Photocatalytic Degradation of Water Pollutants Using Nano-TiO₂

Abstract

This review discusses the utilization of photocatalysis for the degradation of water pollutants. Emphasis is placed on TiO₂ nanoparticles as a benchmark photocatalyst for the destruction of microorganisms and the degradation of a wide variety of organic compounds like phenolics, dyes, pesticides and pharmaceuticals. The mechanism of photocatalytic degradation is elucidated, underlining the importance of reaction kinetics for the efficient design of the processes. The effects of different reaction parameters on photocatalytic degradation are discussed. Surface modification of TiO₂ for visible light response by doping and heterostructuring is outlined. Finally, the challenges in the implementation of this technology for “real” waste water systems are summarized with a few attainable goals.

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1 Introduction

The industrial revolution has led to the pollution of the natural resources in massive proportions. Environmental pollution caused by anthropogenic sources is a day-to-day problem faced by both developing and developed countries. Among the different types of pollution, air and water pollution from the point sources contribute a major share of the overall imbalance of the ecosystem. Common pollutants are usually toxic organic compounds like chlorinated and non-chlorinated aliphatic and aromatic compounds, dyes, detergents and surfactants, agro wastes like insecticides, pesticides and herbicides, disinfection byproducts, volatile organic compounds, plastics, inorganic compounds (e.g., heavy metals), noxious gases (e.g., NO_x, SO_x, CO and NH₃) and pathogens (e.g., bacteria, fungi and viruses). Hence, strict environmental regulations on the use of these recalcitrant pollutants and their safe disposal drives the research community to develop clean and green processes to degrade the pollutants before they are discharged into the atmosphere and water bodies. This review examines “photocatalysis” as an advanced oxidation process for the degradation of different kinds of organic pollutants for environmental remediation.

Photolysis involves the use of ultraviolet (UV) or visible light radiation to effect chemical transformations. Photocatalysis uses a catalyst, usually, a semiconducting oxide to accelerate the photoreaction. The pioneering work of Fujishima and Honda in 1972 [1] on the photosplitting of water (i.e., simultaneous oxidation and reduction of water to oxygen and hydrogen, respectively) on a TiO₂ single crystal electrode led to the onset of photo induced redox reactions on semiconductor surfaces. This remarkable discovery attracted worldwide attention because it showed the possibility of generating hydrogen as a clean source of energy from water. It was soon realized that such redox processes could be utilized for environmental cleanup applications by Frank and Bard in 1977 [2], when they showed the photocatalytic oxidation of CN⁻ and SO₃ ⁻ using different semiconductor materials like TiO₂, ZnO, CdS, Fe₂O₃ and WO₃. This was followed by the demonstration of the TiO₂-catalyzed photodegradation of chlorinated organic compounds by Ollis [3, 4], and the Pt-loaded-TiO₂-catalyzed photochemical sterilization of microorganisms by Matsunaga et al. in the early 1980s [5]. Later, Grätzel, in 1991 [6], showed the first high-efficiency solar cell based on dye-sensitized colloidal TiO₂ films for photovoltaic power generation. Today, the principles of photocatalysis, especially using TiO₂ and its variants are widely employed in water and air purification, self-cleaning surfaces, self-sterilizing surfaces, antifogging surfaces, anticorrosive surface treatments, lithography, photochromic materials, microchemical systems and the selective and green synthesis of organic compounds.

Photocatalysis, as a research area, has witnessed tremendous development over the past two decades, with progress in the synthesis of novel materials and nano-structures, and the design of efficient processes for degradation of organic pollutants. Several classic review articles are dedicated to the principles and mechanism of photocatalysis [7–21], with special emphasis on the electron transfer processes, lattice and electronic structure of TiO₂, the surface chemistry of semiconductor oxides, generation of reactive radicals, chemisorption of small and large molecules, surface modification by doping and photooxidation of organic and inorganic substrates. Hence, photocatalysis can be regarded a well-understood field; yet, immense challenges and opportunities exist in realizing this technology on a large enough scale for pollution abatement.

Some of the traditional methods of water purification include neutralization of acidic and alkaline liquors, ultrafiltration, air stripping, flocculation, extraction, activated carbon adsorption, biological and peroxide/ozone treatment. It is important to note that most of the above methods are non-destructive, i.e., they only transfer the pollutant to another phase and do not ensure its destruction. The peroxide/ozone (H₂O₂/O₃) treatment is an economical way to oxidize pollutants, but O₃ causes air pollution. Biological degradation methods are effective in reducing the biological oxygen demand of the effluent. However, achieving complete mineralization (i.e., complete conversion to CO₂ and H₂O) of the parent organic compound using the above methods is difficult. The potential of photocatalysis to accelerate the rate of degradation reactions is attributed to the generation of reactive hydroxyl radicals (${\text{OH}}^{ \bullet }$), which are the precursors of degradation of any organic or inorganic compound and microorganisms. These reactive species possess a higher oxidation potential (2.80 V) compared to other common oxidants like atomic oxygen (2.42 V), O₃ (2.07 V), H₂O₂ (1.78 V), hydroperoxy radicals (1.70 V) and chlorine dioxide (1.57 V) [15]. Moreover, the thrust to utilize solar radiation has made photocatalysis, the technology of choice for the detoxification of water pollutants.

This review article begins with an explanation of the basic principles of UV photocatalysis and the different semiconductor oxides, which are used as photocatalysts. Emphasis is on TiO₂ as a “benchmark photocatalyst”, and the different synthesis procedures and properties of TiO₂ are briefly discussed. The photocatalytic degradation of various organic compounds like aliphatic and aromatic compounds, dyes, pesticides, pharmaceutical compounds and the destruction of microorganisms are extensively discussed in terms of their pathway of degradation. The effect of different reaction parameters like temperature, pH, solvents, UV light intensity, catalyst loading, substrate concentration, photocatalyst and the presence of anions and cations are discussed. The possibility of extending the absorption spectrum of UV photocatalysts to the visible region by appropriate surface modification is examined. The various mechanistic kinetic models proposed for the degradation of organic compounds are evaluated. The industrial applicability of photocatalysis is analyzed in the chemical engineering point of view, in terms of the different photoreactors that are currently being developed. Finally, the future research perspectives and the possibilities for commercializing this technology for the degradation of “real” industrial effluents are probed.

2 Mechanism of UV Photocatalysis

The mechanism of UV photocatalysis is well-documented [8, 10, 17, 18], and the following reactions represent the key steps in the generation of charge-carriers and hydroxyl radicals, which mediate photocatalytic reactions. A pictorial representation of the mechanism of TiO₂ photocatalysis is shown in Fig. 1.

Fig. 1

Mechanism of photocatalysis on the surface of TiO₂ in presence of UV radiation

Charge-carrier generation:

$${\text{TiO}}_{2} + hv\mathop{\longrightarrow}\limits^{hv >E_{\text{BG}}}h_{\text{VB}}^{ + } + e_{\text{CB}}^{ - }$$

(1)

Charge-carrier trapping:

$$ {\text{Ti}}^{\text{IV}} {\text{OH}}^{ - } + h_{\text{VB}}^{ + } \mathop{\longrightarrow}\limits{{}}{\text{Ti}}^{\text{IV}} - {\text{OH}}^{ \bullet } $$

(2)

$$ {\text{Ti}}^{\text{IV}} {\text{OH}}^{ - } + e_{\text{CB}}^{ - } \overset {} \rightleftharpoons {\text{Ti}}^{\text{III}} - {\text{OH}}^{ - } $$

(3)

$$ {\text{Ti}}^{\text{IV}} + e_{\text{CB}}^{ - } \mathop{\longrightarrow}\limits{{}}{\text{Ti}}^{\text{III}} $$

(4)

Electron–hole recombination:

$$ {\text{Ti}}^{\text{IV}} - {\text{OH}}^{ \bullet } + e_{\text{CB}}^{ - } \mathop{\longrightarrow}\limits{{}}{\text{Ti}}^{\text{IV}} {\text{OH}}^{ - } $$

(5)

$$ {\text{Ti}}^{\text{III}} + h_{\text{VB}}^{ + } \mathop{\longrightarrow}\limits{{}}{\text{Ti}}^{\text{IV}} $$

(6)

$$ h_{\text{VB}}^{ + } + e_{\text{CB}}^{ - } \mathop{\longrightarrow}\limits{{}}{\text{heat}} $$

(7)

Reactions in aqueous medium:

$$ {\text{Ti}}^{\text{IV}} - {\text{H}}_{2} {\text{O}} + h_{\text{VB}}^{ + } \mathop{\longrightarrow}\limits{{}}{\text{Ti}}^{\text{IV}} - {\text{OH}}^{ \bullet } + {\text{H}}^{ + } $$

(8)

$$ {\text{Ti}}^{\text{III}} + {\text{O}}_{2} \overset {} \rightleftharpoons {\text{Ti}}^{\text{III}} - {\text{O}}_{2}^{ - \bullet } $$

(9)

$$ {\text{Ti}}^{\text{IV}} - {\text{O}}_{2}^{ - \bullet } + 2{\text{H}}^{ + } + e_{\text{CB}}^{ - } \overset {} \rightleftharpoons {\text{Ti}}^{\text{IV}} - {\text{H}}_{2} {\text{O}}_{2} $$

(10)

$$ {\text{Ti}}^{\text{IV}} - {\text{O}}_{2}^{ - \bullet } + {\text{H}}^{ + } \overset {} \rightleftharpoons {\text{Ti}}^{\text{IV}} - {\text{HO}}_{2}^{ \bullet } $$

(11)

$$ {\text{Ti}}^{\text{IV}} - 2{\text{HO}}_{2}^{ \bullet } \mathop{\longrightarrow}\limits{{}}{\text{Ti}}^{\text{IV}} - {\text{H}}_{2} {\text{O}}_{2}^{{}} + {\text{O}}_{2} $$

(12)

$$ {\text{Ti}}^{\text{IV}} - {\text{H}}_{2} {\text{O}}_{2}^{{}} + e_{\text{CB}}^{ - } \mathop{\longrightarrow}\limits{{}}{\text{Ti}}^{\text{IV}} - {\text{OH}}^{ \bullet } + {\text{OH}}^{ - } $$

(13)

$$ {\text{Ti}}^{\text{IV}} - {\text{H}}_{2} {\text{O}}_{2}^{{}} + {\text{O}}_{2}^{ - \bullet } \mathop{\longrightarrow}\limits{{}}{\text{Ti}}^{\text{IV}} - {\text{OH}}^{ \bullet } + {\text{OH}}^{ - } + {\text{O}}_{2} $$

(14)

Adsorption–desorption of a reductant (e.g., any organic substrate S):

$$ {\text{Ti}}^{\text{IV}} + S\overset {} \rightleftharpoons {\text{Ti}}^{\text{IV}} - S $$

(15)

$$ {\text{Ti}}^{\text{IV}} - {\text{OH}}^{ \bullet } + S\overset {} \rightleftharpoons {\text{Ti}}^{IV} - {\text{OH}}^{ \bullet } - S $$

(16)

Adsorption–desorption of an oxidant (e.g., metal ion)

$$ {\text{Ti}}^{\text{IV}} + M^{{{\text{n}} + }} \overset {} \rightleftharpoons {\text{Ti}}^{\text{IV}} - M^{{{\text{n}} + }} $$

(17)

Photooxidation of a reductant:

$$ {\text{Ti}}^{\text{IV}} - S + {\text{Ti}}^{\text{IV}} - {\text{OH}}^{ \bullet } \mathop{\longrightarrow}\limits{{}}{\text{Ti}}^{\text{IV}} + {\text{Ti}}^{\text{IV}} - I\mathop{\longrightarrow}\limits{{}}{\text{CO}}_{2} + {\text{H}}_{2} {\text{O}} $$

(18)

$$ {\text{Ti}}^{\text{IV}} - S + {\text{OH}}^{ \bullet } \mathop{\longrightarrow}\limits{{}}{\text{Ti}}^{\text{IV}} - I\mathop{\longrightarrow}\limits{{}}{\text{CO}}_{2} + {\text{H}}_{2} {\text{O}} $$

(19)

$$ {\text{Ti}}^{\text{IV}} - {\text{OH}}^{ \bullet } - S\mathop{\longrightarrow}\limits{{}}{\text{Ti}}^{\text{IV}} - I\mathop{\longrightarrow}\limits{{}}{\text{CO}}_{2} + {\text{H}}_{2} {\text{O}} $$

(20)

$$ {\text{Ti}}^{\text{IV}} - S + {\text{Ti}}^{\text{IV}} (h_{\text{VB}}^{ + } )\mathop{\longrightarrow}\limits{{}}{\text{Ti}}^{\text{IV}} + {\text{Ti}}^{\text{IV}} - I\mathop{\longrightarrow}\limits{{}}{\text{CO}}_{2} + {\text{H}}_{2} {\text{O}} $$

(21)

Adsorption–desorption of the organic intermediate:

$$ {\text{Ti}}^{\text{IV}} + I\overset {} \rightleftharpoons {\text{Ti}}^{\text{IV}} - I $$

(22)

Photoreduction of a metal ion:

$$ {\text{Ti}}^{\text{IV}} - M^{{{\text{n}} + }} + {\text{me}}^{ - } \mathop{\longrightarrow}\limits{{}}{\text{Ti}}^{\text{IV}} - M^{{({\text{n}} - {\text{m}}) + }} $$

(23)

When TiO₂ or any semiconductor oxide is irradiated with UV light of energy greater than or equal to its bandgap (E _BG), valence band holes ($h_{\text{VB}}^{ + }$) and conduction band electrons ($e_{\text{CB}}^{ - }$) are produced (reaction 1). Hoffmann et al. [8] have found by laser flash photolysis studies that the characteristic time scale for this charge-carrier generation reaction is of the order of femtoseconds (fs). The charge carriers generated get trapped on the TiO₂ surface, which occurs over a time scale of tens of nano seconds (ns). Reaction 2 represents the trapping of the holes by the surface hydroxyl groups present in TiO₂, and reactions 3–4 represent the reversible trapping of the electrons on the surface of TiO₂ (shallow traps), and the irreversible trapping or relaxation of the electrons in the bottom of the conduction band (CB) (deep traps), respectively. Ti^IV denotes the four coordinated surface functionality of TiO₂ or the “active site”. An important reaction that competes with the charge-carrier trapping is the electron–hole recombination reaction. As shown by reactions 5–7, electron–hole recombination can occur either at the surface states of the TiO₂, or in the bulk medium due to the delocalization of the electrons and holes from the surface. This is one of the most detrimental reactions in photocatalysis as this affects the interfacial charge transfer processes and hence the quantum efficiency of the photoprocess. Hence, several techniques have been adopted to modify the semiconductor surface to increase the lifetime of the charge carriers by introducing surface trapping sites by the deposition of noble metals or transition metals. Due to the contact between the semiconductor and the metal, electrons flow from the CB of the semiconductor to the metal, until the Fermi levels of the two materials are aligned. This results in enhanced charge-carrier separation.

