This study focusses on the photocatalytic degradation of caffeine (CAF), a stimulating drug and environmental contaminant that poses a threat to humans and the environment. The effect of operating parameters such as CAF initial concentration (5–20 mg/L), catalyst dosage (0.1–0.9 g/L) and pH (3.0–9.0) were explored in detail. The experimental results showed the maximum CAF and chemical oxygen demand (COD) removals of 87.2% and 66.7% respectively. The optimized parameters were: CAF initial concentration – 5 mg/L, catalyst dosage – 0.5 g/L and pH – 7.2. The photocatalytic degradation of CAF followed pseudo-first order kinetics. The obtained experimental data were analysed with response surface methodology (RSM) using Design Expert Software.

  • The optimized parameters were: [CAF]=5 mg/L, [TiO2]=0.5 g/L, pH=7.2.

  • The maximum CAF and COD removals were 86.7 and 66.7% respectively.

  • CAF and COD removals followed pseudo-first-order kinetics.

  • Good agreement between experimental and predicted data.

  • All operating parameters were significant in CAF and COD removals.

Graphical Abstract

Graphical Abstract
Graphical Abstract

Pharmaceutical and personal care products (PPCPs) in the aquatic environment are of environmental concern and have received more attention among the researchers due to their persistence and non-biodegradability (Fathinia & Khataee 2015). PPCPs occur in the aquatic environment because of industrial and municipal wastewater discharges. Even though their concentration is usually at the nanogram level in wastewater, they have toxic impact on both humans and in the environment. Since PPCPs are persistent and non-biodegradable, their removal is of great concern (Barcelo & Petrovic 2008).

Caffeine (C8H10N4O2), a PPCP and persistent organic pollutant (POP), is a psychoactive drug consumed widely across the globe (Lovett 2005) and found in beverages like coffee, tea, and soft and energy drinks, as well as food products including chocolate and ice cream, and some medicines (Miners & Birkett 1996; Indermuhle et al. 2013; Marques et al. 2013; Ghosh et al. 2019). Caffeine has high water solubility (Ks >10,000 mg/L) (Elhalil et al. 2018), a low octanol water partition coefficient (Log Kow = −0.07) and a long half-life (Edwards et al. 2015). Even though short-term exposure to CAF is not a threat to living things (Moore et al. 2008), its intense use can cause mutation, anxiety, tremors (Zhang et al. 2011) and cardiovascular diseases (Torres et al. 2014; Elhalil et al. 2018).

Various methods including chlorination (Gould & Richards 1984), photo-Fenton (Klamerth et al. 2010; Trovo et al. 2013), ozonation (Rosal et al. 2008; Souza & Feris 2015), UV photolysis (Shu et al. 2013) and semiconductor-based heterogeneous photocatalysis (Marques et al. 2013; Arfanis et al. 2017; Elhalil et al. 2018; Luna et al. 2018; Vaiano et al. 2018) have been investigated for CAF degradation in aqueous solutions. UV photolysis is ineffective for CAF removal (Buerge et al. 2003), other methods – for example, ozonation, photo-Fenton and chlorination – are limited by slow reaction rates (Indermuhle et al. 2013; Ghosh et al. 2019).

Heterogeneous photocatalysis is an advanced oxidation process (AOP) applied to degrade POPs and found to be effective (Zhou et al. 2017; Elhalil et al. 2018). When a semiconductor absorbs a photon energy (hν) ≥ the semi-conductor band gap (Eg), an electron (e) may be promoted from the valence band (VB) to the conduction band (CB), thereby creating an electron vacancy – ‘hole’ (h+) (Bahnemann et al. 1997; Fujishima et al. 2008; Gaya & Abdullah 2008). The electron and hole can migrate to the catalyst surface where they participate in redox reactions with the species adsorbed on the catalyst surface. The holes can oxidize H2O and OH to generate hydroxyl radicals (OH) whereas the electrons, while reacting with oxygen, can reduce molecular oxygen O2 to O2•− (Mozia 2010; Laohaprapanon et al. 2015; Puga 2016). The OH generated destroys the POPs, breaking them down into the relatively less toxic end products, CO2 and H2O (Diaz-Uribe et al. 2014). Among the semi-conductors applied as photocatalysts, such as TiO2, ZnO, Fe2O3, WO3, SnO2, and ZrO2 (Sudha & Sivakumar 2015; Ahmad et al. 2016; Awfa et al. 2018; Pathakoti et al. 2018), TiO2 had attracted many researchers and been found successful due to its easy availability, low cost, non-toxicity, chemical and thermal stability, and applicability to solar energy (Bouarioua & Zerdaoui 2017; Rimoldi et al. 2017; Muangmora et al. 2020; Sujatha et al. 2020). As far as is known, no study has been conducted on CAF degradation using intermittent UV irradiation.

