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Universidad del Turabo
Propranolol Degradation by Photocatalysis Using Titanium Oxide
By
Luis G González
BS, Chemical Engineering, University of Puerto Rico
MS, Environmental Management, Universidad Metropolitana
DISSERTATION
Submitted to the School of Natural Sciences and Technology of the Universidad del Turabo
in partial fulfillment of the requirements for the degree of Doctor of Philosophy
in Environmental Sciences
(Environmental Management)
Gurabo, Puerto Rico
May, 2016
ii
Universidad del Turabo
A dissertation submitted in partial fulfillment of the requirements for the degree of
Doctor of Philosophy
27 April, 2016 date of defense
Propranolol Degradation by Photocatalysis Using Titanium Oxide
Luís G González
Approved:
_____________________________ ____________________________ Francisco Márquez Linares PhD José J Ducongé PhD Research Advisor Member _____________________________ ____________________________ Teresa Lipsett PhD María del C Cotto-Maldonado PhD Member and Dean Member _____________________________ Luigi Guariniello PhD Member
UNIVERSIDAD DEL TURABO
CERTIFICATE OF APPROVAL OF DISSERTATION
The dissertation presented by Luís G Gonzalez was revised and approved by the
members of the Dissertation Committee. The form certifying Fulfillment of Academic
Requirements for the Doctorate, signed by the members of the committee, has been filed
with the Registrar and with the Center for Graduate Studies and Research of the
Universidad del Turabo.
MEMBERS OF THE DISSERATION COMMITTEE
Francisco Márquez Linares, Professor, Universidad del Turabo
Chair, Dissertation Committee
Teresa Lipsett, Professor, Universidad del Turabo
Member
José J Ducongé, Professor, Universidad del Turabo
Member
María del C Cotto-Maldonado, Assistant Professor, Universidad del Turabo
Member
Luigi Guariniello
Member
©Copyright 2016
Luis G. González. All Rights Reserved.
v
Dedications
To my dearest Glendy and Gustavo, who supported me patiently and without
complaint during the six years I spent in this endeavor. Once finished this project, I will
open more time to spend together, is a promise; and to my parents who taught me the
importance of the knowledge.
vi
Acknowledgements
First at all I want to recognize my God. He provides the energy, health and wisdom
to complete this project. I want to express my gratitude to Lilly del Caribe, which provided
the financial resources to fund the courses. Also I appreciated all the help, advise,
empathy, guidance, and patience of my advisor Francisco Márquez. I would like to thank
Maria Cotto, for her support, and counsel. Many thanks to my co-workers, Abraham E
García, Abniel Machín, Loraine Soto, Dayna Ortiz, Luis López and Jorge Valentín. We
spent a lot of hours in the laboratory; I have a lot of good memories, and my best wishes
to finish their degrees. Thanks to Fred Schaffner, I remember your word starting this
journey; “If you don’t finish this degree you are just subsidizing the education of others”.
To my caring, loving, and supportive wife, Glendy: my deepest gratitude. It was a
great comfort and relief to know that you were willing to provide management of our
household activities while I am spending time in my studies.
Finally, the financial support from the US DoE, through the Massie Chair Project
at Universidad del Turabo, US DoD under contract W911NF-14-1-0046, the Spanish
Education and Research Ministry under Grant MAT2010-19804, and the Ministerio de
Economía y Competitividad of Spain through the grant ENE2014-57977-C2-1-R are
gratefully acknowledged. Finally, I like to thank to "Servicio Interdepartamental de
Investigación" from Universidad Autónoma de Madrid (Spain) for the use of the
characterization facilities.
vii
Curriculum Vitae
Luis G González López
(a) Professional Preparation
PhD in Environmental Science, Universidad del Turado, (Gurabo), Present.
Master Thesis in Environmental Sciences, Universidad Metropolitana (San Juan), 2003.
BS in Chemical Engineering, University of Puerto Rico (Mayagüez), 1992.
(b) Appointments
2007-present: Senior Environmental Engineer, Lilly del Caribe Inc. Carolina, Puerto Rico.
2001-2007: Auxiliary Head, Environmental Protection and Quality Control Division, Puerto
Rico Electric Power Authority, San Juan, Puerto Rico.
1999-2001: Environmental Affair Supervisor, MOVA Pharmaceuticals Inc., Caguas,
Puerto Rico.
1997-1999: Staff Engineer, Environmental Quality Board, San Juan, Puerto Rico.
(c) Publications:
1. LG González, JI Valentín, F Márquez. pH effects during propranolol degradation
by photocatalysis using TiO2, Ambientis 2016
(d) Credentials
1. Licensed Professional Engineer, Puerto Rico, 18627
2. Register Environmental Manager, National Board of Environmental Professionals,
1138
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(e) Awards
1. School of Engineering Dean’s List - University of PR – Mayaguez Campus
2. Honor List – Metropolitan University
3. Tau Beta Phi Engineer Honor Society
4. Environmental Science Graduate Scholarship – Pierluissi Foundation
5. 2010 Lilly del Caribe Inc. Productivity Award
ix
Table of Contents
page
List of Tables ......................................................................................................... xi
List of Figures ........................................................................................................ xii
List of Appendixes ................................................................................................. xvi
Abstract ................................................................................................................. xvii
Resumen in Spanish ............................................................................................. xix
CHAPTER One Introduction .................................................................................. 1
1.1. Propranolol at the environment ................................................................. 3
1.2. Alternative for drugs degradations ............................................................ 8
1.3. Solar radiation influence ........................................................................... 11
1.4. Influence of the pH .................................................................................... 15
1.5. Regulation ................................................................................................ 17
1.6. Research scope ........................................................................................ 19
CHAPTER Two Methods and instrumentation techniques ..................................... 22
2.1. Raman spectroscopy ................................................................................ 22
2.2. X-ray powder diffraction (XRD) ................................................................. 26
2.3. UV-vis spectroscopy ................................................................................. 30
2.4. Brunauer-Emmett-Teller (BET) surface area ............................................. 35
2.5. Scanning electron microscopy .................................................................. 38
2.6. Liquid chromatography and mass spectrometry ........................................ 43
CHAPTER Three Experimental Methodology ........................................................ 50
3.1. Synthesis of TiO2 nanowires (TiO2NWs) ................................................... 50
3.2. Titanium oxide characterization ................................................................ 52
x
..................................................................................................................... page
3.3. Study of the degradation of propranolol by UV-vis spectroscopy .............. 58
3.4. Propranolol degradation as a function of pH ............................................. 59
3.5. Propranolol degradation as a function of oxygen ...................................... 61
3.6. Selected parameters for the experimental design ..................................... 63
CHAPTER Four Results and Discussion ............................................................... 65
4.1. Effects of pH and catalyst concentration on the photocatalytic
degradation of propranolol ........................................................................ 65
4.2. Oxygen variation effects on the propranolol degradation .......................... 74
4.3. Experimental design ................................................................................. 80
4.4. Characterization of propranolol photodegradation byproducts .................. 87
4.5. Determination of the reaction rate ............................................................. 91
CHAPTER Five Conclusions ................................................................................. 95
LITERATURE CITED ............................................................................................ 98
xi
List of Tables
page
Table 2.6.1. UPLC mobile phase gradient ............................................................. 48
Table 3.2.1. Surface area results for TiO2NWs and anatase .................................. 53
Table 4.1.1. Propranolol degradation as a function of pH and concentration of
catalyst between 0.7 and 1.1 g L-1 (TiO2 anatase) ............................. 66
Table 4.1.2. Propranolol degradation, as a function of pH and concentration of
catalyst between 1.3 and 1.7 g L-1 (TiO2 anatase) ............................. 67
Table 4.2.1. Propranolol degradation yield, using hydrogen peroxide and air
as oxygen sources ............................................................................ 76
Table 4.3.1. Degradation rates obtained for the different experimental
Conditions .......................................................................................... 82
Table 4.3.2. Summary of the statistical fit parameters ........................................... 83
Table 4.3.3. Analysis of variance of the experimental design ................................. 84
Table 4.3.4. Lack of fit for the experimental design ................................................ 84
Table 4.3.5. Estimated coefficients for the experimental design ............................ 86
Table 4.5.1. Summary of propranolol degradation after 6 hours of reaction,
and estimation of the reaction rate ..................................................... 91
Table 4.5.2. Estimation of reactor lengths, based on the degradation yields .......... 94
xii
List of Figures
page
Figure 1.3.1. Parabolic system and focus Illustration ............................................. 12
Figure 1.3.2. Scheme of a plug flow reactor .......................................................... 13
Figure 1.3.3. Continue flow diagram ...................................................................... 14
Figure 1.4.1. Graphical illustration for the electrostatic interaction between
TiO2 and propranolol ........................................................................ 16
Figure 1.6.1. Photocatalysis diagram, representing the energy transition of the
catalyst during the light exposure ...................................................... 20
Figure 2.1.1. Model of solid balls (atoms), connected by springs (bonds) .............. 23
Figure 2.1.2. Rayleight, Stokes, and anti-Stokes transitions .................................. 23
Figure 2.1.3.Thermo DXR Raman spectrometer .................................................... 26
Figure 2.2.1. Bragg diffraction for two beams with identical wavelength in a
crystal (solid) ................................................................................... 27
Figure 2.2.2. Parameters which characterize the shape and size of an
Elementary cubic cell ....................................................................... 29
Figure 2.2.3. Bruker XRD D8 Advance at Universidad del Turabo, Gurabo Camp . 30
Figure 2.3.1. Energy distribution of the different electron orbitals........................... 32
Figure 2.3.2. Scheme of a simple UV-vis spectrometer ......................................... 33
Figure 2.3.3. UV-vis Shimadzu 2401 PC spectrometer .......................................... 34
Figure 2.4.1. Different steps corresponding to the nitrogen adsorption onto the
particle surface ................................................................................. 36
Figure 2.4.2. Linear representation of the BET equation ........................................ 37
Figure 2.4.3. Micromeritics' ASAP 2020 Accelerated Surface Area and
Porosimetry....................................................................................... 38
xiii
page
Figure 2.5.1. Scheme of a conventional high vacuum SEM Instrument ................. 39
Figure 2.5.2. Path of a flow of electrons through an electromagnetic lens ............. 40
Figure 2.5.3. Electron collision on a sample, generating BE, SE and X-rays ......... 41
Figure 2.5.4. Diagram for beam specimen interactions: elastic events, and
inelastic events ................................................................................. 42
Figure 2.5.5. Scanning electron microscope (SEM) JEOL Model JSM-6010LA ..... 43
Figure 2.6.1. Scheme of a conventional liquid chromatograph ............................... 44
Figure 2.6.2. Schematic diagram corresponding to a mass spectrometer .............. 46
Figure 2.6.3. Ion fragmentation and spectrum differences for MS/MS and
MRM mode of Operation ................................................................... 47
Figure 2.6.4. UPLC/MS Water Acquity Series H, coupled with a Xevo TDQ
mass spectrometer ........................................................................... 49
Figure 3.1.1. Four silicon substrates inside the Teflon container............................ 51
Figure 3.1.2. Closed stainless steel autoclave and silicon substrates with
TiO2NWs grown on the surface ......................................................... 52
Figure 3.2.1. SEM images of TiO2NWs at different magnification .......................... 54
Figure 3.2.2. SEM image of commercial anatase .................................................. 55
Figure 3.2.3. Raman spectrum of the as-synthesized TiO2NWs ............................ 56
Figure 3.2.4. Image of the Bruker D8 Advance diffractometer ............................... 57
Figure 3.2.5. X-ray diffraction patterns of commercial anatase and TiO2NWs ........ 58
Figure 3.3.1. UV Spectra of propranolol in aqueous solution, at different
Concentrations .................................................................................. 59
Figure 3.4.1. Propranolol structure balanced with HCl ........................................... 60
xiv
page
Figure 3.4.2. Experimental setup showing the Erlenmeyer with the reaction
Mixture over the magnetic mixer, the air supply line and
fluorescent lamps ............................................................................. 61
Figure 3.5.1. UV-vis spectra of propranolol solutions with different
concentrations of H2O2; the selected concentration of H2O2 ...................... 62
Figure 3.6.1. Experimental layout .......................................................................... 63
Figure 4.1.1. Leverage plot for preliminary run with pH and catalyst concentration
Adjustments ...................................................................................... 68
Figure 4.1.2. Leverage plot for pH variation effects on the percentage of
propranolol Degradation .................................................................... 69
Figure 4.1.3. Leverage plot of the catalyst concentration effect on the percentage
of propranolol degradation ................................................................. 71
Figure 4.1.4. Leverage plot of the combination effects of catalyst concentration
and pH on the percentage of propranolol degradation ....................... 71
Figure 4.1.5. Regression plot ................................................................................. 72
Figure 4.1.6. Quadratic regression leverage plot; catalyst concentration (TiO2)
effects on degradation of propranolol ................................................ 73
Figure 4.1.7. Quadratic regression leverage plot; catalyst concentration (TiO2)
effects on degradation of propranolol ................................................ 74
Figure 4.1.8. Estimated parameter for the new model ........................................... 74
Figure 4.2.1. Leverage plot using H2O2 and air as oxygen sources ....................... 77
Figure 4.2.2. Leverage plot for volume effects on the degradation rate.................. 78
Figure 4.2.3 Leverage plot for TiO2 effects on the degradation rate ....................... 78
page
xv
Figure 4.2.4. Leverage plot for TiO2 concentration and the volume effects
on the degradation rate ..................................................................... 79
Figure 4.3.1. Experimental layout .......................................................................... 80
Figure 4.3.2. DOE Leverage plot ........................................................................... 81
Figure 4.3.3. Cube plot diagram ............................................................................ 87
Figure 4.4.1. UPLC chromatogram of propranolol hydrochloride ........................... 88
Figure 4.4.2. MRM-MS spectra for the degradation byproducts ............................. 89
Figure 4.4.3. Proposed degradation pathway for propranolol ................................. 90
xvi
List of Appendices
page
Appendix One. UV-vis spectra. .............................................................................. 107
Appendix Two. Plug flow reactor calculation .......................................................... 119
xvii
Abstract
LUÍS G GONZÁLEZ (PhD, Environmental Sciences)
Propranolol degradation by photocatalysis using titanium oxide (April/2016)
Abstract of a doctoral dissertation at the Universidad del Turabo.
Dissertation Supervised by Dr Francisco Márquez.
No. pages in text: 121
Pharmaceutical products are manufactured worldwide to be consumed by humans
or animals. Wide dissemination of these pharmaceuticals at low concentrations is evident
today in the environment, especially in the aquatic medium. The behavior and fate of
pharmaceuticals and their metabolites in the aquatic environment is not well known.
Propranolol is a nonselective β-blocker used as a cardiovascular Active Pharmaceutical
Ingredient (API) for treatment of angina pectoris, hypertension, and cardiac arrhythmia.
The effects of propranolol on aquatics organisms have been previously studied. The
exposure of mussels, fish and others aquatic life to propranolol has been investigated in
the literature. These studies demonstrated adverse effects like decrease in byssus
strengths, reduction on byssus thread abundance, lower growth and decrease of
reproduction rate.
Titanium oxide (TiO2) is an n-type semiconductor and a typical photocatalyst,
attracting much attention from both fundamental and practical viewpoints. UV light
irradiation of the TiO2 catalyst generates electron–hole pairs, which can be represented
as localized electrons (Ti3+) and holes (O- and/or •OH radicals).
This research hypothesized that particle surface area has an important role on the
degradation reaction. The titanium oxide structure with high surface area will produce
higher degradation efficiency. Because the TiO2 nanowires (as rutile phase) have greater
xviii
surface area than TiO2 anatase (as particles), TiO2 nanowires will produce higher
degradation rate of propranolol with respect to that produced by TiO2 anatase.
Light is the fuel that drives the catalytic reactions by titanium oxide. All effort to
increase the amount of light involved in the reaction will increase the reaction rate. The
reaction occurs inside a perfluoro methyl alkoxy (MFA) line that is irradiated with UV-
visible light and placed at the focus of a parabolic solar collector to concentrate the light.
The hypothesis argued in this research was that the use of the parabolic collector panel
would increase the degradation of propranolol.
The variation of the pipe diameter was tested; the hypothesis was that larger pipe
diameters would have better yield. Basically, larger pipe diameters increase the radius
and, as a consequence, the increase of the traveling distance of the light and the light
dispersion trough the flow. The proposed research will determine the effect of the pipe
diameters on the degradation process.
The photodegradation reaction yield was monitoring using UV-vis spectroscopy.
The results demonstrated that titanium oxide nanowires, together with the use of the
collector panel and greater pipe diameters have better degradation yields.
xix
Resumen
LUÍS A GONZÁLEZ (PhD, Ciencias Ambientales)
Degradación fotocatalítica de propanolol mediante el uso de oxido de titanio (abril/2016).
Resumen de una Disertación doctoral en la Universidad del Turabo.
