseparation process was due to higher MLSS operationof 10,000 mg/L rather than to the complete solid-liquid separation by the membranes.

4.7. Comparison of the model calculations with meas-urements

The model parameters in this study were deter-mined by laboratory batch experiments and the vali-dation of the parameters is necessary by comparingthe calculation with the measurement in treatmentfacilities. Japan Ministry of Land, Infrastructure andTransport surveyed the concentration of E2 in influ-ents and effluents of 47 wastewater treatment plantsby ELISA method [13]. The survey showed 67%removal in average and dependence of the removal onHRT was observed. ELISA method is said to givelower removal ratio because ELISA detects not onlyE2 but also other compounds. Our model calculationof 94% removal for E2 and 67% removal for E1+E2 isan acceptable result comparing with the survey. Thefact that removal of E2 increased with increase inHRT is also consistent with our model calculation.Tokyo Metropolitan Government measured the trans-fer of E2 to the excess sludge [14]. The result is 2.4%of E2 in the influent was transferred to excess sludge,when our calculation shows 0.1%. The less tendencyof adsorption of E2 to sludge was confirmed both inmodel calculation and in the measurement. Takigamiet al. reported that 30% of E2 in the influent wastransferred to the excess sludge in the case of nightsoil treatment in Japan [46]. This high ratio of thetransfer may be due to the particulate associated E2 inthe influent, because influent in the case of humanexcreta treatment contains very high concentration ofsuspended solids.

At this moment, our model gives a good estima-

tion of the fate of target compounds in biologicalwastewater treatment process. However the changesof the model parameters due to the differences of thesludge property between acclimated sludge and sludgein a real wastewater treatment plant were observedand it is necessary to clarify the effect of sludge type,the effect of humic acid, the changes of biodegrada-tion rate constant due to the differences of MLSS andthe effect of the differences of the water temperaturein the reactor on the parameters.

5. Conclusions

Biodegradation of 17β-estradiol (E2), estrone (E1),17α-ethynilestradiol (EE2), bisphenol A (BPA), ben-zophenone (BZP), clofibric acid (CA), gemfibrozil(GFZ), ibuprofen (IBP), fenoprofen (FEP), ketoprofen(KEP), naproxen (NPX), diclofenac (DCF), indo-methacin (IDM), propyphenazone (PPZ) and carba-mazepine (CAZ) in activated sludge reactor wasexamined and two-phase fate model in which adsorp-tion and desorption of target compounds betweenwater phase and activated sludge phase and biodegra-dation kinetics in activated sludge phase were consid-ered was suggested. Model parameters were deter-mined to assess the fate of the target compounds inwater phase and sludge phase separately. In addition,using the obtained parameters, the effect of operatingconditions on the removal of target compounds wassimulated. The conclusions were summarized asfollows:1) From the results of the biodegradation experiment

at neutral pH condition, water-sludge partition co-efficients (kp) of the target pharmaceuticals wereless than 0.1 L/gMLSS and these values were low-er than those of target estrogens and EDCs like E2,E1, EE2, BPA and BZP.

2) The kp value of E2 was the highest in the targetcompounds and nine times larger than that of E1.In addition, E2 was rapidly biodegraded 60 timesas fast as E1 based on the value of biodegradationrate constant (k1).

3) The kp values of the target compounds except forE2, IBP and CAZ were increased with decrease ofpH of the reactor. Especially in the case of thepharmaceuticals which have a carboxyl group, thekp values at pH=5.6 were 2.5 to 30 times higherthan those at pH=6.7. With the decrease of pH, theincreases of kp of the compounds having one car-boxyl group like CA, GFZ, IBP, FEP, KEP, NPX,DCF and IDM were obvious while those havinghydroxyl groups like E1, EE2 and BPA weresmall.

4) There is a possibility to stimulate the biodegrada-tion of these compounds at the reactor pH between6.7 and 4.4 because the k1 values of E1, EE2, BPA,GFZ, FEP, KEP, NPX and DCF at pH=5.6 werehighest among the series of the experiments. Onthe other hand, the k1 values of BZP, IDM andCAZ were decreased with decrease in pH.

Table 4. Comparison of treatment processes

(i)Conven-tional AS

(ii)Pure

oxygenAS

(iii)Membraneseparation

ASMLSS [mg/L] 1,000 2,000 10,000HRT [hr] 8 3 3SRT [d] 4.8 3.3 83.3C

ON

D

R-SS(Xeff)[mg/L] 10 10 0

InfluentTreatedwater

Treatedwater

Treatedwater

E2 100 6.3 8.2 1.7E1 0 26.6 30.5 10.6

EE2 100 90.7 92.0 78.1BPA 100 28.2 34.2 9.5

5) In the lower pH condition, linear relationshipbetween kp and Kow was able to be observed evenin the case of pharmaceuticals which have a car-boxyl group due to the increase of kp.

6) The simulation shows that the removal ratio of E2and BPA increased with the increase in HRT andMLSS, though the removal of EE2 was less than24% even at infinite SRT.

7) The contribution of excess sludge removal to theoverall removal was shown to be very small be-cause the target compounds have relatively hydro-philic nature and tend to remain in the waterphase.

8) The contribution of residual SS to the effluent loadwere extremely smaller than that in water phaseand almost all of E2, E1, EE2 and BPA in the finaleffluent were in water phase, as the amounts ofthese compounds adsorbed to the residual SS werevanishingly small.

9) Calculation by the parameters determined in themodel showed that higher MLSS operation inmembrane separation activated sludge process isadvantageous for the efficient removal of the tar-get compounds even if it is operated with shortHRT.

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