The objective of this study was to evaluate CAF photocatalytic degradation using intermittent irradiation from a 365 nm UV lamp (1 hour on and 10 minutes off for a trial period of 3 h 30 min) in a batch-scale reactor. Experiments were conducted in order to assess the effect of pH, TiO2 dose, and initial CAF concentration for CAF removal. Photocatalytic degradation kinetics were also studied. Response surface methodology (RSM) using central composite design (CCD) was used to analyse the individual and interactive effects of operating variables on CAF and chemical oxygen demand (COD) removals.

Materials

Caffeine (C8H10N4O2, MW-194.19 g/mol) and titanium dioxide (Evonik Degussa P25, Germany TiO2, 21 nm TEM size) were purchased from Sigma Aldrich. The specific surface of the TiO2 photocatalyst was 50 m2/g, its band gap was 3.2 eV and it was a mixture of anatase (70%) and rutile (30%). Sodium hydroxide (99%), hydrochloric acid (36.5 to 38.0%), dichloromethane, acetonitrile and hexane, all of HPLC grade, came from Merck. COD determination was done using double-distilled water.

Experimental setup

Figure 1 is a schematic of a laboratory-scale, batch photocatalytic reactor. The reactor, made of Plexiglas, had a working volume of 2 L. A 16 W, 365 nm, low pressure, Hg UV-A lamp was used. The lamp was in the centre of the reactor so that irradiation was uniform and was enclosed in a double-layered, quartz glass envelope. Water was recirculated through the envelope to prevent the lamp causing thermo-catalytic effects.

Figure 1

Photocatalytic reactor.

Figure 1

Photocatalytic reactor.

Close modal

Experimental procedure

The reaction mixture was prepared by adding known concentrations of CAF and the photocatalyst to distilled water. Before UV irradiation, the mixtures were stirred vigorously for 30 minutes in the dark, to establish an adsorption/desorption equilibrium on the photocatalytic surfaces. Subsequently, the mixture was stirred under UV irradiation. Sample aliquots were collected at 30 minute intervals and filtered to remove the solid particles. The CAF concentrations in the filtrates were determined using an INFRA DIGI IR513C Digital single beam UV-VIS Spectrophotometer (Gaurav Scientific Chemical, Raipur, India) at 273 nm. Proportional removal was calculated using Equation (1).
formula
(1)

Data analysis

The photocatalytic degradation was optimized using response surface methodology (RSM) based on central composite design (CCD). The three factors, solution pH, initial CAF concentration and COD removal, were assessed for two responses, CAF degradation and COD removal. The experimental data were analysed using Design-Expert software version 7.0.0 Stat-Ease (2005).

CAF – TiO2 dark adsorption and UV photolysis

The probable adsorption of CAF onto the TiO2 surface was evaluated through dark control tests. A 2 L sample containing 5 mg-CAF/L and 0.5 g-TiO2 /L, was covered with aluminium foil and kept in the dark for 24 h. The sample pH was maintained at 7.2. Analysis showed that only 9% of the CAF was adsorbed by the catalyst, perhaps because of electrostatic repulsion. This test was conducted to reduce the errors arising from non-photocatalytic adsorption, etc.

UV photolytic experiments were also conducted by irradiating a 2 L sample containing 5 mg-CAF/L for 180 min in the absence of TiO2. The sample residual CAF concentration was determined after 180 min and CAF removal efficiency was found to be 32%.

Effect of pH on CAF and COD removal

Figures 2(a) and 2(b) show the effect of pH on CAF photocatalytic degradation. The CAF removal efficiencies obtained at pH 3.0, 5.0, 7.2, and 9.0 were 92.3, 89.1, 86.7, and 60.2%, respectively – that is, CAF photocatalytic degradation was best in acidic solution. This could arise from (i) the surface charge, and/or (ii) the agglomerated photocatalyst sizes.

Figure 2

Effects of feed solution pH, TiO2 dose, and initial CAF concentration on CAF removal (a), (c) and (e), and COD removal (b), (d) and (f). Standard operating conditions – 5 mg-CAF/L (initial concentration), 0.5 g-TiO2/L, time 180 min.

