pH Interactions in Solar Degradation of Imidacloprid with TiO

mathematical model that best fits the results is the initial reaction rate logarithm as a function ... The degradation reaction rates ... Universidad ...
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Ind. Eng. Chem. Res. 2006, 45, 8900-8908

Fe/TiO2/pH Interactions in Solar Degradation of Imidacloprid with TiO2/SiO2 Photocatalysts at Pilot-Plant Scale Javier Maruga´ n,*,† Marı´a-Jose´ Lo´ pez-Mun˜ oz,† Wolfgang Gernjak,‡ and Sixto Malato‡ Departamento de Tecnologı´a Quı´mica y Ambiental, ESCET, UniVersidad Rey Juan Carlos. C/Tulipa´ n s/n, 28933 Mo´ stoles (Madrid), Spain and Plataforma Solar de Almerı´a-CIEMAT. Carretera Sene´ s km 4, 04200 Tabernas (Almerı´a), Spain

This work focused on determining iron, TiO2, and pH interaction in the photocatalytic oxidation of the pesticide imidacloprid with TiO2/SiO2 catalysts at pilot-plant scale when TiO2/SiO2, iron and H2O2 are combined. Experimental design techniques have been applied to achieve this goal. The response variable in the mathematical model that best fits the results is the initial reaction rate logarithm as a function of the linear effect of the three variables, the interaction between iron dose and pH, and the quadratic effect of pH and titanium dioxide concentration. The analysis of the results shows that the pH is the most influential variable, followed by the initially added dose of iron, and finally TiO2 concentration. The degradation reaction rates observed are the result of the simultaneous combination of a large number of homogeneous and heterogeneous catalytic reactions related to TiO2 and homogeneous photo-Fenton photocatalytic mechanisms. At acid pH, the influence of the semiconductor-based pathway is quantitatively lower than that of degradation by photoFenton. However, above a critical pH, a synergistic effect between iron and TiO2 degradation mechanisms is observed, increasing the overall reaction rate. 1. Introduction Photochemical processes have been shown to be environmentally friendly technologies for the chemical treatment of polluted drinking water and wastewater containing nonbiodegradable compounds,1-4 especially those activated by wavelengths within the solar spectrum.5 Many articles during recent years have reported a large number of chemical pollutants susceptible to being oxidized by solar-driven advanced oxidation processes such as photo-Fenton (Fe/H2O2/UV) and semiconductor photocatalysis (TiO2/UV).6-10 In addition, more recent studies have shown the photoactivity of aqueous iron(III) species (Fe/UV) for the photodegradation of several chemical compounds.11,12 Moreover, some authors have reported the significant influence on TiO2/UV process efficacy of the presence of iron (Fe/TiO2/UV) 13-15 or hydrogen peroxide (TiO2/H2O2/ UV).16-18 Most of the studies described thus far also show a critical influence of the pH of the solution on the degradation performance of the photoreactions, mainly because of the solubility of the iron species,15 the surface charge of titanium dioxide,19 and the solubility of the pollutant.20 Recently, Nogueira et al.. have reported a multivariate analysis of the combined TiO2/photo-Fenton processes.21 However, to the best of our knowledge, there are no reports on the effects of simultaneous interaction of iron, TiO2, and pH in the presence of H2O2 on the efficiency in solar photodegradation processes. On the other hand, it is well-known that commercial application of aqueous TiO2-based systems is usually limited by the need for recovery of the catalyst after the reaction. For this reason, many attempts have been made to develop supported photocatalysts.22,23 Among them, silica-supported TiO2 materials appear to be a promising way to improve the recovery properties of the catalyst while maintaining an acceptable level of photoactivity.24 * To whom correspondence should be addressed. Tel.: +34 91 664 74 66. Fax: +34 91 488 70 68. E-Mail: [email protected]. † Universidad Rey Juan Carlos. ‡ Plataforma Solar de Almerı´a-CIEMAT.

The aim of this work is to determine iron, TiO2, and pH interaction in the photocatalytic oxidation of the pesticide imidacloprid with TiO2/SiO2 catalysts at pilot-plant scale. Experimental design techniques were employed to achieve this goal. A constant concentration of hydrogen peroxide was used, whereas the other variables were studied on five levels, using a statistical approach with a two-level factorial design, center points and star points, following the response surface methodology,25 which had previously been employed for the modeling of photo-Fenton26-28 and TiO2 photocatalytic processes.29,30 The main advantage of these statistical techniques is that the mathematical model allows the optimization of the operating conditions as a function of the several variables, minimizing the number of experiments, which is especially important when working at pilot-plant scale. The use of pilot plants to optimize operating conditions is especially valuable for designing largescale treatment plants, due to the difficulty in scale-up, labscale results could cause wide errors. Another advantage of studying the process under a wide range of conditions is the possibility of optimization for different applications. For the treatment of heavily contaminated industrial wastewater, optimization of a maximum reaction rate is recommendable. However, if the purpose is the reuse of less polluted wastewater, e.g., as drinking water, addition of reagents that increase the salt load in the water must be avoided. Hence, in such case the optimization should be performed at close to neutral pH. 2. Experimental Section 2.1. Synthesis and Characterization of the TiO2/SiO2 Photocatalyst. The silica-supported TiO2 photocatalyst was synthesized using a sol-gel method, following the hydrolysis and condensation of titanium tetraisopropoxide to incorporate 40 wt % TiO2 in the interior of a commercial porous silica (INEOS ES70Y, SBET ) 257 m2g-1). Characterization of the material shows the average size of titanium dioxide nanocrystals is 7.2 nm. More details about the synthesis, characterization

10.1021/ie061033b CCC: $33.50 © 2006 American Chemical Society Published on Web 11/11/2006

