Kinetics of Oxidation of Selenite to Selenate in the Presence of

Ion chromatographic separation of selenite and selenate using a polyanionic eluent. Pavel Janoš , Peter Aczel. Journal of Chromatography A 1996 749 (...
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Environ. Sci. Technol. 1995, 29,586-594

Kinetics of Oxidatim of Selenite to Setenate in the Presence of Oxygen, Tinia, and tight K A R E N A . GRUEBEL,*,I J A M E S A . DAVIS,$ A N D JAMES 0. LECKIEI Environmental Engineering and Science, Department of Civil Engineering, Stanford University, Stanford, California, and U.S.Geological Survey, Menlo Park, California

A detailed investigation of equilibrium surface adsorption reactions and rate-controlled photochemically induced redox reactions was conducted to include surface complexation modeling in the development of a mechanistic rate law. The investigation included a parametric study of selenite oxidation in the presence of irradiated titania and was divided into five parts, the rate of selenite oxidation as a function of (1) light intensity, (2) pH, (3) ionic strength, (4) oxygen partial pressure, and (5) selenite concentration. The titania used was characterized for its equilibrium surface properties, and surface speciation was modeled using the triple-layer model with the computation routine HYDRAQL. A kinetic model was successfully developed that related the measured quantum yield to titania surface species developed through surface characterization and triple-layer modeling.

Introduction There is great motivation for studying light-induced redox reactions at oxide surfaces. Many major classification of organics have been tested and found to be fully mineralized to C 0 2 including haloalkanes (1, 2), aromatics and haloaromatics (3-61, and surfactants (7, 81, and it has been found that light-induced reactions at oxide surfaces can deactivate microorganisms (9). Inorganic substances susceptible to photodegradation include cyanide (10-12’). Results of mechanistic studies of nonirradiated as well as light-induced reactions taking place at oxide-water interfaces have suggested that surface speciation often controls reaction rates (13,141. Reactions which have been described by mechanisms that include surface speciation are photoassisted or ligand-promoted dissolution reactions ( 1 9 , electron-transfer reactions (16), and light-activated reactions on nonsemiconducting solids ( I 7 ) and semiconducting solids (13). The study reported on here describes the use of a surface speciation description of the hydrated titania surface to characterize light-induced reactions at the oxide-water interface. This study uses an equilibrium surface complexation description of an oxide in solution to evaluate the kinetics of electron transfer reactions involving irradiated titania and the oxidation of selenite. Equilibrium surface speciation, the production of holes and electrons during irradiation of titania with UV light, and subsequent reactions are included in the formulation of the rate law. While selenium is an element of concern in the environment due to its toxicity at elevated concentrations (181,oxidation of selenite to selenate is usually not desirable due to the relatively high mobility of selenate natural systems (19,201. However, selenite is a strongly adsorbing ion that if oxidized yields a weakly adsorbing product, selenate; this tendency was used here to explore the mechanism of oxidation and the use of surface speciation for describing oxidation at the irradiated titania-water interface. Selenite was chosen a reactant because, in addition to strong adsorption properties, selenite does not have numerous intermediates as do many organic reactants, thereby simplifymg the reaction pathways. Experiments using formate as the reactant on irradiated titania, which does not adsorb strongly, were conducted for comparative purposes.

Materials and Methods Water used was from a Milli-Q (MQ) water purification system. The pH was measured using a Orion research Model 701A pH meter with a Corning electrode Model 476541 using standard NBS buffers. Selenite and selenate analyseswere done with a Dionex Model 2000i with a Dionex anion column Model HPIC-ASM using 2.2 mM sodium carbonate plus 7.5 mM sodium bicarbonate. The regenerant was 0.025 N sulfuric acid, and analysis was by conductivity. The precision of selenite analysis was determined to be 2.5% and the accuracy was determined to * Address correspondence to this author at her present address: Erler & Kalinowski, Inc., 1730 South Amphlett Blvd., Suite 320, San Mateo, CA 94402. + Stanford University. U.S. Geological Survey.

