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Amoxicillin degradation at ppb levels by Fenton's oxidation using designof experiments

Vera Homem, Arminda Alves, Lcia Santos

LEP, Departamento de Engenharia Qumica, Faculdade de Engenharia da Universidade do Porto, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal

a b s t r a c ta r t i c l e i n f o

Article history:

Received 26 April 2010

Received in revised form 26 July 2010Accepted 30 August 2010

Available online 27 September 2010

Keywords:

Antibiotic

Amoxicillin

Fenton's reagent

Design of experiments

A central composite factorial design methodology was employed to optimise the amoxicillin degradation using

the Fenton's oxidation treatment. In this study, the variables considered for the process optimisation were thehydrogen peroxide and ferrous ion initial concentrations and the temperature, for an antibiotic concentration of

450 g L1 atpH =3.5. Thismethodologyalso allowedassessingand identifyingthe effectsof thedifferentfactorsstudiedand their interactions in the processresponse. An appropriate quadratic model wasdeveloped in order to

plot the response surface and contour curves, which was used to perform the process optimisation. From thisstudy, it was concluded thatferrous ion concentration and temperature were the variables that most inuencedthe response. Under the optimal conditions (hydrogen peroxide concentration= 3.504.28 mg L1, ferrous ion

concentration=254350 g L1 and temperature= 2030 C), it was possible to achieve total amoxicillin

degradation after 30 min of reaction. 2010 Elsevier B.V. All rights reserved.

1. Introduction

Massive production of antibiotics began during World War II andso far, these compounds have been widely used in order to prevent

and treat infections in the area of human and veterinary medicine andto promote growth in animal farming (Kmmerer, 2009; Lee et al.,2008; Martinez, 2009). Although antibiotics have been used in largescale in the last decades, it was only in recent years that its occurrence

in the environment became a subject of scientic and public relevance(Bound and Voulvoulis, 2006; Ginebreda et al., 2010; Hernando et al.,2006). Residues of human and veterinary antibiotics are present in adiversity of environmental matrices, like surface and groundwater,

hospital and WWTPs efuents, soils and sediments (Batt et al., 2007;Benito-Pea et al., 2006; Watkinson et al., 2009). These compoundsare mainly released into the environment by excretion, reaching thewastewater treatment plants (WWTPs), where they are not com-

pletely removed, and contaminating natural waterways. The slurryand manure applied to the elds are a direct entry route of antibioticsinto the soil and consequently, to the food chain. Depending on theproperties of these compounds, they can reach the groundand surface

waters (Chen et al., 2010; Ding et al., 2009; Hernando et al., 2006 ).Antibiotics act as persistent and bioaccumulative contaminants

and by their nature, they are biologically active compounds,

developed to have an effect on organisms. Therefore, they have the

potential to negatively affect either aquatic or terrestrial ecosystems,even in low concentrations (in the range ofgng L1). Besides that,

antibiotics can also produce antibacterial resistance among micro-organisms and be responsible for several allergenic responses ( Bound

and Voulvoulis, 2006; Daz-Cruz et al., 2008; Halling-Srensen et al.,1998).

Amoxicillin (AMOX) is a broad-spectrum -lactam antibiotic thatbelongs to the penicillin class and is used in veterinary and human

medicine, representing one of the most prescribed antibiotics inEurope and in the United States (Bound and Voulvoulis, 2006;Lissemore et al., 2006). When ingested, 1020% of this antibiotic isabsorbed (Hernando et al., 2006), while the remaining is eliminated

by excretion and ends up contaminating the ecosystem. Pan et al.(2008)recently reported the toxic effects of amoxicillin toward algaeand aquatic microorganisms. Despite these problems caused byantibiotics, so far legal limits have not been regulated.

