Fotocatálisis heterogénea de colorantes azoicos hidrolizados y efluentes textiles simulados sobre nanopartículas inmovilizadas de TIO2

INGENIERÍA QUÍMICA UNIVERSIDAD DE VALLADOLID PROYECTO FIN DE CARRERA FOTOCATÁLISIS HETEROGÉNEA DE COLORANTES DIRECTOS AZOICOS HIDROLIZADOS Y EFLUENTES TEXTILES SIMULADOS SOBRE NANOPARTÍCULAS INMOVILIZADAS DE TiO 2 LAURA DÍEZ MARTÍN JULIO, 2012 INGENIERÍA QUÍMICA UNIVERSIDAD DE VALLADOLID PROYECTO FIN DE CARRERA TÍTULO: HETEROGENEOUS PHOTOCATALYSIS OF HYDROLYSED DIRECT AZO DYES AND SIMULATED DYEHOUSE EFFLUENTS ON IMMOBILIZED TiO 2 NANOPARTICLES ALUMNO: LAURA DÍEZ MARTIN FECHA: JULIO 2012 CENTRO: ECOLE NATIONALE SUPERIEURE DES INDUSTRIES CHIMIQUES (ENSIC, NANCY, FRANCIA) TUTOR: MARIE-NOËLLE PONS CALIFICACIÓN LOCAL: CALIFICACIÓN UVa: Valladolid, 13 de julio de 2012 Coordinador Sócrates Fdo.: Rafael Mato Chaín July 17, 2012 By: Laura Díez Martín Advisor at University of Valladolid: Professor Rafael Mato Chaín Advisor at ENSIC Group of Nancy: Dr. Marie-Noëlle Pons This report represents the final project of a student at University of Valladolid to finish Chemical Engineering studies. The work included in this report was carried out at ENSIC Group (National Polytechnical Institute of Lorraine) in Nancy (France). FINAL PROJECT | Chemical Engineering HETEROGENOUS PHOTOCATALYSIS OF HYDROLYSED DIRECT AZO DYES AND SIMULATED DYEHOUSE EFFLUENTS ON IMMOBILIZED T I O 2 NANOPARTICLES AUTHOR: LAURA DÍEZ MARTÍN TITLE: HETEROGENEOUS PHOTOCATALYSIS OF HYDROLYSED DIRECT AZO DYES AND SIMULATED DYEHOUSE EFFLUENTS ON IMMOBILIZED TiO 2 NANOPARTICLES ADVISOR (France): MARIE-NOËLLE PONS ADVISOR (Spain): RAFAEL MATO CHAÍN Project carried out in: ECOLE NATIONALE SUPERIEURE DES INDUSTRIES CHIMIQUES (Nancy, France) Laboratory of research: LRGP – Sols et eaux, ENSIC – INPL Period of performance: February 2012 – July 2012 JURORS (ENSIC-INPL): Dr. MARIE-NOËLLE PONS Dr. ORFAN ZAHRAA Prof. SERGE CORBEL Acknowledgments I would like to thank very much to Marie-Noëlle Pons, Director of Research of CNRS, for giving me the unique opportunity to work on an innovative and interesting project such as photocatalysis and offering me guidance and advice during its development. Thank you to Steve Pontvianne for his assistance at laboratory. In addition, I would like to thank tthe WPI students, Rebecca and Jesse, for their first introduction to the subject. Finally I would like to express my heartfelt thanks to my parents for their support and confidence. “ Reserve your right to think, for even to think wrongly is better than not to think at all” Hypatia of Alexandria (355? – 415?), Female, Mathematician, Astronomer and Philosopher. CHAPTER 1: LITERATURE REVIEW Díez Martín, Laura 6 CHAPTER 1: LITERATURE REVIEW 1.1. Sustainable development In recent years perception of a sustainable society has increased. The aim of sustainable development is to prevent or minimize pollution in industry, emerging the concept of “Green chemistry”. 1.1.1. Green chemistry Green chemistry is based on the application of chemical engineering for sustainable development, through design, production and application of chemical processes to reduce pollution. Referring to the issue addressed by this project, the twelve green chemistry principles are cited: Green chemistry principle Meaning Prevention It is better preventing the generation of a residue that cleaning it when it has been formed. Atom economy Synthesis methods must be designed to minimize generation of byproducts. Using methodologies that generate products with reduced toxicity If it is possible, synthesis methods must be designed to use and generate substances with low or not toxicity. Generation of effective and not toxic products Chemical products must be created to maintain its efficacy while its toxicity is reduced. Reducing the use of auxiliary substances The use of not essential substances will be avoided. Reduce energy consumption Methods at ambient temperature and pressure will be chosen if it is possible. Use of renewable raw materials The raw material has to be renewable, if it is technically and economically viable. Avoid unnecessary derivatisation The formation of derivative products will be avoided. Enhancement of catalysis Catalysts (as selective and reusable as possible) will be employed, rather than reagents. Generation of biodegradable products Chemicals will be designed to not persist in the environment. Development of analytical methodologies for real-time