*

686

ENVIRONMENTAL SCIENCE & TECHNOLOGY I VOL. 29, NO. 3,1995

0013-936X/95/0929-0586$09.00/0

6-1995 American Chemical Society

be 5% (211. Formate was analyzed on the same anion column using 0.005 M sodium tetraborate. The titania used for all experiments was purchased from Baker and was identified as 100% anatase by X-ray diffraction. The titania was washed in an attempt to remove surface contaminants and impurities; impurities detected before washing included elevated concentrations of sulfate and phosphate, which desorbed from the titania in high pH solutions. The titania was washed with 3 L of 0.1 M HCU100 g, followed by 3-5 L of water, followed by 5-10 L of 0.1 N NaOH followed by continuous flushing with MQ water until the conductivity of the supernatant liquid was that of MQ water. The titania was freeze-dried and stored in cleaned nalgene bottles. Surface area analysis was done with N2 gas adsorption; the solid was outgassed for 13-66 h at 30 "C. Titrations to obtain sodium and chloride binding constants and titania acidity constants used ultrapure salts, acids, and bases and followed routine procedures (21). Titrations of the titania solid were conducted using 25 glL of cleaned titania. Salt titrations were conducted to determine the pH point of zero salt effect as described in Davis (22). Equilibrium adsorption experiments were conducted in 20-mL opaque polycarbonate tubes with O-ring lined caps. Aliquots of solutions of titania, sodium chloride, selenite (Aldrich, 99.9% pure) or selenate, and hydrochloric acid or sodium hydroxide were added to make each sample the same volume and the same ionic strength (0.01M). Sodium chloride, the background electrolyte for all experiments, was used to vary ionic strength in those experiments. Sodium chloride was 99.999% pure (AESAR). Precautions were taken to exclude C02. The containers were rotated in the dark for 18 h, the pH was then measured, the tubes were centrifuged at 3000 rpm for 30 min, and the supernatant liquid analyzed for selenite or selenate. Adsorbed concentration was determined by difference (concentration added minus concentration measured in the supernatant liquid). All manipulations before centrifugationwere done in a darkened room. Irradiated titania experiments were conducted in a 250mL reaction vessel with a flat Pyrexwindow and was waterjacketed and held at 25 "C. The tight-fitting Teflon top had four ports: pH electrode, gas in, gas out, sample tube. All experiments were done using a 350-nm narrow wavelength band pass filter (OrielModel 53400). Experiments varying the intensity of light used UV neutral density filters (Oriel Models 50490, 50510, and 50530). Infrared wavelengths were filtered out using a water filter. During kinetic experiments, pH was continually monitored. Gas mixtures of COZ,0 2 , and NZwere continuously bubbled to maintain pH with the buffering of the sodium bicarbonate. Rate experiments were conducted by withdrawing an aliquot of slurry and filtering through a 0.2-pm nylon filter. Filters were used rather than centrifugation for convenience; preliminary experiments revealed the filters did not adsorb selenite or selenate at any pH value used for these experiments (a pH range of approximately 3.9-9.1). In addition, two aliquots of titania slurry were added to 0.1 N base and mixed for 30 min to desorb selenite and selenate from the surface. Previous analysis showed that a 5-min reaction time desorbed 98% of selenite that had been adsorbed on titania for 24 h or less. Formate oxidation experimentalmethods were identical to selenium experiments with the exception that the formate oxidation

product was not measured. Control experiments were conducted to test formate adsorption on the surface of the titania and whether oxidation of formate and selenite occurred when irradiated with UV light without titania present. The method of initial rates was used to calculate the rate of selenate production. The concentration of selenate produced was used to calculate the rate of reaction rather than the disappearance of selenite because the analytical error was lower than for measurement of selenite. All the selenate was found in solution (Le., no selenate was adsorbed on the titania surface) except during very low pH experiments, hence the additional desorption step needed for selenite and concomitant error was avoided. The method of initial rates was used to calculate formate loss because the formate oxidation product, COz, could not be accurately measured. To calibrate lamp intensity after each experiment, ferrioxalate actinometry was conducted (23)in a clean 250mL reactor, and intensity was calculated assuming a quantum yield of 1.23 for the ferrous ion. The ferrioxalate actinometer modification of Murov (24) and Bowman and Demas (251 were strictly followed.