Ind. Eng. Chem. Res., Vol. 45, No. 26, 2006 8901 Chart 1. Imidacloprid

Table 1. Values and Code Levels of the Experimental Factors codified level

and photocatalytic activity at laboratory scale can be found elsewhere.31 Although the activity of these silica-supported TiO2 photocatalysts has been found to be lower than that of commercial Degussa P25 TiO2, their improvement of the postreaction recovery stage justifies their use,24 especially in pilot-plant experiments where larger amounts of catalyst must be removed from the water prior to discharge, and for their own reuse. 2.2. Chemicals. Technical-grade imidacloprid (97,9%) was supplied by Bayer Hispania S. A. (Barcelona, Spain), whereas the analytical standard was purchased from Riedel-deHae¨n (Seelze, Germany). Imidacloprid is an N-containing insecticide highly soluble and stable in water. Its photocatalytic degradation is already well-known,32 and has previously been used for comparing photocatalytic processes.33 The chemical formula of this pesticide is shown in Chart 1. Imidacloprid has both pyridyl and imidazolidine rings, which makes it of particular interest for the study of the special behavior of N-containing compounds during photocatalytic treatment. Iron sulfate (FeSO4‚7H2O) and reagent-grade hydrogen peroxide (aqueous solution 30%) were used for the Fenton catalyst. Sulfuric acid and sodium hydroxide were used for pH adjustment. Demineralized water came from the PSA (Plataforma Solar de Almerı´a) distillation plant (conductivity < 10 µS‚cm-1, Cl- ) 0.2-0.3 mg‚L-1, NO3- ) 0.5 mg‚L-1, organic carbon < 0.5 mg‚L-1). 2.3. Analytical Methods. Degradation of imidacloprid was followed by reverse-phase liquid chromatography with UV detection at 270 nm in an HPLC-UV (Hewlett-Packard, series 1100) equipped with a C-18 column (LUNA 5 micron-C18, 3 × 150 mm from Phenomenex). The mobile-phase composition was H2O (pH 3)/acetonitrile at a ratio of 80:20 flowing at 0.5 mL‚min-1. Mineralization was monitored with total organic carbon (TOC) measurements in a Shimadzu-5050A TOC analyzer equipped with a nondispersive infrared detector calibrated with hydrogen potassium phthalate standard solutions. Concentration of H2O2 was followed by iodometric titration, whereas dissolved iron concentration (after filtration through Millex-GN 0.2 µm syringe filters) was determined by its colorimetric reaction with 1,10-phenanthroline after reduction of the iron(III) ions with ascorbic acid. 2.4. Photocatalytic Experiments. Solar photodegradation experiments were carried out in a compound parabolic collector (CPC) pilot plant with a total volume of 35 L and 3.09 m2 irradiated surface located at the Plataforma Solar de Almerı´a (latitude 37°N, longitude 2.4°W). The aqueous suspension flows through the system driven by a recirculation pump connected to a reservoir, the irradiated volume inside the solar collectors being 22 L. A schematic representation of the experimental setup can be found in Kositzi et al..34 Before irradiation begins, the collectors are covered. All the chemicals and the TiO2/SiO2 material are added to the tank and mixed until constant concentration is achieved throughout the system. The pH value is adjusted by addition of sodium hydroxide or sulfuric acid solution. Usually 15 min are enough to ensure the complete

factor

-1.68

-1

0

+1

+1.68

F1: TiO2 concentration (g‚L-1) F2: pH F3: Iron dose (mg‚L-1)

0.0 2.8 0.0

0.06 4.5 0.6

0.15 7.0 1.5

0.24 9.5 2.4

0.30 11.2 3.0

mixture of the reactor volume. Then the cover is removed and samples are taken at preset time intervals. The evolution of the irradiance over time was followed with a global UV radiometer (KIPP & ZONEN, model CUV3) mounted on a platform tilted 37° (the same angle as CPC). Measurements are collected in terms of incident WUV‚m-2, UVG. To compare the results of experiments performed under different irradiation conditions, the accumulated energy (per unit of volume in kJ·L-1) incident on the reactor for each sample taken during the experiment, QUV,n, is calculated with eq 1:

QUV,n ) QUV,n-1 + ∆tn × UVG,n ×

ACPC VTOT

(1)

Where, tn is the experimental time for each sample, UVG,n is the average UVG during ∆tn, ACPC is the collector surface (3.09 m2), and VTOT is the total plant volume (35 L). 2.5. Experimental Design. As previously mentioned, a statistical approach has been employed to determine the interaction of iron dose, TiO2 concentration and pH in the solar photodegradation of imidacloprid. All experiments were carried out at constant initial concentrations of imidacloprid and H2O2 of 85 mg·L-1 and 0.3 g·L-1, respectively. Table 1 summarizes the values and levels of every factor in order to obtain a quadratic model according to the response surface methodology. , are the normalized values of the The codified levels, X codif i variables calculated by eq 2:

) Xcodif i

Xi - Xi0 ∆Xi

(2)

where Xi is the absolute value of variable i at level “codif”, Xi0 ) (X high + X low i i )/2 is the center of the experimental region and - X low ∆Xi ) (X high i i )/2 is the unit step upward or downward from the center to the following value of variable i. The experimental design consisted of the following reactions: (i) eight experiments from the two-level factorial design; (ii) three experiments at the central values of the three factors to determine the experimental error and any possible effects of curvature in the response surface; and (iii) six experiments at the so-called star points, which were carried out due to the nonlinear behavior observed in the results. The star points are calculated by keeping two factors at the central value while the other one is set at two other levels (-R/+R) above and below the maximum and minimum of the factorial design. The value of parameter R ensures that the experimental design is orthogonal (for three factors R ) 1.68).25 This means that these points are located on the axes of the coded variables at the same distance from the central point as the factorial design experiments, which allows the same experimental error to be assumed throughout the experimental domain. As observed in Table 1, TiO2 concentration and initially added dose of iron were chosen so that values at the -R level would be null, which means that, in these experiments, pure photoFenton or TiO2 photocatalysis mechanisms are present. pH

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cross interaction. The curvature effect, c, has therefore, been calculated using eq 4, by which, if the response variable in the experimental range studied is linear, the difference between the mean of the center point replicates, rcp0, and the mean of the N N ri0/N, must experiments of the two-level factorial design, ∑ i)1 be lower than the experimental error calculated, taking into account the total number of experiments t‚s‚x1/N+1/r . The resulting value, c ) -1.42 ( 0.39, clearly indicates the nonlinear nature of the response variable in the range of the three independent variables studied.