monitoring Analytical methodologies will be developed after process monitoring. Minimization of chemical accidents The substances used in process, will be selected to minimize the risk of chemical accidents. Table 1.1.Green chemistry principles (Source: Anastas, 1998). CHAPTER 1: LITERATURE REVIEW Díez Martín, Laura 7 1.2. Concerns of water pollution Nowadays, human activity and unbalanced development of society are the causes of water pollution. Practically, there is not any human activity that does not generate wastes, and the volume of them grows exponentially with the industrialization level of a country. The aim to achieve a sustainable growth in water use has led to treat problems related with biological pollution, levels of heavy metals, intensive use of nutrients and organic pollutants, etc Some of tools used to try solve these problems are water disinfection, wastewater treatment before discharge into water supplies, limitation and replacement of nitrates and phosphates in products with a massive use, and developments in analytical chemistry and ecotoxicology. Although discharges from industry and agriculture are the main problem of water pollution, population also has a decisive role in this environmental pollution. From the environmental point of view, besides toxic and dangerous wastes, nonbiodegradable wastes are the most worrying because when they do not receive a specific treatment for destruction or inerting, they can affect the environment. A large quantity of this type of wastes are generated in aqueous solution. The most commonly used biological treatment processes have no action on them. So if there is no additionnal treatment, these wastes are discharged in the environment in most cases. 1.3. Legislation and characteristics of industrial wastewater Industrial effluents often contain substances that are not removed by conventional treatments due to their high concentrations or their chemical nature. Many organic and inorganic compounds that have been identified in industrial wastewater are subject to a special regulation owing to their toxicity or their biological effects at long term. CHAPTER 1: LITERATURE REVIEW Díez Martín, Laura 8 The control of water pollution caused by industrial activities began with the approval of "Federal Water Pollution Control Act" by United States Congress in 1972. USA legislation was completed with the "Clean Water Act" and "Water Quality Act" laws, which were adopted in 1977 and 1978 respectively (EPA, 1972). In Europe, after the enactment of the 16/2002 Law of prevention and integrated pollution control, the pursued objectives have been to reduce the discharge of some specific pollutants and to use advanced systems of water treatment. According to the mentioned 16/2002 Law, the main pollutants with an emission limit value into water are: - Organo-halogenated substances and substances that may generate them in the aquatic environment. - Substances with carcinogenic or mutagenic properties affecting reproduction in the aquatic environment. - Persistent hydrocarbons and bioaccumulative toxic organic compounds. - Cyanides. - Biocides and pesticides. - Substances which have an unfavorable influence on the oxygen balance. These pollutants come from diverse industries and by their nature, concentration or effluent flow, and the wastewater containing them should be treated before discharge or reuse. Table 1.2 contains limit values of discharge for industrial wastewater. Parameter Limit value Temperature 40 ºC pH 6 – 10 COD 1500 mg/l Conductivity at 20 ºC 6000 µ S/cm Nitrates 500 mg/l Ammonium 50 mg/l Sulphates 1000 mg/l Phenols 2 mg/l Inhibition substances 25 equitox/m3 Table 1.2. Limit values of discharge for industrial wastewater (Source: Ruza, 2007). CHAPTER 1: LITERATURE REVIEW Díez Martín, Laura 9 1.4. Technologies for industrial wastewater treatment The objective of wastewater treatment is to remove pollutants present in an effluent in order to ensure certain specifications of discharge determined by a competent administration. The first step to study the appropriate treatments that can be used to treat an effluent, is its characterization. It will be also needed information on its flow rate and its possible fluctuations. The problems of wastewater treatment can be solved in several ways: - Recycling water after removing of pollutants from the effluent. - Exchanging wastes between industries. The waste of an industry sometimes may be a raw