Solid Characterization and Modeling of Surface Equilibrium (Dark) Reactions A description of the surface speciation of the titania-water interface was necessary to explore potential reaction mechanisms for the surface-catalyzedoxidation of selenite. The triple-layer model (26, 23, a surface complexation model (SCM)with modifications by Hayes and Leckie (281, was used in this work. Recent reviews of the triple layer and other SCMs can be found in Sposito (291,Westall (301, Hayes (311, and Davis and Kent (32). The surface acidity of titania is represented by two mass action equations using TiOH to represent a surface hydroxyl, and the Ti represents a titanium atom that is part of the mineral lattice:

+ H+ TiOH = TiO- + H+

TiOH,' = TiOH

(1) (2)

In the absence of other ions, the surface mass balance is then given by [TiOH]

+ [TiOH,'] + [TiO-1 = total surface sites

(3)

where [ I indicate concentrations. In the triple-layer SCM description, electrostatics are included, and intrinsic binding constants for association and dissociation of surface hydroxyls on titania are defined as [TiOH,'] Kalht

= [TiOH][H'] exp(-Fq,IRT)

(4)

The equilibrium constants, Kalht and Kazint,are defined as intrinsic binding constants. F is equal to the Faraday constant, R is the universal gas constant and T is the temperature. The dissociation and protolysis reactions are assigned to the o-plane, hence ly, describes the potential at the o-plane. The binding of the supporting electrolyte VOL. 29, NO. 3 , 1 9 9 5 /ENVIRONMENTAL SCIENCE &TECHNOLOGY

687

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125 pM model fit

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PH FIGURE 1. Adsorption of selenite (closed squares for 125pMselenite; open squares for 25pM)on titania (10 g/L)in 0.01 M NaCl and HYDRAQL model fit of selenite adsorption (dashed line for 125 pM selenite; solid line for 25 pM selenite).

anions and cations, sodium and chloride, that bind weakly to the titania surface are often equated with ion-pair reactions with binding at the P-plane:

+ H+ + C1- = TiOH,'ClTiOH + Na+ = TiO-Na' + H+

TiOH

(6)

(7)

(35) to obtain best fits; and (5) selenite binding constants from selenite titration data and HYDRAQL to obtain best fit (see Gruebel (21) for details of modeling). The acidity constants and electrolyte binding constants determined were as follows: pKalint= -3.60 (eq 4), pKaint= 7.60 (eq 51, pKclint= -5.36 (eq 81, and pKNaint= 5.57 (eq 9), using an outer layer capacitance of 0.2 F/m2 and a best fit inner layer capacitance of 1.4F/m2.

Varying reaction stoichiometries, including proton stoichiometry, placement of selenite in surface planes (0-and ,&planes), and shielding of surface sites (36)were explored to fit the dark selenite adsorption data using HYDRAQL (35). The reaction found to fit selenite adsorption data best was The binding of coordinative complexes such as selenite, also called inner-spherecomplexes or specifically adsorbed species, are postulated to be ligand exchange reactions and are placed in the o-plane (L represents the ligand): TiOH

+ L-, + H+ = TiL- + H,O [TiL-1

KLint = [TiOH][H'] [L-'] exp(-Fq,lRT)

(10)

(11)