In an aqueous medium, valence band (VB) holes can react with the surface adsorbed water molecules to from hydroxyl species (reaction 8), and the trapped CB electrons can react with the dissolved oxygen in the system to form superoxide radicals (reaction 9). These superoxide radicals then undergo a series of reactions 10–14 with the solvated protons and the CB electrons to form hydrogen peroxide, hydroperoxy radicals, hydroxyl anions and hydroxyl radicals. Thus, hydroxyl radicals are generated by both the hole and electron pathways of photocatalysis. When the reactions are carried out in a non-aqueous (organic) medium, the surface bound hydroxyl species present in the semiconductor plays a major role (reaction 2), and the contribution of reactions 8–14 for the overall oxidation of the substrate is negligible.

The next reaction in the sequence is the adsorption of the target material (oxidant or reductant) onto the active sites of the photocatalyst. This is one of the crucial steps in heterogeneous photocatalysis as the reactions take place on the surface of the semiconductor photocatalyst. This is followed by the oxidation of the reductant and the concomitant reduction of the oxidant by the attack of the hydroxyl radicals and CB electrons, respectively. The characteristic time scales for the above two processes are of the order of 100 ns and ms, respectively [8, 13]. This shows that the oxidizing powers of VB holes and hydroxyl radicals are always higher than that of the reducing power of the CB electrons. Moreover, these interfacial electron transfer steps compete with the electron–hole recombination reaction (10 ns), and hence, the practical efficiency or quantum yield is always lower than that of the theoretical yield. Reactions 18–21 denote the different possibilities by which the surface bound or solvated hydroxyl radicals and the VB holes can attack and degrade organic materials. Initially, organic intermediates are formed, which, on longer exposure to UV radiation, undergo mineralization to form CO₂ and H₂O. Once the reaction is complete, the unreacted reactants, intermediates and the products desorb from the surface of the catalyst (reactions 15–17, 22). Similarly, when metal ions are present in the system, they are reduced to their thermodynamically stable oxidation states by the CB electrons (reaction 23). This opens up a possibility to reduce the metal ions from their toxic to non-toxic states (e.g., Cr⁶⁺–Cr³⁺) by photocatalysis. Therefore, the overall photocatalysis reaction can be represented by reaction 24, wherein, the oxidants are reduced and the reductants are oxidized by the action of UV radiation on the semiconductor photocatalyst.

$$({\text{Ox}}_{1} )_{\text{ads}} + ({\text{Red}}_{2} )_{\text{ads}}\mathop{\longrightarrow}\limits^{{\text{hv/TiO}_{2}}}{\text{Red}}_{1}+ {\text{Ox}}_{2}$$

(24)

3 Semiconductor Photocatalytic Materials

Several metal oxides (TiO₂, ZnO, MoO₃, CeO₂, ZrO₂, WO₃, α-Fe₂O₃, SnO₂, SrTiO₃) and metal chalcogenides (ZnS, CdS, CdSe, WS₂, MoS₂) can be used as photocatalysts [10, 12, 17, 18]. However, energetics dictates that, for a semiconductor photocatalyst to be active, the redox potential of photogenerated VB holes must be sufficiently positive to generate hydroxyl radicals and that of CB electrons must be sufficiently negative to generate superoxide radicals. Figure 2 depicts the band structure diagram of the different materials, which have been tested for the photooxidation of organic compounds. It is clear that, TiO₂, ZnO, SrTiO₃ and CdS exhibit favorable bandgap positions compared to the other materials. The material selection is also based on the stability of the material toward photocorrosion. For example, ZnO and CdS have only one stable oxidation state (+2), and are prone to decomposition by VB holes. Furthermore, ZnO undergoes incongruous dissolution, yielding Zn(OH)₂ on the surface, thereby leading to the deactivation of the material over a period of time [18]. However, Ti in TiO₂ is capable of reversibly changing its oxidation state from +4 to +3; hence, TiO₂ is more favorable compared to the other materials. Between the two common crystal structures of TiO₂, viz., anatase and rutile—anatase phase TiO₂ is widely used in photocatalysis while rutile phase TiO₂ is used in pigments. Although rutile phase TiO₂ possesses a smaller band-gap energy (3.0 eV) compared to anatase phase (3.2 eV), indicating the possibility of the absorption of longer wavelength radiation, the former exhibits a higher photoactivity because of the position of the CB edge, which is more negative. This shows that TiO₂-anatase possesses a higher reduction power compared to that of TiO₂-rutile. In addition to the above advantages, other factors like its non-toxic nature (environmentally benign), low cost and the ease of synthesis makes TiO₂ the “photocatalyst of choice” for photocatalytic degradation reactions.

Fig. 2

Band gap energy and band edge positions of different semiconductor oxides and chalcogenides, along with selected redox potentials [12, 17, 22]

4 Synthesis and Properties of TiO₂

Different methodologies are being adopted for the synthesis of TiO₂. Many studies have concentrated on the synthesis of “nano-sized” TiO₂ for applications in photocatalysis. The importance of the nanometer regime stems from the fact that the physical, chemical, electrical and optical properties of the materials change immensely from the macroscopic to the nanoscale. One important property of nanoscale materials is the high surface to volume ratio of the material, which is beneficial to catalysis. This results in catalytic materials with high surface area and high porosity, which can promote high reaction rates owing to the high level of interaction of the reactants on the surface. Another important property is the efficient transport of the electrons and holes across the band gap of the material, which is governed by quantum confinement. The bandgap of the photocatalyst also dictates the wavelength at which the material can be excited. Hence, lower bandgap energies are beneficial for visible light absorption.

TiO₂ photocatalysts have been synthesized in different shapes and morphologies, which include, nanoparticles, nanorods, nanotubes, nanopillars and nanowire arrays, nanobowls, nanowhiskers, aerogels, nanosheets, opal and inversed opals [12, 14]. The synthesis routes can be broadly classified as solution phase and gas phase techniques. Solution phase synthesis is the most preferred technique for the preparation of TiO₂ in the form of powders and thin films. Some of the solution phase techniques are the precipitation method, hydrothermal synthesis, solvothermal synthesis, sol–gel method, sol method (nonhydrolytic sol–gel), micelle and inverse micelle method, combustion synthesis, electrochemical synthesis, sonochemical synthesis and microwave synthesis methodologies. Gas phase technique is widely employed for the synthesis of thin film samples. Some of the gas phase techniques are chemical vapor deposition (CVD), physical vapor deposition and spray pyrolysis deposition. Each of the above synthesis methods possesses a unique advantage over the other techniques, and the characteristics of the final product vary from one method to another. The review article by Chen and Mao [14] discusses each of the above synthesis techniques in detail, with particular emphasis on the morphology, size, shape and properties of the final TiO₂ product obtained in each method. Table 1 [23–30] presents a representative list of the different techniques adopted for the synthesis of TiO₂. These works elucidate that the final properties of TiO₂ nanoparticles like the phase composition (anatase : ru-tile), particle size, porosity, surface area, band gap and surface hydroxyl content can be tailored by varying the reaction conditions like: the precursor compound (TiCl₄, titanium(IV) isopropoxide, etc.), fuel (glycine, oxalyl dihydrazide, hexamethylene tetramine in the case of solution combustion synthesis), hydrolyzing agent (in the case of sol–gel synthesis), molar composition of the reactants, reaction temperature, reaction time (ageing time), calcination temperature and presence of gas atmosphere (air, Ar, NH₃).

Table 1 Physicochemical properties of nano-TiO₂ by various synthesis techniques

One of the synthesis methodologies that has been proven to yield nano-TiO₂ with enhanced characteristics is the solution combustion method (CS TiO₂), developed by Nagaveni et al. [26]. CS TiO₂ exists in anatase phase, possesses a smaller particle size, higher surface area, lower band gap, higher amount of surface hydroxyl species and a highly acidic surface compared to the commercial P-25 TiO₂ (DP-25) produced by Degussa corporation. Figure 3 shows the UV/visible spectra and thermogravimetric analysis of CS TiO₂ and DP-25. It is clear that CS TiO₂ exhibits strong absorption in the visible region due to the carbide ion substitution for oxide ion, of the form TiO_2−2xC_xV_x, where ‘V’ denotes the oxide ion vacancy. Moreover, CS TiO₂ exhibits a higher weight loss compared to DP-25, indicating the presence of higher amount of surface hydroxyl groups. Table 2 [26, 31–35] compares the characteristics of CS TiO₂ with the other commercially available TiO₂ samples. It is evident that the activity of the photocatalyst cannot be standardized based on any single property, but by striking a balance between the different physicochemical properties. In a series of publications it was shown that the photoactivity of CS TiO₂ toward the photooxidation of different class of dyes [36–38], phenolic compounds like chlorophenols, nitrophenols and multiple substituted phenols [39, 40], substituted nitrobenzenes [41], water soluble polymers and plastics [42, 43] and the reduction of metal ions [44], is much higher compared to that of DP-25. More detailed discussions on the degradation of the organic compounds are available in later sections.

Fig. 3

UV/visible absorption spectra of CS TiO₂ and DP-25. The band gap values corresponding to the absorption threshold are shown. Inset: TGA thermograms [26]

Table 2 Comparison of the physicochemical properties of combustion synthesized TiO₂ (CS TiO₂) with commercially available TiO₂ samples

5 UV Photocatalytic Degradation of Organic Compounds

Chlorinated organic compounds like chloroalkanes were the first organic compounds to be degraded by photocatalysis [3, 4, 45]. Besides being widely used as solvents, pesticides, refrigerants and in plasticizers and plastics, these organochlorine compounds are toxic and accumulate in the environment. Hsiao et al. [3], and Pruden and Ollis [4] demonstrated complete mineralization of dichloromethane (CH₂Cl₂), chloroform (CHCl₃), carbon tetrachloride (CCl₄) and trichloroethylene in the presence of TiO₂, to HCl and CO₂. They observed that the chloride ions generated during the reaction act as inhibitors for the conversion of chloroalkanes. A Langmuir–Hinshelwood kinetic model was proposed to find the adsorption and degradation rate coefficients of the chloroalkanes and the chloride ions. The relative order of degradation of the chloromethanes is: CHCl₃ > CH₂Cl₂ > CCl₄.

A general stoichiometric reaction for the photocatalytic degradation of any organochlorine compound can be written as [8]:

$${\text{C}}_{x} {\text{H}}_{y} {\text{Cl}}_{z} + \left( {x + \frac{y- z}{4}} \right){\text{O}}_{2} \mathop{\longrightarrow}\limits^{h\nu,{\text{TiO}}_{2}}x{\text{CO}}_{2} + z{\text{HCl}} + \left( {\frac{y- z}{2}} \right){\text{H}}_{2} {\text{O}}$$

(25)

Many studies have been devoted to the photocatalytic degradation of chlorinated aromatic compounds like chlorophenols and chlorobenzenes, chlorinated pesticides like DDT, hexachlorobenzene, atrazine and parathion, surfactants like sodium dodecyl benzene sulfonate and trimethyl phosphate, aliphatic and olefinic compounds, dyes, nitrogeneous compounds like nitrophenols and nitrobenzenes, carboxylic acids, alcohols and heteroatom compounds. The review articles by Hoffmann et al. [8], Mills and Hunte [10], Legrini et al. [15], Bhatkhande et al. [17] and Blake [46] have discussed the different studies on the photocatalytic degradation of different classes of organic compounds.