Figure 2

Effects of feed solution pH, TiO2 dose, and initial CAF concentration on CAF removal (a), (c) and (e), and COD removal (b), (d) and (f). Standard operating conditions – 5 mg-CAF/L (initial concentration), 0.5 g-TiO2/L, time 180 min.

Close modal

The isoelectric point (pHzc) is the pH at which a molecule has no net/zero electric charges. The pHzc value of TiO2 is 6.3. The TiO2 surface carries a positive charge at low pH, while the charges on CAF and its intermediates are primarily negative and neutral. Thus, at low pH, organic molecule adsorption was facilitated and better photocatalytic degradation was promoted. The photocatalyst also exhibited more photocatalytic activity, due to the greater concentration of hydroxyl radicals. It is noted, too, that TiO2 particles agglomerate when dispersed in water and that their agglomerated sizes vary from 0.2 to 1.2 μm (Fernandez et al. 2014). Particle agglomeration and particle-particle interaction reduce the active sites available for surface holes and electrons, and thus removal efficiency.

Effect of catalyst dose on CAF and COD removal

Pre-assessment of the optimum photocatalyst dose offers several advantages, including (i) avoiding the use of excess photocatalyst, and (ii) total adsorption of efficient photons. In this study, experiments were conducted with 5 mg-CAF/L initial concentration at pH 7.2, and aliquots were collected every 30 min and analysed for residual CAF concentration. The results are depicted in Figures 2(c) and 2(d).

Increasing the photocatalyst dose from 0.1 to 0.5 g/L raised photocatalytic degradation efficiency from 45.1 to 87.2%. Increasing it further, however, lowered removal efficiency; for example, to 57.8% at 0.9 g/L, because the excess photocatalyst dose did not facilitate light scattering but reduced light penetration into the reaction mixture (Qourzal et al. 2012; Elhalil et al. 2018). The optimum catalyst dose of 0.5 g/L was thus chosen for further studies.

Effect of initial CAF concentration on its removal and kinetics

The effect of initial CAF concentration on its degradation was studied by varying its initial concentration from 5 to 20 mg/L. The experiments were conducted at pH 7.2 with 0.5 g/L catalyst dose (the optimum). The results are shown in Figures 2(e) and 2(f). Hydroxyl radicals are short-lived and exist only for nanoseconds, so that they can only react at or near the location where they are formed. Increasing the CAF concentration increases the probability of collision with the oxidizing species, resulting in an increase in the degradation rate.

The experimental data were fitted to pseudo-first-order kinetics with respect to the CAF concentration – Equations (2) and (3) – as reported by others (Shu et al. 2013; Phong & Hur 2015).
formula
(2)
formula
(3)
where [CAF]t (mg/L) – the CAF concentration at time t; [CAF]0 (mg/L) – the initial concentration of CAF; t (min) - the reaction time and k (min−1) – the pseudo-first-order rate constant. First-order rate constants were determined by regression analysis and Table 1 shows the constants (k) and R2 (coefficient of determination) values for different CAF concentrations. The plots for ln [CAF]0/[CAF]t and ln [COD]0/[COD]t versus t are shown in Figures 3(a) and 3(b). The calculated R2 values confirmed the pseudo-first-order kinetics removal of CAF. It was also observed that, as the initial concentration increased from 5 to 20 mg/L, the rate constant fell from 0.01 to 0.0021 for CAF degradation and 0.0053 to 0.0028 for COD removal.
Table 1

Pseudo-first-order kinetic data for CAF degradation and COD removal

CAF degradation
t1/2 (min)COD removal
CAF concentration (mg/L)K (min−1)R2K (min−1)R2
0.01 0.9541 69.3 0.0053 0.9367 
0.0072 0.9757 96.25 0.005 0.9533 
10 0.0053 0.9757 130.8 0.0045 0.9563 
12 0.0041 0.9756 169 0.0039 0.9526 
15 0.0029 0.9473 239 0.0033 0.9488 
20 0.0021 0.8957 330 0.0028 0.9515 
CAF degradation
t1/2 (min)COD removal
CAF concentration (mg/L)K (min−1)R2K (min−1)R2
0.01 0.9541 69.3 0.0053 0.9367 
0.0072 0.9757 96.25 0.005 0.9533 
10 0.0053 0.9757 130.8 0.0045 0.9563 
12 0.0041 0.9756 169 0.0039 0.9526 
15 0.0029 0.9473 239 0.0033 0.9488 
20 0.0021 0.8957 330 0.0028 0.9515 
Figure 3

Pseudo-first-order kinetic plots of (a) ln([CAF]0/[CAF]t), and (b) ([COD]0/[COD]t) versus time for CAF.