material in another process. - Minimizing effluents through changes in product specifications or production process which generate less polluting effluents. - Doing an individual treatment of special effluents. The processes and technologies that are available for treatment of wastewater pollutants are very different. Currently, the treatment techniques most frequently used can be divided into three groups: physical, chemical and biological treatments. The most common conventional technologies are listed in the table 1.3: Physical Treatments Chemical Treatments Biological Treatments Air stripping Chemical stabilization Activated sludge Activated carbon adsorption Catalysis Aerated lagoons Centrifugation Chlor-alkali electrolysis Anaerobic digestion Steam stripping Hydrolysis Stabilization pond Liquid-liquid extraction Electrolysis Trickling filters Distillation Oxidation Enzymatic treatment Electrodialysis Ozonolysis Composting Filtration Photolysis Evaporation Microwave discharge Flotation Neutralization Flocculation Precipitation Ion exchange Reduction Crystallization Reverse osmosis Sedimentation Ultrafiltration Table 1.3. Conventional techniques for wastewater treatment (Source: Hagen,1999). CHAPTER 1: LITERATURE REVIEW Díez Martín, Laura 10 Technologies for wastewater treatment are divided into the following broad groups: - Natural treatments These systems of treatment are not usually employed for industrial wastewater treatment because they require very specific pollution conditions. Examples of this type of treatment are aerated lagoons and green filters. - Primary treatments Their aim is to separation by physical means the particles from the water to be treated. - Secondary treatments They are biological processes used to degrade biodegradable organic matter. There are two main groups: aerobic and anaerobic processes. - Tertiary treatments Traditionally, tertiary processes were used to remove pollutants from water that had not been eliminated in previous treatments. Presently these processes are used for treatment of effluents with very specific pollutants and occasionally it is the only treatment used. Tertiary treatment includes processes such as adsorption, ion exchange, electrodialysis, ultrafiltration, membrane processes, stripping, disinfection, conventional oxidation processes and advanced oxidation processes. For municipal wastewater treatment, pollution is greatly reduced with primary and secondary treatments, but tertiary treatments are also used to comply current regulations and to achieve a higher reclaimed water quality. Many treatment technologies transfer toxic compounds from one medium to another, which is not be a good solution on the long term. The aim of this project is focused on the use of a technology currently under development called "heterogeneous photocatalysis" which is included in advanced oxidation processes. Advanced oxidation processes may constitute in a nearby future one of the main technological resources used for the treatment of effluents contaminated with organic products, which are CHAPTER 1: LITERATURE REVIEW Díez Martín, Laura 11 not treatable by conventional techniques due to their high chemical stability and / or low biodegradability. 1.5. Environment and textile industry Textile industry has had major environmental problems related mainly with water management. The environmental impact of liquid effluents is diverse due to the large variety of raw materials, reagents and methods of production. 1.5.1. Textile production process It is necessary to know the processes which are involved in textile industry in order to understand problems about its effluent production. The main stages in the processing of natural fibres (wool and cotton) appear in figure 1.1: Figure 1.1. Flow chart of a textile industry process (Source: “Ullmann’s Encyclopedia of Industrial Chemistry”). CHAPTER 1: LITERATURE REVIEW Díez Martín, Laura 12 1.5.2. Textile industry and environmental pollution Colored wastewater affects environment and human health if directly discharge without treatment. Wastewater discharged from textile industry is characterised by high chemical demand (COD), low biodegradability, high salt content and is the source aesthetic pollution related to colour. Moreover, the heavy metals and salts from highly coloured wastewater are toxic to aquatic life. Also, it is noteworthy that dyes formula contain numerous auxiliary toxic compounds (Mantzavinos and Psillakis, 