Although many organic compounds have been shown to photocatalytically degrade in presence of TiO₂, the mechanism of degradation of phenolic compounds like phenol, chlorophenols, nitrophenols and other substituted phenols, which are used as intermediates in the manufacturing of pesticides and herbicides, is well understood and documented. The degradation proceeds primarily by the attack of hydroxyl radicals, which results in the hydroxylation of the parent compound at the ortho and para-positions, due to the ortho and para-directing nature of the phenolic –OH moiety. These are the primary intermediates, which, upon further exposure, results in the formation of a fully hydroxylated secondary intermediate species. The next step is the fragmentation of the benzene ring to form C-6 and C-5 aliphatic carboxylic acids and aldehydes.

In the case of chloro or nitro-substituted phenols, the hydroxyl group replaces the substituent group before the ring fragmentation. The longer (C-6, C-5, C-4) chain organic acids and aldehydes on longer exposure periods yield C-3, C-2 and C-1 organic acids. Finally, these shorter chain compounds mineralize to form CO₂ and H₂O. Li et al. [47] elucidated the mechanism of formation of the intermediates during the photocatalytic degradation of 4-chlorophenol and 4-chlorocatechol. Figure 4 shows the degradation pathway of phenol and 4-chlorophenol, adapted from different studies [39, 40, 47]. The photocatalytic degradation of phenol and 4-chlorophenol yields catechol, hydroquinone and chlorocatechol as the primary hydroxylated intermediates. Further hydroxylation steps result in the formation of pyrogallol, hydroxy hydroquinone and 4-chloro dihydroxy phenols. This step is followed by the fragmentation of the dihydroxy phenols to form muconic acid and muconic aldehydes with chloro and hydroxy-substitutions. A detailed mechanism of scission of the benzene ring is depicted in Figure 5. Muconic acid further degrades to smaller organic acids like oxalic acid, maleic acid, succinic acid, fumaric acid, acrylic acid, etc. Finally, these acids mineralize to CO₂ and H₂O after long exposure periods.

Fig. 4

Detailed pathway of degradation of phenol and 4-chlorophenol adapted from different studies. Some of the primary and secondary intermediates are identified as Ph—phenol, 4CP—4-chlorophenol, Cat—catechol, HQ—hydroquinone, 4cCat—4-chlorocatechol, PY—pyrogallol, MU—muconic acid and HHQ—hydroxyl hydroquinone [39, 47]

Fig. 5

Mechanism of cleavage of benzene ring in hydroxy hydroquinone, resulting in the formation of carboxylic acids and aldehydes. The possible sites of ring cleavage are represented by broken lines [47]

Sivalingam et al. [39] studied the effects of different substituents like chloro group, nitro group and methyl group on the kinetics of photocatalytic degradation of phenol, and concluded that the order of degradation is: pentachlorophenol > trichlorophenol > dichlorophenol > 4-chlorophenol ≈ 2-chlorophenol > 2-methyl phenol ≈ 3-methyl phenol > phenol. Similarly, Priya and Madras [40] conducted a thorough study on the effect of multiple substitutions of the above groups on the degradation of phenol. Their results indicate that chloro-methylphenols (cresols) degraded much faster compared to chloro-nitrophenols, which was attributed to the ring deactivating nature of the nitro group for the hydroxyl radicals to react with the phenolic compound. Another interesting conclusion of their study shows that the degradation is independent of the position of the substituents, but depends on the nature of the substituent group. In another study [41], it was found that chloro and hydroxy-substitution in nitrobenzene accelerated the degradation rate, while nitro-substitution resulted in a reduced degradation rate of nitrobenzene.

Other important organic compounds, which have attracted interest in the past decade, include dyes, pesticides and pharmaceutical compounds. The forthcoming sections will examine the various studies on the photocatalytic degradation of these pollutants.

5.1 Dyes

Dyes constitute a major class of organic compounds, which find a multitude of applications in our daily life in clothing, food, paper, leather, cosmetics, plastics, drugs, electronics and printing. The modern textile industry consumes about 80% of all synthetic dyes produced, with 700,000 tons of dyes applied to 40 million tons of fabric annually [48]. One of the major bottlenecks in the textile industry is dye fixation (i.e., spent dye baths, residual dye liquors and water from washing operations contain dye in the hydrolyzed and unfixed form). Although dye fixation depends on the class of the dye, type of fabric and other dyeing parameters, nearly 10% of the dyes used are discharged into the effluent as a result of this process. Hence, reducing the toxicity levels to permissible limits before admitting the dye waste water to aquatic bodies is a critical issue. In this regard, photocatalysis, as an AOP, has played a significant role in the degradation of textile dye effluents. Many reviews exclusively discuss the degradation of different classes of dyes under UV and visible light exposure [48–50], various parameters affecting the degradation of dyes [51], and modified TiO₂ materials for the degradation of dyes [52].

Based on the functional group that constitutes the dye molecules, dyes can be classified as azoic, anthraquinonic, heteropolyaromatic, aryl methane, xanthene, indigo, acridine, nitro, nitroso, cyanine and stilbene. Among all the above dye functionalities, photodegradation of azo dyes has been investigated extensively [50], as these dyes contribute 50% of the commercial dyes. The degradation of a dye can be characterized in two ways: percent decolorization and percent mineralization. Decolorization refers to the reduction in concentration of the parent dye molecule under consideration at its characteristic wavelength, but does not refer to the complete removal of the organic carbon content. This is due to the formation of colored dye intermediates, which might absorb at a different wavelength. Hence, complete degradation or mineralization occurs when all the organic carbon is converted to CO₂. Therefore, analyzing the mineralization of the dyes in terms of the total organic carbon (TOC) content assumes importance. The mechanism of CO₂ evolution from an organic dye intermediate is well-documented and it follows the photo-Kolbe decarboxylation mechanism [53]. The reaction is given by:

$$ \Upphi - {\text{COO}}^{ - } + h_{\text{VB}}^{ + } \mathop{\longrightarrow}\limits{{}}\Upphi^{ \bullet } + {\text{CO}}_{2} $$

(26)

In Eq. 26, $\Upphi$ denotes the organic component of the dye or the dye intermediate. The radical $\Upphi^{\bullet}$ formed as a result of this reaction can undergo further transformation to yield other intermediates with smaller sizes.

Epling and Lin [54] degraded 15 dyes belonging to different classes of functionality in the presence of visible light. Their results show that the presence of electron withdrawing groups retards the degradation of the dye. The order of degradation among the different dyes follows this order: indigo ≈ phenanthrene > triphenyl methane > azo ≈ quinoline > xanthenes ≈ thiazine > anthraquinone. Moreover, the order of degradation of the dyes in the presence of different light sources follows: natural sunlight ≫90 W halogen flood light >150 W spotlight. They have attributed the degradation of the dye to both photosensitized oxidation and reduction mechanisms.

Vinu et al. [38] studied the degradation of 5 anionic, 8 cationic and 3 solvent dyes, each belonging to a different class by molecular structure, with CS TiO₂ and DP-25 in the presence of UV irradiation. It was observed that the order of degradation of the dyes with CS TiO₂ and DP-25 was different, and this was correlated to the surface charge of the catalysts. By monitoring the shift in the characteristic wavelength of the dyes during degradation, it was concluded that the formation and consumption rates of the intermediates were high in the presence of highly acidic surface of CS TiO₂, while significant amounts of intermediates were observed in the presence of DP-25. Overall, anionic dyes exhibited higher decolorization rates compared to the cationic dyes, and the solvent dyes exhibited adsorption dependent degradation.

Silva et al. [55] studied the degradation of mono, di and tri-azo dyes and found that the decolorization followed the order: Solophenyl Green BLE (tri-azo) > Erionyl Red B (di-azo) > Chromotrop 2R (mono-azo). However, the mineralization of the dyes followed the opposite trend. All the above studies suggest that a correlation does not exist between the degradation rate of the dye with the dye structure or the functional groups that characterize the dye. Therefore, it is important to analyze the pathway of degradation of the dyes in order to assess the stability of the different intermediates.

A representative list of the studies devoted to the analysis of the organic intermediates during the degradation of the dyes is presented in Table 3 [53, 56–63]. Rajeshwar et al. [48] provided an extensive list of the studies on the degradation pathway of azo and non-azo dyes. A generalized conclusion is that alkyl substituted (methyl or ethyl) dyes like triphenyl methane or rhodamine dyes degrade by the N-de-alkylation mechanism, which involves the abstraction of the alkyl groups by the hydroxyl radicals resulting in the formation of the corresponding aldehyde as a side product. Once complete dealkylation occurs, fragmentation of the molecule occurs, which results in the formation of different substituted benzene compounds. At long exposure periods, the cleavage of benzene ring results in the formation of low molecular weight organic acids. The degradation of azo dyes involves the cleavage in the vicinity of the azo bond and results in the formation of naphthol and benzoic acid intermediates. Likewise, the degradation pathway of anthraquinone dyes result in the formation of phthalic acid intermediates.

Table 3 Survey of the organic intermediates formed during the photocatalytic degradation of different classes of dyes

The dye molecules also contain other hetero atoms like N, S, Br and Cl in their structure, and hence, an assessment of the fate of these elements during mineralization is also critical. It has been well established that sulfonate groups (–SO₃ ⁻) in anionic dyes are transformed to innocuous sulfate ions (SO₄ ²⁻), primary (–NH₂) and secondary (–NH–) amino groups are converted into ammonium ions (NH₄ ⁺), azo nitrogen (–N=N–) is converted to N₂ and halogen atoms are released into the solution as their respective anions. The following reactions describe the mechanism by which the above transformations take place [53]:

Formation of sulfate ions:

$$ \Upphi - {\text{SO}}_{3}^{ - } + {\text{OH}}^{ \bullet } \to \Upphi - {\text{OH}} + {\text{SO}}_{3}^{ \bullet - } $$

(27)

$$ {\text{SO}}_{3}^{ \bullet - } + {\text{OH}}^{ - } \to {\text{H}}^{ \bullet } + {\text{SO}}_{4}^{2 - } $$

(28)

Formation of ammonium ion:

$$ \Upphi - {\text{NH}} - \Upphi ' + {\text{H}}^{ \bullet } \to \Upphi^{ \bullet } + \Upphi ' - {\text{NH}}_{2} $$

(29)

$$ \Upphi ' - {\text{NH}}_{2} + {\text{H}}^{ \bullet } \to \Upphi^{' \bullet } + {\text{NH}}_{3} $$

(30)

$$ {\text{NH}}_{3} + {\text{H}}^{ + } \to {\text{NH}}_{4}^{ + } $$

(31)

Formation of N₂:

$$ \Upphi - {\text{N}} = {\text{N}} - \Upphi ' + {\text{H}}^{ \bullet } \to \Upphi - {\text{N}} = {\text{N}}^{ \bullet } + \Upphi ' - {\text{H}} $$

(32)

$$ \Upphi - {\text{N}} = {\text{N}}^{ \bullet } \to \Upphi^{ \bullet } + {\text{N}} \equiv {\text{N}} $$

(33)

Formation of chloride/bromide ions:

$$ \Upphi - {\text{Cl}}/{\text{Br}} + {\text{OH}}^{ \bullet } \to \Upphi - {\text{OH}} + {\text{Cl}}^{ - } /{\text{Br}}^{ - } $$

(34)

5.2 Pesticides

Pesticides encompass a class of organic compounds used for preventing, destroying or controlling pests. These are widely applied on agricultural crops to protect them from insects, pathogens, weeds, moths, microbes, etc. However, the continuous usage of pesticides results in poor soil quality, reduced nitrogen fixation for plants and poisoned food sources. Also serious is the transfer of these compounds to water bodies by leaching, percolation, spillage or runoff, which poses ill-effects to human health and other forms of life. Based on the chemical structure, pesticides can be classified as organochlorine compounds, organophosphorous compounds and carbamate compounds, which contain nitrogen, phosphorous, sulfur, chlorine and heterocyclic nitrogen atoms. Therefore, the mineralization of pesticides should result in the conversion of these hazardous compounds to innocuous products of N, S and P, along with CO₂ and H₂O.

A variety of pesticides like atrazine (s-triazine) [64], propanil (acetanilide) [64], molinate (thiocarbamate) [64], pyridaben [65], methamidophos [66], methyl parathion [67], cyproconazole [68], hexachloro benzene [69], dicofol [69], pyrimethanil (fungicide) [70], primicarb (insecticide) [70], propyzamide (herbicide) [70], etc., have been photocatalytically degraded using TiO₂. Many studies have proposed a detailed pathway of degradation of the pesticides by monitoring the formation of intermediates by HPLC/MS/MS and GC/MS techniques. It was found that, during mineralization, phosphorous is converted to orthophosphoric acid (H₃PO₄), nitrogen to NO₃ ⁻ and NH₄ ⁺ ions and sulphur to SO₄ ²⁻ ions. Figure 6 depicts the pathway of degradation of triazophos, an organophosphorous pesticide [71].