(

c ) rcp

Figure 1. Examples of zero-order kinetics fit of imidacloprid photodegradation experiments.

values assigned to the different levels cover a wide range, down to a value close to optimum for photo-Fenton processes at -R.35 3. Results Conversion after 30 min is less than 25% in almost all experiments. Under these conditions, the reaction performance can be described by the initial reaction rate, r0, calculated by fitting the experimental data to a zero order kinetics model. Due to the unavoidable irregular irradiation associated with solar experiments, concentration of the pesticide is plotted against the volumetric UV energy accumulated in the system in kJ‚L-1. For instance, Figure 1 shows the results obtained in the photocatalytic degradation of imidacloprid in three runs with different experimental conditions. Table 2 summarizes the initial reaction rates calculated from the experimental results, to be used as design response variables. Although the experiments are sequentially numbered in order to make the discussion easier, they were carried out in random order to ensure the statistical significance of the results. First of all, the two-level factorial design described by experiments one to eight was completed. Three replications of the center point were also carried out in order to determine the experimental error associated to the measured response variable. According to this approach, the error can be calculated as follows:

error )

s‚t xr

(3)

Where r is the number of center-point experiments, s represents the standard deviation of the center-point replicates and t is the value of the Student’s test parameter for the chosen confidence level and r - 1 degrees of freedom. From the results of experiments 9-11 (see Table 2) an average response of 1.75 mgIMID‚kJ-1 is calculated at the center point, with a standard deviation of 0.135 mgIMID‚kJ-1. The value of the t parameter for a 95% confidence level and two degrees of freedom is 4.303, which leads to an estimated experimental error for the measured response of 0.335 mgIMID‚kJ-1, representing 19% of the average at the center, a relative error that can be assumed when working at pilot-plant scale. First it must be verified that the dependence of the initial reaction rate variable on the three factors studied in the twolevel factorial design experiments (one to eight in Table 2) fits to a linear model, including the effect of every variable and its

0

) x( )

N 0 ∑ i)1 ri -

N

( t‚s‚

1 1 + N r

(4)

As the curvature effect was shown to be significant, an extended experimental design was developed, incorporating “star points” coded as experiment numbers 12-17 (see Table 2). The incorporation of these experiments allows the quadratic effects of every factor to be determined. The expression of the response surface proposed for the description of the initial reaction rate should include nine parameters corresponding to the three single effects, the three binary effects and the three quadratic effects. The possible influence of ternary interactions and XY2-type interactions may be considered negligible in order to maintain a number of parameters with good fit below the system’s degrees of freedom. From the results of fitting, the effects corresponding to [TiO2], [TiO2]‚pH, [TiO2]‚[Fe], [TiO2]2, and [Fe]2 may be considered negligible, as they are below the corresponding error. That means that the results could be fitted to the simplified model shown in eq 5 with only a slight decrease in the correlation coefficient that denoted the goodness of fit (from 0.9286 to 0.9065) and a minor increase in the sum of quadratic residuals (from 9.71 to 12.7). On the other hand, as the equation has fewer

r0 ) (18.7 ( 2.8) - (4.4 ( 0.7)‚pH + (2.0 ( 1.2)‚[Fe] (0.22 ( 0.16)‚pH‚[Fe] + (0.27 ( 0.05)‚(pH)2 (5) parameters, the Fisher value derived from the analysis of variance test (ANOVA) increases considerably, from 10.1 to 29.1, indicating that the fitted model is more plausible. Furthermore, the relative error of the constants remaining in the model is reduced, thus increasing the significance of the corresponding terms. Moreover, the decrease in the number of parameters reduces the estimated error associated with the initial reaction rate predicted. Nevertheless, it should be noticed that the estimated error is very high compared to the experimental error previously calculated (0.335 mgIMID‚kJ-1). In fact, the predicted value for the center point of the experimental design domain is 1.76 ( 1.03 mgIMID‚kJ-1, which represents a relative error of 58%. That means that this model is clearly inadequate for the description of the dependence r0 ) f([TiO2], pH, [Fe]), as shown by the predicted values reported in Table 2. In fact, this model does not predict any influence of [TiO2] on the initial reaction rate, whereas the experimental results seem to indicate the contrary (see for instance experiment numbers five and six). The graphical representation of residuals shows that their distribution is not totally random, especially when plotted against pH (see Figure 2). One of the reasons for such poor results is the wide differences between the initial reaction rates, particularly for slight changes in pH. As may be observed, r0 decreases from 12.37 at pH 2.8 to 1.64-1.90 at pH 7.0. A modification in the response variable is proposed to improve the theoretical predictions of the experimental data.