The specifics of selenite binding to the titania surface are discussed below. Results of Equilibrium Modeling. The data that were used to evaluate constants needed to define triple-layer constants defined above were as follows: (1) surface area, 8.6 m2/g,determined by N2 gas adsorption: (2) site density, 5.8 site/nm2, based on tritium exchange reported by Honeyman (33);(3) point ofzero charge, pH 5.6,determined by salt titration; (4)sodium, chloride, and acidity constants from titration data, utilizing FITEQL (34) and HYDRAQL 588 1 ENVIRONMENTAL SCIENCE &TECHNOLOGY / VOL. 29, NO. 3, 1995

3TiOH

+ SeO,,-

= (TiOHSeO;-)

+ 2TiOHshielded(12)

Selenite binding was modeled as an inner-spherecomplex, located in the o-plane, and pKs$* was 15.5. The model fit and adsorption data for two concentrations of selenite (25 and 125pM)are shown on Figure 1. Experiments done at low ionic strength (0.003 and 0.005 M) and high ionic strength (0.1M) showed that the extent of selenite adsorption was independent of ionic strength, consistent with inner-sphere complexation of selenite (37). The stoichiometry chosen includes the blockage of surface sites by the adsorbed selenite. For a description of this phenomenon, see Gruebel (21) and Balisteri and Chao (38).A plot of surface speciation and solution selenite for 25 pM derived from the model and model constants described above and solution selenite concentrations is included as Figure 2. The concentration of surface species was used in analysis of the kinetic rate law derived below.

PH

3 21

4

5

6

7

8

9

10

11

I

I

I

I

I

I

I

1

Legend TiOH -.- TiO' *..... TiO'Na+

-

---- TiOH - e . -

TiOHzCI-

----TiOHSeO-3 --seo-3 IC

FIGURE 2. Surface speciation and aqueous selenite obtained from HYDRAQL output.

Experimental Results of the Rate Study and Model Development The results of the experimental rate study reveal the empirical dependency of reaction rates on the individual system parameter. The parameters tested here were varied over broad ranges: (1) light intensity from 20 to 480 pEinstein L-' min-'; (2) pH 3.8-9.1; (3) oxygen partial pressure from 0 to 1.0 atm (0-1.2 mM aqueous dissolved oxygen); (4) selenite concentration from 15 to 600pM; and (5) ionic strength from 0.003 to 0.1 M. The effect oflight intensity on the production of selenate was measured at four pH values. All experiments were conducted with 13 pM surface-adsorbed selenite on 10 g/L titania (15pM selenite/m2of titania). This was effected by increasing total selenium in each experiment with increasing pH. The dependence of selenite reaction rate on incident light intensity (at constant pH) is plotted in Figure 3, where the zero-order rate constant is plotted against light intensity calculated from the production of Fe(I1)from the actinometer. At light intensities greater than 220 pEinstein L-' min-', the reaction rate was less than that predictedwith a linear fit. This type of nonlinearityat higher intensities has been reported in the literature (e.g., refs 39-41), which results from increased hole-electron recombination. Experiments conducted with light intensities less than 220 pEinstein L-' min-l were used for kinetic analyses. The equations below represent reactions taking place during oxidation of selenite to selenate, and these were used to obtain a rate law for the overall reaction. Part of the measured data set was used to calibrate the model yielding a self-consistent set of model constants (varying pH and varying oxygen concentration). The remaining data (varyingselenite adsorbed and varying ionic strength) were

used to validate the model and constants. TiOH,' = TiOH TiOH = TiO-

+ Hf

+ Hf

K, lint

(1)

Grit

(2)

+ C1- + Hf = TiOH,+CITiOH + Na' = TiO-Na' + H+ KNF 3TiOH + Se0;- = (TiOHSeO;-) + 2TiOHshielded TiOH

(6)

(7)

K S F (12)

+ 0, = TiOHO, KO, TiOH + hv - hole (h,b+) + electron (ecb-) TiOH

hvb+

+

-

heat

(13) I,

k,,,

+ TiO- -.TiO' khole TiO' + TiO- - TiO' + TiOkexcb TiOHSe0:+ TiO' + TiOHO, TiOHSeO: + TiOH0,- + TiOk,, TiOHSeO: + H,O - Se0:+ TiOH + 2H+ TiOHO, + ecb-- TiOH0,h,b+