Fig. 6

Pathway of degradation of the pesticide, triazophos, established using LC/MS/MS and GC/MS/MS [71]

5.3 Pharmaceutical Compounds

Recently, photocatalytic degradation of pharmaceutical compounds and drugs has received attention, as these compounds are found in the effluents in levels ranging from ng L⁻¹–μg L⁻¹. These compounds are admitted into waste water and aquatic bodies by manufacturing operations, spillage, human and animal excretion and hospital wastes. Besides leading to serious hazards like genotoxicity, endocrine disruption and aquatic toxicity, these xenobiotic substances increase the resistance of the pathogenic bacteria in waste water. These compounds are resistant toward biological degradation and other common oxidation techniques, and thus, build up their concentration in the ecosystem. In fact, clofibric acid, which is used as a regulator of lipids in the blood, is still detected in lakes and rivers, even after 21 years of persistence in the environment [72]. Therefore, photocatalysis has emerged as an alternative for the effective degradation and mineralization of these persistent organic pollutants.

The different pharmaceutical compounds that were subjected to photocatalytic degradation using TiO₂ are listed in Table 4 [72–79]. The degradation of a wide class of compounds has been studied, and many studies have optimized the reaction parameters like pH, O₂ concentration and TiO₂ loading for maximum conversion of the parent drug compound. Most of these studies have also established the pathway of degradation of the pharmaceutical compounds, by following the evolution of the intermediates via mass spectroscopy. A generalized conclusion in each of the above studies is that the time taken for the complete mineralization of the pharmaceutical compound was longer compared to the removal of the parent compound. Calza et al. [80] studied the photocatalytic degradation and ecotoxicity of amiloride, a diuretic agent, and concluded that although amiloride is non-toxic, the degradation intermediates were toxic compounds. Similar results were also observed for salbutamol [79], indicating the importance of complete mineralization of the drug to CO₂, H₂O and inorganic ions. Figure 7 depicts the pathway of degradation of diclofenac, a non-steroidal anti-inflammatory drug [78].

Table 4 Listing of recent studies on the photocatalytic degradation of different pharmaceutical compounds

Fig. 7

Degradation pathway of the non-steroidal anti-inflammatory drug, diclofenac, established using ESI–MS. The dotted lines in the compounds 2 and 7 shows that the hydroxyl radicals can attack either of the benzene rings to form the intermediate [78]

6 Photocatalytic Destruction of Microorganisms

Microorganisms like pathogenic bacteria, fungi, viruses and protozoa in drinking water and air pose a severe threat to human and animal life; they are the primary carriers of infectious diseases like gastroenteritis, cholera, tuberculosis, anthrax, malaria and yellow fever. Conventional disinfection technologies employ chlorine, chlorine dioxide (ClO₂), hypochlorite (OCl⁻) or ozone as disinfectants, owing to their low operating cost and applicability in a wide pH range. However, the byproducts of the above techniques involve the formation of halomethanes and halo acetic acids, which are carcinogenic even at low concentrations. Hence, photolytic (UV-C radiation at 254 nm) and photocatalytic disinfection (UV-A at 365 nm or visible radiation) of microorganisms, using TiO₂ as the photocatalyst has been researched extensively for the past two decades. Table 5 [81–90] shows the different studies devoted to the deactivation of various kinds of microorganisms using different semiconductor materials. Among the different microorganisms, Escherichia coli (E. coli), a Gram negative rod shaped bacterium, owing to its presence in the intestines of humans, animals and birds, serves as a biological indicator to test environmental samples for fecal contamination. Unlike organic compounds, the concentration of microorganisms is usually expressed in terms of the number of colony forming units per mL of the solution (cfu mL⁻¹). CFU refers to the number of viable microbial colonies, which are measured by counting the cell aggregates on an agar plate.

Table 5 Photocatalytic disinfection of microorganisms using TiO₂ in presence of UV and visible light radiation

Cho et al. [91] evaluated the inactivation of E. coli under different light intensities, TiO₂ concentration and pH, and have observed a linear correlation of the inactivation time (for 2-log reduction) with the hydroxyl radical concentration in the system. This study suggests that hydroxyl radicals are more important than the reactive oxygen species, and that they are 1000–10000 times as effective as common oxidants like chlorine, chlorine dioxide or ozone for the disinfection of E. coli. The mechanism of photocatalytic disinfection of microorganisms is different from that of the degradation and mineralization of organic compounds, although the hydroxyl radicals are the precursors of degradation in both the cases. The primary reason concerning the complex nature of inactivation of microorganisms is due to their large size and complex structure compared to organic molecules. This results in several pathways of cell rupture and regeneration.

Many modes of cell wall damage of the microorganisms have been proposed. Matsunaga et al. [92] observed a decrease in Coenzyme A (CoA) content in the cell and a concomitant increase in concentration of the dimeric form of CoA, when E. coli was irradiated in presence of TiO₂. Since the electron transfer between the cell and the TiO₂ is mediated by CoA, the reduction in its concentration was attributed to cell damage. Saito et al. [93] observed a “rapid” leakage of potassium ions and the “slow” release of protein and RNA during the lysis of Streptococcus sobrinus, in presence of UV/TiO₂. Thus, they concluded that the inactivation is due to the loss of permeability of the cell wall of the bacteria. Maness et al. [94] have observed an exponential increase in the concentration of malondialdehyde during the inactivation of E. coli, suggesting that the active species like hydroxyl, hydroperoxy and superoxide radicals attack the polyunsaturated phospholipids in E. coli, which results in lipid peroxidation and hence the loss of respiratory activity of the cell.

Thus, it is unequivocally accepted that the cell wall damage induced by the active species in presence of UV/TiO₂ is the primary cause for the death of the microorganisms. However, it must be ensured that complete disinfection (99.999%) takes place and microorganisms are indeed in their inactive state, even after the irradiation and/or TiO₂ is removed from the system. This is because, the presence of active bacteria may result in their reproduction, as organic compounds like aldehydes, ketones and carboxylic acids, which are usually the products of cell damage, serve as nutrients for further growth. It has widely been observed that the inactivation rate of microorganisms in pure, deionized water is higher compared to that in the presence of tap water or water contaminated with ionic species or humic substances [95]. This is due to the osmotic stress in deionized water, which results in the easy leakage of potassium, calcium and magnesium ions through the cell membrane, thereby leading to the loss of permeability. Moreover, humic substances compete for the reactive radicals, which results in the inhibition of the disinfection rate.

From Table 5, it is clear that TiO₂ and its modified forms have shown superior photocatalytic activity for the disinfection of a wide class of Gram-positive and Gram-negative bacteria and other microorganisms in water, both in presence of UV and visible light irradiation. The initial concentration of the microorganisms that is widely used in the recent works corresponds to 10³–10⁹ cfu mL⁻¹. It is also interesting to note that the optimum catalyst concentration varies widely across the different studies, suggesting the strong dependence on the intensity of irradiation, with high intensities requiring lesser catalyst loading. Pal et al. [96] recently evaluated the disinfection of air borne E. coli in a continuous annular reactor in presence of TiO₂. Complete inactivation of E. coli was observed using UV-A irradiation of 3.4 mW cm⁻² intensity, 85% relative humidity and 1516 mg m⁻² of TiO₂, within a residence time of 1.1 min. Recently, Ag is incorporated into TiO₂, either on the surface or in the lattice, to enhance the biocidal activity of bare TiO₂ [85–87]. The advantages of having Ag as a component in the photocatalyst are three fold: (i) Ag⁺ ions possess an inherent antimicrobial activity, which complements the disinfection ability of TiO₂, (ii) Ag, when impregnated on the surface of TiO₂, acts as electron trapping sites, which retards the unwanted charge-carrier recombination, (iii) nano-sized Ag promotes the formation of electrons in presence of visible radiation, due to the surface-plasmon excitation. These electrons are transferred to the conduction band of TiO₂, thereby leading to the formation of reactive superoxide radicals. However, it has been observed in a recent study that an optimum loading of 1% Ag onto TiO₂ yielded a maximum rate of disinfection of E. coli [85]. The synthesis of Ag nanoparticles and their incorporation onto different substrates by different techniques, and the anti-microbial activity are discussed elsewhere [97].

7 Effect of Reaction Conditions

7.1 Temperature

Minor incremental changes in temperature do not significantly affect the rate of photocatalytic reactions. However, higher temperatures might result in the reduction of dissolved oxygen in the solution. Dissolved oxygen is one of the key elements in photocatalysis, as it aids in scavenging CB electrons, thereby leading to the formation of hydroxyl radicals by the electron pathway. Moreover, higher temperatures result in desorption of the organic compounds from the surface of the photocatalyst. Because photocatalytic degradation is a surface mediated phenomenon, desorption of the organic compound before the reaction results in a decrease in the reaction rate. Naeem et al. [98] studied TiO₂ photocatalyzed degradation of phenol, 4-chlorophenol and 4-nitrophenol in the temperature range 25–45°C and found that increasing the temperature does not significantly enhance the degradation rates. The apparent activation energy of photocatalytic degradation ranges from 9.68 to 21.44 kJ mol⁻¹, which is much lower than that of thermal degradation reactions (e.g., 66.5 kJ mol⁻¹ for the thermal degradation of poly(α-methyl styrene) in solution [99]).

7.2 pH

Photocatalytic degradation reactions are highly sensitive to pH of the reaction mixture. This is due to the fact that the adsorption of the organic compound onto the photocatalyst surface, and, therefore, the degradation reaction depends on the surface charge of the photocatalyst and also on the ionization state of the organic compound. TiO₂ exists in the following protonated and deprotonated forms in acidic and basic medium, respectively [48].

Acidic medium:

$$ > {\text{Ti}} - {\text{OH}} + {\text{H}}^{ + } \overset {} \rightleftharpoons > {\text{Ti}} - {\text{OH}}_{2}^{ + } $$

(35)

Basic medium:

$$ > {\text{Ti}} - {\text{OH}} + {\text{OH}}^{ - } \overset {} \rightleftharpoons > {\text{TiO}}^{ - } + {\text{H}}_{2} {\text{O}} $$

(36)

Hence, the adsorption of positively charged organic compounds is facilitated at a basic pH, while that of negatively charged species is favorable at an acidic pH of the TiO₂ surface. In this regard, pH_zpc, the zero-point charge pH or the isoelectric pH of the TiO₂ photocatalyst plays a crucial role. At a pH < pH_zpc, the TiO₂ surface becomes positively charged (acidic), while at a pH > pH_zpc, it becomes negatively charged (basic). The effect of pH on the photocatalytic degradation of dyes was extensively reviewed by Konstantinous and Albanis [50], and Akpan and Hameed [51]. Sivalingam et al. [39] observed that dyes like Orange G (anionic) and Methyl Red (neutral) degrade at higher rates at low pH (4.1) values, while Congo Red (anionic) and Alizarin Red S (anionic) degrade at high pH (9.1) values. Devi et al. [100] investigated the degradation of anionic and cationic dyes in presence of Mo⁶⁺ ion-substituted TiO₂ under different pH’s, and correlated the degradation behavior of the dyes with the adsorption tendency of the dye at different pH levels. They observed that the rate coefficients for the degradation of anionic dyes were higher at an acidic pH (5.6), while that of cationic dyes were higher at a basic pH (8.0). Therefore, it can be concluded that pH is a very complex parameter, which depends both on the surface charge of the photocatalyst and the nature of the organic compound, and hence, it is difficult to standardize the pH conditions for the degradation of a specific class of organic compounds. However, for the inactivation of microorganisms, it was found that the disinfection rate is nearly the same in the pH range of 4–9. This was attributed to the acid-induced proteins in E. coli and Salmonella typhimurium, which impart acid tolerance to these cells [95, 101].

7.3 Wavelength and Intensity of the Light Source

The properties of the UV light source, viz., the wavelength and intensity, play a key role in the excitation of semiconductor photocatalyst and the generation of reactive radicals. Matthews and McEvoy [102] degraded phenol and salicylic acid in the presence of 254 nm (UV-C; germicidal lamp) and 350 nm (UV-A; blacklight fluorescent lamp), and concluded that the photocatalytic degradation rate is higher in presence of 254 nm radiation. This is because of the high energy of the 254 nm photons (112.6 kcal Einstein⁻¹) compared to that of the 350 nm photons (81.7 kcal Einstein⁻¹). However, the thrust to realize photocatalytic degradation in the presence of sunlight or visible radiation has resulted in light sources operating at wavelengths 365 nm and above, preferable to the 254 nm high-energy radiation, which is filtered by the atmosphere.