Figure 3

Pseudo-first-order kinetic plots of (a) ln([CAF]0/[CAF]t), and (b) ([COD]0/[COD]t) versus time for CAF.

Close modal
In pseudo-first-order reactions, the half-life depends on the reaction rate constant and is given by Equation (4).
formula
(4)

The k values obtained in this study coincide with the results observed by others (Chuang et al. 2011; Luna et al. 2018; Mai et al. 2018; Sacco et al. 2018; Ghosh et al. 2019; Muangmora et al. 2020). Table 2 shows comparisons of the pseudo-first-order rate constants. The half-life, t1/2, determined was 69 min at the optimized concentration of 5 mg-CAF/L. While this coincides with the results obtained by others, Sacco et al. (2018) reported t1/2 as 92 min and Elhalil et al. (2018) reported 87 min.

Table 2

Literature comparisons for pseudo-first-order rate constants

CitationLight sourceCAF initial concentration (mg/L)Removal efficiency (%)K (min−1)
Mai et al. (2018)  8 W halogen UV lamp 100 0.044 
Sacco et al. (2018)  UV LED 12 W, 365 nm lamp 25 96 0.0075 
Muangmora et al. (2020)  UV C lamp 99 0.0302 
CitationLight sourceCAF initial concentration (mg/L)Removal efficiency (%)K (min−1)
Mai et al. (2018)  8 W halogen UV lamp 100 0.044 
Sacco et al. (2018)  UV LED 12 W, 365 nm lamp 25 96 0.0075 
Muangmora et al. (2020)  UV C lamp 99 0.0302 

Optimization of operating variables for intensification of CAF degradation and RSM modelling

The interactions between dependent (CAF and COD removal) and independent (initial CAF concentration, catalyst dose and pH) variables were analysed using a quadratic model. For the experimental data, an RSM model with central composite design (CCD) was employed. The experiment parameters and the experimental design are shown in Tables 3 and 4.

Table 3

CCD parameters for CAF degradation

ParameterSymbolLow (−1)Center (0)High (+1)
x1 CAF concentration (mg/L) 12.5 20 
x2 Catalyst dose (g/L) 0.1 0.5 0.9 
x3 pH 
ParameterSymbolLow (−1)Center (0)High (+1)
x1 CAF concentration (mg/L) 12.5 20 
x2 Catalyst dose (g/L) 0.1 0.5 0.9 
x3 pH 
Table 4

Experimental data in CCD for studying CAF photodegradation

RunFactor 1 A: CAF concentration (mg/L)Factor 2 B: Catalyst dose (g/L)Factor 3 C: pHResponse 1 CAF removal (%)Response 2 COD removal (%)
10.00 0.50 7.00 64.8 58.8 
15.00 0.50 7.00 44.9 43.8 
5.00 0.30 7.00 63.4 58.2 
5.00 0.50 3.00 92.3 69.5 
1.89 0.50 7.00 86.6 66.7 
12.00 0.50 7.00 55.4 53.3 
20.00 0.50 7.00 35.6 42.6 
8.00 0.50 7.00 75.9 62.9 
5.00 0.50 7.00 87.3 66.7 
10 12.50 0.50 9.00 60.2 55.3 
11 5.00 0.70 7.00 72.8 60.1 
12 5.00 0.10 7.00 45.1 49.4 
13 5.00 0.90 7.00 57.8 53.2 
14 5.0 0.50 7.00 86.7 66.7 
15 12.50 0.50 5.00 89.1 68.3 
RunFactor 1 A: CAF concentration (mg/L)Factor 2 B: Catalyst dose (g/L)Factor 3 C: pHResponse 1 CAF removal (%)Response 2 COD removal (%)
10.00 0.50 7.00 64.8 58.8 
15.00 0.50 7.00 44.9 43.8 
5.00 0.30 7.00 63.4 58.2 
5.00 0.50 3.00 92.3 69.5 
1.89 0.50 7.00 86.6 66.7 
12.00 0.50 7.00 55.4 53.3 
20.00 0.50 7.00 35.6 42.6 
8.00 0.50 7.00 75.9 62.9 
5.00 0.50 7.00 87.3 66.7 
10 12.50 0.50 9.00 60.2 55.3 
11 5.00 0.70 7.00 72.8 60.1 
12 5.00 0.10 7.00 45.1 49.4 
13 5.00 0.90 7.00 57.8 53.2 
14 5.0 0.50 7.00 86.7 66.7 
15 12.50 0.50 5.00 89.1 68.3 

The experimental data were thus validated, and the variables' synergistic and antagonistic effects were determined and analysed with the minimum number of experiments. The second-order polynomial equation was obtained to describe the correlation between the independent variable and CAF degradation. The ANOVA results for CAF degradation and COD removal are given in Tables 5 and 6.