(14) (15)

(16) (17)

(18) (19) (20)

The model was constructed using the above equations and assuming the adsorption-desorption reactions were VOL. 29, NO. 3. 1995 I ENVIRONMENTAL SCIENCE &TECHNOLOGY

989

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18 PH

16 14

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12 dSe/dt molesR m i d 10 x 10-8 8

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INTENSITY mM €in/ L min FIGURE 3. Rate constant (mol 1-' min-l x 108 selenate produced) versus light intensity (IrEinstein 1-l min-l). The error bars are the average error of the standard deviation of the duplicate rate constants. Experimental conditions: 10 g/Ltitania, 0.01 M NaCI, and 13 pM adsorbed selenite.

in equilibrium during the reaction (designated by an equal sign). TiO- in eqs 16-18 represents negative surface sites including TiO- plus TiO-Na+. The concentrations of TiOand TiO-Na+ were obtained from equilibrium modeling of surface speciation using parameters derived above. TiO' represents a reactive radical created by hole capture by the negatively charged surface titania site. It was assumed that eq 15 is first order with respect to holes, Le., rate = krecombination x holes. It was further assumed that a steadystate existswith respect to T i 0 and holes dTiOldt= dholel dt = 0. Combining and rearranging: dSeO:/dt

4

-

{ kh,l,[TiO-]k,,[TiOHSe0,2-] [TiOHO,] > / {(kreCr'

k,o,,[TiO-l) (k,,,,[TiO-I

+ kse[TiOHSe0,2-l [TiOHO,])} (21)

dSeO,'/dt

= effective quantum yield

(22)

Ia

The model input included measured Za values and adsorbed selenite and oxygen. The input for adsorbed selenite concentration (TiOHSe032-) was determined by the difference between selenite added and selenite in the supernatant at time equal to zero during the kinetic experiment. The input for negative surface site concentration (TiO- and TiO-Na+)was derived from HYDRAQL model calculations using surface speciation calculations for the experimental conditions of interest and equilibrium constants derived from experiments conducted in the dark. S90

ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 29, NO. 3, 1995

The mechanistic model includes adsorbed oxygen at the titania surface (eq 18). No direct measurements were made, instead literature data were used in conjunction with the assumption that oxygen behaves in a Langmurian manner: OzKmak, TiOHO -(23) - 1 O,k, Kmaxis the maximum in concentration of adsorbed oxygen and kl is the adsorption constant. The assumptions needed for Langmuir adsorption should be valid for oxygen because it is uncharged, does not exhibit a dipole, and therefore probably has no electrostatic energy associated with its adsorption. The value of kl of 8.84 x lo3 L/mol reported by Okamoto et al. (42,431for oxygen adsorption on anatase in a system similar to one used in this study was used here to calculate TiOHOZ. Kma used in eq 23 was chosen to be 3.4 x mol/L (4.0 x 10-6pmol/m2x 10 g/L x 8.6m2/g), the Kmaxdetermined for selenite binding to this titania at pH 3 (21). A nonlinear least-squares fitting routine using the method of Levenberg-Marquardt ( 4 4 )was used to obtain model constants. Because there was a linear relationship between intensity and rate below 220 pEinstein L-l min-l, all the rate data with intensity values less than 220,uEinstein L-l min-I were used to calculate the measured effective quantum yields. These quantum yields are considered effective because the relationship between the light adsorbed by the actinometer and the light adsorbed by the titania is unknown. A total of 50 data points were included in the model fit. The significance of the model fit lies in the goodness of fit of the data to the model predictions.