Disertación Supervisada por el Dr Francisco Márquez.
No. de páginas en el texto: 121
Los productos farmacéuticos son fabricados en todo el mundo para ser utilizados
por seres humanos o animales. Estos productos están ampliamente difundidos, en
concentraciones bajas, en el medio ambiente, en especial en sistemas acuáticos. El
comportamiento y la difusión de los productos farmacéuticos y sus metabolitos en los
sistemas acuáticos no son muy conocido. El propanolol es un β-bloqueante no selectivo
utilizado para el tratamiento de la angina de pecho, hipertensión, y arritmias cardíacas.
Los efectos del propanolol sobre organismos acuáticos han sido estudiados previamente.
Entre estos estudios, cabe destacar algunos desarrollados sobre el efecto de exposición
en mejillones, peces y otros organismos acuáticos. Estas investigaciones han puesto de
manifiesto la presencia de efectos adversos, tales como la disminución en la fortaleza de
los bisos en los mejillones, reducción en la abundancia de bisos, menor crecimiento, y
disminución de la tasa de reproducción.
El óxido de titanio (TiO2) es un semiconductor de tipo n y un fotocatalizador,
ampliamente estudiado desde hace varias décadas debido a sus posibles usos y elevada
disponibilidad. Cuando el TiO2 es irradiado mediante luz ultravioleta, se generan pares
electrón-hueco que pueden ser representados como electrones localizados (Ti3+) y
huecos (O- y/o radicales OH).
xx
Esta investigación plantea la hipótesis de que el área superficial del catalizador es
un factor de máxima relevancia en la reacción de degradación. La estructura de óxido de
titanio con mayor área superficial tendrá una mayor eficiencia en la degradación. Debido
a que los nanohilos de TiO2 tienen mayor área superficial que el TiO2 (con estructura de
anatasa), los nanohilos tendrán una mayor eficiencia de degradación de propanolol.
La luz es el agente activador para las reacciones fotocatalíticas. Todo esfuerzo
para ampliar la cantidad de luz que irradia una reacción fotocatalítica aumentará la
eficiencia del proceso. En esta investigación, la reacción ocurre dentro de una tubería
basada en perfluoro metil alkoxi (MFA), que ha sido irradiada con luz ultravioleta-visible y
colocada en el foco de un colector solar parabólico, para concentrar la luz sobre la tubería.
Otra de las hipótesis de esta investigación es que el uso del panel colector parabólico
aumentará la eficiencia de degradación de propanolol.
El efecto en la variación del diámetro de la tubería ha sido también otro de los
parámetros investigados. La hipótesis al respecto consiste en que los tubos con mayor
diámetro darán lugar a un mejor rendimiento en la degradación de propanolol.
Básicamente, el tubo con mayor diámetro tiene un radio mayor y, como consecuencia, la
distancia que tiene que recorrer la luz y la dispersión de la luz a través del flujo interno de
la tubería aumenta.
La reacción de fotodegradación ha sido estudiada mediante espectroscopia UV-
vis. Los resultados demostraron que los nanohilos de óxido de titanio, junto con el uso
del panel colector y tubería de mayor diámetro, producen un aumento considerable en el
rendimiento de degradación de propanolol.
1
Chapter One
Introduction
Tons of pharmaceuticals products are annually produced worldwide to be
consumed by humans or animals. Few would disagree that we live in an age of
pharmaceutical dependency. There seems to be pills for every illness. As the Canadian
singer Celine Dion reflected in a brief radio interview following the death of Michael
Jackson in June 2009, in recent years the King of Pop was taking pills to sleep, pills to
wake up, pills to perform’ (translated from the French). Wide dissemination of these
pharmaceuticals at low concentrations, mainly in the aquatic environment, is evident
today. Such concentrations have been detected in aquatic media such as influents and
effluents from wastewater treatment plants (WWTP), surface waters (rivers, lakes,
streams, estuaries, among others), seawater, groundwater and drinking water.
Pharmaceuticals are designed to target specific metabolic and molecular pathways in
humans and animals, but they often have significant side effects, too. The scientific
community is in broad agreement with the possibility that adverse effects may arise from
the uncontrolled presence of pharmaceuticals in the environment, not only for human
health, but also for aquatic organisms.
The sources of the pharmaceuticals products can be diverse. In the United States,
the contribution of manufacturing facilities to the release of medicinal products is generally
considered as low, even though pollution downstream of manufacturing plants has been
sporadically observed while monitoring specific sites (Raloff 1998, Carlsson et al. 2009;
Cardoso et al. 2014). The hospital wastewaters are also recognized as a source of Active
Pharmaceutical Ingredients (API) contamination and potential release, due to medicine
2
excretion by patients as well as diagnostic, laboratory and research activities (Kummerer
2001; Verlicchi et al. 2012). The human use is considered to be the largest contributor to
the release to the environment, especially through excretion (i.e. urine, fecal) and by
incorrect disposal of unused medicines through sinks and toilets. Between 30% and 90%
of the orally administered doses are generally excreted as active substances in the urine
of animals and humans (Mudgal et al. 2013). In addition animal care industry represents
another source of surface water contamination. The pharmaceuticals products are used
in animal nursing operations, such as injections to treat farm animals and may run off into
surface water via urine and feces without any decontamination processes (Matsui et al.
2008, Kummerer 2009). Typically pharmaceuticals manufacturing, hospitals and
household have the sewers lines connected to public wastewater systems Publicly Owned
Treatment Work (POTW). Effluents from POTW are identified as a major source of
pharmaceuticals products in receiving water bodies. The unmetabolized forms or active
metabolites excreted via urine or feces, after human absorption, and unutilized
pharmaceuticals, are eliminated into raw sewage (Daughton and Ternes 1999). Some of
these compounds are not degraded in wastewater treatment systems and are therefore
discharged into the aquatic environment.
β-blockers have been used to treat human hypertension since the end of the
decade of the 60's. Market demand, as well as the continuous increase in medical
prescriptions, is considerably increasing each year. The popularity of β-blockers stems
from the high incidence of cardiovascular disease. In fact, this is the primary cause of
hospitalization and death in both Canada and the United States (Xu et al. 2010). Human
and veterinary uses are the major sources of drugs in the environment, where the
majorities are generated from excretion and discharge to the environment into wastewater
treatment plants. According to the European Federation of Pharmaceutical Industries and
Associations (EFPIA), unused medicinal products destined for humans represent 3% to
3
8% of the medicinal products sold (Mudgal et al. 2013). The extensive use of β-blockers
has resulted in their identification in water bodies as a consequence of sewage effluents
discharges. The high level of drugs use represents the major source of the β-blocker
propranolol and its subsequent release to the environment. Propranolol is extensively
metabolized, and less than 10% is excreted as the parent drug, mostly in the feces (Khetan
and Collins 2007).
The β-blockers are endocrine disruptors in which their mechanism of action
consists in the block action of endogenous catecholamines, epinephrine and
norepinephrine (noradrenaline) on adrenergic beta-receptors. The mammalian
adrenergic system is comparable with the adrenergic system of fish and the homologous
octopaminergic system in aquatic invertebrates, in particular mollusks (Massarsky et al.
2011). These similarities, as well as the knowledge of the β-blockers effects on human,
were used to build a wide picture of the endocrine-disrupting potential of β-blockers,
particularly during the stress response. The main conclusion is that β-blockers have
endocrine-disrupting effects over aquatic organism (Massarsky et al. 2011).
1.1. Propranolol at the environment
Several β-blockers (i.e. propranolol, bisoprolol and metoprolol) were identified in
wastewater at high concentration levels; 0.59, 2.9 and 2.2 µg L-1, respectively, in surface
water (Sacher et al. 2001). Other pharmaceuticals products were detected in sediments
at Lakes Päijänne and Haapajärvi of Finland. The most abundant pharmaceutical found
in the sediments was citalopram (15 to 290 ng g-1), but bisoprolol (7 to 38 ng g-1),
acebutolol (4 to 13 ng g-1), propranolol (9 to 43 ng g-1) and sertraline (4 to 14 ng g-1) were
also found (Lahti 2012). In other monitoring study performed in the U.K., propranolol was
4
found in wastewater treatment plants at concentration values of 76 ng L-1 (Fent et al. 2006)
and 10 ng L−1 (Hilton and Thomas 2003). Also, measurable concentrations of metaprolol,
propranolol and carbamazepine were detected in various dam reservoirs in Höje Sweden,
demonstrating persistence in water environment. Variations in the concentrations were
observed in the range of 0.05 µg L-1 (Bendz et al. 2005).
The municipal wastewater outfall from wastewater treatment facilities in
Mississippi, Texas, and New York, were sampled to investigate the occurrence of
metoprolol, nadolol, and propranolol. The total amount of samples was 34 and propranolol
was identified in all wastewater samples with concentration as high as 1.9 µg L-1. In
addition, this study showed that propranolol concentration remains relatively constant
(Huggett et al. 2003).
β-blockers bind to the beta-adrenergic receptors and block its activation by
physiological agonists. These receptors are located in mammals in many tissues,
including heart, and its blockage causes a decrease in heart rate and contraction. β-
blockers differ in specificity to the different receptor subtypes; some are non-specifically
acting on 1 and 2-receptors (propranolol), while others are specific for the receptor
subtype 1 (atenolol). Propranolol is a nonselective β-blocker used as a cardiovascular
API for treatment of angina pectoris, hypertension, and cardiac arrhythmia. Currently,
about 50 million Americans are diagnosed with hypertension and more than 4 million suffer
from angina (Shakya 2011).
Propranolol is a water-soluble API with established toxicity to some aquatic
species. The effects of propranolol on aquatics organisms were previously studied
(Huggett et al. 2002, Cleuvers 2005, Dzialowski et al. 2006, Liu et al. 2009, Ericson et al.
2010). The exposure of mussels to propranolol has been investigated (Ericson et al.
2010), revealing that a decrease on byssus strengths, reduction on byssus thread
abundance, and lower growth, were the main observed effects, among others. This study
5
strongly suggests that propranolol bind to the mussels tissue and imply that the mussels
bioaccumulate the substance.
Also, studies on medaka fish demonstrate half maximum effective concentration
(EC50) at 24.3 mg L-1, and the reduction on rainbow trout growth rate on concentration of
at least 1 mg L-1 (Liu et al. 2009). The algal (Pseudokirchneriella subcapitata) and rotifer
(Brachionus calyciflorus), exposed for 24 hours, showed toxicity at 5.0 mg L-1 of
propranolol (Liu et al. 2009). In fact, propranolol showed chronic toxicity for some aquatics
species. In the fish O. latipes, significant changes in plasma steroid levels occurred. The
number of eggs released by fish was reduced after 4 week of exposure to 0.5 and 1 g L-1
(Huggett et al. 2002). In Daphnia magna, heart beat rate, fecundity, and biomass were
reduced after chronic exposure to 0.11 mg L-1 (Dzialowski et al. 2006).
The acute toxicity of propranolol on freshwater crustacean (Thamnocephalus
platyurus and Oryzias latipes) was determined as 10.31 mg L-1 for a 24 hr LC50, and 8.71
mg L-1 for 96 hr (Kim et al. 2009). A significant adverse impact was observed in the
Daphnia magna, especially in first and second generation of D. magna test, where ca.
10% of both generations died. Other experimentations show adverse alteration of
morphology, function, capacity, or growth in D. magna (Stanley et al. 2006, Besse and
Garric 2008, Dietrich et al. 2010). The no-observed-effect level (NOEL) is defined as the
greatest concentration or amount of a substance, found by experiment or observation, that
causes no alterations of morphology, functional capacity, growth, development, or life
span of target organisms distinguishable from those observed in normal (control)
organisms of the same species and strain under the same defined conditions of exposure
(Duffus et al. 2007). The lowest-observed-effect level (LOEL) is defined as the lowest
concentration or amount of a substance (dose), found by experiment or observation, that
causes any alteration in morphology, functional capacity, growth, development, or life
span of target organisms distinguishable from normal (control) organisms of the same
6
species and strain under the same defined conditions of exposure (Duffus et al. 2007).
The LOEL and NOEL, on body mass alteration, was measured to be 0.22 and 0.44 mg L-
1, respectively (Dzialowski et al. 2006). The NOEL and LOEL for fecundity were
determined to be 0.055 and 0.11 mg L-1. The LOEC on heat rate was measured to be
0.055 mg L-1. Propranolol at concentrations of 0.88 mg L-1 or higher, has direct toxic
effects on the reproductive system of D. Magna exposed (Dzialowski et al. 2006).
Toxicity of propranolol and metoprolol, in the embryos and larvae of zebrafish
(Danio rerio), was investigated (Liwei et al. 2014). It was observed that the 48hr heart rate
decreased significantly at each drug concentration compared to the controls. A significant
decrease in the 96hr hatching rate in the two groups treated with 16 mg L-1 of propranolol
was also observed. The 96hr LC50 of propranolol in the zebrafish larvae was 2.48 mg L-1.
Consequently, fish and invertebrates may be adversely impacted (survival, growth,
reproduction) by exposure to β-blockers in municipal wastewater effluents. Long-term
exposure to propranolol reduced reproduction in C. dubia at 250 mg L-1 and in H. azteca
at 100 mg L-1 (Huggett et al. 2002). Other adverse effects were observed on D. magna,
generating the membrane destabilization (Huggett et al. 2002), whereas mussels
exhibited an increase in lipid peroxidation (Solé et al. 2010). In addition, Taylor et. Al.
(2010) provided molecular evidence for D. Magna alterations to fatty acids and oxylipids,
including disruption of the eicosanoid biosynthesis pathway. D. magna, Desmodesmus
subspicatus and Lemna minor were used to determine the ecotoxicity of β-blockers.
Propranolol was toxic, with EC50 of 7.7 mg L-1 in the D. magna test, and 0.73 mg L-1 in the
algal test (Cleuvers 2005).
The interactions of β-blockers on aquatic organisms are diverse; basically the
drugs could affect organisms in multiple ways. The toxicity was studied via the disruption
of the cell membrane integrity; Narcosis is a nonspecific toxicity, via disruption of
membrane integrity. Stanley et al. (2006) investigated the effects of two propranolol
7
enantiomers (R-propranolol and S-propranolol). Acording to this research, acute toxicity
in D. magna was observed, as the result of a non enantioselective process, in the range
of 1.40 to 1.67 mg L-1 (Stanley et al. 2006). The D. magna immobilization LOEC was
observed with propranolol at concentrations ranging from 409.3 to 869.0 g L-1 (Stanley et
al. 2006). In order to study the effects over cyclic adenosine monophosphate (cAMP),
propranolol was administered to the mussels Mytilus galloprovincialis in a wide
concentration range, with values as low as 0.3, 3 and 30ng L-1, and as high as 300 ng L-
1. Adenylyl cyclase is a G protein coupled receptor-triggered signaling cascade used in
cell communication. Following a 7 day exposure, the mussel cAMP levels were
significantly reduced in digestive gland, increased in mantle/gonads, and unaffected in
gills. Evidence was provided for propranolol affecting cell signaling in Mytilus
galloprovincialis; moreover, the substance interacts with the specific biochemical
pathways for which it was designed. Catalase and glutathione s-transferase were
differently affected by propranolol in the mussel’s tissues. Mussel haemocyte lysosome
membrane stability, a sensitive biomarker of animal health status, was concentration-
dependently reduced following propranolol exposure (Franzellitti et al. 2011).
The persistence of propranolol in the aquatic environmental media was
demonstrated. Effort was made to determine this persistence and the effects of oxidation
and photolysis of drugs on aqueous media. The half-life times (t1/2) of various drugs (i.e.
carbamazepine, diclofenac, clofibric acid, ofloxacin, sulfamethoxazole and propranolol) at
varying seasons and latitude were estimated. The research demonstrated half-life
photodegradation times of carbamazepine and clofibric acid of ca. 100 days in winter, and
for sulfamethoxazole, diclofenac, ofloxacin and propranolol underwent much faster
degradations with t1/2 of 2.4, 5.0, 10.6 and 16.8 days, respectively (Andreozzi et al. 2003).
8
1.2. Alternative for drugs degradations
Advanced Oxidation Processes (AOPs) are an alternative for degrading these
pharmaceutical products. The possibility of solar photoelectrolysis has been
demonstrated in a significant number of researches (Matthews 1988; Andreozzi et al.