Table 5

ANOVA results for CAF removal efficiency

SourceSum of SquaresdfMean SquareFp
Model 444.85 740.98 28.78 <0.0001 Significant 
A-CAF concentration 4.43 4.43 0.17 0.6892  
B-catalyst dose 121.10 121.10 4.70 0.0619  
C-pH 893.22 893.22 34.69 0.0004  
AC 589.42 589.42 22.89 0.0014  
B2 1,329.97 1,329.97 51.66 <0.0001  
C2 476.65 476.65 18.51 0.0026  
Residual 205.96 25.75    
Lack of Fit 205.78 29.40 163.32  Not Significant 
Pure Error 0.18 0.18 0.0602   
Cor Total 4,651.82 14     
SourceSum of SquaresdfMean SquareFp
Model 444.85 740.98 28.78 <0.0001 Significant 
A-CAF concentration 4.43 4.43 0.17 0.6892  
B-catalyst dose 121.10 121.10 4.70 0.0619  
C-pH 893.22 893.22 34.69 0.0004  
AC 589.42 589.42 22.89 0.0014  
B2 1,329.97 1,329.97 51.66 <0.0001  
C2 476.65 476.65 18.51 0.0026  
Residual 205.96 25.75    
Lack of Fit 205.78 29.40 163.32  Not Significant 
Pure Error 0.18 0.18 0.0602   
Cor Total 4,651.82 14     

Std. Dev.=5.07; Mean=67.86; C.V %=7.48; Adeq Precision=17.08.

Table 6

ANOVA results for COD removal efficiency

SourceSum of squaresdfMean squareFp
Model 990.88 165.15 19.78 0.0002 Significant 
A-CAF concentration 0.72 0.72 0.086 0.7772  
B-catalyst dose 9.02 9.02 1.08 0.3289  
C-pH 208.74 208.74 25.00 0.0011  
AC 147.98 147.98 17.73 0.0030  
B2 266.94 266.94 31.97 0.0005  
C2 124.42 124.42 14.90 0.0048  
Residual 66.79 8.35    
Lack of Fit 66.79 9.54 0.19 0.9581 Not Significant 
Pure Error 0.000 0.000    
Cor Total 1,057.67 14     
SourceSum of squaresdfMean squareFp
Model 990.88 165.15 19.78 0.0002 Significant 
A-CAF concentration 0.72 0.72 0.086 0.7772  
B-catalyst dose 9.02 9.02 1.08 0.3289  
C-pH 208.74 208.74 25.00 0.0011  
AC 147.98 147.98 17.73 0.0030  
B2 266.94 266.94 31.97 0.0005  
C2 124.42 124.42 14.90 0.0048  
Residual 66.79 8.35    
Lack of Fit 66.79 9.54 0.19 0.9581 Not Significant 
Pure Error 0.000 0.000    
Cor Total 1,057.67 14     

Std. Dev.=2.89; Mean=58.37; C.V %=4.95; Adeq Precision=14.445.

ANOVA with a high coefficient of determination (R2) reveals a good agreement between the experimental and predicted values. In this study, ANOVA work yielded R2 and adjusted R2 values of 0.9557 and 0.9225, and 0.9369 and 0.8895, respectively, for CAF and COD removal, indicating that the quadratic model is adequate. The degree of freedom (df) indicates the number of estimated parameters used to compute the source's sum of squares. The Model F-value (test for comparing the source's mean square to the residual mean square) of 28.78 for CAF and 19.78 for COD removals obtained in this experiment implies that the model is significant. The ‘lack of fit’ is the amount by which the model's predictions miss observations. In other words, lack of fit’ is the variation of data around the fitted model. It should be insignificant for the model to fit well in the experimental data. The non-significant ‘Lack of Fit F-value’ of 163.32 and 0.19 obtained for CAF and COD removals indicates that there is a good correlation between process variables and response. The normal plot of residuals and the predicted vs actual response are shown in Figure 4. The residuals fall on a straight line, suggesting that the errors are distributed normally.

Figure 4

Normal probability plot of residuals, and predicted vs actual for CAF photocatalytic degradation [(a) & (c)], and COD removal [(b) & (d)].

Figure 4

Normal probability plot of residuals, and predicted vs actual for CAF photocatalytic degradation [(a) & (c)], and COD removal [(b) & (d)].