+

model 7.OOE-04 6.OOE-04 5.00E-04 Quatum

Yield

4.00E-04 3.00E-04 2.00E-04 1.00E-04

O.OOE + 00 2.00

3.00

4.00

5.00

6.00

7.00

8.00

- log (negative site concentration) FIGURE 4. Quantum yield versus negative log negative site concentration (PO: data (squares), model fit (solid line) end 20% change in predicted quantum yield (broken lines). The data points represent the average quantum yield for all measurements made at that particulate pH value. There are eight values for each negative log site concentrations of 5.8 and 3.8, six for 5.2, and 12 values for 4.2. The error bars are 1 SO of the average quantum yield measurements for each pH.

The rate constants obtained from the fitting routine are as follows:

khole= 2.2 x 10” M-‘ s-]

k,,

= 1.7 x lo9 M-’ s-’

k,,= 3.0 x

lo6 s-l

k x c h= 9.7 X lo7 M-‘ S-l It is important to note that these rate constants pertain to heterogeneous reactions; therefore, comparison with homogeneous rate constants is not appropriate. The fastest rate constant obtained, the reaction of the hole with a negative surface site (kh&), is consistent with extremely short lifetimes of holes and electrons, on the order of nanoseconds (45). Figure 4 displays a plot of the quantum yield versus the negative log of the negative site concentration. Large negative surface concentrations are generated at high pH values, and small negative surface concentrations are generated at low pH values (21). For clarity, average quantum yields at a given pH are plotted rather than an individual datum. The error bars on either side of the data points are one standard deviation of the average quantum yield (21). The solid line is the calculated quantum yield calculated by the fitting routine. The dotted and broken lines are *20% of the predicted quantum yield. The model agrees fairly well with data collected at pH values equal or greater than 5.5 (minus the log negative surface site concentration less than 5.3). The quantum yield predicted for the lowest pH value is higher than the value measured. Equilibrium modeling also was less successful at low pH values. Both of these effects are probably due to the presence of surface sulfate and phosphate contamination at low pH (see Materials and Methods above). Figure 5 displays a plot for data and model prediction of quantum

yield versus concentration of dissolved oxygen. The model predicts the trend measured in the quantum yield quite well. The influence of Kmax(eq 23), the maximum oxygen adsorbed concentration, on the rate constants was tested. The model fit was not sensitive to the value of Kma, but the rate constants become larger as Kmaxbecomes smaller. Two sets of experiments were not included in the calibration of model constants: data for variable selenite and variable ionic strength. Aplot of quantum yieldversus aqueous selenite is shown in Figure 6. The predicted quantum yield rises sharply and reaches a plateau due to the increase of selenite on the titania surface. The maximum concentration of selenite adsorbed on the titania at this pH (5.5)was 52pM reachedwith 125pMtotal selenite in the system. Increasing the total selenite concentration to 200 or 600 pM did not change the surface concentration of selenite, nor did it significantly change the quantum yield. The surface model of selenite oxidation is consistent with the plateau in quantum yield as a function of adsorbed selenite. If the reaction occurred in the solution phase, for example, with a solution-phase free radical, the correlation between surface concentration of selenite and quantum yield would not be expected. This finding is also consistent with other studies in which surface species have been found to control reaction rates (e.g., refs 14, 46, and 48). Hence, formulation of rate laws without considering surface adsorption may not allow investigation of potentially critical reaction steps. The effect of ionic strength on reaction rate was evaluated in experiments in which ionic strength was varied between 0.003 and 0.01 M. Surface selenite was held constant at 13 pM; however, total selenite and pH were either 25 pM selenite and pH 7.8 or 20 pM selenite and pH 5.5. Figure 7 presents the measured data and the model fit predicted by the rate law and previously generated rate constants. The model predictions fit as well as the model predictions VOL. 29, NO. 3, 1995 /ENVIRONMENTAL SCIENCE &TECHNOLOGY

691

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I

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6.00E-04

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5.OOE-04

0

data

4.OOE-04

-

error

--------+20 %

3.00E-04

2.00E-04 1.00E-04

v

- 20%

O.OOE + 00

I

1.o

0.8 Dissolved Oxyoen (mmoles/L)

0.0

0.2

0.4

0.6

FIGURE 5. Quantum yield versus oxygen concentration: data (squares), model fit (solid line), and 20% in predicted quantum yield (broken lines). The error bars are derived from the standard deviation of the rate constant.