2004). Serious health problems such as cancer can be caused by azo dyes and products of their degradation like aromatic amines, because there are carcinogenic. In order to achieve sustainable development, the treatment of dye before its discharge is important. According to the report of Japan Consulting Institute (1994), textile industry is the fifth major industry that become source of environmental problem as it can be seen in table 1.4. However, textile industry is the largest industry discharging colouring effluent. TYPE OF INDUSTRY PERCENTAGE OF WATER POLLUTION Food and beverage 40,5 Rubber and product 14,1 Chemical 11,8 Palm oil 11,6 Textile and leather 9,0 Raw natural rubber 8,6 Paper 4,4 Table 1.4. Industrial sources of water pollution (Source: Environmental Quality Report, 2004). CHAPTER 1: LITERATURE REVIEW Díez Martín, Laura 13 In figure 1.4. typical pollution loads of different production processes in textile industries are mentioned: Figure 1.2. Pollution loads of textile wet operations (Source: Cooper, 1978). To reduce water pollution caused by textile industry, a study must be done to treat the textile effluent efficiently. CHAPTER 1: LITERATURE REVIEW Díez Martín, Laura 14 1.6. Textile wastewater The need to manage rationally the limited water resources and environmental aggression that involves polluted waters, has given rise to more restrictive environmental laws. This fact has forced the research and development of technologies for wastewater treatment in industrial applications. 1.6.1. Characterization of industrial wastewater from textile industries Daily, textile industries consume large amounts of water in most of their processes. The effluents generated are generally characterized by high chemical oxygen demand (COD), high temperature, unstable pH, suspended solids and chloro organic compounds. In addition, as it was explained above, these effluents are a source of pollution owing their colour. The significant characteristic of textile effluents is their strong colour due to residual dyes. It is estimated that around 15% of the total amount of dyes is lost during synthesis and processing. Dyes concentration in wastewater is usually lower than any other chemicals, but due to their strong color they are visible even at very low concentrations, thus causing serious aesthetic and pollution problems in wastewater disposal (Zollinger, 1991). 1.6.2. Need to treat textile wastewaters Hazards that may be due to the uncontrolled discharge of textile effluents, are: Medium-term dangers: - Color, turbidity and odor The accumulation of organic matter in textile effluents provokes bacteria proliferation, foul odor generation and abnormal coloration. - Eutrophication Under the action of microorganisms, the dyes release nitrates and phosphates into the environment. A high amount of these ions can be toxic to aquatic life. The CHAPTER 2: BACKGROUND Díez Martín, Laura 20 Syntheses with compounds already containing the azo group: - exposure of concealed or protected amino groups - acylation of aminoazo compounds - alkylation and acylation of phenolic hydroxyl groups - metal-complex formation Toxicity According to the EU criteria for classification of dangerous substances, the acute toxicity of azo dyes is rather low. There are three ways by which azo dyes can be toxic: - For their structure (there are azo dyes that contain amines or other carcinogenic groups). - By reduction reaction, azo dyes can turn into aromatic amines. Some of these amines are carcinogenic. In the following figure it is shown the reduction of an azo dye: Figure 2.4. Scheme of reduction reaction for azo dyes.. (1) Azo dye (2) Original di-azo components (3) Linking component with additional amine - By direct oxidation reaction, azo dyes can be activated and highly reactive electrophilic diazonium salts can be generated. Moreover, it is important to notice that many azo textile dyes can cause skin hypersensitivity and allergy. Some of them like tartrazine may increase allergic reactions towards other substances. CHAPTER 2: BACKGROUND Díez Martín, Laura 21 2.1.2. Direct Dyes Direct dyes are relatively large molecules with high affinity for cellulose fibres. They are binding to the fibres by Van der Waals forces. Direct dyes are mostly azo dyes with more than one azo bond or phthalocyanine, stilbene or oxazine compounds. Some direct dyes have high light fastness. In the color index, the direct dyes form the second largest