Close modal

The residuals vs predicted, residuals vs run, Box-Cox plot for power transforms, and residuals vs concentration, for both CAF and COD removals, are shown in Figures 5 and 6.

Figure 5

Residuals vs predicted and residuals vs run photocatalytic values, for CAF degradation [(a) & (c)] and COD removal [(b) & (d)].

Figure 5

Residuals vs predicted and residuals vs run photocatalytic values, for CAF degradation [(a) & (c)] and COD removal [(b) & (d)].

Close modal
Figure 6

Box-Cox plot for power transforms and residuals vs CAF concentration, for CAF photocatalytic degradation [(a) & (c)] and COD removal [(b) & (d)].

Figure 6

Box-Cox plot for power transforms and residuals vs CAF concentration, for CAF photocatalytic degradation [(a) & (c)] and COD removal [(b) & (d)].

Close modal

The 3D surface plots are shown in Figure 7. Design-Expert software version 7.0.0 Stat-Ease (2005) with desirability approach was used to predict the maximum CAF and COD removal efficiencies (Stamatis et al. 2015). Maximum removal efficiencies were obtained at acidic pH because the surface charge on TiO2 is then positive. Increasing the TiO2 dose increased CAF removal efficiency up to 0.5 g-CAF/L, after which it decreased. Light screening and scattering caused the removal efficiency to decrease, while catalyst particle agglomeration also contributed substantially (Antonopoulou et al. 2012; Rani & Karthikeyan 2021). Increasing initial CAF concentrations also led to a fall in removal efficiency because the availability of hydroxyl radicals was inadequate.

Figure 7

RSM 3D surface plots for CAF [(a) and (b)] and COD removal [(c) & (d)].

Figure 7

RSM 3D surface plots for CAF [(a) and (b)] and COD removal [(c) & (d)].

Close modal

The photocatalytic degradation of CAF was evaluated in a slurry photocatalytic reactor with intermittent UV irradiation. The highest CAF and COD removals were 86.7 and 66.7% respectively at optimized conditions: CAF=5 mg/L; pH=7.2 and TiO2=0.5 g/L. CAF and COD removals followed pseudo-first-order kinetics. The experimental data were analysed with RSM modelling, using Design-Expert software. ANOVA yielded R2=0.9557 and adjusted R2=0.9225 for CAF removal, and R2=0.9369 and adjusted R2=0.8895 for COD removal, confirming good agreement between the experimental and predicted values. The RSM 3D surface plots also showed that all three operating parameters studied were significant in CAF removal. The study's results also showed that CAF molecules were not degraded completely and COD removal was less than CAF removal.

All relevant data are included in the paper or its Supplementary Information.