2004; Esplugas et al. 2007; Skoumal et al. 2009; Isarain-Chávez et al. 2010; Milà i Canals
et al. 2010; Cotto-Maldonado 2012). The AOP techniques implemented include ozone
treatments, oxidation by hydrogen peroxide, Fenton processes, photolysis, and
photocatalysis by peroxide in presence of UV radiation. The degradation and
mineralization of the propranolol was assessed by direct photolysis and TiO2
photocatalysis, using artificial light (Xe-lamps) and solar irradiation. Propranolol removal
was accomplished after 240 min at 77% and 71% for the solar and artificial light,
respectively (De la Cruz et al. 2013). The removal was tested on different TiO2
concentrations (0.1, 0.2, 0.4 g L−1). De la Cruz et al. (2013) found best results when 0.4
gL−1 was used, using artificial and solar lights. Propranolol degradation was accomplished
after 240 min at 81%, using solar radiation, and at 94% using artificial light (De la Cruz et
al. 2013). The degradation rate increases dramatically as TiO2 concentration is lower than
2.0 mg L-1 (An et al. 2010). In addition, another study (Abellán et al. 2007; Nasuhoglu et
al. 2012) demonstrated that the optimal catalyst concentration ranged from 0.2 to 1.0 mg
L-1. A separate study (Cotto-Maldonado 2012) demonstrated an optimum concentration
of 0.6 mg L-1. With all these previous studies in mind, it is clear that the optimum catalyst
concentration is a crucial parameter to be considered and will determine the final results.
As part of the current work, different preliminary tests will be done with the aim to establish
the appropriate concentration of the catalyst.
9
Other studies were designed to measure photodegradation rates of selected
pharmaceuticals, including propranolol, and estrogens in surface water, at environmental
concentrations ranging from 1 to 2 g L-1 (Lin and Reinhard 2005). Natural
photodegradation in aquatic environments may occur via two principal processes: i) direct
photolysis, which consists of light absorption by the chemical itself; and ii) indirect
photolysis, that consist of the light absorption with photosensitizers. These
photosensitizers commonly found in surface water are dissolved organic matter, nitrates,
and nitrites. Some researchers measured the photodegradation rates of selected
pharmaceuticals (i.e. gemfibrozil, ibuprofen, ketoprofen, naproxen, and propranolol) and
estrogens in surface water at environmental concentrations (Lin and Reinhard 2005).
During these investigations, the measured half-life (t1/2) for naproxen and ibuprofen ranged
from 1.9 hours to 200 hours, respectively. The t1/2 was measured to be 2.5 min for
ketoprofen, between 2 to 5 h for naproxen, and ranging from 1.1 to 4.8 h for propranolol.
Other type of AOP is the ozonation. Ozonation is the oxidation method most
commonly used in the removal of these new emergent pollutants. Approximately 90% of
the dark oxidation treatments found in the scientific literature correspond to ozonation
(Esplugas et al. 2007). Several compounds (i.e. pesticides, anti-inflammatories,
antiepileptics, antibiotics and natural and synthetic estrogens) were degraded with ozone,
with degradation rates of ca. 90%. However, some compounds appear to be more
recalcitrant to the oxidation.
Fenton treatments have been used successfully to remove herbicides and
antibiotics. The Fenton and photoelectro-Fenton (PEF) degradation of solutions of the β-
blocker propranolol hydrochloride, with 0.5 mmol dm−3 Fe2+ at pH 3.0, has been studied.
For this research, the equipment used includes a single cell with a boron-doped diamond
(BDD) anode, an air diffusion cathode (ADE) for H2O2 electro-generation and a combined
cell containing the above BDD/ADE pair coupled in parallel to a Pt/carbon felt (CF) cell.
10
Under these experimental conditions, the 90% of propranolol was degraded in 120 min
(Isarain-Chávez et al. 2010).
AOPs, which can be driven by solar irradiation, can provide some advantages
because they potentially could use less energy (i.e. electricity). The photocatalytic
process uses light and a catalyst to carry out a chemical reaction. Commonly, some
semiconductors are used as catalysts, including TiO2, ZnO, Fe2O3, CdS and ZnS. The
semiconductors act as sensitizers, induced by the light, to produce an ox-redox reaction
due to their electronic structure which is characterized by a filled valence band and an
empty conduction band. The absorption of a photon of energy greater than the band-gap
energy leads to the formation of an electron/hole pair. The solar photocatalytic process
involves the use of the near-UV part of the solar spectrum (wavelength shorter than 380
nm) to excite a semiconductor catalyst in the presence of oxygen. The conduction band
electrons liberated from the catalyst surface produce radicals of the oxygen molecule in
the solution. In these circumstances, oxidizing species, either bound hydroxyl radical
(.●OH) or free holes, which attack contaminants, are generated producing a progressive
breaking of molecules yielding CO2, H2O and dilute inorganic acids (Malato et al. 2002).
The optimum catalyst concentration was established between 0.5 g L-1 and 1.0 g L-1 of
TiO2 (Abellán et al. 2007, Cotto-Maldonado 2012, Soto-Vázquez et al. 2016). The
degradation of the contaminants can be described using the Langmuir equation (Yang et
al. 2010).
The degradation of three β-blockers (i.e. atenolol, metoprolol and propranolol) was
determined in the presence of isopropanol and methanol. The photocatalytic degradation
of these pollutants was conducted adding 2.0 g L−1 of photocatalyst (Degussa P25) in a
glass reactor, and using a high-pressure mercury lamp as irradiation source. Degradation
rates of atenolol, metoprolol and propranolol were measured to be 94.7%, 93.1% and
77.5%, respectively (An et al. 2010). The intermediates of the degradation were studied
11
by HPLC/MS, where several species were suggested. Among these intermediates, were
identified: i) naphthol (m/z =145) formed from side chain cleavage, ii) amino-diol
(m/z=134), iii) one monohydroxylated intermediate (m/z=161) of naphthol, iv) seven
intermediates with m/z=276, corresponding to the addition of a residue of 16 amu to the
parent compound, v) five dihydroxylated intermediates with m/z=292, vi) and seven
trihydroxylated intermediates with m/z=308 (Yang et al. 2010).
The surface area represents an important factor in the degradation of
contaminants, when photocatalysts are used. The increase in the rate constants seems
to be due to the increase in the total surface area of the photocatalysts, producing a higher
number of active sites available for the photocatalytic reaction (Yang et al. 2010). Large
surface areas can be obtained by decreasing the particle size of the photocatalyst when
the particle has a single domain size. (Jang-Dong et al. 2001). Commercial TiO2 (Degussa
in anatase phase) has a surface area of 56 m2 g-1 (Velegraki and Mantzavinos 2008). TiO2
(as nanowires in rutile phase) can be synthesized with surface areas of ca. 480 m2 g-1
(Cotto-Maldonado 2012).
1.3. Solar radiation influence
The solar photochemical processes use UV or near-UV sunlight (300–400 nm),
but in some photochemical synthesis processes, sunlight with wavelength of 600 nm or
higher can be absorbed (Robert and Malato 2002). If solar energy is required to
photoexcite the catalyst (i.e. TiO2), a solar radiation collector can be used to increase the
photo-irradiation and efficiency of this process. A Parabolic Trough Collector (PTC) is a
device designed to collect electromagnetic radiation from the sunlight by using an
appropriate spatial geometry. PTC is a relatively mature technology with commercial
12
devices that could be easily modified to perform photochemical degradation processes.
The solar panel with parabola shape is used to concentrate the light on a point. With the
help of this system, the sun reflects on the panel and the energy is concentrated at a point
called the focal point. The Figure 1.3.1. shows a section of a parabolic system, indicating
the pathway of the solar radiation, and the location of the focal point.
Figure 1.3.1. Parabolic system and focus Illustration.
Additionally, during the interaction of radiation with matter, there are other effects
that should be considered. Thus, when light encounters a surface or tries to pass through
an object, it is scattered. The particulates (i.e. TiO2) and the pollutant (i.e. propranolol) in
aqueous solution can affect the light pass through the solution, creating scattering centers
and affecting the irradiation process. Light scattering is a form of propagating energy,
which is scattered and can be considered as the refraction of a ray. As mentioned
previously, TiO2 particles in solution can affect the light path, especially because TiO2 is
immiscible in water and solution turbidity increases by increasing the TiO2 concentration.
The increase of the turbidity in the solution can decrease the transmittance of the light
13
through the solution. The optimum catalyst concentration for any catalytic process must
be determined, because an excess of the catalyst can affect the absorption of photons in
the solution. Photocatalytic reaction rate depends mainly on the light absorption of the
photocatalyst. Unfavorable light scattering and reduction of light penetration into the
solution are observed with an excess of photocatalyst in the reaction mixture (Gaya and
Abdullah 2008). The reduction of light, caused by light scattering, could lead to the
presence of areas at the reactor where the reaction cannot occur. Basically the lack of
light in certain parts of the reactor can be caused by light scattering (Nasuhoglu et al.
2012).
The plug flow reactor (PFR) is defined as a series of little segments of flow "plugs",
each with a uniform composition, traveling in the axial direction of the reactor, with each
plug having a different composition from the ones before and after it (See Figure 1.3.2.).
The fluid in the PFR is perfectly mixed in the radial direction but not in the axial direction.
The flow pattern is very similar to a piston.
Figure 1.3.2. Scheme of a plug flow reactor.
The area of the “plugs” increases due to increasing diameter. The radius is the
distance where the light must travel to irradiate all the “plugs”. Intuitively, it can be
assumed that the increases in the areas produce an increase in the probability of the light
scattering. The light needs to travel more distance increasing the probability to be
scattered by the molecules present in the solution. If the plug flow reactor is located at
14
the focus of the solar collector panel, at more distance light traveling more the opportunity
of light scattering, which means that the flow near the center of the pipe will receive less
light. As it was mentioned previously, the increase in light intensity would increase the
degradation rate during the photocatalytic degradation. It can be easily assumed that the
differences on diameters on the plug flow reactor will affect the light pass through the
solution, and as a consequence, the rate of the reaction.
One of the fundamental concepts on flow is the continuity of flow (Equation 1.3.1.).
Continuity states that no fluid is lost or gained and no cavities are formed or destroyed as
the fluid passes through a conduit. When the fluid is essentially incompressible, as for
liquids, continuity can be expressed as follows:
Figure 1.3.3. Continue flow diagram.
Where Q is the flow (volume/time), a is the cross sectional area, and V is the velocity
(length/time) (Brater et al. 1976). In pipes, the cross sectional area is a circle, where r is
the circle radius (Equation 1.3.2.).
𝑎 = 𝜋𝑟2 Equation 1.3.2.
Q= a1V1 = a2V2 Equation 1.3.1.
15
1.4. Influence of the pH
Considering that the photocatalytic reaction takes place at the surface of the
catalyst, the affinity between the catalyst and the contaminant is of paramount relevance.
Once excitation of the catalyst occurs, there is enough time, in the nanosecond time scale,
for the created electron-hole pair to undergo charge transfer to adsorbed species on the
semiconductor surface from solution or gas phase contact (Linsebigler et al. 1995). The
electron transfer process is more efficient if the species (i.e. pharmaceuticals) are pre-
adsorbed on the surface (Matthews 1988). That proximity, or adsorptivity between TiO2
and the pharmaceutical, is transcendental for the reaction in order to increase the reaction
rate in photocatalytic reactions. In this regard, the pH may markedly affect the charge of
propranolol and TiO2 in solution. Molecules with the same charge repel one another and
prevent them from coming into contact; on the contrary, those with opposite charge will
attract each other. The zero point charge (pHzpc) is defined as the pH of the suspension
at which the surface charge density is equal zero (Krishnan and Anirudhan 2003). For pH
> pHzpc the surface charge will be negative, and at lower pH (pH < pHzpc), the surface
charge will be positive. Propranolol has a pHzpc of 5.8 (Ye et al. 2013) and TiO2 has a
pHzpc of 6.25 (Hoffmann et al. 1995). On the basis that photocatalysis reaction takes place
at the surface of the catalyst, any improvement on propranolol and TiO2 adsorption will
increase the degradation of propranolol.
Ye et al. (2013) carried out several studies by FTIR spectroscopy and molecular
modeling on the adsorption of propranolol on the surface of TiO2 particles. When pH <
5.8 both, the TiO2 surface and propranolol were positively charged, and the electrostatic
repulsion resulted in a low adsorption capacity. When pH was between 5.8 to 6.25 the
TiO2 surface was negatively charged, and propranolol was positively charged (see Figure
16
1.4.1.). The electrostatic attraction led to an enhanced adsorption affinity. At pH > 6.25,
propranolol and TiO2 exist mainly as negatively charged species, resulting in a reduced
adsorption. These electrostatic interactions could explain why propranolol and TiO2 have
better attraction on pH ranges from 5 to 6. The fate of propranolol in the environment can
be strongly influenced by its adsorption, due to the fact that the adsorption capacity of
propranolol on TiO2 increases from 0.3 to 2.3 μm g-1 in the pH range of 5 to 9 (Ye et al.
2013).
Figure 1.4.1. Graphical illustration for the electrostatic interaction between TiO2
and propranolol.
However, electrostatic interactions alone cannot explain the observed adsorption
at pH values below 5.8, where both surface and propranolol were positively charged, and
at pH values above 6.25, where both surfaces are negatively charged. Interactions, other
than electrostatic forces, would be involved in the adsorption of propranolol on TiO2. Ye
et. al. (2013) explained, according to FTIR analyses that the hydroxyl and amino groups
of propranolol interact with the TiO2 surface at pH values ranging from 5 to 9. The
hydrogen bonding between the -NH2+- group of propranolol and the TiO2 surface would
increase from pH 5 to 9 due to the decrease of the positive charge of the TiO2 surface.
17
Meanwhile, a pronounced shift in OH bending vibration suggested that interactions
between the hydroxyl group of propranolol and the surface of the catalyst might be the
dominant adsorption mechanism at pH values ranging from 5 to 7.
The pH of the solution is a determining factor that can increase or decrease the
adsorptivity between the catalyst surface and the organic compound to be degraded in
the solution. The theory of surface charge suggests that the best charge affinity between
propranolol and TiO2 will be founded at pH range from 5.8 to 6.25 (Ye et al. 2013).
1.5. Regulation
The United States Clean Act (CWA) imposes to the Environmental Protection
Agency (EPA) requirements to protect and restore the ecological integrity of the national
water bodies. The section 304(a) of the CWA ordered EPA to develop ambient quality
standards criteria (AQSC). The AQSC concentration levels are selected to preserve and
protect the quality of the nation water bodies. The quality of the bodies must take in
consideration the usages like swimming, drinking water, fishing, fish spawning and
navigation. The AQSC must be developed based solely on scientific determination on the
relation between the pollutant concentration on bodies, and its effects. The first list of
AQSC was published by EPA in early 1980’s. Later, in 1985, the EPA published
Guidelines for deriving numerical national water quality criteria for the protection of aquatic
organisms and their uses (therefore the Guidelines). The Guidelines provided a common
methodology, uniform and transparent, for the analysis required to select the AQSC limits.
Recently, pharmaceutical manufacturing products are reaching the water bodies
systems. As consequence a considerable attention has been generated by these “new
contaminants”. EPA categorized these contaminants as contaminants of emerging
concern (CEC). This term has been since 1990 for chemicals and substances that have
18
no regulatory standard, was founded in water bodies and are presumed to potentially
caused deleterious effects in aquatic life (Ankley et al. 2008). Although the CEC have
shown low acute toxicity, they cause reproductive effects at very low concentrations
(Woodling et al. 2006, Blazer et al. 2007, Sanchez et al. 2011). Also, the exposure effects
to the CEC during the early stages of life may not be observed until mature, which means
a potential issue for the preserving of aquatic life. The traditional toxicity test described at
the Guidelines may not be enough comprehensive for criteria derivation of the CEC. The
CEC have specific modes of actions that may affect diverse types of aquatic organisms.
In order to handle this need, the EPA developed in 1998 the white paper of aquatic life
criteria for contaminants of emerging concern. The white paper provided guidance on
how criteria development for CECs could be facilitated as a supplemental interpretation of
the guidelines. The white paper proposed some modifications to expand the areas of
concern, with respect to specific toxicological characteristics. The white paper introduces
the importance of the identification of the toxicological disruption effects to the organism.
As an example, the white paper introduce the needs to measure different levels of the
biological structure related to survival, growth, and reproduction ends points for aquatic
organisms. These measurements include; (i) biochemical measures (i.e. female specific
yolk precursor protein vitellogenim, estradiol, testorenone), (ii) histopathological
measurements (i.e. proportion of spermatogonia, presence of testis-ova), (iii) gross
morphology (i.e. secondary sex characteristics, coloration) and (iv) behavior measures
(i.e. nest building, defense/aggression). Even after these important and transcendental
changes, the document continues without being approved.
EPA continues avoiding the establishment of AQSC standards for CECS. On at
least three times, they included pharmaceutical products in the Contaminant Candidate
List (CCL); however EPA did not promulgate the AQSC final standard. The first
appearance on CCL occurred in 2008, where nitroglycerin appeared (FR 2008); later EPA
19
proposed a new list on 2009, which included 10 pharmaceuticals (i.e. 1 antibiotic
(erythromycin) and 9 hormones (17-a-estradiol, 17-b-estradiol, equilenin, equilin, estriol,
estrone, ethinyl estradiol, mestranol, and norethindrone); and a third publication in 2015,
which retain 5 hormones (17b-estradiol, equilin, estriol, estrone, and ethinyl estradiol) and
added 2 new hormones (i.e. testosterone and 4-androstene-3,17-dione) (FR 2009; FR
2015).