7.OOE-04 6.00E-04

model

*

5.OOE-04

-

Quantum 4.00E-04 Yield

3 .OOE-04 2.OOE-04

error

-------- + 20%

Pt

1'00E-04 O.OOE + 00 0.00

data

- 20% I

0.05

0.1 0

0.1 5

aqueous selenite (mmoJes/L) FIGURE 6. Quantum yield versus aqueous selenite concentration: data (squares), model fit (solid line), and 20% in predicted quantum yield (broken line). For clarity, the average adsorbed selenite concentration was used to calculate model results for the two experiments that contained 0.07 and 0.08 mM aqueous selenite. The anor bars are derived from the standard deviation of the rate constant.

for data used to generate the constants (Figures 4 and 5). These results confirm the importance of surface speciation in controlling reaction rates in that the surface concentration of selenite was constant and independent of ionic strength, but the quantum yield was not independent of ionic strength. These results also clearly demonstrate the advantage of the triple-layer formulation of SCMs, in that the triple-layer formulation successfully accounts for the changes in surface speciation as a function of ionic strength. Formate Oxidation. The rate of formate oxidation in the presence of titania and light was explored to test the 692

ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 29,NO. 3, 1995

proposed model. The rate of reaction of formate alone and in the presence of selenite may further the understanding of the reaction mechanism. Formate was chosen as the oxidant because it is an anion (pK, 3.75) that does not strongly adsorb on the titania surface. Because the reaction of formate and oxygen on irradiated titania produces CO;! (49), the loss of formate was measured rather than product formation. Experiments conducted showed that formate was not oxidized in a titania-oxygen mixture when the system was not irradiated. Adsorbed formate was below detection on the titania surface at the pH values

8.00E-04

I

7.OOE-04

mode'

I

6.OOE-04 5.00E-04

Quantum

4.00E-04

Yield

3.00E-04

2.OOE-04 1.00E-04 O.OOE + 00

2.00

3.00

-

4.00 5.00 6.00 7.00 log (negative surface sites)

8.00

FIGURE 7. Quantum yield versus negative log negative site concentration for ionic strength data: data (squares), model fit (solid line), and 20% in predicted quantum yield (broken lines). The error bars are derived from the standard deviation of the rate constant. TABLE 1

Formate Oxidation Quantum Yields quantum yield selenate production formate loss (molPinstein) (mol/Einstein) pH 3.5

10-4

4.7 x 10-4

8.5 8.5 1.2 5.2

anions present (125 pM initial formate and/or selenite)

x

5.90 selenite and formate

x x

5.78 5.81 3.85 5.71

x

formate formate formate selenite

used during these experiments. Experimental conditions and results for the formate oxidation experiments and concurrent selenite oxidation experiments are given in Table 1. Oxidation experiments were carried out at pH 3.8 and 5.8. The oxidation of formate proceeded faster at pH 5.8, although adsorbed formate could not be detected at either pH value. When both selenite and formate were added in equimolar concentrations, the quantum yield of formate oxidation decreased by 39% and the quantum yield of selenite oxidation decreased by 30%. Adsorbed selenite concentration did not change in the presence of formate. The decrease in both rates suggests that selenite and formate were competing for the same reactant radical.