Ahmad
R.
,
Ahmad
Z.
,
Khan
A. U.
,
Mastoi
N. R.
,
Alam
M.
&
Kim
J.
2016
Photocatalytic systems as an advanced environmental remediation: recent developments, limitations and new avenues for applications
.
Journal of Environmental Chemical Engineering
4
(
4
),
4143
4164
.
Arfanis
M. K.
,
Adamou
P.
,
Moustakas
N. G.
,
Triantis
T. M.
,
Kontos
A. G.
&
Falaras
P.
2017
Photocatalytic degradation of salicylic acid and caffeine emerging contaminants using titania nanotubes
.
Chemical Engineering Journal
310
(
2
),
525
536
.
Bahnemann
D. W.
,
Hilgendorff
M.
&
Memming
R.
1997
Charge carrier dynamics at TiO2 particles: reactivity of free and trapped holes
.
Journal of Physical Chemistry B
101
(
21
),
4265
5275
.
Barcelo
D.
&
Petrovic
M.
2008
Emerging Contaminants From Industrial and Municipal Wastes: Occurrence, Analysis and Effects. The Handbook of Environmental Chemistry
.
Springer
,
Berlin
.
Heidelberg 5/5S/5S/1
, pp.
1
35
.
Buerge
I. J.
,
Poiger
T.
,
Muller
M. D.
&
Buser
H. R.
2003
Caffeine an anthropogenic marker for wastewater contamination of surface waters
.
Environmental Science and Technology
37
(
4
),
691
700
.
Chuang
L. C.
,
Luo
C. H.
,
Huang
S. W.
,
Wu
Y. C.
&
Huang
Y. C.
2011
Photocatalytic degradation mechanism and kinetics of caffeine in aqueous suspension of nano-TiO2
.
Advanced Materials Research
214
(
1
),
97
102
.
Design Expert, Version 7.0.0
2005
Stat-Ease, Design Expert Inc., Minneapolis
.
Diaz-Uribe
C.
,
Vallejo
W.
&
Romos
W.
2014
Methylene blue photocatalytic mineralization under visible irradiation on TiO2 thin films doped with chromium
.
Applied Surface Science
319
(
1
),
121
127
.
Edwards
Q. A.
,
Kullikov
S. M.
&
Garner-O'Neale
L. D.
2015
Caffeine in surface and wastewaters in Barbados, West Indies
.
SpringerPlus
4
(
57
),
1
12
.
Elhalil
A.
,
Elmoubarki
R.
,
Farnane
M.
,
Machrouhi
A.
,
Sadiq
M.
,
Mahjoubi
F.
,
Qourzal
S.
&
Barka
N.
2018
Photocatalytic degradation of caffeine as a model pharmaceutical pollutant on Mg doped ZnO-Al2O3 hetero structure
.
Environmental Nanotechnology Monitoring and Management
10
(
1
),
63
72
.
Fernandez
R. L.
,
McDonald
J. A.
,
Khan
S. J.
&
Clech
P. L.
2014
Removal of pharmaceuticals and endocrine disrupting chemicals by a submerged membrane photocatalysis reactor (MPR)
.
Separation Purification and Technology
127
(
1
),
131
139
.
Fujishima
A.
,
Zhang
X.
&
Tryk
D. A.
2008
TiO2 photocatalysis and related surface phenomena
.
Surface Science Reports
63
(
12
),
515
582
.
Gaya
U. I.
&
Abdullah
A. H.
2008
Heterogeneous photocatalytic degradation of organic contaminants over titanium dioxide: a review of fundamentals, progress and problems
.
Journal of Photochemistry and Photobiology C: Photochemistry Reviews
9
(
1
),
1
12
.
Ghosh
M.
,
Manoli
K.
,
Shen
X.
,
Wang
J. H.
&
Ray
A. K.
2019
Solar photocatalytic degradation of caffeine with titanium dioxide and zinc oxide nanoparticles
.
Journal of Photochemistry and Photobiology A
377
(
1
),
1
7
.
Indermuhle
C.
,
De Vidales
M.
,
Saez
C.
,
Robles
J.
,
Canizares
P.
,
Garcia-Reyes
J.
,
Molina-Diaz
A.
,
Comninellis
C.
&
Rodrigo
M. A.
2013
Degradation of caffeine by conductive diamond electrochemical oxidation
.
Chemosphere
93
(
9
),
1720
1725
.
Klamerth
N.
,
Malato
S.
,
Maldonado
M.
,
Aguera
A.
&
Fernandez-Alba
A.
2010
Application of photo-Fenton as a tertiary treatment of emerging contaminants in municipal wastewater
.
Environmental Science and Technology
44
(
5
),
1792
1798
.
Laohaprapanon
S.
,
Matahum
J.
,
Tayo
L.
&
You
S.-J.
2015
Photodegradation of reactive black 5 in a ZnO/UV slurry membrane reactor
.
Journal of Taiwan Institute of Chemical Engineers
49
(
1
),
136
141
.
Lovett
R.
2005
Coffee the demon drink?
New Scientist.
187
,
38
41
.
Luna
R.
,
Solis
C.
,
Ortiz
N.
,
Galicia
A.
,
Sandoval
F.
,
Zermeno
B.
&
Mochezuma
E.
2018
Photocatalytic degradation of caffeine in a solar reactor system
.
International Journal of Chemical Reactor Engineering
16
(
10
),
1
10
.
Marques
R. R.
,
Sampaio
M. J.
,
Carrapico
P. M.
,
Silva
C. G.
,
Morales-Torres
S.
,
Drazie
G.
,
Faria
J. L.
&
Silva
A. M.