Ind. Eng. Chem. Res., Vol. 45, No. 26, 2006 8903 Table 2. Experimental Results and Predictions with Eq 5 and Eq 6 Models experiment

variable levels

response variable r0

eq 7 model

eq 10 model

number

code

[TiO2] (g‚L-1)

pH (-)

[Fe] (mg‚L-1)

(mg‚kJ-1)

log r0

(mg‚kJ-1)

residue

log r0

(mg‚kJ-1)

log r0 residue

r0 residue

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

-1/-1/-1 +1/-1/-1 -1/+1/-1 +1/+1/-1 -1/-1/+1 +1/-1/+1 -1/+1/+1 +1/+1/+1 0/0/0 0/0/0 0/0/0 -R/0/0 +R/0/0 0/-R/0 0/+R/0 0/0/-R 0/0/+R

0.06 0.24 0.06 0.24 0.06 0.24 0.06 0.24 0.15 0.15 0.15 0.00 0.30 0.15 0.15 0.15 0.15

4.5 4.5 9.5 9.5 4.5 4.5 9.5 9.5 7.0 7.0 7.0 7.0 7.0 2.8 11.2 7.0 7.0

0.6 0.6 0.6 0.6 2.4 2.4 2.4 2.4 1.5 1.5 1.5 1.5 1.5 1.5 1.5 0.0 3.0

4.13 3.84 1.07 1.37 4.90 7.34 1.37 1.35 1.90 1.71 1.64 1.87 3.01 12.4 1.25 1.50 2.02

0.616 0.585 0.031 0.135 0.690 0.865 0.137 0.129 0.278 0.214 0.232 0.271 0.478 1.092 0.097 0.177 0.306

5.00 5.00 1.05 1.05 6.79 6.79 0.85 0.85 1.76 1.76 1.76 1.76 1.76 10.61 2.30 1.10 2.43 χ2 )

0.87 1.16 -0.02 -0.31 1.89 -0.54 -0.52 -0.50 -0.14 0.05 0.13 -0.10 -1.25 -1.76 1.05 -0.41 0.41 12.7

0.579 0.660 0.057 0.138 0.741 0.822 0.091 0.172 0.237 0.237 0.237 0.285 0.442 1.074 0.090 0.155 0.319

3.79 4.57 1.14 1.37 5.51 6.64 1.23 1.49 1.72 1.72 1.72 1.93 2.76 11.9 1.23 1.43 2.09 χ2 )

-0.0373 0.0751 0.0258 0.0025 0.0508 -0.0435 -0.0457 0.0435 -0.0414 0.0226 0.0046 0.0146 -0.0369 -0.0183 -0.0069 -0.0229 0.0135 0.0211

-0.337 0.728 0.070 0.003 0.611 -0.703 -0.135 0.137 -0.176 0.014 0.084 0.059 -0.246 -0.541 -0.020 -0.072 0.066 1.96

As the differences in r0 are over 10, a logarithmic response might lead to a better fit of the response surface without losing any degree of freedom. Similarly, the possible linearity of dependence of the initial reaction rate on the three variables studied must also be verified. The curvature effect calculated, c ) -0.1573 ( 0.10, once again indicates the nonlinear nature of the response variable in the experimental domain studied. Consequently, a nonlinear response surface including the quadratic effects was proposed. According to the fit results, the effects corresponding to [TiO2]‚pH, [TiO2]‚Fe, and [Fe]2 could be considered negligible, as their values are below their corresponding error. Conse-

r0

r0

quently, the results could be fitted to the simplified model shown in eq 6.

log r0 ) (1.83 ( 0.133) - (1.05 ( 0.458)‚[TiO2] (0.370 ( 0.032)‚pH + (0.154 ( 0.052)‚[Fe] (0.014 ( 0.007)‚pH‚[Fe] + (4.86 ( 1.42)‚([TiO2])2 + (0.020 ( 0.002) × (pH)2 (6) The reduction in the number of parameters slightly increases the error of fit in the sum of quadratic residuals (from 0.0195 to 0.0211), although the correlation coefficient remains high

Figure 2. Analysis of residuals from fitting with eq 5 model. (a) Calculated vs experimental. (b) Residuals against TiO2 concentration; (c) Residuals against pH; (d) Residuals against iron dose.

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Table 3. Main Reactions in the TiO2/ Fe/ H2O2/UV System TiO2 + hν f e- + h+ h+ + OH- f •OH e- + O2 f •O2e- + h+ f heat e- + H2O2 f •OH + OHFe2 + + H2O2 f Fe3+ + •OH + OHFe3 + + H2O2 f Fe2+ + •HO2 + H+ [Fe3 + L-] + hν f [Fe3+ L-]* f Fe2+ + •L Fe3+ + e- f Fe2+

(R1) (R2) (R3) (R4) (R5) (R6) (R7) (R8) (R9)

(from 0.9866 to 0.9855). On the other hand, once again, the reduction in the number of model parameters significantly increases the Fisher value (from 57.1 to 113.0). Additionally, a decrease is produced in the response error, to lower than the experimental error (0.046 vs 0.082). The predicted value for log r0 at the central point of the experimental design domain is 0.237 ( 0.046, which represents a relative error of 19%. The transformation of this log r0 into the corresponding initial reaction rate r0 gives 1.726 + 0.193/-0.174 mgIMID‚kJ-1, resulting in a relative error of +11%/-10%, much lower than the 58% obtained from using r0 as response variable directly. Table 3 reports the predicted values for the initial reaction rate of every experiment in terms of both r0 and log r0. Notice that the residuals calculated in terms of r0 are much lower when using the logarithmic response, leading to a χ2 value of 1.96 in comparison with the value of 12.7 obtained with eq 5. The graphical representation of the residuals (Figure 3) denotes that their distribution is almost random, and that their absolute values are much lower than in Figure 2, especially for pH. From the results presented above it can be concluded that the response surface that best fits the experimental dependence of the initial reaction rate is as expressed in eq 6. The three-