1.6. Research scope
The extensive dissemination of pharmaceutical drugs at low concentrations mainly
in the aquatic environment is a troublesome situation. These pharmaceuticals can be
found spread in influents and effluents from wastewater treatment plants, surface waters,
seawater, groundwater and drinking water. The behavior and fate of pharmaceuticals and
their metabolites in the aquatic environment is practically unknown. The photocatalytic
degradation of pharmaceutical products is an extraordinary option. Currently, the
treatment of contaminants on water media requires the use of chemicals and high-energy
consumption. The use of photocatalytic reactions for pharmaceutical degradations would
be an extraordinary way to cut energy costs and reduce consumption of chemicals in the
process.
The first goal of this research was to study the ability of TiO2 in the photocatalytic
degradation of propranolol in aqueous solution. Titanium dioxide is an n-type
semiconductor and a typical photocatalyst, attracting much attention from both
fundamental and practical viewpoints. It has been used in many industrial applications,
including environmental control, solar cells, gas sensors, pigments and human care
products. The photocatalytic mechanism of the photodegradation process is affected by
20
the light source (irradiation energy), catalyst concentration and the presence of other
organic substances or ions in the solution (See Figure 1.1.6.). UV light irradiation on the
TiO2 catalysts generates electron–hole pairs, which can be represented as localized
electrons (Ti3+) and holes (O- and/or ·OH radicals). Some of these electron-hole pairs
disappear by recombination on bulk TiO2, while other electrons and holes diffuse to the
surface of the TiO2 catalysts to react with molecules, leading to photocatalytic reactions
such as hydrogenolysis and the formation of oxygen-containing organic compounds
(Masaku and Masato 2003).
Figure 1.6.1. Photocatalysis diagram, representing the energy
transition of the catalyst during the light exposure (Adapted
from Mahamed and Bahnmann 2012).
In our case, the solar heterogeneous photocatalytic process consists in using the
near-UV part of the solar spectrum (wavelength shorter than 380 nm) to excite a
semiconductor catalyst, in the presence of oxygen. The conduction band electrons
liberated from the catalyst surface produce radicals of the oxygen molecule in the solution.
21
In these circumstances, oxidizing species, either bound hydroxyl radical (.●OH) or free
holes, which attack contaminants, are generated producing a progressive breaking of
molecules yielding CO2, H2O and dilute inorganic acids (Malato et al. 2002). The optimum
catalyst concentration was established between 0.5 g and 1.0 g of TiO2 (Abellán et al.
2007, Cotto-Maldonado 2012). The degradation of the contaminants follows the Langmuir
principle, suggesting that particle surface area has an important role on the reaction
efficiency. Titanium oxide particles with higher surface areas will behave better in
degradation processes. In the present research, the TiO2 has been used in two crystalline
forms (anatase and rutile). Because the TiO2 nanowires (in rutile phase) have greater
surface area that TiO2 anatase, it is expected that TiO2 nanowires (rutile) carry out a better
and optimal degradation process of propranolol.
The light is the energy source that promotes the catalysis by titanium dioxide.
Every effort leading to an increase in the reaction energy will make the process more
efficient. The reaction will occur at a MFA line that will be irradiated with light. The MFA
line will be placed at the focus point of a PTC. The focus point is the place in PTC where
the light is concentrated. The effect of using the PTC in degradation reaction will be tested.
The hypothesis was that the use of the parabolic collector panel would increase the
degradation of propranolol. This research evaluated the efficiency of the degradation
process in presence or absence of a parabolic solar panel.
The variation on pipe diameter was also tested. The hypothesis was that at larger
pipe diameters the lower reaction rates. Basically, larger pipe diameters increase the
radius and, as a consequence, the traveling distance of the light. The increase at the
travel distance will increase the light dispersion through the flow, reducing the efficiency
of the photocatalytic process. The research determined the effects of the pipe diameters
on the degradation reaction.
22
Chapter Two
Methods and Instrumentation Techniques
This chapter describes the experimental techniques utilized during this research.
These techniques include Raman spectroscopy, X-ray diffraction, UV-vis spectroscopy,
Brunauer-Emmett-Teller (BET) surface area, and scanning electron microscopy. These
instrumental techniques are located in different research centers, such as Universidad del
Turabo (main campus of Gurabo), Lilly del Caribe, and Universidad Autónoma de Madrid.
2.1. Raman spectroscopy
Raman spectroscopy is a technique used to observe vibrational, rotational, and
other low-frequency modes in a molecule. When a light beam of a monochromatic light
(laser) hit a material, the majority part of the light beam is dispersed with the same
frequency as the original beam; this is known as elastic radiation. This elastic radiation
does not provide any kind of molecular information. Another small part of the light beam
is scattered inelastically. The scattered inelastic beam returns with a specific frequency
based on the molecule composition of the material, this is known as the Raman effect.
The frequency variations observed in this phenomenon are due to certain
variations in energy of the molecular bonds. Intuitively, each of these bonds can be
understood as a spring connecting two masses (see Figure 2.1.1.). The bonds are excited
with monochromatic light, which produces a movement (vibrational and rotational).
23
The frequency generated by the movements is a characteristic of each bond, and the
movements correspond to a particular value of the molecular energy.
Figure 2.1.1. Model of solid balls (atoms), connected by springs
(bonds).
There are two types of inelastic dispersions that can be measured by Raman
spectroscopy. The Stokes occurs when the energy of the disperse photon is lower than
the incident wave; if the energy of the disperse photon is greater, then is known as Anti-
stokes (see Figure 2.1.2.). Measurements of the Raman effects are based on the change
in the polarizability of molecular bonds during an excitation process.
Figure 2.1.2. Rayleigh, Stokes, and anti-Stokes transitions.
24
According to the Maxwell-Boltzmann Law of energy distribution, the molecules are
in the lowest energy state, consequently is much more probable that Stokes scattering
occurs. Therefore, the intensity of the Stokes scattering is about 100 times that of Anti-
Stokes scattering. In general, only the most intense Raman bands (Stokes) are used for
characterizing materials.
Raman exhibits different relative sensitivities for different functional groups.
Raman spectroscopy is most sensitive to C-S and C-C multiple bonds, and some aromatic
compounds are more easily detected by means of their Raman spectra. Water has a very
intense IR absorption spectrum, but a particularly weak Raman signal. Therefore, water
has only limited IR windows that can be used to examine aqueous solutes, while its Raman
spectrum is almost completely transparent and useful for solute identification. The two
major limitations of Raman spectroscopy are that the minimum detectable concentration
specimen is typically 10-1 M to 10-2 M and that the impurities present in many substances
fluoresce, showing interferences with the Raman scattered signal (USP 2012).
The Raman spectrum looks similar to an infrared spectrum plotted linearly in
absorbance units. The intensity (counts per second, or cps) is plotted in the y-axis, and
the shifted energies, with respect to the energy of the excitation source, are plotted in the
x-axis; the x-axis is generally labeled as Raman Shift, in cm-1 or wavenumber. The Raman
shift represents the difference between the absolute peak positions of the sample and the
wavelength of the excitation laser. The spectrum analysis is done in a similar way as the
infrared spectra. Frequently, the strongest peaks in a Raman spectrum are weak in the
IR spectrum, and vice versa, and, therefore, both techniques, IR and Raman
spectroscopies, are complementary to each other. Raman spectroscopy is a useful
technique because often quick and accurate measurements can be made without
destroying the sample (solids, semi-solids, liquids or even gases), and with a minimum of
25
preparation. The Raman spectrum gives us information about the fundamental vibrational
modes of the molecule.
The Raman spectrometers contain, at least, an excitation source (laser), a fiber
optic, optical lens, monochromator, and the detector. The monochromatic light, generated
by a laser source, is used to excite the material to be analyzed (sample). The fiber optic
is normally the medium where the light travels, and the optical lens concentrate the light
onto the sample, capturing the Raman signal. The monochromator captures and
separates the waves; later the detector identifies the different waves captured at the
monochromator and converts them to digital signals.
Although titanium oxide (as anatase or rutile phase) and TiO2NWs in different
crystal forms have been extensively characterized by Raman spectroscopy (Han et al.
2009, Cotto-Maldonado 2012, Mali et al. 2012), in order to characterize the crystalline
phase of the catalysts before use, TiO2NWs were analyzed by this technique. TiO2NWs
were analyzed using a Raman spectrometer Thermo DXR, equipped with a 780 nm laser
source, and coupled to an objective of 10X (Olympus, Carl-Zeiss).
26
Figure 2.1.3. Thermo DXR Raman spectrometer used for the
present research.
2.2. X-ray powder diffraction (XRD)
Another nondestructive technique used for material characterization is the X-ray
powder diffraction (XRD). XRD is an easy technique used for identification of crystalline
material that also provides information on unit cell dimensions. The XRD technique is
based on the principle that when monochromatic X-rays hit a crystal sample, scattered
waves have either constructive or destructive interferences. These X-rays are produced
by a cathode ray tube, filtered to produce monochromatic radiation, concentrated, and
directed toward the sample. The interaction of the incident rays with the sample produces
constructive interferences (and a diffracted ray) when conditions satisfy Bragg's Law
(Bakeev 2005). The Bragg’s Law describes the relation of the wavelength, the diffraction
angle and the lattice spacing in a sample. The XRD instrument detects process and
counts the diffracted X-ray by scanning the sample through a range of 2θ angles. Because
27
the crystal can be randomly oriented, all possible diffraction directions of the lattice should
be attained. Conversion of the diffraction peaks to d-spacings allows identification of the
material, because each material has a set of exclusive d-spacings; this is achieved by
comparison of d-spacings with standard reference patterns. According to the Bragg’s
Law, constructive interferences have the following relationship between the inter-planar
spacing (dhkl) and angle of diffraction:
2𝑑ℎ𝑘𝑙 sin 𝜃 = 𝑛𝜆
where n is the order of diffraction, and λ is the wavelength of X-ray.
Figure 2.2.1. Bragg diffraction for two beams with identical wavelength
in a crystal (solid).
The diffraction condition establishes that to maintain the same path length and
remain in-phase, the x-rays must be deviated at an angle equal to the angle on incidence.
The diffracted beam is the result of the combined deviated ray. There are two types of
28
angle geometry, θ-2θ and θ-θ. In the θ-2θ geometry, the primary optics and the x-rays
source are fixed and the sample holder moves around θ, meanwhile the secondary optics,
and the detector move around 2θ. In the θ-θ geometry the sample position is fixed,
meanwhile the primary and secondary optics, and the x-ray source move around the θ.
The three major components for X-ray instruments are the X-ray detector, the sample
holder, and the X-ray tube. The X-rays are produced in a cathode ray tube, when a heated
metal filament generates electrons. The high voltage, typically ca. 10 000 V, is generated
across the metal filament, which draw the electrons to the target. Once electrons have
sufficient energy to dislodge internal electrons configuration, a spectrum is produced.
The amount of scattered intensity, collected by a proportional or scintillation
counter, is plotted against 2θ, this is known as a diffractogram. The typical way to use the
result from X-ray difractogram is to compare its peak pattern with a large set of data library.
If the data library is not available, the peaks spacing, peaks position, intensity values and
shapes of peaks must be analyzed to determine the properties of the specimen.
The difractogram can be used to determine the lattice constant of the specimen.
Firstly, by calculating the expected 2θ position of the first few peaks in the diffraction
pattern, and then by determining the (hkl) values for the first few peaks. The Bragg's law
can be used to determine the inter-planar spacing (dhkl), and obtain lattice constant using
the standard formula for the expected crystal system. The lattice parameters (a, b, c are
cell parameters and α, β, γ, are the angles) of the crystalline system can be experimentally
determined (see Figure 2.2.2.).
29
Figure 2.2.2. Parameters which
characterize the shape and size of an
elementary cubic cell (or unit cell).
The TiO2 samples were analyzed using a XRD Bruker D8 Advance (see Figure
2.2.3.). The X ray diffraction patterns were collected in the range of 5 to 80o with a scan
speed of 3o per min.
30
Figure 2.2.3. Bruker XRD D8 Advance at Universidad del
Turabo, Gurabo campus. Image of the X ray
diffractometer (A); the chamber with the X-ray tube (B);
and the automatic sample holder (C).
2.3. UV-vis spectroscopy
When a molecule is bombarded by thermal, electrical discharge or electromagnetic
radiation, it absorbs energy and enters into an excited state. Then it comes back to its
normal state by emitting a spectrum of electromagnetic radiation. Every molecule has a
signature absorption spectrum, and this property is used to identify materials and
molecules. The spectrum is composed of bands of light corresponding to the
characteristic wavelengths. This spectrum can be emission and/or absorption spectra,
which are complementary. In general, the wavelengths in the emission spectra
correspond to the wavelengths absorbed in the absorption spectra. This complementary
spectrum properly constructed, are extremely useful in the qualitative and quantitative
identifications.
31
A bombarded molecule can have multiple modes of motion. These movements
can be by vibration, in which the atomic bond varies in length (longitudinal vibrations), or
in which the atoms oscillate in a direction perpendicular to the interatomic bond
(transverse vibrations), or by the rotation of a group of atoms around a node. The energy
absorbed or emitted by the molecules has characteristic energy values, which can be
distributed to the corresponding vibrational, rotational, or electronic levels. The principle
of spectroscopy is very simple: a sample is exposed to a varying frequency of radiation
and a detector captures the outgoing radiation.
In this research, the degradation of propranolol was characterized by using UV-vis
spectroscopy. The standard spectral range corresponding to the UV-vis spectroscopy is
from 190 nm to 1 100 nm, but a narrower interval, from 190 nm to 800 nm, is normally the
standard. The UV range lies between 190 nm and 380 nm, and the visible component is
from 380 nm to 800 nm. The energy in this spectral range is greater than that of the IR
range and generates electronic transitions, in addition to vibrational and rotational
processes. The distances among rotational levels are smaller than those among
vibrational levels, while the higher energies are found in electronic transitions. When UV-
vis light passes through a transparent material, certain wavelengths may be absorbed by
the material. This selective absorption is the basis for UV-vis spectroscopy. Light
absorption is measured as a decrease in light intensity, as a result of the interaction of the
light energy with the absorbing material. The lost energy is converted into heat and/or
chemical reactions. It is possible to identify several absorbing components of a mixture
on the basis of their individual pattern of absorption versus wavelength.
Molecules that absorb in the UV-vis range are classified as chromophores or
auxochromes. Chromophore groups are responsible for the color of the compound and
absorb radiation at a specific wavelength. The absorption of light by a sample in the
ultraviolet or visible region is accompanied by a change in the electronic state of the
32
molecules in the sample. The energy supplied by the light will promote electrons from their
ground state orbitals to higher energy, excited state orbitals or antibonding orbitals.
Potentially, three types of ground state orbitals may be involved in the transition: σ
molecular bonding, π molecular bonding, and non-bonding atomic orbitals (n), in addition
to two types of antibonding (σ* and π*) orbitals. A transition in which a bonding s electron
is excited to an antibonding σ orbital is referred to as σ to σ* transition. In the same way,
π to π* represents the transition of one π bonding electron to an antibonding π orbital (see
Figure 2.3.1.).
Figure 2.3.1. Energy distribution of the
different electron orbitals.
Auxochrome groups are groups of atoms that do not absorb in the UV-vis range;
however, their presence in the molecule affects the absorption of chromophore groups.
This group includes the following functional groups: OH, NH2, CH3, NO2, Cl, OH, NH2,
CH3, and NO2.
33
A simple spectrometer consists of a light source, a wavelength selector (i.e. a
filter), a sample cell, and a detector (see Figure 2.3.2.).
Figure 2.3.2. Scheme of a simple UV-vis spectrometer.
The absorbance of a sample is directly proportional to the material concentration
that causes the absorption; that is, the amount of radiation transmitted by the sample
decreases as the concentration increases.
One of the most widespread applications of the UV-vis spectroscopy in industry is
the determination of the concentration of solutions. A wave passing through a transparent
medium, a solution for example, loses some of its energy. The Lambert-Beer law
correlates intensity of absorbed incident radiation and the concentration of the solution
(Battikha 2007):
𝐴 = ε𝑐λ
Where ε is the molar absortivity, c is the concentration, and λ is the wavelength.
This equation has the disadvantage that is true only for monochromatic light and if the
physical and chemical properties of the substance do not change with the change in
concentration.