The intensity of radiation is related to the photon energy flux and quantum yield of the photoprocess. Photon energy flux is defined as the number (or energy) of photons per second per unit area incident on the reaction mixture. It is expressed in terms of the intensity of the incident radiation (I ₀), volume of the reaction mixture (V) and the area of the exposed solution (A) as I ₀ VN _A E _λ/A, where N _A is Avagadro’s number of photons per mole, and E _λ is the energy of the incident photon at wavelength λ. Photon flux is expressed in terms of W m⁻² and is usually determined by chemical actinometric techniques [103]. Quantum yield, $\Upphi$(λ), is defined as the ratio of number of molecules undergoing chemical transformation to the number of photons absorbed in that period of time. As the number of photons absorbed depends on the input energy density of the photons, the intensity of the light source has a positive effect on the photocatalytic degradation rate of an organic compound. Ollis et al. [45] classified the variation of the reaction rate with intensity into three regimes. At low I ₀, the degradation rate is linearly proportional to I ₀; at intermediate I ₀, the degradation rate is proportional to I ^1/2₀ , and at high I ₀, the degradation rate is independent of I ₀, due to mass transfer limitations. Meng et al. [104], by assuming that the total number of H₂O/OH⁻ in the system is insufficient to capture the holes, showed that, in the intensity range from 0.86 to 6.8 mW cm⁻², the adsorption and degradation rate constants signifying the degradation of p-chlorobenzoate vary with the intensity as I ^−1/2 and I ^1/2, respectively. Wu and Chern [105] used a first-order correlation of the form, [hν] = I ₀ exp (−k[TiO₂]), to account for the screening effect of the TiO₂ particles at high intensities of the UV radiation. The nonlinear dependence of the rate coefficients on the UV intensity was predicted by their model. Thus, the effect of light intensity on the photocatalytic degradation rate is not straightforward and is dependent on the reactor configuration and the concentration of the TiO₂ photocatalyst.

7.4 Catalyst Loading

The concentration of the photocatalyst is one of the critical parameters that determines the degradation rate of any organic compound. This is dependent on the volume of the solution being treated and the initial concentration of the organic compound. It has been widely observed that the degradation rate increases with an increase in catalyst loading. This is due to the availability of more active catalyst sites at higher concentrations, which results in the generation of more hydroxyl species. However, when loading is increased beyond an optimum value, there is no appreciable increase in the degradation rate. This is because the catalyst particles scatter light, reducing the effective light intensity reaching the bulk reaction solution. In the literature, 0.4–3.5 g L⁻¹ of catalyst has been used for the photocatalytic degradation of different organic compounds. Sivalingam et al. [36] observed that the optimum loading of CS TiO₂ for the degradation of dyes is 1 g L⁻¹.

The above argument also holds good when the catalyst particles are immobilized on a substrate like fiberglass, glass slides, glass tubes, etc. In such cases the loading is characterized by the surface coverage of the catalyst, denoted as mass per unit area of the substrate. Hence, the number of coating cycles is a critical parameter, which has to be tuned for the maximum degradation rate. Lim et al. [106] have compared the different dip-coating procedures for the immobilization of TiO₂, 5 coating cycles on woven fiberglass exhibited the highest photocatalytic degradation rate for Methylene Blue. However, in another study, it was found that a direct correlation of optimum catalyst loading for the degradation of organic compounds with the deactivation of microorganisms does not exist. The optimum loading in the case of microorganisms is always lesser than that required for the degradation of organic compounds. For the TiO₂ coated glass sheets, the optimum loading was 0.5 mg cm⁻² for the deactivation of E. coli, while it was 1.1 mg cm⁻² for the degradation of atrazine and formic acid, under the same conditions of illumination [101]. Therefore, owing to the economics of the catalyst, an optimum concentration is always favorable to study the photocatalytic degradation of organic compounds.

7.5 Presence of Organic Solvents

Organic solvents pose a deleterious effect on the degradation rate of an organic compound. Epling and Lin [107] observed that the degradation rate of Methylene Blue decreased significantly, when 1% of acetonitrile was added to the reaction mixture. Aarthi and Madras [37] also observed a decrease in the degradation rate of Rhodamine B when the composition of acetonitrile or ethanol was increased in the aqueous medium. This observation is attributed to the fact that the solvation of the CB electrons is reduced in the presence of solvent, which results in the electron–hole recombination. Another possible reason is that the organic solvents scavenge the VB holes, thereby reducing the possibility of generation of hydroxyl radicals. However, organic solvents are beneficial for the partial oxidation of organic compounds to achieve high selectivities for a particular product. This finds applications in the synthesis of fine chemicals by photocatalysis.

7.6 Pollutant Concentration

It is well-known that the rate of degradation is higher at higher concentrations of the organic compound. Especially, for the degradation of colored organic compounds like dyes, the degradation rate exhibits an initial increase with dye concentration, but decreases after a certain critical concentration. This is attributed to the screening of UV radiation by the dye molecules before reaching the catalyst surface. However, the catalyst concentration can be tuned based on the concentration of the organic compound, so that the organic compound can be significantly adsorbed onto the catalyst surface and degraded. Most of the degradation studies have employed a concentration of the organic compounds in the range of 10–200 mg L⁻¹, which agrees well with the concentration of the common pollutants in real wastewater.

7.7 Presence of Anions and Oxidizing Agents

Industrial effluents are composed of a large number of organic compounds, humic substances and inorganic substances, such as anions and metal ions. Hence, an evaluation of the degradability of an organic compound under the influence of such externally added ions is important. It is generally observed that anions like carbonate, bicarbonate, chloride and sulfate ions retard the degradation of organic compounds, in accordance with the following reactions [48–51]:

$$ {\text{CO}}_{3}^{2 - } + {\text{OH}}^{ \bullet } \mathop{\longrightarrow}\limits{{}}{\text{CO}}_{3}^{ \bullet - } + {\text{OH}}^{ \bullet - } $$

(37)

$$ {\text{HCO}}_{3}^{ - } + {\text{OH}}^{ \bullet } \mathop{\longrightarrow}\limits{{}}{\text{CO}}_{3}^{ \bullet } + {\text{H}}_{2} {\text{O}} $$

(38)

$$ {\text{Cl}}^{ - } + {\text{OH}}^{ \bullet } \mathop{\longrightarrow}\limits{{}}{\text{Cl}}^{ \bullet } + {\text{OH}}^{ - } $$

(39)

$$ {\text{SO}}_{4}^{2 - } + {\text{OH}}^{ \bullet } \mathop{\longrightarrow}\limits{{}}{\text{SO}}_{4}^{ \bullet - } + {\text{OH}}^{ - } $$

(40)

$$ {\text{SO}}_{4}^{ \bullet - } + {\text{H}}_{2} {\text{O}}\mathop{\longrightarrow}\limits{{}}{\text{SO}}_{4}^{2 - } + {\text{OH}}^{ \bullet } + {\text{H}}^{ + } $$

(41)

It is clear that all these anions scavenge the hydroxyl radicals to form the respective anion radicals. In the case of the sulfate anion, a sulfate anion radical can result in the formation of hydroxyl radicals according to reaction 41. However, these radicals are again scavenged according to reaction 40, and hence there is a net reduction in the rate of photocatalytic degradation of the organic compound. Azevedo et al. [108] evaluated the effect of saline media on the photocatalytic degradation of phenol and concluded that, at a low concentration of NaCl (2 g L⁻¹), the rate was unaffected, while at a high concentration of NaCl (50 g L⁻¹), there was a drastic reduction in the degradation rate of phenol. However, complete removal and mineralization of phenol was observed. They modeled the reaction using extended-lumped saline kinetics and predicted the time evolution profiles of phenol, intermediates and CO₂. Devi et al. [100] conducted extensive experiments to evaluate the effect of anions on the degradation of anionic and cationic dyes, and found that the presence of sulfate anions result in the highest reduction in the degradation rate of the dyes, while the presence of oxalate anions show the lowest reduction in rate. Thus the reduction in rate due to the presence of different anions for the degradation of Rhodamine B follows the order: SO₄ ²⁻ > Cl⁻ > HCO₃ ⁻ > NO₃ ⁻ > CO₃ ²⁻ > C₂O₄ ²⁻. A similar retardation effect was also observed for the inactivation of microorganisms in presence of TiO₂. According to the results of Rincón and Pulgarin [95], the order of retardation of E. coli in presence of different anions is as follows: Cl⁻ > NO₃ ⁻ > SO₄ ²⁻ ≫ HCO₃ ⁻ > HPO₄ ²⁻, where the chloride and phosphate ions exhibit the minimum and maximum inhibiting effect, respectively.

The presence of oxidizing agents such as persulfate and H₂O₂ has a positive effect on the degradation rate of the organic compound, which is attributed to the generation of hydroxyl radicals by these oxidizing agents, according to the following reactions [48–51]:

$$ {\text{S}}_{2} {\text{O}}_{8}^{2 - } + e_{\text{CB}}^{ - } \mathop{\longrightarrow}\limits{{}}{\text{SO}}_{4}^{2 - } + {\text{SO}}_{4}^{ \bullet - } $$

(42)

$$ {\text{H}}_{2} {\text{O}}_{2} + e_{\text{CB}}^{ - } \mathop{\longrightarrow}\limits{{}}{\text{OH}}^{ \bullet } + {\text{OH}}^{ - } $$

(43)

$$ {\text{H}}_{2} {\text{O}}_{2} + {\text{O}}_{2}^{ \bullet - } \mathop{\longrightarrow}\limits{{}}{\text{OH}}^{ \bullet } + {\text{OH}}^{ - } + {\text{O}}_{2} $$

(44)

The sulfate anion radical generated by reaction (42) reacts with water to form a hydroxyl radical by reaction (41). Reactions (43)–(44) are the key reactions for the generation of hydroxyl radicals in presence of H₂O₂. It was previously shown that these two reactions are responsible for the enhanced photocatalytic inactivation of E. coli in presence of TiO₂, even at very low concentrations of H₂O₂ (0.3 mM). However, when the concentration of H₂O₂ is higher than the optimum, the following reactions occur, which result in the quenching of the hydroxyl radicals, thereby resulting in a reduction of the degradation rate [48–51]:

$$ {\text{H}}_{2} {\text{O}}_{2} + 2h_{\text{VB}}^{ + } \mathop{\longrightarrow}\limits{{}}{\text{O}}_{2} + 2{\text{H}}^{ + } $$

(45)

$$ {\text{H}}_{2} {\text{O}}_{2} + {\text{OH}}^{ \bullet } \mathop{\longrightarrow}\limits{{}}{\text{H}}_{2} {\text{O}} + {\text{HOO}}^{ \bullet } $$

(46)

$$ {\text{HOO}}^{ \bullet } + {\text{OH}}^{ \bullet } \mathop{\longrightarrow}\limits{{}}{\text{H}}_{2} {\text{O}} + {\text{O}}_{2} $$

(47)

Therefore, careful optimization of the concentration of the oxidants is a must for achieving maximum photocatalytic degradation rates.

7.8 Presence of Metal Ions

In the recent past, extensive research has been conducted on the effects of metal ions on the degradation of organic compounds. It is imperative to note that metal ions like Ag⁺, Hg²⁺, Cu²⁺, Pb²⁺, Cd²⁺, Ni²⁺ and Cr⁶⁺ are toxic and have infinite lifetimes. Hence, their accumulation in the environment leads to biomagnification. Reduction of metal ions by photocatalysis is an important subject and many studies have dealt with this aspect [44, 109]. A number of studies have also focused on the simultaneous degradation of organic compounds and reduction of metal ions using TiO₂. Prairie et al. [110] observed that the rate constant for the reduction of Cr⁶⁺–Cr³⁺ is strongly dependent on the concentration of salicylic acid, and the rate constant exhibits a sudden drop at salicylic acid concentrations higher than the optimum value. Moreover, the highest degradation rate of salicylic acid was observed in presence of Au³⁺. An important result of their work shows that only those metal ions whose half-reaction standard reduction potential is greater than 0.3 V (vs NHE) can be treated by photocatalysis.

A careful evaluation of the works of Chen et al. [111], Aarthi and Madras [37], and Kyung et al. [112] shows that the rate of degradation of Rhodamine B decreases in the presence of Cu²⁺, Fe³⁺, Zn²⁺ and Al³⁺, while increasing with the presence of Cr⁶⁺ and Ag⁺ ions. This suggests that the electronic state of the metal ions also plays a major role in the degradability of the organic compound. Wang et al. [113] studied the photocatalytic degradation of phenol in presence of Cu²⁺ and F⁻ ions using DP-25 TiO₂. The I-order degradation rate coefficient of phenol in presence of different ions exhibited the following trend: k(Cu²⁺+F⁻) > k(F⁻) > k(Cu²⁺) > k(without Cu²⁺ or F⁻). The observed effect was attributed to the enhanced charge-carrier separation induced by Cu²⁺ and F⁻.

A common feature in most of the works reporting synergistic degradation of organic compounds in the presence of metal ions is that the pH of the reaction mixture was in the acidic regime. For example, the reduction of Cr⁶⁺–Cr³⁺ occurs in the presence of protons according to the following reaction [114]:

$$ 2{\text{Cr}}_{2} {\text{O}}_{7}^{2 - } + 16{\text{H}}^{ + } \to 4{\text{Cr}}^{3 + } + 8{\text{H}}_{2} {\text{O}} + 3{\text{O}}_{2} $$

(48)

Hence, an acidic medium can provide excess protons for the reduction of Cr⁶⁺ compared to a neutral or basic medium. Moreover, metal ions like Cr⁶⁺ and Cu²⁺ precipitate as hydroxides in the basic pH regime, which prevents them from getting adsorbed onto the TiO₂ surface. In a recent study, Vinu and Madras [114] observed that the presence of phenol accelerated the reduction of Cu²⁺–Cu⁺, while this was not possible in the absence of phenol (Fig. 8). The presence of Cu²⁺ ions did not significantly alter the degradation rate of phenol, while the presence of Cr⁶⁺ enhanced the degradation of phenol.