In the last years, advanced oxidation processes (AOPs) have beenstudied as treatments processes for waters and wastewaters. Theyshould be seen as an alternative or a complement for the conventionaltreatments (Trov et al., 2008). As a complement, AOPs were

developed to be a pre-treatment step, in which the pollutants areoxidised to by-products that are easily biodegradable and less toxic,preventing the death of microorganisms that are present in the

subsequent biological treatments (Tekin et al., 2006). Among theseAOPs, the Fenton method is one of the most used treatments, due toits high performance and simplicity of technology, low cost and lowtoxicity of the reagents (Lee and Shoda, 2008; Wang, 2008).

The oxidation reaction with Fenton's reagent is based on thehydrogen peroxide decomposition in acidic medium, catalysed by

Science of the Total Environment 408 (2010) 62726280

Corresponding author. Tel.: +351 225081682; fax: +351 225081449.

E-mail address:[email protected](L. Santos).

0048-9697/$ see front matter 2010 Elsevier B.V. All rights reserved.

doi:10.1016/j.scitotenv.2010.08.058

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ferrous ion. This process involves several parallel and consecutivereactions, but it can be represented for the dominant step (Eq. (1))(Oliveira et al., 2006):

Fe2

H2O2Fe3

HO

OH

1

The efciency of this process depends on several variables, namely

temperature, pH, hydrogen peroxide, ferrous ion concentration andtreatment time. In order to achieve high performances, theseexperimental conditions must be optimised. Until now, most

published studies are based only on the single-factor-at-a-timeapproach, considering the effect of each variable independently andkeeping all other conditions constant. However, this methodologydoes not take into account the interactions between parameters andconsequently, their effect on the process response. With the purpose

of overcoming this disadvantage, the application of experimentaldesign (DoE) becomes essential. This statistical approach allows amultivariate analysis, using a minimum number of experiments(Arslan-Alaton et al., 2009).

In the last decade, some studies about advanced oxidation ofantibiotics have been published. However few investigations have beendone about the degradation of amoxicillin based on Fenton process.Elmolla and Chaudhuri (2009a,b)investigated the degradation of the

antibiotics amoxicillin, ampicillin and cloxacillin in aqueous solutionsby Fenton and photo-Fenton process. The initial concentration ofthese antibiotics was around 100 mg L1 and under optimal conditions(COD (chemical oxygen demand)/H2O2/Fe

2+molar ratio=1:3:0.30 for

Fenton and H2O2/COD molarratio= 1.5, H2O2/Fe2+molarratio= 20 for

photo-Fenton) they were completely removed after 2 minutes. Theconcentrations studied are much higher than those determined inenvironmental matrices. Trov et al. (2008)studied the photodegrada-

tion of amoxicillin, benzabrate and paracetamol by photo-Fenton.Initial amoxicillin concentration was 42 mg L1 and this antibiotic wasalmost degraded. Concentrations used were far from those found in

environmental matrices, due to the lack of sensitivity of the analyticalmethod used. Arslan-Alaton and Dogruel (2004) studied a pre-

treatment of penicillin formulation efuent, containing amoxicillintrihydrate and potassium clavulanate by AOP. The exact concentration

of amoxicillin in the efuent was unknown, but a maximumconcentration of 400 mg L1 was expected (COD= 1395 mg L1).From the AOPs applied (ozonation, H2O2/UV, Fenton and photo-Fenton), the most promising in terms of COD removal were ozonation

and photo-Fenton, allowing the almost degradation of amoxicillin after60 min. Again, the initial concentrations of amoxicillin were far fromthe low concentrations expected to appear in environment. In allthese works, the amoxicillin removal is evaluated by COD or TOC (total

organic carbon) readings. However, the detection limits in thesemethods are still high (about 110mg L1), when compared with thelevels found in environmental matrices (at ppb levels). Therefore, suchanalytical methods were not sensitive enough to be used in real

environmental matrices. Due to high antibiotic concentration, this typeof approach is often used to treat the contamination at the source,avoiding possible matrix effects, which negatively affect the oxidationprocesses performance. Nevertheless, in some of the studies mentioned

above, the initial antibiotic concentration remains too high, even to actdirectly on the contamination source.