2013
Photocatalytic degradation of caffeine: developing solutions for emerging pollutants
.
Catalysis Today
209
(
1
),
10
115
.
Miners
J. O.
&
Birkett
D. J.
1996
The use of caffeine as a metabolic probe for human drug metabolizing enzymes
.
General Pharmacology: The Vascular System
27
(
2
),
245
249
.
Moore
M.
,
Greenway
S.
,
Farris
J.
&
Guerra
B.
2008
Assessing caffeine as an emerging environmental concern using conventional approaches
.
Archives of Environmental Contamination and Toxicology
54
(
1
),
31
35
.
Mozia
S.
2010
Photocatalytic membrane reactors (PMRs) in water and wastewater treatment
.
Separation and Purification Technology
73
(
2
),
71
91
.
Pathakoti
K.
,
Manubolu
M.
&
Hwang
H. M.
2018
Nanotechnology applications for environmental industry
. In:
Handbook of Nanomaterials for Industrial Applications
, Vol.
48
(
Chaudhery
M. H.
ed.).
Elsevier
,
Amsterdam, The Netherlands
, pp.
894
907
.
Puga
A. V.
2016
Photocatalytic production of hydrogen from biomass-derived feed stocks
.
Coordination Chemistry Reviews
315
(
1
),
1
66
.
Qourzal
S.
,
Barka
N.
,
Belmouden
M.
,
Abaamrane
A.
,
Alahiane
S.
,
Elouardi
M.
,
Assabbane
A.
&
Ait-Ichou
Y.
2012
Heterogeneous photocatalytic degradation of 4-nitrophenol on suspended titania surface in a dynamic photo reactor
.
Fresenius Environmental Bulletin
21
(
7
),
1972
1981
.
Rimoldi
L.
,
Meroni
D.
,
Falletta
E.
,
Pifferi
V.
,
Falciola
L.
,
Cappelletti
G.
&
Adizzone
S.
2017
Emerging pollutant mixture mineralization by TiO2 photocatalysts. The role of the water medium
.
Photochemical and Photobiological Sciences
16
(
1
),
60
66
.
Rosal
R.
,
Rodriguez
A.
,
Perdgon-Melon
J. A.
,
Petre
A.
,
Garia-Calvo
E.
,
Gomez
M. J. A.
,
Aguera
A.
&
Fernandez-Alba
A. R.
2008
Degradation of caffeine and identification of transformation products generated by ozonation
.
Chemosphere
74
(
6
),
825
831
.
Sacco
O.
,
Vaiano
L.
,
Rizzo
L.
&
Sannino
D.
2018
Photocatalytic activity of a visible light active structured photocatalyst developed for municipal wastewater treatment
.
Journal of Cleaner Production
175
(
1
),
38
49
.
Souza
F. S.
&
Feris
L. A.
2015
Degradation of caffeine by advanced oxidative O3 and O3/UV
.
Ozone: Science and Engineering
37
(
4
),
397
384
.
Stamatis
N.
,
Antonopoulou
M.
&
Konstantinou
I.
2015
Photocatalytic degradation kinetics and mechanisms of fungicide tebuconazole in aqueous TiO2 suspensions
.
Catalysis Today
252
(
1
),
93
99
.
Sudha
D.
&
Sivakumar
P.
2015
Review on the photocatalytic activity of various composite catalysts
.
Chemical Engineering and Processing: Process Intensification
97
(
1
),
112
133
.
Torres
A. C.
,
Barsan
M. M.
&
Brett
C. M. A.
2014
Simple electrochemical sensor for caffeine based on carbon and Nafion-modified carbon electrodes
.
Food Chemistry
149
(
1
),
215
220
.
Trovo
A. G.
,
Silva
T. F.
,
Gomes
O.
,
Machado
A. E.
Jr
,
Neto
W. B.
,
Muller
P. S.
&
Daniel
D.
Jr
2013
Degradation of caffeine by photo-Fenton process: optimization of treatment conditions using experimental design
.
Chemosphere
90
(
2
),
170
175
.
Vaiano
V.
,
Matarangolo
M.
&
Sacco
O.
2018
UV-LEDs floating-bed photoreactor for the removal of caffeine and paracetamol using ZnO supported on polystyrene pellets
.
Chemical Engineering Journal
350
(
1
),
703
713
.
Zhang
J.
,
Wang
L. P.
,
Guo
W.
,
Peng
X. D.
,
Li
M.
&
Yuan
Z. B.
2011
Sensitive differential pulse stripping voltammetry of caffeine in medicines and cola using a sensor based on multi-walled carbon nanotubes and Nafion
.
International Journal of Electrochemical Science
6
(
4
),
997
1006
.
Zhou
P.
,
Xie
Y.
,
Fang
J.
,
Ling
Y.
,
Yu
C.
,
Liu
X.
,
Dai
Y.
,
Qin
Y.
&
Zhou
D.
2017
Cds quantum dots confined in mesoporous TiO2 with exceptional photocatalytic performance for degradation of organic pollutants
.
Chemosphere
178
(
1
),
1
10
.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (CC BY-NC-ND 4.0), which permits copying and redistribution for non-commercial purposes with no derivatives, provided the original work is properly cited (http://creativecommons.org/licenses/by-nc-nd/4.0/).