Fig. 8

Concentration profiles of phenol and Cu²⁺ during the simultaneous oxidation–reduction of phenol+Cu²⁺ using CS TiO₂. The phenolic intermediates, viz., catechol and hydroquinone were observed only in the presence of Cu²⁺ [114]

Sun et al. [115] showed that, among the different metal ions like Cu²⁺, Fe³⁺, Mn⁴⁺, Ce⁴⁺, V⁵⁺ and Cr⁶⁺, only Cr⁶⁺ accelerated the photooxidation of 4-chlorophenol in presence of visible light. Therefore, it can be summarized that the simultaneous degradation-reduction of such two-component systems containing an organic compound and a metal ion is dependent on the pH of the solution, concentration of the metal ions and the organic compound, adsorption of the metal ion and the electronic states of the metal ions.

8 Mechanistic Models for Photocatalytic Degradation

8.1 Models for the Degradation of Organic Compounds

It is well reported that the rate of photocatalytic degradation of the organic compounds follows the classical Langmuir–Hinshelwood (L–H) kinetics [116]. Sivalingam et al. [36] derived the rate equation for the photocatalytic degradation of dyes by incorporating the reactions including charge-carrier generation, recombination, adsorption–desorption of the substrate, generation of hydroxyl radicals and the oxidation of the adsorbed organic compound by hydroxyl radicals and holes. The rate equation, which resembles the L–H equation, is given by:

$$ - r_{\text{A}} = \frac{{K_{0} ((k_{{0{\text{h}}}} /K_{0} ) + k_{0} )C_{\text{A}} }}{{1 + K_{0} C_{\text{A}} }} $$

(49)

where, r _A denotes the rate of consumption of the organic compound, C _A is the concentration of the organic compound, and K ₀ is the equilibrium adsorption rate coefficient, which includes the adsorption of the organic compounds and hydroxyl radicals. The rate coefficients k _0h and k ₀ signify the oxidation of the organic compound by direct hole attack and by the hydroxyl radicals, respectively. Hence, the compound rate coefficient $k_{\text{r}} = (k_{{0{\text{h}}}} /K_{0} ) + k_{0}$ denotes the oxidation of the organic compound. A simple way to determine the rate coefficients K ₀ and k _r is the initial rate method. In this method, the equation is inverted and rearranged so that a plot of 1/C _A0 versus 1/r _A0 yields the slope and intercept, from which K ₀ (in L mg⁻¹) and k _r (in mg L⁻¹ min⁻¹) can be evaluated. The equation is given by

$$ - \frac{1}{{r_{{{\text{A}}0}} }} = \frac{1}{{k_{\text{r}} K_{0} }}\frac{1}{{C_{{{\text{A}}0}} }} + \frac{1}{{k_{\text{r}} }} $$

(50)

It is worthwhile to note that the equilibrium adsorption coefficient, K ₀ determined from the L–H equation is different from the adsorption coefficient that is determined by the Langmuir adsorption isotherm. This is because the equilibrium adsorption coefficient determined by the Langmuir isotherm denotes the adsorption–desorption of the organic compound in the dark, while K ₀ signifies the adsorption of the organic compounds onto the catalyst surface and the desorption of the products from the surface during the photoreaction. Hence, it is imperative to note that K ₀ is dependent on other reaction parameters including the intensity of UV irradiation, concentration of oxygen and the catalyst concentration.

As most of the organic compounds are present at trace levels in the atmosphere or effluent stream, the term K ₀ C _A ≪ 1 in the denominator of Eq. 49. Hence, the rate equation can be simplified to a first-order equation with ‘k’ as the first-order rate constant signifying the degradation of the organic compound [39].

$$ - r_{\text{A}} = - \frac{{{\text{d}}C_{\text{A}} }}{{{\text{d}}t}} = kC_{\text{A}} $$

(51)

The solution of the above equation is given by $C_{\text{A}} = C_{{{\text{A}}0}} \exp ( - kt)$. The rate coefficient, k, can be determined by a linear plot of ln(C _A0/C _A) versus t. The value of the rate coefficient reported in the literature for the degradation of organic compounds varies over a wide range and, therefore, it is difficult to establish a specific range of variability. This is because the rate coefficient is dependent upon the type of the catalyst (anatase/rutile TiO₂), intensity of the UV radiation, catalyst loading and other reaction parameters like pH, and the presence of anions and cations.

Li et al. [117] developed a kinetic model for the rate of degradation of Rhodamine B dye in presence of a TiO₂-coated, activated carbon catalyst by including the fractional surface coverage of the hydroxyl radicals and the dye, on the catalyst surface. The L–H parameters were found to depend on the intensity (I) of the UV radiation according to the following equations:

$$ k_{\text{r}}^{ - 1} = \alpha I^{ - 1/2} + \beta $$

(52)

$$ K_{0} = \eta I^{ - 1/2} + \varpi $$

(53)

where, α, β, η and ω are lumped constants, expressed in terms of the rate coefficients and signifying the individual steps. They have observed good agreement of the model with the experimental data at different light intensities.

Wu and Chern [105] adopted a cyclic network reduction technique to derive the rate expression for the degradation of Methylene Blue. The rate of decomposition of Methylene Blue was found to depend on the initial concentration of the dye, light intensity, TiO₂ loading and dissolved oxygen concentration. The rate expression is given by:

$$ - r_{\text{A}} = \frac{{k_a^{'} C_A }}{{1 + k_b^{'} C_A}} $$

(54)

where, $k_{a}^{'} = \frac{{k_{4} [h\nu ][{\text{TiO}}_{2} ]}}{{1 + k_{1} [h\nu ]}}$ and $k_{b}^{'} = \frac{{k_{2} + k_{3} [h\nu ]}}{{1 + k_{1} [h\nu ]}}$. The concentration profiles were simulated by integrating Eq. 54 in the limits C _A |_t=0 = C _A0 and C _A |_t=t′ = C _At. The rate coefficients were determined by nonlinear curve fitting of the following expression with the experimental data:

$$ \ln \left( {\frac{{C_{At} }}{{C_{{A0}} }}} \right) + k_b^{'} (C_{At} - C_{{A0}} ) = - k_a^{'} t $$

(55)

Almquist and Biswas [118] investigated the effect of dissolved oxygen on the kinetics of degradation of phenol in presence of DP-25. Their results show that dissolved oxygen has an inhibiting effect on the degradation of phenol when the concentration of phenol is of the order of the solubility of oxygen in water. They developed a three-parameter model that describes the dependence of the degradation rate on the concentration of phenol and dissolved oxygen. The rate equation is given by:

$$- \frac{{{\text{d}}C_A }}{{{\text{d}}t}} = \frac{{bC_{{{\rm O}_{2}}} C_A \left\{ {\sqrt {1 + {a \mathord{\left/ {\vphantom {a{C_{{{\rm O}_{2} }} }}} \right. \kern-\nulldelimiterspace}{C_{{{\rm O}_{2} }} }}} - 1} \right\}}}{{1 + cC_A }} $$

(56)

The model parameter ‘a’ depends on the light intensity profile inside the reaction slurry, light absorption and the efficiency of electron-hole formation and recombination. The parameters ‘b’ and ‘c’ depend mainly on the type of TiO₂. The parameters were determined by nonlinear curve fitting. Therefore, the differing kinetic equations suggest that, although L–H and the first-order model satisfactorily describes the overall kinetics of degradation of organic compounds, more thorough models must be used to unravel the effects of different reaction parameters like the UV light intensity, catalyst loading, oxygen concentration and the mode of reactor operation.

8.2 Modeling of Microbial Inactivation

The kinetics of photocatalytic disinfection of microorganisms is quite different from that of the organics because the inactivation profiles are characterized by three distinct regimes. In the first regime, a “shoulder” or a slow deactivation of the microorganisms occurs due to the self-defense and auto-repair mechanisms of the bacterial cell membrane against the hydroxyl radicals [119]. Once the hydroxyl radical concentration builds up in the system and a certain number of critical molecules are denatured, perforation of the bacterial membrane occurs, as the anti-stress enzymes are unable to prevent the membrane from oxidation. Thus, in the second regime, a log-linear reduction in concentration of the microorganism is observed. The last part of the deactivation process is characterized by a slow reduction in concentration or tailing of the concentration profile, due to the release of organic compounds into the medium, which competes with the inactivation of the microorganism.

Several empirical models have been proposed to account for the different regimes of deactivation of microorganisms [120]. These include a delayed Chick-Watson, modified Chick-Watson, Hom and modified Hom equations. The modified Hom equation, which fits well with the bacterial concentration profile has three adjustable parameters and is expressed as:

$$ \log \frac{{C_{0} }}{C} = k_{1} [1 - \exp ( - k_{2} t)]^{{k_{3} }} $$

(57)

where, C ₀ and C are the initial concentration and concentration at time ‘t’ of the microorganism in the system. The parameters k ₁, k ₂ and k ₃ in the above model have no physical significance. Therefore, rigorous mechanistic models are necessary to describe the kinetics of the deactivation of microorganisms. Initially, the mechanism of rupturing the cell wall of the microorganism, thereby inactivating the organism, was represented as a series of consecutive events of different damage levels [120, 121]:

$$C_{0} \mathop{\longrightarrow}\limits^{{k_{1} }}C_{1}\mathop{\longrightarrow}\limits^{{k_{2} }}C_{2}\mathop{\longrightarrow}\limits^{{k_{3} }}C_{3} \cdots\mathop{\longrightarrow}\limits^{{k_{n} }}C_{n}$$

(58)

where, k _i denotes the kinetic rate coefficient for the damage from level i − 1 to i. Labas et al. [121] coupled the radiation transport equation with this model and observed that the threshold limit for bacterial damage corresponds to two levels (n = 2). Other parameters in their model correspond to the inactivation rate coefficient k, and the reaction order with respect to the local volumetric rate of photonic absorption of the bacteria.

Marugán et al. [120] recently proposed a modified mechanism for the deactivation of E. coli, represented as:

$$C_{\text{undamaged}} \mathop{\longrightarrow}\limits^{{k_{1}}}C_{\text{damaged}} \mathop{\longrightarrow}\limits^{{k_{2}}}C_{\text{inactivated}} \mathop{\longrightarrow}\limits^{{k_{3}}}C_{\text{product}}$$

(59)

where, C _undamaged denotes the undamaged population of the microorganism, C _damaged denotes the lumped population at all intermediate levels of damage, C _inactivated denotes the microorganisms in the inactive state and C _product denotes the products of microbial cell lysis, which are released into the reaction medium. The L–H-like model for the above mechanism is given by:

$$ \frac{{{\text{d}}C_{\text{undamaged}} }}{{{\text{d}}t}} = - k\frac{{KC_{\text{undamaged}}^{\text{n}} }}{{1 + KC_{\text{undamaged}}^{\text{n}} + KC_{\text{damaged}}^{\text{n}} }} $$

(60)

$$ \frac{{{\text{d}}C_{\text{damaged}} }}{{{\text{d}}t}} = k\frac{{KC_{\text{undamaged}}^{\text{n}} - KC_{\text{damaged}}^{\text{n}} }}{{1 + KC_{\text{undamaged}}^{\text{n}} + KC_{\text{damaged}}^{\text{n}} }} $$

(61)

where, the rate coefficients k, K and n correspond to the interaction of the hydroxyl species with the microorganism, microorganism with TiO₂, and the products of bacterial lysis with the hydroxyl species, respectively. The above expression is based on the assumption that the rate coefficients for the intrinsic reaction steps for the undamaged and the damaged cells are the same. Thus, the rate coefficients K, k and n signifying the pseudo-adsorption, inactivation and inhibition, represent the initial lag, log-linear decrease and final lag phases of the bacterial disinfection profiles, respectively. This model has been validated for the deactivation of E. coli with different catalysts of varying concentrations, and in presence of anions like chloride, bicarbonate and phosphate, and humic acids [122].

8.3 Modeling of Multicomponent Systems

Industrial effluents are composed of a mixture of different organic compounds (dyes, phenolics, chlorinated compounds) and metal ions. The rate of degradation of an organic compound in the presence of another will be different from individual degradation rates. Therefore, kinetic modeling of multicomponent systems yields useful information on the interaction between the different species in the system, competition of the reactants and products for the active sites, and the mechanism of degradation. Priya and Madras [123] studied the photocatalytic degradation of mixtures of 4-chlorophenol and 4-nitrophenol to simulate the industrial effluent. They modeled the rate of degradation of chlorophenol (cp) and nitrophenol (np) using the following rate equations with individual L–H rate parameters (k _cc, K _cp, k _nn and K _nn) and interaction parameters (k _cn and k _nc):

$$ - r_{\text{cp}} = \frac{{(k_{\text{cc}} - k_{\text{cn}} C_{\text{np}} )C_{\text{cp}} }}{{1 + K_{\text{cp}} C_{\text{cp}} + K_{\text{np}} C_{\text{np}} }};\quad - r_{\text{np}} = \frac{{(k_{\text{nn}} - k_{\text{nc}} C_{\text{cp}} )C_{\text{np}} }}{{1 + K_{\text{cp}} C_{\text{cp}} + K_{\text{np}} C_{\text{np}} }} $$

(62)

The above model accounts for the competitive inhibition of the rate of degradation of cp by np, and vice-versa. The denominator in the above equations accounts for the competition of cp and np for the active site of TiO₂. By linearizing the above expressions, the rate coefficients were determined. Based on the values of k _cn and k_nc, it was found that the degradation of chlorophenol was unaffected by the presence of nitrophenol, while the degradation of the nitrophenol was significantly affected by the presence of the chlorophenol.