The authors could not found in literature studies for amoxicillinlevels as those observed in water matrices, or studies in which the

experimental design is applied for the process optimisation ofamoxicillin degradation. Thus, the present study pretends toimplement a method with specic measurements of amoxicillin(not equivalent COD or TOC) at g L1 levels applied to Fenton

degradation of amoxicillin. The optimisation of variables thatinuence the Fenton degradation was performed applying experi-

mental design.

2. Materials and methods

2.1. Chemicals and standards

Amoxicillin, 900 g per mg (ref. A8523), was obtained fromSigma-Aldrich (St. Louis,USA).An aqueous stock solutionof 56 mg L1

of amoxicillin was prepared and from this, calibration standards with

concentrations between 25 and 500g L1 of amoxicillin were

prepared in distilledwater. From the stock solution,a control standardof450 g L1 was prepared weekly. Hydrogen peroxide solution (30%)in stable form was purchased from Merck (Darmstadt, Germany) and

was used to prepare aqueous stock solution 2 g L1. Iron (II) sulfateheptahydrate (Merck) was used to prepare 0.2 g L1 stock solution inacidic medium. The pH of the antibiotic solutions was adjusted byusing H2SO4or NaOH 1 M (Merck) until pH= 3.5 (nal condition). To

stop the Fenton's reaction sodium sulte anhydrous from Merck(Darmstadt, Germany) was applied. Acetonitrile HPLC grade fromPanreac (Barcelona, Spain) and o-phosphoric acid 85% p.a. fromPronalab (Lisbon, Portugal) were utilized. All solutions were preparedwith distilled water, previously ltered through 0.45 m nylon lter

membranes (Supelco, Sigma-Aldrich, Sintra, Portugal).

2.2. Analytical method

Antibiotics concentration was determined by HPLC equipped with apump L-7100, an autosampler L-7250 and a diode array detector (DAD)L-7450 from Merck Hitachi LaChrom (Darmstadt, Germany). Data wasacquired and processed by HSM D-7000, version 3.1, software.

Chromatographic analysis of amoxicillin was performed using areversed-phase (RP) C18 column, type Purospher STAR (250 mm4 mm i.d., particle size: 5 m), keptat room temperature in combinationwith a guard column (4 mm 4 mm i.d.) also Purospher STAR. The

mobile phase was composed of acetonitrile (5%) ando-phosphoric acid(pH= 2.5) in water (95%), running in isocratic conditions. Theow ratewas 0.8 mL min1 and the injection volume was 100 L. The scanningwavelength range was 220400 nm and the UV absorption of

amoxicillin was measured at 230 nm. This method was based in a

previous one, already described byTeixeira et al. (2008).The retention time of amoxicillin was 15.00.5 min. A linearity

range from 25 to 500 g L1 (eight calibration points) was achieved,

with a coefcient of determination of 0.999, and a detection andquantication limits of 11 and 36 g L1, respectively (calculated fromthe calibration curve parameters). Other main validation parameterswere: intermediate precision 0.38.0% and repeatability 0.83.8%

(expressed as coefcient of variation evaluated at 3 concentrationlevels) and accuracy 98.8104.9% (expressed as percentage of recoveryof spiked solutions at 3 concentrationlevels). Theuncertainty associatedwith analytical method was evaluated according to the proposed

procedure in the EURACHEM/CITAC guide (Ellisson et al., 2000). Theglobal uncertainty ranged from 2 to 21%, whenconcentrations decreasefrom 500 g L1 down to the detection limit.