34
The absorbed energy (absorbance, A), or transmitted (transmittance, T), follows a
logarithmic function of the absorption coefficient, concentration (c), and the path length (l)
(Lenz et al. 2002):
𝐴 = 𝑙𝑜𝑔10 (I
I0) = 𝑙𝑜𝑔10
100
T= Tcl
UV-vis spectroscopy is used for quantitative analysis, studies of reaction rate,
characterization of mixtures, identifying compounds and, as detector for a wide variety of
experimental techniques (for example HPLC). Quantitative analysis requires calibration
curves to adequately characterize the variation of concentration and absorbance (or
transmittance). Reaction rates may be derived by following the variation of the
concentration of a compound in a vessel with time-on-stream. In this investigation the
photodegradation of propranolol was characterized by using UV-vis spectroscopy. In our
case, a Shimadzu 2401 PC spectrometer (see Figure 2.3.3.) was used.
Figure 2.3.3. UV-vis Shimadzu 2401 PC spectrometer
used for the present research.
35
2.4. Brunauer-Emmett-Teller (BET) surface area
One of the most common and prolific procedures for the determination and
measurement of surface areas and capillarity is the Brunauer-Emmett-Teller (BET)
adsorption model. The BET model can determine the surface area of solids (powder)
based on the physical adsorption of a gas (i.e nitrogen) by the powder. The model
calculates the amount of gas adsorbed by the surface, pores or cavities of the powder.
The measured surface area includes the entire surface accessible to the gas whether
external or internal. The adsorbate gas is incorporated on the powder surface forming a
monomolecular layer. Physical adsorption is the result of the weak forces, described by
Van der Waals, between the adsorbate gas and the adsorbent surface area of the powder.
Figure 2.4.1. shows the four steps during the gas adsorption onto the particle
surface. At low gas pressures, gas molecules are adsorbed on the surface of isolated
sites (step 1). When the pressure increases, the number of adsorbed gas molecules also
increases, forming a monolayer on the surface of the particles (step 2). Later, the pressure
continues increasing, and starts to form a multilayer cover (step 3). The smaller pores are
filled first, before the surface is completely covered. If the pressure continues increasing,
the particle surface is filled completely (step 4).
36
Figure 2.4.1. Different steps corresponding to the nitrogen adsorption
onto the particle surface (Adapted from Santiago-Buey and Estaire-
Gepp 2014).
Samples require a pre-treatment process where they are pre-treated at high
temperature in vacuum in order to remove any contaminants, including water, N2, CO2,
and other components absorbed on the surface. Then, the solid is cooled (typically at the
boiling point of the gas, at 77 K). One of the functions of the cooling process is the
improvement of the gas adsorption to obtain the isotherm during the experimentation.
Adsorption continues until the amount of nitrogen adsorbed is in equilibrium with the
concentration in the gas phase. The determination is usually carried out at the
temperature of liquid nitrogen. The amount of gas adsorbed can be measured by a
volumetric or continuous flow procedure. The model theory is described by the next
equation:
1
𝑉𝑎 (𝑃0
𝑃 − 1)= (
𝐶 − 1
𝑉𝑚𝐶) (
𝑃
𝑃0) +
1
𝑉𝑚𝐶
37
Where P is partial vapor pressure of the adsorbate gas in equilibrium with the
surface at 77.4 K (b.p. of liquid nitrogen), in pascal; Po is the saturated pressure of
adsorbate gas, in pascal; Va is the volume of gas adsorbed at standard temperature and
pressure (STP) [273.15 K and atmospheric pressure (1.013 × 105 Pa)], in milliliters; Vm is
the volume of gas adsorbed at STP to produce an apparent monolayer on the sample
surface, in milliliters; and C is a dimensionless constant that is related to the enthalpy of
adsorption of the adsorbate gas on the powder sample.
The specific surface areas of the catalysts used in the present research were
determined by the BET method using a Micromeritics ASAP 2020 (see Figure 2.4.3.).
Figure 2.4.2. Linear representation of the BET equation.
38
Figure 2.4.3. Micromeritics' ASAP 2020
Accelerated Surface Area and
Porosimetry, used in this research
(Universidad Autónoma de Madrid).
2.5. Scanning electron microscopy
The scanning electron microscopy (SEM) is one of the most useful techniques
used in material science. The magnification of samples allows the characterization of
morphologies, topology, surface, texture and composition. The SEM reveals levels of
detail and complexity inaccessible by light microscopes. Scanning electron microscopes
are composed by several important parts; a source (electron gun), a series of lenses
(condensers and objective), a series of apertures (micron-scale holes in metal film),
control for specimen position, the sample holder for beam/specimen interaction, and an
image capture system (see Figure 2.5.1.).
39
Figure 2.5.1. Scheme of a conventional high
vacuum SEM Instrument.
The magnification occurs by focusing a beam of electrons on a sample. An
electron gun is the source of electrons, and typically is made of a heated tungsten filament.
Other more expensive instruments use LaB6, or a tungsten crystal, and are either heated
or powered by a high electrical potential. The voltage of acceleration generated by the
electron gun ranges from 0.5 to 50 kV. A series of electromagnetic lens and apertures
are used to control the diameter of the bean, as well as to focus the beam on the specimen.
The path of the electron beam is quickly modified by a set of deflection coils, which help
to scan the sample. The electromagnetic lenses are used to adjust the beam source that
comes from the electron gun, and also to focus the beam on the specimen. The
electromagnetic lenses are coils of wire wrapped on a soft iron form where current flows.
This flow produces a magnetic field, and the electrons assume a helical path spiraling
down the column (see Figure 2.5.2.).
40
Figure 2.5.2. Path of a flow of electrons
through an electromagnetic lens.
The condenser lens controls the diameter of the beam, as well the focus of the
beam on the specimen surface. Condenser lenses are usually located at the top of the
column, while the objective lens is always located at the bottom. The beam passes
through the condenser lenses, allowing refocusing or recentering on the sample, as
necessary. The condenser lenses converges the cone of the electron beam to a spot
below it, before the cone flares out again and is converged back again by the objective
lens and down onto the sample. Subsequently, the diameter of the electron beam is
modified by passing through the objective lenses. When primary electrons strike the
specimen, the specimen itself emits secondary electrons. These secondary electrons are
attracted by a collector, being accelerated and guided to the scintillator. In the scintillator,
the kinetic energy is converted into higher or lower brightness points, producing visible
light. This light is directed to an amplifier where it is converted into an electrical signal,
which passes to the computer monitor where the image is formed, line-by-line, and point-
by-point.
41
The electron beam can interact with the electric charge field of the nucleus and
electrons of the specimen. These interactions are responsible for multiple signals as, for
example, backscattered electrons (BSE), secondary electrons (SE), or X-rays and Auger
electrons (see Figure 2.5.3.).
Figure 2.5.3. Electron collision on a
sample, generating BE, SE and X-rays.
Inelastic events occur when an electron beam interacts with the electric field of an
electron from the sample (see Figure 2.5.4. B). This process is responsible for an energy
transfer to the sample, and a potential expulsion of an electron from that atom, as a
secondary electron (SE). SEs have, by definition, energies lower than 50 eV. If the
vacancy, due to the creation of a secondary electron, is filled by an electron coming from
a higher energy orbital, an X-ray emission is produced.
42
Elastic events occur when a beam electron interacts with the electric field of the
nucleus of a specimen atom, resulting in a change in direction of the beam electron without
a significant change in energy scattered beam electron (< 1eV) (see Figure 2.5.4. A). If
the elastically scattered beam electron is deflected back out of the specimen, the electron
is known as BSE, BSEs can have an energy range from 50 eV to nearly the incident beam
energy. However, most backscattered electrons retain at least 50% of the incident beam
energy.
Figure 2.5.4. Diagram for beam specimen interactions: elastic events (A);
and inelastic events (B) (Adapted from Hafner 2007).
In this research the synthesized catalysts were characterized using a high vacuum
SEM, model JEOL JSM-6010LA (see Figure 2.5.5.). This technique is the primary tool to
characterize the morphology of the synthetized TiO2NWs.
43
Figure 2.5.5. Scanning electron
microscope (SEM) JEOL, model
JSM-6010LA, located at
Universidad del Turabo, Gurabo
campus.
2.6. Liquid chromatography and mass spectrometry
Liquid chromatography (LC) coupled with mass spectrometry (MS/MS) has been
the major quantitation analysis approach in pharmaceutical, agrochemical, forensic,
consumer products, and related industries (Delamoye et al. 2004). In the past decades,
advances in LC-MS technology, better instrument designs and fast commercialization of
MS have made it a top choice among many analytical tools. Liquid chromatography
coupled with mass spectrometry (LC-MS) has significant advantages in speed, specificity
44
and sensitivity over other approaches of chemical analysis. Figure 2.6.1. shows a
common arrangement for a LC system composed by a mobile phase, pump, sample
injection point, column (stationary phase), detector, waste collection system and computer
system for data capture. Detectors have the function to monitor the concentration or
quantity of the components of the sample emerging from the column. Detectors can be
of different type, including UV-vis detectors, photodiode array, refractive index,
conductivity, fluorescence and mass spectrometers. For purposes of this section, we will
continue describing the technique LS-MS, which was used for the identification of the
degradation byproducts of propranolol.
Figure 2.6.1. Scheme of a conventional liquid chromatograph.
Samples injected into the LC system are generally required to be in a liquid form,
free from particles and non-volatile salts that preferably match the initial LC mobile phase
(MP) components. In chromatography there is an equilibrium between the stationary
phase (SP) and the MP; during elution there is a transfer of molecules from the mobile
45
phase to the stationary phase and back to the mobile phase, and so on back and forth
down the length of the column, which results in separation of various components. The
distance along the column that it takes to make one of these transfers between phases
and re-equilibrate is called the "theoretical plate height." If it takes less distance, that
means the plates are narrow and there are more of them in the column, which means
more transfers between phases can take place, which makes the column more efficient.
That of course means better resolution and a better peak separation.
The sample specimen is introduced into the mobile phase and interacts with the
stationary phase as the mobile phase is flowing along the column. Partition equilibrium
will be maintained since some analyte molecules will return to mobile phase and some
molecules move to stationary phase. This will result in continuous mass transfer
happening between the flowing mobile phase and the stagnant stationary phase during
the whole process of separation. Resistance to mass transfer is dependent on the speed
with which partition equilibrium is achieved. Since the resistance to mass transfer is not
the same for all molecules, this will result in peak broadening of the analyte in the column.
Mass spectrometry (MS) is a powerful technique for identifying the chemical
composition of a compound or a mixture. A sample undergoes chemical fragmentation
resulting in the formation of charged particles, called ions, in an electronic or magnetic
field. The ratio of charge to mass (m/z) of the charged particles is obtained as the result
of their passing through electric and magnetic fields, and is then recorded by an electronic
detector in a mass spectrometer. MS has been applied to many fields for both qualitative
and quantitative uses, due to its excellent specificity, sensitivity and resolution. The design
of a mass spectrometer has three essential modules: (1) an ion source, which transforms
the molecules in a sample into ionized molecular forms (they can be singly or multiply
charged ions, or adduct ions); (2) a mass analyzer, which sorts the ions by their masses
by applying electric and magnetic fields; and (3) a detector, which converts signal to
46
electrical current, then measures the value of some indicator quantity, and thus provides
data for calculating the abundance of each ion fragment present (see Figure 2.6.2.). The
ion source is the crucial part of MS, which ionizes the sample material. Techniques for
ionization have been key to determining what types of samples can be analyzed by MS.
LC-MS method is only possible when the analytes are present as their molecular
ions, in droplets, during ionization process. In the ionization source, charged droplets are
formed by spraying the sample solution through a high voltage (2–5 kV) capillary, in the
presence of a strong electric field. The charged droplets move towards the mass
spectrometer inlet, generating analyte ions during evaporation and droplet fission.
Figure 2.6.2. Schematic diagram corresponding to a mass spectrometer.
Collection of several mass spectral data can be useful when specific information
is required. In MRM mode, two stages of mass filtering are employed on a triple
quadrupole mass spectrometer. In the first stage, an ion of interest (the precursor) is
preselected in Q1 and induced to fragment by collisional excitation with a neutral gas
(normally argon) in a pressurized collision cell (Q2). In the second stage, instead of
obtaining full scan MS/MS, where all the possible fragment ions derived from the precursor
are mass analyzed in Q3, only a small number of sequence-specific fragment ions
47
(transition ions) are mass analyzed in Q3. This targeted MS analysis using MRM allows
rapid and continuous monitoring of the specific ions of interest.
Figure 2.6.3. Ion fragmentation and spectrum differences for MS/MS and MRM mode of
operation (Adapted from (Keshishian et al. 2007).
In this investigation, propranolol degradation compounds were characterized by
using a UPLC Water Acquity Series H, coupled with a Xevo TDQ mass spectrometer (see
Figure 2.6.4.). The instrument is located in the Puerto Rico Energy Center (PREC), at
Universidad del Turabo. Two mobile phases (MP) were used during the research; MP-A
was composed by water and 0.1% of formic acid; and MP-B was acetonitrile and 0.1%
formic acid. The flow gradient of the mobile phases was performed starting with a ratio of
80% of MP-A and 20% of MP-B, that was gradually changed to 50% of MP-A and 50% of
48
MP-B for the first 4 min; after that, this ratio was maintained up to minute 6 (see Tabla
2.6.1.).
Table 2.6.1. UPLC mobile phase gradient.
Mobile Phase A (%) Mobile Phase B (%) Time (min)
80% 20% 0
50% 50% 4 min
50% 50% 4 – 6 min
The propranolol byproducts were separated on a Syncronis C8 column (3mm X
100 mm X 3 µm). The Xevo TDQ MS system was operated in the multiple reaction
monitoring (MRM) mode, in positive ionization (ES+), and using a dwell time of 0.025 s for
each analyte channel. All of the analytes were determined separately. The MS conditions
were optimized for propranolol. The optimum instrument parameters were as follows:
probe source temperature (TEM) was maintained at 350°C, the ion capillary voltage and
cone voltage were maintained at 2.99 kV and 6 V, respectively.
49
Figure 2.6.4. UPLC/MS Water Acquity Series H,
coupled with a Xevo TDQ mass spectrometer, located
in the Puerto Rico Energy Center (PREC) at
Universidad del Turabo, Gurabo campus.
50
Chapter Three
Experimental Methodology
The following section describes the methodology used to characterize the
synthesized TiO2 catalyst and the analysis of the results. Likewise this section describes
the procedures used to obtain the UV-vis spectra of propranolol to monitor the propranolol
degradation through the reaction time. The formal experiment was preceded by two (2)
preliminary experiments. These two experimentations were used to explore the effects of
pH and oxygen on the reaction. The next section describes the procedure used to test
the research hypotheses.
3.1 Synthesis of TiO2 nanowires (TiO2NWs)
The synthesis of TiO2 nanowires has been previously described (Cotto-Maldonado
2012, Cotto-Maldonado et al. 2013, Soto-Vázquez et al. 2016). This synthesis used 37%
HCl, titanium tetrachloride, and deionized water. Silicon substrates (polished single
crystal Si,<100> wafers) were used as supporting material for the growth of the TiO2NWs.
A solution of 30 mL of deionized water and 30 mL of 37% HCl was mixed in a glass beaker
for 10 min. Next, 4 mL of titanium tetrachloride, as Ti precursor, were carefully added
drop wise. The reaction is exothermic and required mixing in a fume hood. The reaction
mixture was magnetically stirred for 30 min. The resulting solution was introduced into a
Teflon line reactor. Next, small pieces of silicon substrates were introduced into the Teflon
lined reactor. The silicon substrates were placed vertically around the inside perimeter of
the Teflon container; Figure 3.1.1. shows the substrate arrangement inside the Teflon
lined reactor.
51
Figure 3.1.1. Four silicon substrates inside
the Teflon container.
The Teflon container was introduced into a stainless steel autoclave that was
subsequently transferred to an oven (Figure 3.1.2. A). The increasing of temperature and
autogenous pressure activates the nanostructure formation. Autoclaves were then
carefully introduced into an oven at 180 °C for 2 hours. The synthesized TiO2NWs is
deposited on the surface of the silicon substrate (see Figure 3.1.2. B). After reaction, the
autoclaves were allowed to cool to room temperature and the silicon substrate (with
TiO2NWs grown on the surface) were removed with tweezers and washed thoroughly with
DDW. The synthesized TiO2NWs were transferred to a glass beaker and dried overnight
in an oven at 40 oC.
52
Figure 3.1.2. Closed stainless steel autoclave (A), and silicon substrates with
TiO2NWs grown on the surface (B).
3.2 Titanium oxide characterization
The surface area was determined by the Brunauer–Emmett–Teller (BET) method
with N2 adsorption at low temperature. The specific surface area is determined by physical
adsorption of an inert gas (N2) on the surface of the solid, and by calculating the amount
of adsorbate gas corresponding to a monomolecular layer on the surface. Three samples
of TiO2NWs and one sample of commercial anatase were measured. The samples were
analyzed using a Micromeritics' ASAP 2020 Accelerated Surface Area and Porosimetry
instrument. The Table 3.2.1. shows the surface area results.