dimensional plots of the response surfaces at constant value of one of the independent variables are displayed in Figures 4, 5, and 6, together with the corresponding contour plots (curves of constant response). The fixed variable was selected to be the experimental -1, 0, and +1 coded values, which permits simultaneous inclusion of the experimental data graphic analysis of the model fit. Although the response surfaces have been displayed in the complete extended domain of the factors, from coded -R to +R, only the points inside the spherical experimental domain could be predicted by eq 6 with the response error calculated by fitting. Consequently, the experimental sphere was projected over the response surface to mark the area in which the model could be properly applied. The extrapolation of the model outside this border could lead to very high estimation errors even to the point of meaningless results. 4. Discussion 4.1. Chemistry of the TiO2/Fe/H2O2/UV System. The system under study is of a rather complex nature, as it combines TiO2 photocatalysis and the photoassisted Fenton reaction in the same reactor. Consequently, a large number of homogeneous and heterogeneous catalytic reactions are taking place simultaneously, as summarized in Table 3. First, the two systems are considered separately and then the effects that arise from their combination are analyzed. The initial reaction in TiO2 heterogeneous photocatalysis is the charge separation which takes place in the semiconductor particle, promoting an electron from the valence band to the conduction band when photons with higher energy than the band gap of the material, Eg, are incident on it, (R1). For TiO2 Eg is around 3.2 eV, corresponding to a wavelength of approximately

Figure 3. Analysis of residuals from fitting with eq 6 model. (a) Calculated vs experimental. (b) Residuals against TiO2 concentration; (c) Residuals against pH; (d) Residuals against iron dose.

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390 nm (exact value depends on crystalline phase, crystallite size, etc.), i.e., of the photons available in the solar spectrum, only those in the UV-A and UV-B bands can promote the reaction. The positively charged electron hole remaining after charge separation is a powerful oxidant which can oxidize hydroxyl ions adsorbed on the surface to generate uncharged hydroxyl radicals, which can desorb from the surface (R2). It is commonly assumed that pollutant oxidation takes place on the surface or at least in its immediate vicinity. Hydroxyl radicals, as well as the electron hole itself, can then oxidize the pollutant. The electron promoted to the conduction band can reduce an electron acceptor, usually dissolved oxygen (R3). This reaction has been identified as the rate-limiting step in the overall heterogeneous TiO2 photocatalysis kinetics responsible for the process’s low quantum efficiency because of the high recombination rate of electrons and electron holes (R4). the addition of electron acceptors, such as H2O236 (R5) and peroxodisulfate,37 has been proposed to improve the quantum efficiency, thereby reducing the extent of recombination, and additional oxidizing species are generated. In the presence of dissolved iron and H2O2, Fenton and Fenton-like reactions, (R6) and (R7), respectively, constitute a catalytic iron redox cycle leading to the decomposition of H2O2 and the generation of hydroxyl and peroxyl radicals. Upon irradiation, photoreduction of ferric iron complexes also takes place (R8). Depending on the ligand (hydroxyl ions, organic acids, etc.) this ligand-to-metal charge-transfer reaction can lead to the formation of hydroxyl radicals or to the direct oxidation of the ligand. Although reactions (R6) to (R8) are applicable to dissolved iron, equivalent reactions take place on iron hydroxides and iron oxides, usually at lower reaction rates than in the homogeneous phase. Feng and Nansheng38 presented an overview of these processes and the relevant literature. Iron precipitation and aging of the precipitate, i.e., gradual removal of crystal water and crystallization, is a slow, complex process.39 As they proceed, the iron precipitate becomes more stable and loses part of its reactivity. Thus Fenton and photo-Fenton processes may also take place at pH where iron precipitates by using soluble iron salts when the rather freshly precipitated iron hydroxides are still very unstable and therefore highly reactive.20 By reaction (R9), ferric ion in the TiO2/photo-Fenton combined system can easily be adsorbed on the TiO2 surface,15,40 reduced by a conduction band electron, and subsequently be desorbed as ferrous ion. Therefore, in addition to reactions (R7) and (R8), an alternative ferric iron reduction pathway at higher pH can boost the catalytic iron cycle and hydroxyl radical generation. Ferric ion also improves charge separation on the TiO2 surface by capturing the conduction band electron, stabilizing the valence band electron hole, and reducing the recombination rate.15 Consequently, TiO2/Fe combination is synergistic, increasing the activity of both TiO2 and Fenton hydroxyl radical generation mechanisms. Summarizing, the fate of the iron species can be described as a continuous process of oxidation/reduction and leaching/ precipitation, the extent of which is strongly dependent on the pH. 4.2. pH-[Fe] Interaction at Constant [TiO2]. As shown in Figure 4, the initial reaction rate is higher as the iron dose increases and pH decreases at constant TiO2 concentration. The effect of iron is more pronounced at low pH, which is in agreement with the pure photo-Fenton Fe/UV/H2O2 results usually reported in the literature. This trend is observed in all

Figure 4. 3-D graphical representation of the response surface at the TiO2 concentration -1, 0, and +1 code levels; inset: corresponding contour plots. b represents the experimental points. The circle in the inset plot and the curve over the 3-D surface represent the projection of the experimental domain in which the model could be applied.

the TiO2 levels, with slightly higher reaction rates as the TiO2 concentration increases. Consequently, it can be said that the presence of TiO2 increases the activity of the pure photo-Fenton mechanism. 4.3. [TiO2]-[Fe] Interaction at Constant pH. The model clearly predicts a higher reaction rate as the total iron amount present increases at constant pH (Figure 5). However, the dependence on TiO2 concentration shows a minimum, with

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Figure 5. 3-D graphical representation of the response surface at the pH -1, 0, and +1 code levels; inset: corresponding contour plots. b represents the experimental points. The circle in the inset plot and the curve over the 3-D surface represents the projection of the experimental domain in which the model could be applied.

slightly higher values at 0.05 g‚L-1 and 0.25 g‚L-1 than at 0.15 g‚L-1. Yet, the dependence on TiO2 is very weak, especially at high pH. The same trend is observed at different pH, although as the pH increases, less activity is clearly achieved. This effect is more pronounced when pH is increased from 4.5 to 7.0, and results similar to these are obtained for pH values of 7.0 and 9.5.