2.3. Experimental procedure

All experiments were performed in a batch thermostatic reactor

with a capacity of 250 mL (inner diameter: 7.5 cm, height: 11.5 cm).The outside of the reactor was covered with aluminium foil to protectfrom light and an inlet for temperature measuring was placed on thetop of the reactor. Uniform mixing was provided using a magnetic

stirrer and a thermostatic bath was used in order to keep thetemperature constant. For every experiment, the reactor was lledwith 100 mL of amoxicillin aqueous solution at 450 g L1. Then, thepH was adjusted with H2SO4or NaOH solution. The required amount

of iron (II) sulphate was added to the reactor and the reaction beganwith the addition of a certain quantity of H2O2solution. Aliquots were

withdrawn from the reactor at selected intervals for liquid

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chromatographic analysis. To ensure the stop of Fenton's reaction, anexcess of sodium sulphite anhydrous was added.

2.4. Experimental design and process optimisation

As mentioned above, statistical experiment design and responsesurface methodology (RSM) are useful tools to verify the effects of

different factors and of their interactions in the process response

within a certain range and with a minimum number of experiences.The optimisation procedure involves studying the response of thestatistically design experiments, estimating the coefcients by tting

the experimental data to the response functions, predicting theresponse of the tted model and checking the adequacy of the model.

The application of response surface methodology permitted toestablish a mathematical relationship between dependent andindependent variables and the process optimisation. Therefore,

experimental data weretted to a second-order polynomial equationas follows (Arslan-Alaton et al., 2009; Rodrigues et al., 2009):

Y= b0 + n

ibixi +

n

ibiix

2i +

n

j N i

n

i = 1bijxixj 2

In Eq.(2),Yrefers to the response, xito the codied independentvariables,b0 is the interception term, bi determines the inuence ofthe variable i in the response (linear term), bii is a parameter that

determines the shape of the curve (quadratic effect) and bijcorresponds to the effect of the interaction among variable i and j.To convert the natural variables (Xi) in dimensionless codied values(xi) it is necessary to use the Eq. (3):

xi = XiX0 =X 3

where X0 denotes the value of variable i in the centre of the domain

(xi=0) andXrefers to the difference of thatvariable betweenxi=+1andxi= 0.

The statistical analysis proceeds with an ANOVA test, which

evaluates the adequacy of the model tting. The variations that occurin the response can be attributed to the model and are not due torandom errors if the F-ratio is higher than the Fisher's F-value andconsequently if the F-probability is less than 0.05 (for 95% condence

level). To determine which parameters and/or interactions havestatistical meaning, the Student's t-test was used. If t-probability issmaller than 0.05, the parameter or interaction are signicant. ThePareto analysis also provides information on the variables signicance

and on the percentage effect of each factor on the response (Pi),according to Eq.(4):

Pi = b2i

=

n

ibi

! 100 4

In this study, a central composite factorial design (CCD) was

employed to optimise the reaction parameters, considering C/C 0after30 min as the response. The choice of this treatment time was doneaccording to the results obtained in the preliminary assays. The effectof initial concentration of H2O2(X1), Fe

2+ (X2) and temperature (X3)

was assessed applying response surface methodology. In order todevelop this study, sixteen experiments were performed, eight ofwhich corresponded to the factorial design, six to the expansions andtwo were central points to check repeatability. Values of the

independent variables and their variation limits were determinedbased on the preliminary runs as well as on the literature ( Table 1).Experimental data analysis was developed using the JMP 5.0.1software and the statistical validation was achieved by ANOVA test

at 95% condence level.

3. Results and discussion

3.1. Preliminary runs

In the Fenton process the production of HO radicals depends ofseveral factors such as pH, concentration of H2O2 and Fe

2+,

temperature and treatment time. The application of experimentaldesign to four or more parameters would conduct to a larger numberof experiments; therefore some preliminary runs were performed toachieve a suitable treatment time and initial pH. These experiences

and literature review also constitute a starting point to set ranges forthe study variables.