53
Table 3.2.1. Surface area results for TiO2 NWs and anatase.
Morphologies Surface Area (m2-g-1)
Sample 1 Sample 2 Sample 3 Average
TiO2NWs 388 445 423 419
Anatase 58
The samples were characterized by SEM. The samples were prepared by
dispersing a small amount of catalyst in ethanol. After that, the solution was deposited on
the surface of a silicon wafer and allowed to evaporate at room temperature. Then,
samples were placed on the sample holder of the SEM. The SEM characterization was
carried out at an accelerating voltage of 10 kV, work distance ranging from 11 to 12 mm,
and using a spot size of 25 mm. Figure 3.2.1. A, illustrates the synthesized structures with
spherical pattern, crowed growth and forming several layers of spherical particles.
Figure 3.2.1., shows descriptive details of the synthesized nanowires. The images
are characterized by having nanowires of ca. 100 nm diameter and lengths around 3-4
μm, emerging from small spherical particles, with diameters ranging from 5 to 8 µm. The
same particle morphology was observed in all samples, demonstrating consistency in the
synthesis procedures. At higher magnifications (see Figure 3.2.1. C) is observed the
branching level of the TiO2NWs, which can explain the unexpectedly high surface area of
this material.
54
Figure 3.2.1. SEM images of TiO2NWs at different
magnification: 900X (A); 7,500X, side view (B); 13,000X,
side view (C); and 14,000X, top view (D).
The SEM images of the commercial anatase show particles with diameters of ca.
0.06 µm and the presence small aggregates (see Figure 3.2.2.). This material has the
appearance of solid, non-porous, and smooth particles, without apparent cavities,
suggesting less surface area than the synthesized TiO2NWs.
55
Figure 3.2.2. SEM images of commercial anatase at different
magnification: 5,000X (A); 9,000X (B); 12,000X (C); and
35,000X (D).
The crystalline structure of the synthesized TiO2NWs was confirmed by Raman
spectroscopy (see Figure 3.2.3.). The specimen was located in the Raman sample holder,
at room temperature, and then the sample was focused with the instrument objective. The
rutile phase exhibits the most intense peaks at ca. 618 cm-1 and 446 cm-1 and a minor
contribution at 236 cm-1. Based on the space group D4h14 for rutile, and assumed site
symmetries for the Ti and O atoms within the unit cell, group-theoretical analysis shows
four Raman-active “lattice vibrations”, assigned as follows: A1g (610 cm-1) and Eg (446 cm-
1), which are associated to Ti-O bonds (Krishnamurti 1962, Hardcastle 2011), and a broad
band observed near 160 cm-1- 240 cm-1 that has been assigned to O-O interactions. The
anatase phase shows Raman peaks at 144 cm-1, 197 cm-1, 399 cm-1, 515 cm-1, 519 cm-1
and 639 cm−1. These bands can be attributed to the six Raman active modes of anatase
phase, with symmetries Eg, Eg, B1g, A1g, B1g and Eg, respectively (Wang et al. 2011). The
56
peaks at 444 cm-1 and 608 cm-1 unambiguously confirm the rutile crystal structure of the
as-synthetized TiO2NWs.
Figure 3.2.3. Raman spectrum of the as-synthesized
TiO2NWs.
Titanium oxide has different crystal structures that have been characterized by
using XRD (Thamaphat et al. 2008). Thamaphat et al. (2008) characterized four
commercial samples of TiO2 (anatase, nanopowder; anatase micropowder; rutile
nanopowder; and rutile micropowder). Thamaphat et al. (2008) reported XRD patterns for
rutile with strong diffraction peaks at 27°, 36°, 43° and 55°. On the other hand, XRD
patterns for anatase exhibited strong diffraction peaks at 25°, 37°, 38°, 39°, 48°, 54° and
55°.
X-rays patterns of different samples of TiO2NWs and the commercial anatase were
measured by using a Bruker XRD D8 Advance diffractometer (Figure 3.2.4.). Samples
57
were slightly milled, using a ceramic mortar. Next, the samples were deposited onto the
sample holders and introduced in the sample tray. The diffraction patterns were recorded
in the range of 5 to 80 º (Theta/2Theta), applying steps of 0.0195º.
Figure 3.2.4. Image of the Bruker D8
Advance diffractometer, used in this
research.
Figure 3.2.5. shows the X-ray diffraction pattern for the synthesized TiO2NWs and
commercial anatase. Figure 3.2.5. B, which corresponds to the synthesized TiO2NWs,
was unambiguously assigned to the rutile phase. All the diffraction peaks (i.e. 27°, 36°,
43° and 55°) corresponding to the rutile structure (Dhahir 2013), are present in the XRD
pattern of TiO2NWs. Figure 3.2.5. A, shows the XRD pattern for commercial anatase (i.e.
25o, and 48o), confirming the expected structure.
58
Figure 3.2.5. X-ray diffraction patterns of anatase (A), and commercial TiO2NWs (B).
3.3. Study of the degradation of propranolol by UV-vis spectroscopy
The following section describes the procedures for the quantification of propranolol
in aqueous solution by UV-vis spectroscopy. The aqueous solution was prepared using
propranolol hydrochloride 99% acquired from ACROS Organics. The calibration solutions
were prepared using deionized water. The maximum concentration of propranolol was
set to 250 ppm with additional dilution to 125 ppm, 75 ppm, 50 ppm, 37 ppm, 25 ppm, 10
ppm and 1.25 ppm. All the solutions were analyzed by using a Shimadzu UV-2401 PC
instrument (see Figure 2.3.2.). The results of UV-vis spectroscopy were evaluated using
the Beer-Lambert Law (Equation 3.3.1.).
A=ϵlC Equation 3.3.1.
where A corresponds to the absorbance of the solution, epsilon (ϵ) is the molar absorptivity
or the molar absorption coefficient, l is the path length of the cell holder (in cm) and C is
59
the concentration of the solution in molL-1. Following the Beer-Lambert Law,
concentrations greater than 50 mgL-1 were discarded because the absorbance at ca. 289
nm was greater than 1.
Figure 3.3.1. UV spectra of propranolol in aqueous
solution, at different concentrations.
The absorbance at 289 nm was selected as the most appropriate for measuring
the concentration of propranolol. The epsilon value was estimated to be 0.0192 M-1cm-1.
3.4. Propranolol degradation as a function of pH.
The pH can affect the particle charge in the solution and, as a consequence, affect
the interaction between the molecules involved in the degradation process (propranolol,
and catalyst). In order to determine the effects of pH on propranolol degradation, the pH
was modified by using diluted HCl. The pHzpc for propranolol and TiO2 are between 5.8
60
and 6.25 (Ye et al. 2013), promoting the molecular interaction between them. Based on
the previous statement, the solution was adjusted only in the acid range, to explore the
pH effects on the molecular proximity between both systems. In addition, the commercial
propranolol used is balanced with HCl and, in order to avoid interference of other ions,
HCl solution was used to modify the pH instead another acid (see Figure 3.4.1.).
Figure 3.4.1. Propranolol structure balanced with HCl (adapted
from Sigma Aldrich SDS).
The change of pH was accomplished by adding drop wise a solution of HCl 0.01M
until the solution reached the desire pH value. 20 mg of propranolol was added to
deionized water to generate an aqueous solution of propranolol with a concentration of 50
mg L-1. Next the solution was transferred to a 500 mL Erlenmeyer flask. The solution was
mixed using a magnetic stirrer for 10 min. A source of oxygen was added using an air
pump, with a volume flow rate of ca. 10 mL min-1. The solution was irradiated by using
two 40W circular fluorescent lamps (see Figure 3.4.2.). The reaction time was set to 6
hours, taking an aliquot of 10 mL at initial time and after 6 hours. Preliminary runs showed
that 6 hours was the adequate time for the propranolol degradation, shorten reaction times
61
did not lead to an acceptable degradation of propranolol. The aliquots were filtered using
a line filter of 0.45 µm to separate the catalyst. The samples were analyzed by UV-vis
spectroscopy in the wavelengths range of 200 nm to 400 nm.
Figure 3.4.2. Experimental
setup showing the
Erlenmeyer with the reaction
mixture over the magnetic
mixer, the air supply line and
fluorescent lamps.
3.5. Propranolol degradation as a function of oxygen
The previous model described on Section 3.4 showed that propranolol can be
degraded, however the reaction yield was very low (30% - 40% yield). In order to
increase the degradation yield an extra source of oxygen was added, in addition to the
air flow introduced to the reaction mixture. A solution of hydrogen peroxide (H2O2) was
62
used for this purpose. From a H2O2 solution 50% v/v, a new solution 1:10 water:H2O2
(v/v) was prepared. The H2O2 modified the UV spectrum of the propranolol solution.
Higher H2O2 concentration can completely modify the spectra hindering the ability to
monitor the propranolol degradation by UV-vis spectroscopy. The Figure 3.5.1. shows
the effects of the H2O2 addition to the propranolol solution. The concentration of 0.029
M of H2O2 was selected as appropriate for monitoring of the degradation process. The
0.029 M of H2O2 in solution permitted the study of the degradation process at 289 nm.
The selected concentration of H2O2 is shown as the bold orange spectrum.
Figure 3.5.1. UV-vis spectra of propranolol solutions with
different concentrations of H2O2.
63
3.6. Selected parameters for the experimental design
The experimental setup is based on a simple arrangement composed by a
retention pot with mixer, hose, peristaltic pump, MFA (perfluoro methyl alkoxy) pipe,
parabolic trough concentrator (PTC) and four spiral fluorescent lamps (see Figure 3.6.1.).
Figure 3.6.1. Experimental layout.
The reaction solution was introduced into a modified plastic reservoir. The plastic
container was modified to include connection for the airflow, solution inlet stream and
solution outlet stream. The reaction solution inside the reservoir was permanently stirred.
The reaction mixture was recirculated into the system with a peristaltic pump connected
to a MFA line. The MFA was carefully located in the focus of the PTC. The PTC was
made of a stainless steel frame and a polished aluminum surface. Four (4) fluorescent
lamps, in vertical position were used to irradiate the PTC.
The starting solution of propranolol and catalyst in water was prepared. 50 mL of
the starting solution, together with 0.7 mg L-1 of the catalyst and 50 mg L-1 of propranolol
were mixed in the reservoir. The solution was adjusted to pH 6.0 with HCl, and the
64
recirculation flow into the pipe was set to 91 mL min-1. The reaction was carried out for 6
hours, and the solution was permanently stirred with a magnetic shaker. A source of
oxygen was added using an air pump and hydrogen peroxide (0.029 M). A total of 48
tests were performed to accommodate the tree treatments by two levels model. The
treatments consisted in the use of two titanium oxide crystal structures (i.e. anatase, and
TiO2NWs), two different diameter of the pipe reactor (i.e. 0.0625 in., and 0.1875 in) and
the use of a solar collector panel. The air pump had the capacity to produce 10 L min-1 of
air. The peristaltic pump was adjusted to solution flow of 91 mL min-1. The MFA pipes
have a length of 13 inches which was the same length of the parabolic collector.
65
Chapter Four
Results and Discussion
This chapter has been divided into three sections. The first two sections are
devoted to discuss the preliminary experimentation. The first section discusses the results
obtained by varying the pH and concentration of catalyst and the second section discusses
the effects of oxygen sources and its corresponding effects on the degradation yield. The
third section focuses on the results obtained with the design of experiment used to test
the proposed hypotheses.
4.1 Effects of pH and catalyst concentration on the photocatalytic degradation of
propranolol
This study was accomplished with the aim to test the effects of the pH variation
and catalyst concentration on the propranolol degradation. The preliminary
experimentation was developed using anatase as catalyst. The results obtained are
summarized in Table 4.1.1. and Table 4.1.2.
66
Table 4.1.1. Propranolol degradation, as a function of pH and concentration of catalyst
between 0.7 and 1.1 g L-1 (TiO2 anatase).
Percentage of degradation pH TiO2 Concentration (gL-1)
30.0 6.3 0.7
33.4 6 0.7
31.5 5.5 0.7
32.8 5 0.7
31.8 4.5 0.7
35.0 4 0.7
36.2 6.3 0.9
41.5 6 0.9
40.5 5.5 0.9
40.4 5 0.9
38.9 4.5 0.9
41.2 4 0.9
39.8 6.3 1.1
37.0 6 1.1
36.0 5.5 1.1
36.1 5 1.1
38.6 4.5 1.1
36.0 4 1.1
67
Table 4.1.2. Propranolol degradation, as a function of pH and concentration of catalyst
between 1.3 and 1.7 g L-1 (TiO2 anatase).
Percentage of degradation pH TiO2 Concentration (g L-1)
36.9 6.3 1.3
44.4 6 1.3
42.3 5.5 1.3
43.0 5 1.3
42.9 4.5 1.3
38.5 4 1.3
43.0 6.3 1.5
42.5 6 1.5
42.0 5.5 1.5
42.0 5 1.5
42.0 4.5 1.5
43.0 4 1.5
37.0 6.3 1.7
42.9 6 1.7
40.0 5.5 1.7
34.0 5 1.7
35.0 4.5 1.7
43.0 4 1.7
The pH was adjusted from 4 to 6.3. The pH of 6.3 was found without the addition of HCl
solution, and lower pH concentrations were adjusted by dropwise with diluted HCl solution
(0.01 N). The TiO2 concentration was varied from 0.7 to 1.7 mg L-1. In this preliminary
study, the degradation yield ranged from 34% to 43%.
Figure 4.1.1. corresponds to the graphical representation for the model, known as
leverage plot graph. The dots represent the degradation percentage (%), the dotted blue
line corresponds to the averaged results, the solid red line is the predicted line, and the
68
doted red line corresponds to the confidence bands for the regression line. The regression
line is also known as the line of the means. Because the red line does not contain the
blue dotted line, the model represents better the results than the mean of the results. This
result is also confirmed using the pvalue that in this case is 0.0089 (pvalue < 0.05).
Figure 4.1.1. Leverage plot for preliminary run with pH
and catalyst concentration adjustments.
69
Figure 4.1.2. Leverage plot for pH variation effects on the
percentage of propranolol degradation.
The leverage plot for the pH variations shows that the red line is contained by the
blue dotted line, suggesting that the pH contribution is not statistically (see Figure 4.1.2.).
This is supported by a pvalue of 0.7638 that is greater than the alpha value (α) 0.05, meaning
that pH does not have significant effects on the percentage of degradation. Alpha (α)
corresponds to the erroneous probability of rejecting the null hypothesis, when it is true.
In regression analysis, the null hypothesis occurs when the coefficients of the regression
line are zero (0), meaning that effects do not have significant statistically contribution
explaining the response variable representing in this experimentation by the percentage
of degradation. The null hypothesis can only be rejected then, when the pvalue is equal or
less than 0.05. In the case of TiO2 concentration, the red dotted lines did not contain the
blue dotted lines (average of the percentage of degradation) suggesting that the TiO2
concentration has significant effect on the degradation yield (see Figure 4.1.3.). The pvalue
for TiO2 concentration was <0.0009, much smaller than 0.05 meaning that the TiO2
70
concentration has a statistically significant effect on explaining the variability observed on
percentage of degradation.
As can be seen at Figure 4.1.4., the red line does containing the blue dotted line,
and the pvalue is 0.5571 which is greater than alpha (α) of 0.05, meaning that the combined
effects of pH and TiO2 concentration do not have a significant effect on percentage of
degradation.
Figure 4.1.3. Leverage plot of the catalyst concentration
effect on the percentage of propranolol degradation.
71
Figure 4.1.4. Leverage plot of the combination effects of
catalyst concentration and pH on the percentage of
propranolol degradation.
The R2 adjusted for the model is 0.23, meaning that this model can predict the 23%
of degradation results observed. The complementary explanation to these results is that,
there are other variables that are needed to predict the remaining 67% of degradation
results observed.
A visual inspection of the results (see Figure 4.1.5.) shows a decrease in the yields
at lower and higher concentration ranges of the catalyst. This pattern can be visualized
by adjusting the experimental values to a quadratic regression model (red line in Figure
4.1.5.).
72
Figure 4.1.5. Regression plot. The dots represent the
percentage of degradation at different TiO2
concentrations; the red line corresponds to the quadratic
regression.
Figure 4.1.6. illustrates the effect of catalyst concentration on the propranolol
degradation; the predicted catalyst concentration is represented by the red dotted lines.
The catalyst concentrations do not contain the blue dotted line, which represents the
average of the percentage of degradation. The catalyst concentrations have a significant
effect on the degradation yield because the pvalue is less than 0.001.
73
Figure 4.1.6. Quadratic regression leverage plot; catalyst
concentration (TiO2) effects on the degradation of
propranolol.