Similarly, when a metal ion is present in the system along with an organic compound, simultaneous oxidation and reduction reactions occur, and the kinetics of the reaction is affected by the complex interaction of the organic compound and metal ion with the TiO₂ surface. A detailed discussion on this topic is available in Sect. 7.8. The retardation of the rate of degradation of dyes in presence of metal ions was modeled by Aarthi et al. [37], and their kinetic model relates the rate of degradation of the dye (r _D) with the concentration of the dye [D] and the metal ion [M ⁿ⁺]. The equation is given by:

$$ - \frac{1}{{r_{D} }} = \left( {\frac{1}{[D]} + K_{2} } \right)\frac{{(1 + K_{6} [M^{{{\text{n}} + }} ])}}{{(k_{0} + K_{6} k_{7} [M^{{{\text{n}} + }} ])}} $$

(63)

The lumped rate coefficients in the above model, viz. K ₂, K ₆, k ₀ and k ₇, were determined by nonlinear regression, and the model was validated for the degradation of different dyes, including Rhodamine B [37], Rhodamine 6G [37], Sulforhodamine B [37] and Azure B [124], in presence of Cu²⁺. One shortcoming of this model is that it does not account for the concomitant reduction of metal ions during the degradation of the organic compound. With this in mind, Vinu and Madras [114] modeled the simultaneous and synergistic degradation of phenolic compounds (phenol and 4-nitrophenol), and the reduction of metal ions (Cu²⁺ and Cr⁶⁺), by assuming competitive adsorption of metal ions and the phenolic compounds onto the TiO₂ surface. The steady-state rates through the individual phenol degradation and metal ion reduction pathways, derived using the network reduction technique, are given by:

$$ \left( { - \frac{1}{{r_{{{\text{Ph}},0}} }} - K_{2} } \right) = \frac{1}{{[{\text{Ph}}]_{0} }}\left( {\frac{1}{{K_{1} }} + \frac{{[M^{{{\text{n}} + }} ]}}{{K_{3} }}} \right) $$

(64)

$$ \left( { - \frac{1}{{r_{{M^{{{\text{n}} + }} ,0}} }} - K_{5} } \right) = \frac{1}{{[M^{{{\text{n}} + }} ]_{0} }}\left( {\frac{1}{{K_{4} }} + \frac{{[{\text{Ph}}]}}{{K_{6} }}} \right) $$

(65)

where, r _Ph,0 and r _Mn+,0 denote the initial rate of degradation of phenolic compound and the reduction of metal ions, respectively. This model accounts for the contribution of the metal ions for the rate of degradation of the phenolic compound and vice versa. The lumped rate coefficients K ₂ and K ₅ were determined by individually degrading phenolic compounds and metal ions, and the other rate coefficients were evaluated by conducting multiple experiments at different phenol and metal ion concentrations. Using this model, the rate coefficients can be determined uniquely by a simple linear regression.

8.4 Modeling of Degradation Intermediates

The intermediates formed during the degradation of organic compounds can have a deleterious effect on the overall degradation rate, since these compounds compete for the active sites of the catalyst. Hence, by knowing the formation and consumption rate of the different intermediates, the relative importance of each of them on the overall mineralization of the parent compound can be assessed. Previous studies on the degradation of phenolic compounds, dyes and pesticides have monitored the concentration of the various intermediates during degradation. For example, the predominant intermediates observed during the degradation of phenol include catechol, hydroquinone, hydroxy hydroquionone, benzoquinone and oxalic acid. The kinetics of formation and consumption of these intermediates was modeled by considering a simple series reaction mechanism with first-order reactions [39, 40], represented as:

$${\text{A}}\mathop{\longrightarrow}\limits^{{k_{\text{f}}}}{\text{Intermediate}}\mathop{\longrightarrow}\limits^{{k_{\text{c}}}}{\text{Product}}$$

(66)

where, k _f and k _c are the formation and consumption rate coefficients of the intermediates. By writing rate equations for A, intermediate and the product, an expression for the concentration of the intermediate can be derived as [125]:

$$ \frac{{C_{\text{int}} }}{{C_{{A{\rm 0}}} }} = \frac{{k_{\text{f}} }}{{k_{\text{c}} - k_{\text{f}} }}\left( {\exp ( - k_{\text{f}} t) - \exp ( - k_{\text{c}} t)} \right) $$

(67)

The concentration profiles of the primary hydroxylated species show an initial increase and subsequent decrease with time due to the formation of secondary hydroxylated species. Hence, there is a time (t _max) at which the concentration of the intermediate is maximum (C _max). Therefore, by differentiating the above equation with respect to t and C _int, expressions for t _max and C _int,max were derived as [125]:

$$ t_{\max } = \frac{{\ln ({{k_{\text{f}} } \mathord{\left/ {\vphantom {{k_{\text{f}} } {k_{\text{c}} )}}} \right. \kern-\nulldelimiterspace} {k_{\text{c}} )}}}}{{k_{\text{c}} ({{k_{\text{f}} } \mathord{\left/ {\vphantom {{k_{\text{f}} } {k_{\text{c}} - 1)}}} \right. \kern-\nulldelimiterspace} {k_{\text{c}} - 1)}}}} $$

(68)

$$ \frac{{C_{{\text{int} ,\max }} }}{{C_{{A{\rm 0}}} }} = \left( {\frac{{k_{\text{f}} }}{{k_{\text{c}} }}} \right)^{{1/(1 - {{k_{\text{f}} } \mathord{\left/ {\vphantom {{k_{\text{f}} } {k_{\text{c}} }}} \right. \kern-\nulldelimiterspace} {k_{\text{c}} }})}} $$

(69)

Thus, by solving these two equations with t _max and C _int,max from the experimental data, k _c and k _f can be determined. More importantly, the ratio k _c /k _f, which signifies the relative rate at which the intermediate is consumed, can be used as a quantifying factor to assess the stability of the different intermediates and the effective mineralization of the parent compound. The formation of catechol and hydroquinone during the photocatalytic degradation of phenol in presence of Cu²⁺ ions and CS TiO₂ is depicted in Fig. 8. The curves for catechol and hydroquinone represent the model fits.

9 Visible Light Degradation of Organic Compounds

9.1 Second Generation TiO₂ Photocatalysts

The first generation TiO₂ or pristine TiO₂ proves to be an efficient photocatalyst in the UV region. However, the wide band-gap (3.2 eV) of anatase TiO₂, corresponding to an absorption threshold of 390 nm, limits its use in the visible range (400–800 nm) in practical applications. Moreover, solar radiation is comprised of c.a. 50% visible radiation and less than 5% UV radiation. Hence, extending the spectral absorption of TiO₂ to the visible region is vital for the development of energy efficient degradation processes.

Second generation TiO₂ catalysts encompass a wide variety of the cationic and anionic substituents in TiO₂. The cationic substituents mainly include metal ions, while the anionic substituents include C, N and S. Numerous studies have examined the substitution of lower valent (+1, +2, +3), iso valent (+4) and higher valent (+5, +6) metal ions in the lattice of TiO₂ for the photocatalytic degradation of organic compounds. This includes noble metals, transition metals, lanthanide metals and alkaline metals. Table 6 [126–131] presents a list of the various studies conducted on the photocatalytic activity of metal ion-doped TiO₂. Although there is a general consensus that metal ion doping extends the absorption spectrum of TiO₂ to the visible region, the photocatalytic activity of the metal ion-doped TiO₂ compared to the undoped TiO₂ varies across different studies. From the table, it is evident that doping of some metal ions enhances the photoactivity, while others result in a reduction of photoactivity.

Table 6 Effect of different metal ion substitutions in TiO₂ for the photocatalytic degradation of organic compounds

Choi et al. [126], by studying the transient absorption decay of the trapped electrons, showed that the dopant energy levels serve as trap sites for the electrons and holes, apart from the surface trap sites. The low activity exhibited by metal ion-doped TiO₂ is due to these states acting as recombination centers. Hence, the photoactivity of metal ion-doped TiO₂ strongly depends on the dopant concentration, energy level of the dopant within the TiO₂ lattice, d-electronic configuration, distribution of dopant, interfacial charge transfer and light intensity. Nagaveni et al. [130] conducted a thorough photoluminescence study of the different metal ion-doped TiO₂ (M _xTi_1-xO_2±δ), synthesized by the solution combustion technique, and observed a reduction in the emission intensity of the metal ion-doped samples. The metal ions form inter-band energy levels above the valence band or below the conduction band, which result in lower band gap of the doped TiO₂ materials. Serpone et al. [127] showed that doping of Cr³⁺, Fe³⁺ and V⁵⁺ in the lattice of TiO₂ results in a lower photoactivity for the oxidation of oxalic acid, but an enhanced activity for the photoreduction of water to H₂. Similarly, Pd²⁺ ion substitution in CS TiO₂ was found to be beneficial for gas phase CO oxidation, NO reduction and NO decomposition [132], while it exhibited a negative effect for liquid phase degradation of organic compounds [133]. This shows that a generalization of the activity of metal doped TiO₂ compared to the undoped TiO₂ is not possible for a wide class of reactions.

Another method by which metal ions can be incorporated in TiO₂ is by impregnation on the surface. Paola et al. [134] investigated the effect of different transition metals impregnated TiO₂ for the photocatalytic degradation of aliphatic and aromatic compounds and found that the highest mineralization efficiency was obtained with bare TiO₂. In addition to the above result, Vinu and Madras [133, 135] showed that TiO₂ impregnated with Pd or Ag exhibits higher photoactivity compared to doped-TiO₂. The higher activity exhibited by the metal ion-impregnated TiO₂ is attributed to the formation of a Schottky barrier, which results in the scavenging of electrons and holes, thereby preventing unfavorable recombination reaction.

While metal ions are substituted for the Ti atoms in the lattice, anions are substituted for oxygen in the oxide. Hence, these are represented as TiO_2-xD_x, where D is usually N, C or S. The first study on anion-substituted TiO₂, TiO_2-xN_x, was carried out by Asahi et al. [136] for the photocatalytic degradation of Methylene Blue and gaseous acetaldehyde in presence of visible radiation. Based on X-ray photoelectron spectroscopic analysis, they observed an optimum concentration of N to be 0.25 atomic%. Khan et al. [137] incorporated C in TiO₂ by flame pyrolysis, which shows a band gap of 2.32 eV, and high activity for photosplitting of water (photoconversion efficiency = 8.35%). Unlike the cation-doped TiO₂, anion-doped TiO₂ exhibits a high photoactivity in the visible region compared to undoped and commercial DP-25 due to narrowing of the band-gap. In fact, the band gap narrowing of N doped TiO₂ was attributed to the mixing of N 2p and O 2p energy levels. This requires the elevation of valence band maximum or the lowering of conduction band minimum by the introduction of new energy level of the anion dopant, with a more homogeneous distribution and without a loss of the crystal structure of the host TiO₂. The rules for any non-metal to be substituted for oxygen in TiO₂ to elevate the valence band, are as follows [138]: (i) the electronegativity of the non-metal dopant should be lesser than that of oxygen, and (ii) the radius of the dopant should be comparable to that of oxygen for a more uniform distribution.

Serpone [139] demonstrated that the visible light activity of the anion-doped TiO₂ is not due to the narrowing of the band-gap, but due to the defects associated with the oxide ion vacancy, which results in the formation of color centers. Color centers are essentially a single or a pair of electrons associated with an oxygen vacancy. For MgO, it has been shown that the ground state of the color centers lie above the O 2p valence band. Table 7 [140–144] shows the different studies on the anion-doped TiO₂ for the visible light degradation of organic compounds.

Table 7 A survey of the recent studies on the photocatalytic degradation of organic compounds using anion-doped TiO₂

9.2 Heterostructuring of TiO₂

Heterostructuring refers to the modification of the surface of pristine TiO₂ by employing (i) narrow band-gap semiconductor dopants (like CdS, PbS, CdSe, Bi₂S₃), (ii) dyes as sensitizers and (iii) co-catalysts [138]. Different schemes of charge-carrier transfer have been proposed for heterostructured TiO₂ materials, viz. traditional charge-carrier transfer, sensitization, indirect Z-scheme, direct Z-scheme, vectorial electron transfer and co-catalyst coupling. The main idea of these heterostructuring procedures is to isolate the electrons and holes at two different reaction sites in order to prevent recombination. This enhances the efficiency of simultaneous oxidation and reduction reactions. Moreover, the incorporation of small band-gap semiconductors, dyes and co-catalysts, increases the probability of absorption in the visible range. Liu et al. [138] reviewed such schemes in terms of their mechanisms, materials and the key issues involved in their implementation. Figure 9 depicts the two different modes of charge transfer in presence of a sensitizing dye and a narrow band-gap semiconductor. Some important design considerations for the heterostructured systems, for effective interfacial charge transfer, are as follows:

Fig. 9

Mechanism of charge carrier transfer in a dye sensitized TiO₂, and b narrow band gap semiconductor coupled TiO₂

• The main semiconductor (TiO₂) and the dopant semiconductor need to have suitable electronic structure, i.e., the dopant should have a higher conduction band minimum and valence band maximum compared to TiO₂, for the smooth injection of electrons downhill from the conduction band of the dopant, and the transfer of holes uphill to the valence band of the dopant.