3.1.1. Effect of the pHThe pH value affects the generation of hydroxyl radicals and

consequently, the oxidation efciency. In this study, different pHvalues were tested in the range of 2.9 to 6.5. The choice of this range

was made in accordance with the pKa's values of the amoxicillin(Fig. 1). In order to correctly perform the quantication by HPLC-DAD,it was necessary to ensure that amoxicillin is present in the same formin all assays (in the form ofCOO/NH3

+).

Experiments showed that the maximum degradation was reachedfor a pH of 3.54.5 (Fig. 2), as mentioned in the literature (Oliveiraet al., 2006). For pH values below 3, the Fenton's reaction (Eq.(1)) isseverely affected, causing the reduction of hydroxyl radicals in

solution. Hydrogen peroxide is more stable at low pH, due to theformation of oxonium ion (H3O2

+), which improves its stability and,

Fig. 2. Effect of pH in the degradation of amoxicillin (T=40 C, CAMOX =450g L1,

CH2O2 =2.35 mg L1

, CFe2 += 95 g L1

).

Fig. 1.Chemical structure of amoxicillin and pKa values.

Table 1

Experimental range and levels of process variables.

Parameter Coded levels (xi)

1.682 1 0 1 1.682

[H2O2] (mg L1) 0.42 1.2 2.35 3.5 4.28

[Fe2+] (g L1) 30 95 190 285 350

T (C) 20 30 45 60 70

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presumably, greatly reduces its reactivity with ferrous ion (Elmollaand Chaudhuri, 2009a,b). Some authors also suggest that at low pHthe amount of soluble iron Fe3+ decreases, inhibiting the radical OH

formation. On the other hand, at pH= 12 an inhibition in thehydroxyl radicals formation exists, due to H+ ions scavenging (Lucasand Peres, 2006):

HO

H

eH2O 5

For pH values above 4, the precipitation of iron hydroxides occurs,inhibiting both the regeneration of the active specie Fe2+ and the

formation of hydroxyl radicals (El-Desoky et al., 2010). Therefore, inthe subsequent assays the pH was set to 3.5.

3.1.2. Effect of the H2O2concentrationThe amount of hydrogen peroxide is another parameter that

inuences the Fenton process. The results shown in Fig. 3 demon-

strated that in the range tested the degradation of amoxicillin wasslightly enhanced when the H2O2 dosage increased from 0.60 to

2.35 mg L

1. Inthe samegure it is possible to observe that forhigherconcentrations, the performance of the reaction oxidation remains

practically unchanged (the only difference is the higher initialreaction rates for higher H2O2 concentrations). This fact has alreadybeen mentioned in the literature by several authors. The increasing ofthe H2O2 concentration may promote an inhibitory effect by the

hydroxyl radicals scavenging (Eq.(6)) and the formation of anotherradical (HO2

), which has an oxidation potential considerably smallerthan HO (Arslan-Alaton et al., 2009).

HO H2O2HO

2H2O 6

The peroxide concentration was subsequently studied in the DoE,in the range between 0.42 and 4.28 mg L1.

3.1.3. Effect of the Fe2+ concentration

In this work, the study of ferrous ion concentration had also beenconsidered for DoE. Fig. 4 shows the relationship between thedegradation of amoxicillin and the initial concentration of ferrousion. The Fe2+ acts in the decomposition of hydrogen peroxide as a

catalytic agent. In the studied range it was veried that if itsconcentration increases, the degradation of amoxicillin is alsoincreased. Above 120 min, using any concentration in this range, atotal removal was achieved. It is important to notice that in Portugal,

according to the national Decree no. 236/98, the emissions levelsof iron in the discharge of wastewaters cannot exceed 2 mg L1. TheFe2+ concentrations studied are far from this value.

3.1.4. Effect of the temperatureTo evaluate the effect of temperature further assays were

performed. Accordingly with Fig. 5 the reaction rate of amoxicillindegradation was increased by increasing the temperature. This could

be explained by the Arrhenius law, since the kinetic constant raises

with the temperature.