These results do not match a pure TiO2 photocatalytic mechanism, in which more activity would be expected as the semiconductor concentration increases. On the other hand, the influence of the iron content is much stronger than the weak dependence on TiO2, what seems to point to the photo-Fenton mechanism as mainly responsible for degradation, reducing the significance of the TiO2 or TiO2/Fe degradation mechanisms. On the other hand, the minimum observed in dependence of the initial reaction rate on the titanium dioxide concentration suggests the existence of a compromise between two opposite effects: a beneficial effect due to the semiconductor-assisted photocatalytic degradation and a detrimental effect on the homogeneous photo-Fenton degradation produced by competition with iron ions for photons. When the TiO2 concentration is increased from 0.05 g‚L-1 to 0.15 g‚L-1, it seems that the detrimental effect is more important, whereas at 0.25 g‚L-1, the increase in the extension of the UV/TiO2 and/or UV/TiO2/ Fe degradation mechanism compensates for the detrimental effect on the homogeneous photo-Fenton reaction, increasing the global degradation rate. This beneficial effect could also be produced by acceleration of the homogeneous Fenton catalytic cycle induced by redox processes involving iron ions on the TiO2 surface. Finally, it should be remarked that in all cases, and not only the experiment at pH 2.8, measurements of dissolved iron showed that most of the iron content is separated from the suspension when filtered through a 0.2 µm filter. That means that iron remains active during the heterogeneous phase, either as iron hydroxides or adsorbed on the titania-silica surface. However, the activity of soluble iron is much higher than that of the heterogeneous species, which explains the strong decrease in the degradation reaction rate as pH increases. 4.4. [TiO2]-pH Interaction at Constant [Fe]. As for the [TiO2]-pH interaction shown in Figure 6, once again, a clear increase in the initial reaction rate is observed as the pH decreases at constant iron dose, whereas a minimum appears when analyzing the dependence on TiO2 concentration. Similar trends are observed at different [Fe] levels, with higher initial reaction rates as the iron content increases. These results confirm the proposed competition between the homogeneous photo-Fenton and the semiconductor assisted photocatalytic degradation mechanisms, especially at low pH. Consequently, the expected synergistic effect of the Fe/TiO2 combination predicted from the system chemistry only seems to occur at nonacidic pH, when the homogeneous Fenton reaction becomes less important. In acidic solutions, the photoFenton pathway is so active that the presence of TiO2, instead of increasing the activity, produces a detrimental effect attributed to the competition for photons between reactions (R1) and (R8). 4.5. Calculation of the Highest Reaction Rate. The highest initial reaction rate may be found by applying the Newton optimizing algorithm inside the spherical experimental domain studied. According to the model represented by eq 6, the highest value is obtained at

[TiO2] ) 0.16 g‚L-1 (coded value: 0.1) pH ) 2.84 (coded value: -1.68) [Fe] ) 1.7 mg‚L-1 (coded value: 0.24)

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of heavily contaminated industrial wastewater, further work outside the experimental scope covered in this work would be required to achieve the overall optimization of pilot plant operation, probably to find that the optimal pH is that of a pure photon-Fenton process.25 However, for the treatment of less polluted water, e.g., pesticide contaminated groundwater, in which an increase in the salt load must be avoided, the model presented enables the reaction rate to be determined for operating conditions at a pH closer to neutral. 5. Conclusions

Figure 6. 3-D graphical representation of the response surface at the iron dose -1, 0, and +1 code levels; inset: corresponding contour plots. b represents the experimental points. The circle in the inset plot and the curve over the 3-D surface represents the projection of the experimental domain in which the model could be applied.

Predicted r° ) 12.3 mgIMID‚kJ-1 However, as may be observed from the response surfaces represented in Figure 4, this point does not correspond to a maximum. In fact, the extrapolation of the model outside the experimental domain studied predicts higher reaction rates for lower pH, and higher TiO2 and iron dose. Consequently, if the application permits the use of a lower pH, e.g., the treatment

It has been pointed out that the correct selection or modification of the response variable is a key to good modeling of the experimental data derived from multivariate analysis. This work has shown that, despite the inclusion of nonlinear quadratic terms in the response surface equation, poor fit could be obtained if the response variable shows values with different order of magnitude. In this case, the change to a logarithmic response variable produce an strong improvement in the fitting results, leading to more plausible models with a lower number of parameters. Concerning the physicochemical significance of the model, pH is clearly the variable most influencing the reaction rate, followed by the initially added dose of iron and finally TiO2 concentration. The observed imidacloprid solar photodegradation reaction rates are the result of the simultaneous combination of a large number of homogeneous and heterogeneous catalytic reactions related to TiO2 and homogeneous photo-Fenton photocatalytic mechanisms. Although the influence of semiconductor photocatalysis is quantitatively lower than photoFenton-based degradation, the presence of a minimum in activity with TiO2 must be remarked. In fact, it seems that the initial reaction rate decreases as the titania content increases, due to a detrimental effect produced by competition for photons. However, above a critical value at which the semiconductor photocatalytic contribution begins to be significant, the presence of titania increases the reaction rate. This beneficial effect could be due exclusively to direct photocatalytic degradation of the pesticide, or to beneficial titania/iron interactions improving the iron redox cycle of the photo-Fenton catalytic mechanism. The results clearly point out that, within the experimental domain studied, the maximum degradation rate can be achieved at pH values below 3, and for applications in which these conditions are viable, addition of TiO2 is not recommended, as it produced a detrimental effect on the faster photo-Fenton based degradation. On the other hand, it must be remarked that at neutral pH values there is a synergistic combination of iron and TiO2 degradation mechanisms. Consequently, for applications in which acid pH must be avoided, the combined system is recommended, as it will reduce the amount of solid catalyst required or increase the throughput in the plant, as desired. The initially applied doses of iron are low enough to permit discharge into any body of water or biological treatment. Only in the case of intended reuse as drinking water must the iron be retained. Acknowledgment Financial support for this work was provided by “Ministerio de Ciencia y Tecnologı´a” through the project PPQ2003-3984. Thanks are due to the whole Solar Chemistry Team at the Plataforma Solar de Almerı´a for their help during the experiments.