• The above condition is also applicable for sensitizers, although there is no transfer of holes to the HOMO. Moreover, high surface area of TiO₂ is necessary for the enhanced adsorption of the sensitizer.

• Intimate contact between the two different phases (e.g., a p–n junction in the case of traditional transfer or Ohm/Schottky contact in the case of co-catalysts) is necessary.

Table 8 [145–154] presents the different studies on the sensitized degradation of organic compounds using modified TiO₂ materials. It is clear that a wide variety of sensitizers like narrow band-gap semiconductors, organic dyes and conjugated polymers are being coupled to TiO₂ to enhance the visible light response. Moreover, the time taken for the complete degradation of the organic compounds varies from 1 to 10 h, which shows the importance of optimizing the various reaction conditions like the initial concentration of the organic compound, catalyst loading and the intensity of the light source. Hence, a fair comparison of the photoactivity of the different modified TiO₂ materials requires the evaluation of the kinetic rate coefficients of degradation.

Table 8 Survey of the recent studies on sensitized degradation of organic compounds using modified TiO₂

10 Photocatalysis in Practice

10.1 Immobilization of TiO₂

The photocatalytic degradation reactions considered thus far have been conducted in small volume (0.1–10 L) batch reactors, usually in immersion well photoreactors [36], in which the catalyst particles are suspended and continuously stirred in the reaction mixture. While this configuration is beneficial for the high mass transfer of the reactants and products on the catalyst surface, which results in high degradation rates of organic compounds, this mode of operation is not suitable for large-scale applications involving large volumes of effluents, due to the inherent problem associated with the separation of the catalyst particles after the completion of the reaction. This escalates the costs related to the operation of the unit due to the complex downstream operations involved.

A solution to the above scale up issue is to immobilize the catalyst on a suitable support material. Many different supports have been explored for the immobilization of TiO₂, viz. glass beads [155], flexible fiber glass cloth [156], glass tubes [157], cotton [158], stainless steel [159], ZnO tetrapods [160], silicone rubber film [161], PTFE mesh sheets [162], polystyrene beads [163], low density support (perlite) [164] and porous lavas (pumice stone) [165]. A good support is characterized by its inertness to UV radiation, non-toxic nature, corrosion and erosion resistance at highly acidic and basic conditions and good adhesion to the catalyst particles. The different immobilization procedures include dip-coating, pasting, spray coating from suspension, sol–gel technique, CVD, sputtering and electrophoretic deposition. Usually, catalyst particles are coated many times on the supports to achieve better photocatalytic activity. However, excessive layers results in the detachment of the outer catalyst layers and cracking of the surface. Lim et al. [106] compared four different dip-coating methods for the mineralization of Methylene Blue and concluded that a hybrid method with 5 coating cycles and a calcination period of 1 h at 500°C yielded the best results. Moreover, the suitability of the substrates for immobilization followed the order: woven fiberglass ≈ fiberglass ≫ Al plate ≥ glass plate. However, the optimum number of coating cycles for the effective degradation of an organic compound is different from that required for the degradation of a microorganism. This was demonstrated in wall and fixed-bed reactors, where 2 dip-coating cycles exhibited the highest deactivation of E. coli, whereas, 3 dip-coating cycles were necessary for the effective degradation of Methylene Blue [166].

The degradation of organic compounds and microorganisms is, however, always lesser in an immobilized catalyst system compared to the suspended catalyst system. This is because of the reduction in the surface area of the catalyst, which results in the lesser adsorption of the reactants. Moreover, there is a significant reduction in activity of the immobilized catalyst with time due to the eventual loss of the catalyst particles from the surface, and the fouling of the catalyst, caused by the adsorption of the degradation products on the catalyst surface. Although the adsorbed products can be eliminated by calcination of the immobilized catalyst, this might affect the surface characteristics of the catalyst. Rao et al. [167] evaluated the reduction in activity of TiO₂ on different supports for the degradation of Acid Orange 7 and observed that the reductions in efficiency were a factor of four on TiO₂/polymer film, five on TiO₂/cellulosic fibers and ten on TiO₂/pumice stone after a period of 4 weeks. In a different study, Nakashima et al. [162] investigated the degradation of endocrine disrupting compounds like 17β-estradiol, bisphenol-A and 2,4-dichlorophenol using TiO₂ immobilized on PTFE mesh sheets. They observed 4.5 times enhancement in the mass transfer rate of these compounds when the PTFE sheets were rotated at 60 rpm compared to conventional circulation of the reaction mixture. In spite of the shortcomings, the recent research in the development of novel supports and immobilization protocols makes immobilized systems the preferred configuration for large-scale utilization of photocatalysis for the degradation of water pollutants.

10.2 Photocatalytic Reactor Modeling

Small scale batch reactors are widely used for the evaluation of the catalytic activity of novel photocatalytic materials, and for establishing the mechanism and kinetics of photocatalytic degradation reactions. Nevertheless, industrial decontamination of effluents requires large volumes to be processed. Hence, continuous operation is the preferred method, with catalyst particles immobilized on suitable supports. Different reactor configurations have been found suitable for photocatalytic degradation reactions, which include, thin film, flat plate, fluidized bed, packed bed, rotating disc, fountain type slurry, tubular, membrane, fiber, monolithic, bubble column, air-lift loop, Taylor-vortex flow and concentrating and non-concentrating solar reactors. A detailed description of the various photocatalytic reactor configurations is available elsewhere [168]. Given a wide range of reactor configurations, it is important to critically evaluate them based on the mass transfer limitations, spectral energy distribution of the light source, axial and radial dispersion of the reactants, catalyst layer thickness and energy efficiency, in order to find the best configuration for a particular class of pollutant and reaction conditions. Therefore, in depth modeling of these reactors based on the first principles chemical engineering approach is important.

The key component that distinguishes photocatalytic reactors from conventional reactors is the dependence of the kinetics of the reaction on the irradiance of the light source. Hence, models for photocatalytic reactors incorporate local volumetric rate of energy absorption (LVREA) in the rate expression. This is represented as [169–171]:

$$ r = k_{\text{R}} [e_{\lambda }^{{{\text{a}},v}} (\underset{\raise0.3em\hbox{$\smash{\scriptscriptstyle-}$}}{x} )]^n \frac{{K_{\text{R}} C_{\text{R}} }}{{1 + K_{\text{R}} C_{\text{R}} }} $$

(70)

where, r denotes the rate of the reaction per unit reactor volume, k _R denotes the rate coefficient for the degradation of the pollutant R, which is independent of light intensity, K _R denotes the equilibrium adsorption coefficient, C _R denotes the concentration of the pollutant, and e ^a,v _λ signifies the LVREA, which is dependent on the position vector x in the reaction space, and the exponent n signifies the dependence of the rate on LVREA. The selection of n is based on the light intensity and was discussed in Sect. 7.3. An expression for LVREA is [171]:

$$ e_{\lambda }^{{{\text{a,}}v}} (\underset{\raise0.3em\hbox{$\smash{\scriptscriptstyle-}$}}{x} ) = \kappa_{\lambda } (\underset{\raise0.3em\hbox{$\smash{\scriptscriptstyle-}$}}{x} )G_{\lambda } (\underset{\raise0.3em\hbox{$\smash{\scriptscriptstyle-}$}}{x} ) $$

(71)

where, κ _λ is the spectral volumetric absorption coefficient, which is a function of the concentration of the absorbing species, and G _λ is the spectral local incident radiation [171].

Equation 70 shows that the rate follows L–H kinetics, but any appropriate rate form (like first-order or multicomponent L–H) can be used, based on the influence of the different reactants. Thus, by incorporating the rate of the reaction in the mass balance or continuity equations, and solving the equation with appropriate boundary conditions at steady-state, yields the concentration profiles of the reactant as a function of space inside the reactor. Similarly, by solving the momentum balance equation, the velocity profiles can be obtained. Jarandehei and Visscher [172] carried out a computational fluid dynamics simulation of a flat plate photocatalytic reactor with a serpentine geometry for the photocatalytic degradation of trichloroethylene. They found that the kinetics of the reaction is better captured by the L–H model than the first-order model. By analyzing the velocity and concentration profiles inside the reactor they observed that the laminar flow becomes unstable at a Reynolds number around 900, and mixing was efficient in the 180^° sharp turns inside the reactor due to the formation of vortices.

Imoberdorf et al. [171] determined the LVREA inside a fluidized bed photoreactor using a Monte Carlo approach to track the photons. They have considered the shadowing effect of the spheres, absorption of radiation by the TiO₂-coated particles and reflection by the spheres. It was found that operating the bed at low expansions resulted in the effective absorption of the radiation. Chen et al. [173] evaluated the internal and external mass transfer resistances for the immobilized TiO₂ photoreactor, used for the degradation of benzoic acid. Their results indicate that, although the external mass transfer resistance can be minimized by increasing the velocity of the flow field (i.e., the Reynolds number), the internal mass transfer was limited by the TiO₂ film thickness. They observed the optimum catalyst layer thickness to be 5 μm, above which there was no effect of mass transfer on the rate of reaction. This correlates to the discussion in the previous section, where the number of coating cycles was found to be detrimental to the degradation of the pollutants in immobilized catalyst systems. Dijkstra et al. [174] evaluated the effects of different parameters like radial dispersion, external mass transfer, flow rate, catalyst loading and oxygen concentration on the degradation of formic acid in different immobilized reactor configurations. Their results suggest that membrane and packed bed reactors show better performance compared to fiber and tubular reactors. Imoberdorf et al. [175] employed the kinetic information obtained from an 81 cm² flat plate lab scale photoreactor to model a 5209 cm² multi-annular, series flow, pilot-scale photoreactor, for the degradation of perchloroethylene. The model, based on the mass balance and radiation transport equations, without any adjustable parameters, was able to predict the experimental conversion of perchloroethylene within an error limit of 5.6%. Thus, modeling of photocatalytic reactors is important for performance assessment, optimal design and scaling up, in large-scale industrial applications.

11 Concluding Remarks

In this comprehensive review, we have covered the fundamental aspects of photocatalysis as applied to the degradation of water pollutants. Over the past two decades, nano-sized TiO₂ has emerged as a leading photocatalyst with the potential to catalyze the degradation and mineralization of a wide range of toxic organic compounds, such as chlorinated organics, phenolics, dyes, pesticides and herbicides, surfactants, pharmaceutical compounds and drugs and microorganisms. The current trend in photocatalysis research is aimed at extending the spectral absorption of pristine or bare TiO₂ to the visible region, better harvesting solar radiation. Toward realizing this goal, many modified forms of TiO₂, such as anion-substituted TiO₂, dye-sensitized TiO₂ and heterostructured-TiO₂, have produced encouraging results.

One of the difficulties faced by the photocatalysis community is that TiO₂ synthesized by different protocols exhibit different physicochemical properties and substrate specific photoactivities and, hence, a single photocatalytic test with a specific material is not representative of its behavior for a wide class of organic compounds. Ryu and Choi [32] conducted the photocatalytic degradation of 19 test substances belonging to different classes of organic compounds using eight commercial TiO₂ samples, and concluded that each TiO₂ sample exhibits better photocatalytic activity compared to others for each class of organic compounds. Only DP-25 TiO₂ exhibited a better photoactivity for most of the organic compounds and can therefore be regarded as a yardstick for the assessment of the activity of novel photocatalytic materials. Therefore, owing to the ever increasing number of publications in this research area, the goal is to standardize the procedures, test substrates and photocatalytic activity, in order to have a rational comparison of the results of the different studies. Moreover, testing the degradation behavior of a single substrate is not representative of the “real” waste water or an effluent from a chemical plant. Hence, a degradation study of the multicomponent systems is a prospective research area. Although it is well-documented that the presence of humic substances, organic solvents, and chloride, sulfate and phosphate species retard the rate of degradation of organic compounds, evaluation of the degradation of systems with two or more organic compounds, metal ions or microorganisms is a relatively less explored topic.

The industrial viability of photocatalysis is driving research in the development of immobilized catalysts and photocatalytic reactors. In this venture, kinetic modeling of the reaction and reactor assumes paramount importance in the evaluation of the various rate limiting factors, optimum reaction conditions and scaling of reactors for the degradation of organic compounds. Currently, the large-scale applicability of photocatalysis for the degradation of organic pollutants is hindered by the costs involved in the operation of the treatment plant. Hence, more research in the selection of materials for the design of equipments and cheaper ways of catalyst synthesis and immobilization procedures is the key for further development. The authors do believe that exciting research opportunities exist in this field in the years to come.