Figure 4.1.7., illustrates the quadratic effect of the catalyst concentration, this term
have a pvalue is less than 0.05 (pvalue = 0.005). The effects of linear and quadratic terms for
concentration are significant, because both the pvalue are less than 0.05. The new model
must consider the linear and quadratic terms of concentration. This model has an average
mean of 38.6% and is better than the previous one because the adjusted R2 is 0.51, so
this model can predict 51% of the degradation. The mathematical expression for this
model can be expressed as y = 33.39 + 6.16X – 18.39X2 (Figure 4.1.8.)
74
Figure 4.1.7. Quadratic regression leverage plot;
catalyst concentration (TiO2) effects on the degradation
of propranolol.
Figure 4.1.8. Estimated parameters for the new model.
4.2. Oxygen variation effects on the propranolol degradation
Although the prediction of the model was improved, the percentage of degradation
was less than 50% (see Table 4.1.1.), which does not provide a significant relevance as
a potential solution for contamination control. In order to increase the degradation yield,
a new source of oxygen (H2O2 0.029 M) was selected because, under these conditions,
75
H2O2 does not interfere the absorption spectrum, and propranolol degradation can be
monitored by UV-vis spectroscopy. During this new round of tests, the pH was fixed at
6.3, and the lower and higher TiO2 concentrations were not considered in the experimental
model because the previous tests showed no significant effects on the percentage of
degradation. The lower TiO2 concentrations with no significant effects could be justified
due to the fact that at lower concentrations the small amount of TiO2 is limiting the reaction
by a lack of catalyst. On the other hand, a greater amount of TiO2 increases the turbidity
of the solution resulting in a reduction on the amount of light through the solution. The
reduction of light through the solution reduces the photocatalytic activity in the reaction.
The Table 4.2.1. shows the results for this second model using hydrogen peroxide and air
as oxygen sources.
76
Table 4.2.1. Propranolol degradation yield, using hydrogen peroxide and air as oxygen
sources.
Volume of Solution (mL) TiO2 Concentration (mgL-1) Percentage of Degradation
400 0.5 68
400 0.7 68
400 0.9 72
400 1.1 71
400 1.3 71
400 0.5 66
400 0.7 71
400 0.9 71
400 1.1 69
400 1.3 75
200 0.5 69
200 0.7 85
200 0.9 80
200 1.1 77
200 1.3 80
200 0.5 74
200 0.7 80
200 0.9 79
200 1.1 79
200 1.3 80
By using the H2O2, as additional source of oxygen, the percentage of degradation
of propranolol experienced a significant increase, reaching values of ca. 85% (Table
4.2.1.). The new observations were statistically analyzed using a regression model in
order to explain the variable effects on the percentage of degradation. The Figure 4.2.1.
represents the leverage plot for the new degradation model. As can be seen there, the
blue dotted line, corresponding to the percentage of degradation, is higher than in the
77
previous model. On the other hand, the red dotted line does not contain the blue dotted
line, meaning that the regression model explain better the results than the percentage of
degradation mean (pvalue <0.0001). Figure 4.2.1. shows the effect of the reaction volume
on the percentage of degradation. The volume of the reaction solution had statistical
significant effects on the yields (pvalue = 0.0001).
Figure 4.2.1. Leverage plot using H2O2 and air as
oxygen sources.
The concentration of TiO2 had statistical significant effects on the yields (pvalue =
0.0234), but less than volume (pvalue < 0.001) (see Figure 4.2.3.); and the combined effects
(TiO2 concentration and reaction volume) did not have significant effect (pvalue = 1.0) (see
Figure 4.2.4.).
78
Figure 4.2.2. Leverage plot for volume effects on the
degradation rate.
Figure 4.2.3. Leverage plot for TiO2 effects on the
degradation rate.
79
Figure 4.2.4. Leverage plot for TiO2 concentration and the
volume effects on the degradation rate.
The elimination of pH variation as variable, the adjustment of the TiO2
concentration, and the addition of volume as variables resulted in the improvement of the
model. The R2 adjusted was 0.66 (previous R2 adjusted was 0.51), suggesting that volume
helps to explain the response (yield) in the model.
The previous two models provided relevant information. The above-mentioned
models demonstrated that: (1) pH does not have significant effects on yield; (2) the volume
of solution and TiO2 concentration has a significant effect on yield; (3) the maximum yield
was observed at 0.7 g L-1 of TiO2; and (4) it is needed to add other variables in order to
obtain a better model. The previous two models were made using commercial TiO2 with
anatase structure. TiO2NWs was synthesized with the aim to increase the surface area of
the catalyst, with regard to the commercial TiO2. Commercial TiO2 with anatase structure
and the as-synthesized TiO2NWs (with rutile structure) were characterized using different
80
experimental techniques. The specific surface area was determined by the BET method.
TiO2 anatase and TiO2NWs rutile have surface areas of 58 and 419 m2 g-1, respectively
(Table 3.2.1.). The synthesis of TiO2NWs meets the requirement to increase the surface
area of the catalyst. These crystal structures were confirmed by XRD and Raman.
4.3. Experimental design
In this section are shown the effects of the different experimental parameters
involved on the degradation of propranolol. These parameters consist of the different
crystal structure of the catalyst, the reactor diameter, and the light intensity. The
experimentation design consisted in using TiO2 anatase and TiO2NWs, two different
reactor diameters (i.e. 0.0625 in., 0.1875 in) and the use of a solar collector panel. The
experimentation was performed in a system composed by a plastic reservoir, air
compressor, mixing system, peristaltic pump, and four fluorescent spiral lamps (Figure
4.3.1.).
Figure 4.3.1. Experimental layout.
81
Two aliquots per run were collected; at the initial time (time zero) and at final time
(6 hours after). The final design of the experiment (DOE) consisted of a factorial 2x2x2,
with three replications per combination of experimental conditions. The Table 4.3.1.
shows the experimental results (percentage of degradation) per experimental parameter.
The first column describes the type of catalyst (crystal structure), the second column
describes the MFA line internal diameter, the next column indicates if the PTC is used,
and the forth column shows the degradation yield for the combination of the experimental
parameters.
Figure 4.3.2. DOE leverage plot. Dots represent
the experimental results (degradation yield), and
the solid redline represents the predicted results.
82
Table 4.3.1. Degradation rates obtained for the different experimental conditions.
Morphology Pipe diameter Use of
PTC
Response (percentage of
Degradation)
Rutile NW 0.0625 in Yes 56
Rutile NW 0.0625 in Yes 51
Anatase 0.1875 in No 55
Anatase 0.1875 in No 58
Anatase 0.1875 in Yes 61
Rutile NW 0.1875 in Yes 71
Anatase 0.0625 in No 16
Rutile NW 0.0625 in No 46
Rutile NW 0.1875 in No 60
Anatase 0.0625 in No 22
Rutile NW 0.0625 in Yes 56
Anatase 0.0625 in None 18
Rutile NW 0.1875 in No 60
Anatase 0.1875 in Yes 60
Anatase 0.1875 in Yes 61
Rutile NW 0.0625 in None 42
Anatase 0.0625 in Yes 26
Rutile NW 0.0625 in None 66
Anatase 0.0625 in Yes 28
Rutile NW 0.1875 in Yes 69
Rutile NW 0.0625 in None 37
Anatase 0.0625 in Yes 28
Rutile NW 0.1875 in Yes 75
Anatase 0.1875 in None 59
83
Although the mean yield had a decrease when compared with the previous model,
the error of the model was substantially reduced. All the observations are close to the
predicted line (solid red line). The error between the observations and the predicted line
is small; also the model had no outliers (Figure 4.3.2.). The pvalue is less than 0.0001,
which means that this model explains the results of percentage degradation substantially
better than the percent of the degradation mean. The R2 adjusted was 0.98, showing an
impressive improvement of the model (Table 4.3.2.). This model on average is expected
to explain the 98% of the observations.
Table 4.3.2. Summary of the statistical fit parameters.
Parameter Value
RSquare 0.981
RSquare Adj 0.975
Root Mean Square Error 2.793
Mean of Response 49.208
Observations 24
In the analysis of variance, the model hypothesis was that the model was not
significant and cannot explain the results. Since the calculated pvalue is less than 0.05, this
hypothesis was rejected (see Table 4.3.3.). The results obtained are in agreement with
the fact that the model is appropriate to predict the responses.
84
Table 4.3.3. Analysis of variance of the experimental design.
Source DF Sum of Squares Mean Square F Ratio
Model 6 7077.2500 1179.54 151.0998
Error 17 132.7083 7.81 Prob > F
C. Total 23 7209.9583 <0.0001
The Table 4.3.4. shows the results for the lack of fit analysis for the design of the
experiment. For this analysis, the hypothesis is the model, as constructed, and it does not
need more adjustments. Because the pvalue is greater than 0.05 (pvalue = 0.6239), the
hypothesis cannot be rejected. This result is consistent with the fact that the model is
appropriate as constructed. The model includes the necessary independent variables and
combinations of variables, required to explain the responses.
Table 4.3.4. Lack of fit for the experimental design.
Source DF Sum of Squares Mean Square F Ratio
Lack Of Fit 1 2.04167 2.04167 0.2500
Pure Error 16 130.66667 8.16667 Prob > F
Total Error 17 132.70833 0.6239
The new model must consider the linear and quadratic terms. Table 4.3.5. shows
all estimated coefficients for the new model. All estimated coefficients with a pvalue less
than 0.05 have a significant influence on the model. Only the combined effects of light
intensity and pipe diameter did not have significant effect on the percentage of degradation
(pvalue of 0.0854).
85
The magnitude of the effects on the percentage of degradation can be observed
in the column “estimated” in Table 4.3.5. As an example, if we consider that the
coefficients of morphology and pipe diameter are 8.21 and 13.7, respectively, it means
that the change in diameter of the pipe has a greater effect than the morphology on the
percentage of degradation. The smaller coefficient was observed for the combination of
light intensity and pipe diameter, with a value of 1.041667, and is consistent with the pvalue
of 0.0854, which is greater than 0.05.
The higher percentage of degradation (71.3%) was found with the combination of
TiO2NWs, the higher pipe diameter (0.1875 in), and use of the panel (Figure 4.3.3.). The
worst combination of experimental parameters consisted of the use of anatase, smaller
pipe diameter (0.0625 in), and without panel (yield of ca. 18.9%). The use of TiO2NWs
implies better percentage of degradation than anatase, and the use of the PTC (panel)
clearly improves the degradation yield. The use of larger pipe diameters (0.1875 in)
increases the percentage of degradation with respect to the results obtained by using the
smaller diameter (0.0625 in). This result is clearly contrary to what was previously
hypothesized, where large pipe diameter would reduce the reaction rates. A possible
explanation deals with the fact that if both the recirculation flow and the time of reaction
during the experimentation are constants, the variation of the pipe diameter results in
changes in the residence time of the reactor. The smaller pipe diameter (0.0625 in) has
a residence time of 3.87 sec, while the pipe diameter (0.1875 in) has a residence time of
0.43 secs. A smaller residence time means that the flow in the reactor travels faster and,
as a consequence, the radiation exposure is reduced, which necessarily implies a
reduction in the degradation rate
86
Table 4.3.5. Estimated coefficients for the experimental design.
Term Estimate Std Error t Ratio Prob>|t|
Intercept 49.2 0.570 86.3 <.0001*
Morphology [Anatase] -8.21 0.570 -14.4 <.0001*
Morphology [Rutile] 8.21 0.570 14.4 <.0001*
Diameter [0.0625 in] -13.7 0.570 -24.0 <.0001*
Diameter [0.1875 in] 13.7 0.570 24.0 <.0001*
Panel [No] -4.29 0.570 -7.53 <.0001*
Panel [Yes] 4.29 0.570 7.53 <.0001*
Diameter[0.0623 in] *Morphology
[Anatase]
-4.29 0.570 -7.53 <.0001*
Diameter [0.0623 in] *Morphology [Rutile] 4.29 0.570 7.53 <.0001*
Diameter [0.1875 in] *Morphology
[Anatase]
4.29 0.570 7.53 <.0001*
Diameter [0.1875 in] *Morphology [Rutile] -4.29 0.570 -7.53 <.0001*
Panel [No] *Morphology [Anatase] 1.29 0.570 2.26 0.0369*
Panel [No] *Morphology [Rutile] -1.29 0.570 -2.26 0.0369*
Panel [Yes] *Morphology [Anatase] -1.29 0.570 -2.26 0.0369*
Panel [Yes] *Morphology [Rutile] 1.29 0.570 2.26 0.0369*
Panel [No] *Diameter [0.0623 in] -1.04 0.570 -1.83 0.0854
Panel [No] *Diameter [0.1875 in] 1.04 0.570 1.83 0.0854
Panel [Yes] *Diameter[0.0623 in] 1.04 0.570 1.83 0.0854
Panel [Yes] *Diameter [0.1875 in] -1.04 0.570 -1.83 0.0854
.
87
Figure 4.3.3. Cube plot diagram.
4.4. Characterization of propranolol photodegradation byproducts
The propranolol was followed by UPLC-MS/MS. The initial aliquot of ca. 50 mg L-
1 was diluted to 1:100 (v:v) and analyzed to confirm the presence of propranolol (mass
weight of 260 m/z) (see Figure 4.4.1.)
The MRM-MS mode was used to identify potential degradation byproducts of
propranolol. The main goal of this experimentation was not to identify all the degradation
byproducts, but since several compounds are identified, the degradation pathway should
be similar to that previously described in other investigations. Degradation byproducts
were previously identified and, based on this knowledge, the presence of these
decomposition compounds was confirmed (Santiago-Morales et al. 2013). An aliquot of
the reaction mixture was withdrawn after 6 hours of reaction, and was diluted 1:100 (v:v)
in water. The diluted sample was analyzed by UPLC-MS/MS, confirming the presence of
88
at least 3 degradation byproducts, with molecular masses of 119 m/z, 133 m/z, and 165
m/z. The MRM spectra are illustrated in Figure 4.4.2.
Figure 4.4.1. UPLC chromatogram of propranolol
hydrochloride.
89
Figure 4.4.2. MRM-MS spectra for the degradation byproducts, with molecular weights
of 119 m/z (A), 133 m/z (B) ca, and 166 m/z (C).
These three degradation byproducts were previously identify and characterized by
Santiago-Morales et al. 2013. Santiago-Morales et al. (2013) proposed the molecular
90
structure of C5H12NO2 for the 119 m/z byproduct, C6H14NO2 for the 133 m/z compound,
and C6H14NO4 for the 165 m/z molecule.
The first degradation products (P1 to P6) are isomers with molecular weight of ca.
276.15 (C16H22NO3), corresponding to the addition of 16 mass units to the parent
compound (260.16 m/z), imputable to monohydroxylated intermediates. Later, the
degradation proceeds along two different paths: (1) the formation of compounds (P7) from
the fragmentation of the naphthol; and (2) the formation of the compound P8, by
substitution of the amino (NH2) with NOH. The degradation by oxidation continues until
the final compounds (PA, PB and PC) are obtained.
Figure 4.4.3. Proposed degradation pathway for propranolol.
91
4.5. Determination of the reaction rate
The reaction rate is defined as the change in the concentration of either the
reactant or the product over a period of time. The reaction rate is expressed in terms of
the concentration (amount per unit volume) of a product that is formed in a time, or the
concentration of a reactant that is consumed in time. The Table 4.5.1. shows the results
for the estimation of the reaction rate for the propranolol degradation.
Table 4.5.1. Summary of propranolol degradation after 6 hours of reaction, and estimation
of the reaction rate.
Time (min)
Concentration (mgL-1)
Molarity Instantaneous reaction rate (molL-1min-1)
Average reaction rate
(molL-1min-1)
0 55 2.1 10-04
7.7 10-09 120 32 1.2 10-04 1.2 10-08
240 19 7.3 10-05 7.0 10-09
360 12 4.6 10-05 3.7 10-09
The degradation of propranolol using TiO2NWs can be described using the
Langmuir equation (Yang et al. 2010):
−dc
dt=
kKC
1 + KC
where C is the concentration of the substance, k is the reaction rate constant, and K is the
adsorption constant. When the concentration is very low, (KC 1), the equation simplifies
to a pseudo-first order kinetic law:
92
−dc
dt= k1C
𝑟 = −𝑘𝐶𝑎
In this research, and because the reaction is simplified as a pseudo-first order
reaction, the reaction rate constant for the degradation of propranolol was measured to be
7.7 10-9 mol s-1, with a constant rate of 1.52 min-1.
The plug flow reactor (PFR) model is used to predict the behavior of chemical
reactors of such design, so that key reactor variables, such as the dimensions of the
reactor, can be estimated. The key assumption is that as a plug flows through a PFR, the
fluid is perfectly mixed in the radial direction but not in the axial direction (forwards or
backwards). Each plug of differential volume is considered as a separate entity, effectively
an infinitesimally small continuous stirred tank reactor, limiting to zero volume. As it flows
down the tubular PFR, the residence time (t) of the plug is a function of its position in the
reactor (Schmidt 2005).