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Literature Cited (1) Legrini, O.; Oliveros, E.; Braun, A. M. Photochemical Processes for Water Treatment. Chem. ReV. 1993, 93, 671. (2) The AOT Handbook; Calgon Carbon Oxidation Technologies: Ontario, 1996. (3) US/EPA Handbook of AdVanced Photochemical Oxidation Processes, EPA/625/R-98/004; U.S. Government Printing Office: Washington, DC, 1998. (4) AdVanced Oxidation Processes for Water and Wastewater Treatment; Parsons, S., Ed.; IWA Publishing: London, 2004. (5) Mun˜oz, I.; Rieradevall, J.; Torrades, F.; Peral, J.; Dome´nech, X. Environmental Assessment of Different Solar Driven Advanced Oxidation Processes. Sol. Energy 2005, 79, 369. (6) Gogate, P. R.; Pandit, A. B. A Review of Comparative Technologies for Wastewater Treatment. I: Oxidation Technologies at Ambient Conditions. AdV. EnViron. Res. 2004, 8, 501. (7) Gogate, P. R.; Pandit, A. B. A Review of Comparative Technologies for Wastewater Treatment. II: Hybrid Methods. AdV. EnViron. Res. 2004, 8, 553. (8) Konstantinou, I. K.; Albanis, T. A. Photocatalytic Transformation of Pesticides in Aqueous Titanium Dioxide Suspensions Using Artificial and Solar Light: Intermediates and Degradation Pathways. Appl. Catal., B 2003, 42, 319. (9) Pera-Titus, M.; Garcı´a-Molina, V.; Ban˜os, M. A.; Gime´nez, J.; Esplugas S. Degradation of Chlorophenols by Means of Advanced Oxidation Processes: A General Review. Appl. Catal., B 2004, 47, 219. (10) Malato, S.; Blanco, J.; Vidal, A.; Richter, C. Photocatalysis with Solar Energy at a Pilot-Plant Scale: An Overview. Appl. Catal., B 2002, 37, 1. (11) Mailhot, G.; Sarakha, M.; Lavedrine, B.; Ca´ceres, J.; Malato, S. Fe(III)-Solar Light Induced Degradation of Diethyl Phthalate (DEP) in Aqueous Solutions. Chemosphere 2002, 49, 525. (12) Mı`×f0ta´nkova´, H.; Mailhot, G.; Pilichowski, J. F.; Kry´sa, J.; Jirkovsky´, J.; Bolte, M.; Mineralisation of Monuron Photoinduced by Fe(III) in Aqueous Solution. Chemosphere 2004, 57, 1307. (13) Sclafani, A.; Palmisano, L.; Davı`, E. Photocatalytic Degradation of Phenol in Aqueous Polycrystalline TiO2 Dispersions: the Influence of Fe3+, Fe2+ and Ag+ on the Reaction Rate. J. Photochem. Photobiol. A 1991, 56, 113. (14) Piera, E.; Tejedor-Tejedor, M. I.; Zorn, M. E.; Anderson, M. A. Relationship Concerning the Nature and Concentration of Fe(III) Species on the Surface of TiO2 Particles and Photocatalytic Activity of the Catalyst. Appl. Catal., B 2003, 46, 671. (15) Mı`×f0ta´nkova´, H.; Mailhot, G.; Jirkovsky´, J.; Kry´sa, J.; Bolte, M. Mechanistic Approach of the Combined (iron-TiO2) Photocatalytic System for the Degradation of Pollutants in Aqueous Solution: an Attempt of Rationalisation. Appl. Catal., B 2005, 57, 257. (16) Augugliaro, V.; Ga´lvez, J. B.; Va´zquez, J. C.; Lo´pez, E. G.; Loddo, V.; Mun˜oz M. J. L.; Rodrı´guez S. M.; Marcı`, G.; Palmisano, L.; Schiavello, M.; Ruiz, J. S. Photocatalytic Oxidation of Cyanide in Aqueous TiO2 Suspensions Irradiated by Sunlight in Mild and Strong Oxidant Conditions. Catal. Today 1999, 54, 245. (17) Barakat, M. A.; Tseng, J. M.; Huang, C. P. Hydrogen PeroxideAssisted Photocatalytic Oxidation of Phenolic Compounds. Appl. Catal., B 2005, 59, 99. (18) Mahmoodi, N. M.; Arami, M.; Limaee, N. Y.; Tabrizi, N. S. Decolorization and Aromatic Ring Degradation Kinetics of Direct Red 80 by UV Oxidation in the Presence of Hydrogen Peroxide Utilizing TiO2 as a Photocatalyst. Chem. Eng. J. 2005, 112, 191. (19) Ferna´ndez, J.; Kiwi, J.; Baeza, J.; Freer, J.; Lizama, C.; Mansilla, H. D. Orange II Photocatalysis on Immobilised TiO2. Effect of the pH and H2O2. Appl. Catal., B 2004, 48, 205. (20) Pe´rez-Estrada, L. A.; Maldonado, M. I.; Gernjak, W.; Agu¨era, A.; Ferna´ndez-Alba, A. R.; Ballesteros, M. M.; Malato, S. Decomposition of Diclofenac by Solar Driven Photocatalysis at Pilot Plant Scale. Catal. Today 2005, 101, 219. (21) Nogueira, R. F. P.; Trovo, A. G.; Paterlini, W. C. Evaluation of the Combined Solar TiO2/photo-Fenton Process Using Multivariate Analysis. Water Sci. Technol. 2004, 49, 195.