3.1.5. Effect of the treatment timeIn order to determine the required reaction time for maximum

amoxicillin removal, the results obtained in these preliminary assayswere carefully analysed. As can be veried, if low amounts of reagents

were used, the time required to completely degrade amoxicillinwould be too high. The opposite situation also occurs. Therefore, it is

Table 2

Experimental design and response based on experimental runs and predicted values

proposed by central composite design.

Run X1 X2 X3 C/C0, 30 min C/C0, 30 min

[H2O2] (mg L1) [Fe2+] (g L1) T (C) Experimental PredictedCI

1 2.35 190 45 0.19 0.25 0.092 1.20 95 30 0.43 0.43 0.09

3 1.20 95 60 n.d. 0.04 0.09

4 0.42 190 45 0.17 0.15 0.09

5 1.20 285 60 n.d 0.00 0.09

6 3.50 95 60 0.21 0.23 0.09

7 2.35 350 45 0.08 0.06 0.09

8 1.20 285 30 0.17 0.20 0.09

9 3.50 285 60 n.d. 0.04 0.09

10 2.35 190 45 0.29 0.25 0.09

11 2.35 30 45 0.47 0.42 0.0912 3.50 285 30 n.d. 0.00 0.09

13 4.28 190 45 0.19 0.15 0.09

14 3.50 95 30 0.33 0.38 0.09

15 2.35 190 20 0.29 0.26 0.09

16 2.35 190 70 n.d. 0.00 0.09

n.d.

undetectable; CI

condence interval (1.96standard deviation).

Fig. 5. Effect of temperature in thedegradationof amoxicillin (pH= 3.5,C AMOX =450 g

L1, CH2O2 =2.35 mg L1, CFe2 += 95 g L

1).

Fig. 4. Effect of the ferrous ion concentration in the degradation of amoxicillin

(pH=3.5, T=40 C, CAMOX =450 g L1

, CH2O2 =2.35 mg L1

).

Fig. 3.Effect of the peroxide hydrogen concentration in the degradation of amoxicillin

(pH=3.5, T=40 C, CAMOX =450 g L1, CFe2 += 95 g L

1).

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necessary to assume a compromise between the amount of reagentsand the treatment time. For that reason the treatment time was set to30 min.

3.2. Experimental design (CCD Central Composite Design)

After the exploratory runs, the experiments for the construction ofthe experimental design were performed according to Table 2. As

mentioned above, two assays were performed in the centre of thecubic domain (run 1 and 10). For such replicates the dimensionlessconcentration (C/C0) after 30 min of reaction uctuates between 0.19and 0.29, which corresponds to a standard deviation of 0.07, an

acceptable value in this kind of experiments.The JMP software was used to calculate the coefcients of the

second-order tting equation and the model suitability was testedusing the ANOVA test. Therefore, the second-order polynomialequation should be expressed by:

Y= 0:2450:002x10:107x20:088x30:035x1x2

+ 0:06x1x3+ 0:048x2x30:034x210:0004x

220:046x

23

7

wherex1 is the hydrogen peroxide concentration, x2 the ferrous ionconcentration andx3the reaction temperature.

It can be seen from Eq. (7) that the response decreases with thehydrogen peroxide concentration, ferrous ion concentration andtemperature (coefcients with negative signals). The comparisonbetween the model prediction and the experimental response is given

in the parity plot ofFig. 6. As can be seen, the values predicted by thesecond-order model agree very reasonably with the experimentaldata. InTable 3are summarized the analysis of variance (ANOVA) forthe model. In this table, the mean squares were obtained dividing the

sum of squares for each variation source by their degrees of freedom.The model F-ratio was calculated as the ratio of the model meansquare and the residual mean square.