Discussion of Selenite Oxidation Reaction and Its Relationship with Surface Speciation The data and empirical rate law suggest that (1)selenite is oxidized as a charged surface-adsorbed species and that selenate, the product, does not cause poisoning of the surface; (2) oxygen is reduced as a neutral surface-adsorbed species; (3) rate of oxidation is not a simple function of pH when all other parameters are held constant; and (4) low surface concentrations of formate oxidize more quicklythan high surface concentrations of selenite. The rate of oxidation of selenite is clearly a function of adsorbed concentration of negativelycharged selenite. This

is evident from Figure 6, which displays selenite versus effective quantum yield at variable total selenite. The selenite oxidation rate did not decrease as the product was forming, suggesting that either (1) adsorbed selenate did not interfere with the oxidation reaction or (2) the selenate desorption occurred quickly and thereby did not interfere with the oxidation reaction. Surface adsorption of oxygen modeled as an uncharged molecule obeying Langmuirian behavior is consistent with the findings of other researchers including Okamoto (42, 43). However, constant adsorbed selenite with a variable surface charge (effected by varying pH or ionic strength) did not yield a constant product. In fact, there is not a simple relationship between pH or ionic strength and oxidation rate, nor is there a simple relationship between surface species and oxidation. The reaction steps included in the rate law formulation imply that negative surface sites, including those containing weakly adsorbed species, e.g., Na+ , are the sites of Ti@ radical creation. Figure 2 displays the very weak pH dependence on the concentration ofTiOH sites on titania and the strong pH dependence on the concentration of negative surface sites, TiO- and TiO-Na+. In the mechanistic formulation, the combination of adsorbed selenite, TiO' radical, and adsorbed oxygen are necessary for the oxidation to occur (eq 23). Trimolecular reactions in the gas or liquid phase are not common. However, the reaction of three species is less difficult in this system because the reactants are all present on the surface. The adsorbed selenite, adsorbed oxygen, and titania radical need to be near each other on the surface. The migration of T i 0 radical (eq 22) by hole jumping allows this configuration to occur often. The reaction given by eq 23 is the rate-determining step, consistent with needing three reactants coincident in time and space. It is unknown if this reaction step, which includes the transfer of two electrons, might in fact be more appropriately modeled as more than one step, e.g., two separate electron transfers; VOL. 29, NO. 3, 1995 I ENVIRONMENTAL SCIENCE & TECHNOLOGY 1593

however, we could not find another mechanism which fit the data. Although formate does not bind as strongly as selenite, it is oxidized more quickly than selenite. Therefore, if formate is oxidized by the same surface radical as selenite, the selectivity of the reaction must be much higher than that of selenite. This may occur because formate, which does not strongly adsorb on the titania surface, may not influence the distribution of negatively charge surface sites to the extent of selenite influence of negative sites. Therefore, negative surface sites (as site of TiO' formation) and formate have a higher probability of being in close proximity and consequently are more likely than selenite to oxidize. In summary, the triple-layer model was used to develop a model of the surface speciation of titania in the presence of sodium chloride,the background electrolyte,and selenite. The surface species were incorporated into a rate law to describe light-activated oxidation of selenite. The kinetic model which incorporated surface speciation utilizing the triple-layer model successfully modeled all conditions tested. These results clearly demonstrate that SCMs can be used during the development of mechanistic models of light-induced redox reactions. Further, there is an advantage to using the triple-layer formulation of SCMs, in that the triple-layer formulation successfully accounts for the changes in surface speciation as a function of ionic strength.

Acknowledgments The authors acknowledge the insights provided by Dr. Theodore Mill regarding photochemistry. Dr. Gary Curtis provided a computer program of the nonlinear least squares fitting routine and helped with experimental design. The authors acknowledge the constructive comments of three anonymous reviewers.

Nomenclature Pn Kalint Ka2 int F 1c'O

*P

R T Kclint

KNP~

micrometer intrinsic binding constant for eq 1 intrinsic binding constant for eq 2 Faraday constat potential at the o-plane potential at the P-plane universal gas constant temperature intrinsic binding constant for eq 8 intrinsic binding constant for eq 9

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Received f o r review April 25, 1994. Revised manuscript received October 14, 1994. Accepted December 12, 1994.@

ES940255A @

Abstract published in Advance ACS Abstracts, January 15, 1995.