(22) Pozzo, R. L.; Baltana´s M. A.; Cassano, A. E. Supported Titanium Oxide as Photocatalyst in Water Decontamination: State of the Art. Catal. Today 1997, 39, 219. (23) Byrne, J. A.; Eggins, B. R.; Brown, N. M. D.; McKinney B.; Rouse, M. Immobilization of TiO2 Powder for the Treatment of Polluted Water. Appl. Catal., B 1998, 17, 25. (24) Aguado, J.; van Grieken, R.; Lo´pez-Mun˜oz, M. J.; Maruga´n, J. Removal of Cyanides in Wastewater by Supported TiO2-Based Photocatalysts. Catal. Today 2002, 75, 95. (25) Box, G. E. P.; Hunter, W. G.; Hunter, J. S. Statistics for Experimenters: An Introduction to Design, Data Analysis, and Model Building; Wiley: New York, 1978. (26) Oliveros, E.; Legrini, O.; Hohl, M.; Mu¨ller, T.; Braun, A. M. Large Scale Development of a Light-Enhanced Fenton Reaction by Optimal Experimental Design. Chem. Eng. Proc. 1997, 36, 397. (27) Torrades, F.; Pe´rez, M.; Mansilla, H. D.; Peral, J. Experimental Design of Fenton and Photo-Fenton Reactions for the Treatment of Cellulose Bleaching Effluents. Chemosphere 2003, 53, 1211. (28) Gernjak, W.; Fuerhacker, M.; Ferna´ndez-Iba´n˜ez, P.; Blanco, J.; Malato, S. Solar Photo-Fenton TreatmentsProcess Parameters and Process Control. Appl. Catal., B 2006, 64, 121. (29) Ferna´ndez, J.; Kiwi, J.; Lizama, C.; Freer, J.; Baeza, J.; Mansilla, H. D. Factorial Design of Orange II Photocatalytic Discolouration. J. Photochem. Photobiol. A 2002, 151, 213. (30) Liu, H. L.; Chiou Y. R. Optimal Decolorization Efficiency of Reactive Red 239 by UV/TiO2 Photocatalytic Process Coupled with Response Surface Methodology. Chem. Eng. J. 2005, 112, 173. (31) van Grieken, R.; Aguado, J.; Lo´pez-Mun˜oz, M. J.; Maruga´n, J. Synthesis of Size-Controlled Silica-Supported TiO2 Photocatalysts. J. Photochem. Photobiol. A 2002, 148, 315. (32) Malato, S.; Ca´ceres, J.; Agu¨era, A.; Mezcua, M.; Hernando, D.; Vial, J.; Ferna´ndez-Alba, A. R. Degradation of Imidacloprid in Water by Photo-Fenton and TiO2 Photocatalysis at a Solar Pilot Plant: A Comparative Study. EnViron. Sci. Technol. 2001, 35, 4359. (33) Malato, S.; Blanco, J.; Campos, A.; Ca´ceres, J.; Guillard, C.; Herrmann, J. M.; Ferna´ndez-Alba, A. R. Effect of Operating Parameters on the Testing of New Industrial Titania Catalysts at Solar Pilot Plant Scale. Appl. Catal. B 2003, 42, 349. (34) Kositzi, M.; Poulios, I.; Malato, S.; Ca´ceres, J.; Campos, A. Solar Photocatalytic Treatment of Synthetic Municipal Wastewater. Water Res. 2004, 38, 1147. (35) Pignatello, J. J. Dark and Photoassisted Fe3+-Catalyzed Degradation of Chlorophenoxy Herbicides by Hydrogen Peroxide. EnViron. Sci. Technol. 1992, 26, 944. (36) Pelizzetti, E.; Carlin, V.; Minero, C.; Gra¨tzel, M. Enhancement of the Rate of Photocatalytic Degradation on TiO2 of 2-Chlorophenol, 2, 7Dichlorodibenzodioxin and Atrazine by Inorganic Oxidizing Species. New J. Chem. 1991, 15, 351. (37) Malato, S.; Blanco, J.; Maldonado, M. I.; Ferna´ndez-Iba´n˜ez, P.; Campos, A. Optimising Solar Photocatalytic Mineralisation of Pesticides by Adding Inorganic Oxidising Species: Application to the Recycling of Pesticide Containers. Appl. Catal., B 2000, 28, 163. (38) Feng, W.; Nansheng, D. Photochemistry of Hydrolytic Iron(III) Species and Photoinduced Degradation of Organic Compounds: A Minireview. Chemosphere 2000, 41, 1137. (39) Flynn, C. M., Jr. Hydrolysis of Inorganic Iron(III) Salts. Chem. ReV. 1984, 93, 31. (40) Aran˜a, J.; Gonza´lez Dı´az, O.; Miranda Saracho, M.; Don˜a Rodrı´guez, J. M.; Herrera Melia´n, J. A.; Pe´rez Pen˜a, J. Maleic Acid Photocatalytic Degradation Using Fe-TiO2 Catalysts. Dependence of the Degradation Mechanism on the Fe Catalysts Content. Appl. Catal., B 2002, 36, 113.

ReceiVed for reView August 7, 2006 ReVised manuscript receiVed October 2, 2006 Accepted October 3, 2006 IE061033B