The results show that the variations that occur in the response maybe associated to the model, rather than to the experimental error. Suchconclusion is obtained through the comparison of the F-ratio withFisher's F-value (F-ratioNF9,6 =4.1) and conrmed by the F-probability(ProbNFb0.05). The R2 value is also indicative of the polynomial t

quality. After that, the signicant variables and interactions were

identied (bold values atTable 4) by the Student's t-test (Hinkelmannand Kempthorne, 2008). Based on the fact that coefcients aresignicant if the ProbN|t| is smaller than 0.05 (95% condence level), it

is possible to conclude that the ferrous ion concentration (x2), thetemperature (x3, x3

2) and its interaction with hydrogen peroxide andferrous concentration (x1x3,x2x3) are the most signicant variables.

Pareto analysis (Fig. 7) also provided information on the variables

signicance and on the percentage effect of each factor on theresponse. The response (C/C0after 30 min) is affected mainly for theferrous ion concentration (38%) and temperature (26%).

3.3. Response surface and contour plots

Three-dimension response surface and two-dimension contourplots of the model-predicted response were also obtained using the

JMP software, in order to assess the relationship between processvariables and the treatment response.

As can be seen in the Figs. 810, depending on the reactiontemperature, the H2O2 concentration and Fe

2+ concentration, theymay have a positive or negative effect on the amoxicillin degradation.Fig. 8 presents the response surface for different initial H2O2concentrations. It is possible to verify that for the same Fe2+

concentration level, the increase in temperature did not alwaysinuence positively the amoxicillin degradation. However, for thesame temperature level, an increase in the ferrous concentration leads

to increased antibiotic degradation, until C/C0 =0 is reached. Asexpected, the contour plots are distinct for different H2O2concentra-tion levels.For 1.20 mg L1 and 2.35 mgL1 H2O2, a total degradationwas only achieved for high temperatures (TN60 C). For greater

concentration levels of hydrogen peroxide, C/C0 =0 was reached forFe2+ concentrations above 318 g L1 for all the studied tempera-tures. Therefore, it can be concluded that increasing H 2O2concentra-tion, it is possible to achieve total degradation to lower levels of

Table 4

Estimates of the quadratic model (b1 H2O2 concentration coefcient, b2 Fe2+

concentration coefcient,b3 temperature coefcient).

Term Esti mate Standard error t-ratio ProbN|t|

Main effects Intercept 2.45101 0.39101 6.25 0.0008

b1 1.93103 15.1103 0.13 0.9022

b2 1.07101 0.15101 7.08 0.0004

b3 8.84102 1.51102 5.87 0.0011

Interactions b12 3.50102 1.97102 1.78 0.1256

b13 6.00102

1.97102

3.05 0.0225

b23 4.75102 1.97102 2.41 0.0500

b11 3.40102 1.83102 1.86 0.1120

b22 4.55104 1.83104 0.02 0.9810

b33 4.64102 1.83102 2.54 0.0442

Fig. 7. Pareto analysis (b1 H 2O2 concentration coefcient,b 2 Fe2+concentration

coefcient, b3

temperature coefcient).

Table 3

ANOVA test for the response function.

Source Freedom degrees Sum of squares Mean square F-ratio ProbNF

Model 9 3.48 101 3.86102 12.47 0.0031

Error 6 1.86 102 3.10103

Lack oft 5 1.36 102 2.72103

Pure error 1 5.00 103 5.00103

R2

=0.949.

Fig. 6.Parity plotcomparing the removal data for t= 30 min with the model predictions.

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temperatureand/or Fe2+ concentration levels. Fig.9 shows thesurface

plots and response contour for amoxicillin removal (expressed asdimensionless concentrations) as a function of H2O2 concentrationsandtemperature for95, 190and 285 g L1 Fe2+ concentration levels.For the rst two levels of Fe2+ concentration, the highest removal

occurred when H2O2concentration was kept at its minimum and the

temperature at its maximum. Another possibility is the use of elevated

amounts of Fe2+ (285 g L1) and H2O2 (N2.74 mg L1) and low

temperatures (b60 C). Some conclusions obtained until now, may becorroborated by the information of Fig. 10. As expected, totaldegradation at low temperatures only occurs for high Fe2+ and H2O2

amounts.