L = ϑ ∫dC
−r
Ca
Cao Equation 4.5.4.
where L is the length of the reactor in meters, r is the reaction rate in molL-1s-1, C is the
concentration in molm3 and ϑ is the volumetric flow in m3s-1
when r = −kCa Equation 4.5.5.
93
the reaction is a pseudo-first order reaction, where r is the reaction rate in mol L-1s-1 and
Ca in the propranolol concentration in molm-3. Substituting equation 4.4.5. in equation
4.4.4., the new expression is:
L = ϑ ∫dC
−kCa
C𝐚
C𝐚o Equation 4.5.6.
that can be expressed as:
L =ϑ
k∫
dC
Ca
Ca
Cao Equation 4.5.7.
and solving the integral equation:
L =ϑ
kln
Cao
Ca Equation 4.5.8.
where L is the reactor length (m), ϑ is the volumetric flow (m3L-1), and Ca is the
concentration of the reactant (molL-1)
The Table 4.5.2. shows the estimation of reactor lengths for a fixed volumetric flow
of 4.3745 Lsec-1 (ca. 100,000 gallons per day), using the reaction rate determined during
this research at different degradation yields (see Appendix B for mathematical
explanation). As discussed previously, the reaction was performed on laboratory scale
with PTC length of ca. 30.48 cm. Potentially, the use of a larger reactor could increase
the degradation yield of propranolol. Using the design equations for a plug flow reactor,
the reactor length was estimated for different degradation yields. These estimations
94
suggest that a degradation yield of 95% can be achieved with a reactor of ca. 8.6 m, and
99% with a reactor of ca. 13 m.
Table 4.5.2. Estimation of reactor lengths, based on the degradation yields.
Volumetric Flow (L s-1)
Rate Constant
(s-1) Yield
Initial Concentration
(mol L-1)
Final Concentration
(mol L-1)
Length (m)
Length (Ft)
4.3745 1.522 100% 0.00021 2.12077 10-08 26.465 86.80
4.3745 1.522 99% 0.00021 2.12077 10-06 13.232 43.40
4.3745 1.522 98% 0.00021 4.24154 10-06 11.241 36.87
4.3745 1.522 97% 0.00021 6.3623 10-06 10.076 33.05
4.3745 1.522 95% 0.00021 1.06038 10-05 8.608 28.23
4.3745 1.522 90% 0.00021 2.12077 10-05 6.616 21.70
95
Chapter Five
Conclusions
This research proves the effectiveness of titanium oxide as an alternative for the
treatment of water media contaminated with pharmaceuticals products. The synthesis of
TiO2NWs was fully optimized, reducing the reaction time in half, and demonstrating the
production of TiO2 as rutile nanowires. In a first step, preliminary tests were performed
with the purpose to improve the experimental design model. This research showed that
pH variations from 4 to 6.3 did not have significant effects in the degradation, and also it
was demonstrated that the catalyst concentration in the solution could have negative
impact on the degradation yield. Lower and higher concentration ranges of the catalyst
provided a decrease in the degradation yield of propranolol in aqueous solution. The
percentage of degradation was importantly improved by the addition of a small source of
oxygen, as H2O2. This reagent improved the degradation yield from 38.6% to 74.3%,
reducing the statistical error (Radj) from 0.51 to 0.66.
The experimental design for this study considered various experimental
parameters. As a result, it was determined that the increase of the surface area of the
catalyst, the use of small pipe diameters, and the use of a parabolic trough (PTC) collector,
have positive effects, increasing the percentage degradation of propranolol. This research
hypothesized that surface area plays an important role in the degradation reaction.
TiO2NWs, with a greater surface area than commercial anatase, demonstrated better
performance, confirming the first hypothesis. Subsequently, the use of PTC to increase
96
and concentrate the light irradiation on the reactor pipe increased the degradation yield,
confirming the second hypothesis. However, in the case of the third hypothesis, it was
observed that the use of higher reactor pipe diameters produced a decrease in the
degradation yield. This result was justified as follows: In this research, the recirculation
flow was maintained constant during all the degradation experiments and, in this case, a
decrease in pipe diameter increases the residence time, because pipe diameter and
residence time are magnitudes inversely proportional to each other during a constant
recirculation flow. The reduction in the residence time decreases the exposure time of the
solution to the light and, as a consequence, involves a decrease in the degradation yield.
The model designed in this research proved to be efficient and had the potential
to predict 98 % of the results (Radj = 0.98). The introduction of three different experimental
conditions: (1) surface area of the catalyst, (2) pipe reactor diameter, and (3) light
irradiation (by using a PTC), proved to improve and help to increase the predictable results
of the model.
The use of PTC and TiO2NWs proved to be effective for the catalytic
photodegradation of pharmaceuticals in aqueous media. The introduction of PTC
represents an opportunity for future investigations, providing a low energy consumption
alternative. In this research was estimated the reaction rate and reaction rate constant for
the catalytic photodegradation of propranolol. Also, enough data to estimate the length of
plug flow reactor and PTC for an upscale design for a treatment system have been
provided.
The future treatment system can be focused on facilities with the potential to
generate a significant amount of pharmaceuticals wastewaters. These types of facilities
include manufacturing sites and hospitals. As it has been demonstrated in the present
research, wastewater treatment systems, using a translucent pipe reactor, PTC, and
based on photocatalytic processes, are scientifically and technically feasible. According
97
to estimates made in this research, 99% of degradation yield can be achieved using a
PTC and a reactor of ca. 13 m length, capable of processing a flow of 4.3745 L s-1 (ca.
100 000 gallons per day) of contaminated water. The manufacturing discharges of 4.3745
L s-1 are appropriated and representative for standard manufacturing sites. Because
manufacturing plants have their own treatment plants before discharge to a POTW, a
system similar to the used in this research (scaled to the specific conditions of the plant)
can be used to treat manufacturing discharges.
Future research should be developed to improve and maximize the use of PTC in
combination with the use of photocatalysts. This improvement can be oriented to better
understand the effects of pipe diameter, the increase of the efficiency of light radiation to
improve the surface reflecting of the PTC, the improvement of the mixing, variations in
residence time, reaction processes in parallel, and for testing with real wastewater
discharges.
98
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Appendix One
UV-vis Spectras
This appendix includes all the UV-vis spectra obtained during the photocatalytic
processes, following the same order of presentation that Table 4.3.1.
Figure A.1.1. UV-vis spectra for the propranolol degradation using
TiO2NWs, a pipe diameter of 0.0625 in, and PTC. The degradation
yield was 56%.
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
20
0
21
3
22
5
23
8
25
0
26
3
27
6
28
8
30
1
31
3
32
6
33
9
35
1
36
4
37
6
38
9
Ab
s
Wavelength (nm)
0 min
Peroxide
6 Hrs
108
Figure A.1.2. UV-vis spectra for propranolol degradation using TiO2NWs,
a pipe diameter of 0.0625 in, and PTC. The degradation yield was 51%.
Figure A.1.3. UV-vis spectra for propranolol degradation using anatase,
pipe diameter of 0.1875 in, and no PTC. The degradation yield was 55%.
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
20
02
11
22
22
34
24
52
56
26
72
78
29
03
01
31
23
23
33
43
46
35
73
68
37
93
90
Ab
s
Wavelength (nm)
0 min
Peroxide
6 Hrs
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
4
20
02
11
22
22
34
24
52
56
26
72
78
29
03
01
31
23
23
33
43
46
35
73
68
37
93
90
Ab
s
Wavelength (nm)
0 min
Peroxide
6 Hrs
109
Figure A.1.4. UV-vis spectra for propranolol degradation using anatase,
pipe diameter of 0.1875 in, and no PTC. The degradation yield was 58%.
Figure A.1.5. UV-vis spectra for propranolol degradation using anatase,
pipe diameter of 0.1875 in, and PTC. The degradation yield was 61%.
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
4
20
02
11
22
22
34
24
52
56
26
72
78
29
03
01
31
23
23
33
43
46
35
73
68
37
93
90
Ab
s
Wavelength (nm)
0 min
Peroxide
6 Hrs
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
20
02
11
22
22
34
24
52
56
26
72
78
29
03
01
31
23
23
33
43
46
35
73
68
37
93
90
Ab
s
Wavelength (nm)
0 min
Peroxide
6 Hrs
110
Figure A.1.6. UV-vis spectra for propranolol degradation using TiO2NWs,
pipe diameter of 0.1875 in, and PTC. The degradation yield was 71%.
Figure A.1.7. UV-vis spectra for propranolol degradation using anatase,
pipe diameter of 0.0625 in, and no PTC. The degradation yield was 16%.
-1
0
1
2
3
4
5
6
20
0
21
1
22
2
23
4
24
5
25
6
26
7
27
8
29
0
30
1
31
2
32
3
33
4
34
6
35
7
36
8
37
9
39
0
Ab
s
Wavelength (nm)
0min
Peroxide
6 Hrs
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
20
02
11
22
22
34
24
52
56
26
72
78
29
03
01
31
23
23
33
43
46
35
73
68
37
93
90
Ab
s
Wavelength (nm)
0 min
Peroxide
6 Hrs
111
Figure A.1.8. UV-vis spectra for propranolol degradation using TiO2NWs,
pipe diameter of 0.0625 in, and no PTC. The degradation yield was 46%.
Figure A.1.9. UV-vis spectra for propranolol degradation using TiO2NWs,
pipe diameter of 0.1875 in, and no PTC. The degradation yield was 60%.
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
4
20
02
11
22
22
34
24
52
56
26
72
78
29
03
01
31
23
23
33
43
46
35
73
68
37
93
90
Ab
s
Wavelength (nm)
0 min
Peroxide
6 Hrs
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
20
02
11
22
22
34
24
52
56
26
72
78
29
03
01
31
23
23
33
43
46
35
73
68
37
93
90
Ab
s
Wavelength (nm)
0 min
Peroxide
6 Hrs
112
Figure A.1.10. UV-vis spectra for propranolol degradation using anatase,
pipe diameter of 0.0625 in, and no PTC. The degradation yield was 22%.
Figure A.1.11. UV-vis spectra for propranolol degradation using TiO2NWs,
pipe diameter of 0.0625 in, and PTC. The degradation yield was 56%.
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
4
20
02
11
22
22
34
24
52
56
26
72
78
29
03
01
31
23
23
33
43
46
35
73
68
37
93
90
Ab
s
Wavelength (nm)
0 min
Peroxide
6 Hrs
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
20
02
11
22
22
34
24
52
56
26
72
78
29
03
01
31
23
23
33
43
46
35
73
68
37
93
90
Ab
s
Wavelength (nm)
0 min
Peroxide
6 Hrs
113
Figure A.1.12. UV-vis spectra for propranolol degradation using anatase,
pipe diameter of 0.0625 in, and no PTC. The degradation yield was 18%.
Figure A.1.13. UV-vis spectra for propranolol degradation using TiO2NWs,
pipe diameter of 0.1875 in, and no PTC. The degradation yield was 60%.
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
20
02
11
22
22
34
24
52
56
26
72
78
29
03
01
31
23
23
33
43
46
35
73
68
37
93
90
Ab
s
Wavelength (nm)
0 min
Peroxide
6 Hrs
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
20
02
11
22
22
34
24
52
56
26
72
78
29
03
01
31
23
23
33
43
46
35
73
68
37
93
90
Ab
s
Wavelength (nm)
0 min
Peroxide
6 Hrs
114
Figure A.1.14. UV-vis spectra for propranolol degradation using anatase,
pipe diameter of 0.1875 in, and PTC. The degradation yield was 60%.
Figure A.1.15. UV-vis spectra for propranolol degradation using anatase,
pipe diameter of 0.1875 in, and PTC. The degradation yield was 61%.
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
20
02
11
22
22
34
24
52
56
26
72
78
29
03
01
31
23
23
33
43
46
35
73
68
37
93
90
Ab
s
Wavelength (nm)
0 min
Peroxide
6 Hrs
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
20
02
11
22
22
34
24
52
56
26
72
78
29
03
01
31
23
23
33
43
46
35
73
68
37
93
90
Ab
s
Wavelength (nm)
0 min
Peroxide
6 Hrs
115
Figure A.1.16. UV-vis spectra for propranolol degradation using TiO2NWs,
pipe diameter of 0.0625 in, and PTC. The degradation yield was yield
42%.
Figure A.1.17. UV-vis spectra for propranolol degradation using anatase,
pipe diameter of 0.0625 in, and PTC. The degradation yield was 26%.
-1
0
1
2
3
4
5
6
20
0
21
1
22
2
23
4
24
5
25
6
26
7
27
8
29
0
30
1
31
2
32
3
33
4
34
6
35
7
36
8
37
9
39
0
Ab
s
Wavelength (nm)
0 min
Peroxide
6 Hrs
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
4
20
02
11
22
22
34
24
52
56
26
72
78
29
03
01
31
23
23
33
43
46
35
73
68
37
93
90
Ab
s
Wavelength (nm)
0 min
Peroxide
6 Hrs
116
Figure A.1.18. UV-vis spectra for propranolol degradation using TiO2NWs,
pipe diameter of 0.1875 in, and no PTC. The degradation yield was 66%.
Figure A.1.19. UV-vis spectra for propranolol degradation using TiO2NWs,
pipe diameter of 0.1875 in, and PTC. The degradation yield was 69%.
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
4
20
02
11
22
22
34
24
52
56
26
72
78
29
03
01
31
23
23
33
43
46
35
73
68
37
93
90
Ab
s
Wavelength (nm)
0 min
Peroxide
6 Hrs
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
20
02
11
22
22
34
24
52
56
26
72
78
29
03
01
31
23
23
33
43
46
35
73
68
37
93
90
Ab
s
Wavelength (nm)
0 min
Peroxide
6 Hrs
117
Figure A.1.20. UV-vis spectra for propranolol degradation using TiO2NWs,
pipe diameter of 0.0625 in, and no PTC. The degradation yield was 37%.
Figure A.1.21. UV-vis spectra for propranolol degradation using anatase,
pipe diameter of 0.0625 in, and PTC. The degradation yield was 28%.
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
4
20
02
11
22
22
34
24
52
56
26
72
78
29
03
01
31
23
23
33
43
46
35
73
68
37
93
90
Ab
s
Wavelength (nm)
0 min
Peroxide
6 Hrs
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
4
20
02
11
22
22
34
24
52
56
26
72
78
29
03
01
31
23
23
33
43
46
35
73
68
37
93
90
Ab
s
Wavelength (nm)
0 min
Peroxide
6 Hrs
118
Figure A.1.22. UV-vis spectra for propranolol degradation using TiO2NWs,
pipe diameter of 0.1785 in, and PTC. The degradation yield was 75%.
Figure A.1.23. UV-vis spectra for propranolol degradation using anatase,
pipe diameter of 0.1875 in, and no PTC. The degradation yield was 59%.
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
20
02
11
22
22
34
24
52
56
26
72
78
29
03
01
31
23
23
33
43
46
35
73
68
37
93
90
Ab
s
Wavelength (nm)
0 min
Peroxide
6 Hrs
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
20
02
11
22
22
34
24
52
56
26
72
78
29
03
01
31
23
23
33
43
46
35
73
68
37
93
90
Ab
s
Wavelength (nm)
0 min
Peroxide
6 Hrs
119
Appendix Two
Plug Flow Reactor Calculation
This appendix includes the engineering considerations to upscale a treatment
system. The reaction rate and constant rate found in this research were used to calculate
the length of a larger plug flow reactor. The estimation was based on a system of 4.3745
Ls-1, which is equivalent to 100,000 gallons per day.
Variable Definition
L : length in meters
r : rate of reaction in 𝑚𝑜𝑙
𝑚3×𝑠
C : concentration in 𝑚𝑜𝑙
𝑚3
ϑ : volumetric flow in 𝑚3
𝑠
k : rate constant in 1
𝑠
The design equation for a plug flow reactor is L = ϑ ∫dC
r
Ci
Cio
For a first order reaction, the reaction rate can be expressed as r = −kCa
Substituting r as –kCa in the plug flow reactor the expression, then L = ϑ ∫dC
−kCa
Ci
Cio
Because k is a constant, then, L =ϑ
k∫
dC
Ca
Ci
Cio
Then L =ϑ
kln
Cao
Ca , where Cao is the initial concentration of propranolol and Ca is the
propranolol concentration at 6 hours.
Using the values determined during this experimentation, k = 1.5224 1
𝑠, ϑ = 4.3745
𝐿
𝑠 , Cao
= 2.1207 10-4 𝑚𝑜𝑙
𝑚3 , Cao = 2.1207 10-6 𝑚𝑜𝑙
𝑚3
120
L =4.3745
1.5224ln
2.120710−4
2.120710−6
L = 13.23 m
The results obtained for estimating reactor lengths, from the process described above, are
shown in Table 4.5.2. (Chapter 4 Results and discussion), with degradation yields ranging
from 90% to 99.9%.
121
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