Fig. 8. Responsesurfaceand contour plots fordimensionlessconcentration of amoxicillin after 30 min of reactionas a functionof initial Fe2+ concentration and reaction temperature

(initial AMOX concentration=450 g L1, (A) [H2O2]=1.20 mg L1, (B) [H2O2]= 2.35 mg L

1, (C) [H2O2]= 3.50 mg L1).

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For real applications in WWTPs, the lowest concentrations andtemperature should be selected in order to minimize the reagents andenergy consumption and consequently the operating costs. Actually,

theFigs. 810show that good performances can also be attained at

lower temperatures and moderate reagents concentrations.

In addition to the studies mentionedabove,the applicability of thisempirical model was tested by some additional experiments, aimingto conrm the prediction ability of the model. As suggested from

Table 5, deviations betweenthe experimental and predicted C/C0 ratio

are slight.

Fig. 9. Responsesurfaceand contourplots fordimensionlessconcentration of amoxicillin after 30 min of reactionas a functionof initial H2O2 concentration and reaction temperature

(initial AMOX concentration=450 g L1, (A) [Fe2+]=95 g L1, (B) [Fe2+]=190g L1, (C) [Fe2+]=285 g L1).

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4. Conclusions

The degradation of amoxicillin by oxidation with Fenton's reagent

depends on several process variables, namely, hydrogen peroxide and

ferrous ion concentration, temperature and pH. Some preliminary

runs were performed, considering the effect of each variableindependently and keeping all other conditions constant (single-

factor-at-a-time approach). These experiments were carried out with

Fig. 10. Response surface and contour plots for dimensionless concentration of amoxicillin after 30 min of reaction as a function of initial H2O2concentration and initial Fe2+

concentration (initial AMOX concentration=450 g L1, (A) T=30 C, (B) T=45 C, (C) T=60 C).

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the purpose of establish the variable ranges. In addition, theyprovided information about the pH value and the treatment time

more appropriate.After that, a central composite design was applied to evaluate the

effect of H2O2 and Fe2+ concentration and temperature in the

amoxicillin degradation (450 g L1) after 30 min, at pH=3.5. Theexperimental data were tted to a second-order model, which

predicted the results reasonably. This experimental design allowedto conclude that among the three variables considered, onlytemperature and catalyst concentration affects statistically theresponse (dimensionless concentration of amoxicillin after 30 min

of reaction). Moreover, it was concluded that the effect of eachindependent variable on the response depends on the value of theother, due to the existence of cross-interactions. Thus, any one of thevariables could positive or negatively affects the amoxicillin degra-dation. The model predicts that total amoxicillin degradation should

be obtained for a wide range of experimental conditions. Therefore,some additional runs (where the response was optimised) wereperformed to test model validity.

The data obtained revealed that Fenton's oxidation is a promising

treatment for amoxicillin degradation.

Acknowledgments

The authors thank the Fundao para a Cincia e a Tecnologia(FCT), Portugal, for nancial support (SFRH/BD/38694/2007).

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Table 5

Model-predicted and experimentally obtainedC/C0, after 30 min forFenton's treatment

of 450g L1 of amoxicillin.

Experimental conditions C/C0experimental

C/C0predicted

[H2O2] (mg L1) [Fe2+] (g L1) T (C) Minimum Maximum

1.20 95 40 0.30 0.25 0.43

2.35 95 40 0.26 0.26 0.44

3.50 95 40 0.54 0.24 0.42

2.35 190 40 n.d. 0.16 0.34

2.35 95 60 n.d. 0.07 0.25

3.50 190 30 0.17 0.10 0.28

n.d. undetectable.


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