dye class with respect to the amount of different dyes. Their classification refers to various planar, highly conjugated molecular structures with one or more anionic sulfonate group. Chemically, the dyes may contain the sulphonate group (-SO 3 - ), essential for water-solubility. CHAPTER 2: BACKGROUND Díez Martín, Laura 22 2.2. Titanium dioxide The polycrystalline semiconductor most used as catalyst in photocatalytic processes is titanium dioxide. This is due to its photo-stability, exceptional optical and electronic properties, no high value of band gap, low cost. It also presents the advantage of being non toxic. Chemical structure TiO 2 exists in three crystallographic forms, anatase, rutile and brookite, but only anatase and rutile are used in photocatalysis. The non-high value of band gap of TiO 2 together with the position of the valence band holes, allows that very energetic holes are generated in the semiconductor. This situation increases the ease for oxidation reactions to occur. Anatase Rutile 3,23 eV - 384 nm 3,02 eV - 411nm Figure 2.5. Crystal structure of anatase and rutile. (Source: Candal, 2001) In both structures, each atom of titanium is located in the center of an octahedron of oxygen atoms. Each oxygen has three coplanar titanium atoms. In the rutile, the oxygen atoms form a compact hexagonal lattice which is slightly distorted. The three angles Ti-O-Ti are almost equal with a value of 120°. CHAPTER 2: BACKGROUND Díez Martín, Laura 23 In anatase, an angle of Ti-O-Ti is about 180° and the other two about 90°. Oxygen atoms form a body-centered cubic lattice. Anatase is thermodynamically less stable than rutile, but its formation is kinetically favored at lower temperatures (<600 ° C), which explains its most active area and its higher density of active sites for adsorption of substances (Epling et al, 2002a, Arslan et al, 2000) Properties In table 2.2 physical and mechanical properties of TiO 2 are summarized. The table 2.3 shows optical properties of TiO 2 (Source: CERAM Research Ltd, 2002). Table 2.2. Typical physical and mechanical properties of TiO 2 . CHAPTER 2: BACKGROUND Díez Martín, Laura 24 Table 2.3. Optical properties of TiO 2 . It has been proved that TiO 2 is the most resistant semiconductor material with respect to corrosion and photocorrosion (Neppolian et al, 2002). A special feature of TiO 2 is the capacity to use natural UV radiation. In the photocatalytic processes with TiO 2 the area of solar spectrum utilized is small, but the study of this technology is promising, owing the abundance and low cost of this natural resource. In the last years, research and development in this field has accelerated dramatically. Preparation technique TiO 2 can be prepared by both liquid and gas phase processes. The sol-gel method is one of the most used liquid phase techniques to synthesize thin films, powders and membranes. Among the many advantages of this technique are ease of processing, control over composition, purity and homogeneity of the obtained materials (Hamadanian et al, 2008). Toxicity A study (Chung et al, 1999) found that ultrafine (less than 0,1 microns) particles of the anatase form of titanium dioxide are pathogenic or disease causing. However, if TiO 2 particles used to act as a sunscreen are small enough, they can penetrate the cells, leading to photocatalysis within the cell, causing DNA damage after exposure to sunlight (EPA, 2009). The worry about skin cancer has appeared with this concept. CHAPTER 2: BACKGROUND Díez Martín, Laura 25 It was noted that the inhalation of titanium dioxide has not induced lung tumours in humans but it is important to note that rats are extremely sensitive species that develop tumours in the lungs. Other studies have related that workers exposed to titanium dioxide have showed no statistically significant relationship between exposure and diseases. It is reasonable to conclude then, that titanium dioxide is not a cancer-causing substance and is generally safe for use in photocatalytic processes. CHAPTER 2: BACKGROUND Díez Martín, Laura 26 2.3. Photocatalytic treatment A photocatalytic process is based on the change in the rate of a chemical reaction, or its initiation under UV, visible or infrared radiation in presence of a catalyst that absorbs light and is involved in the chemical transformation of substances participating in the reaction. 2.3.1. Historical perspective of catalysis J. J. Berzelius (1779 – 1848) coined the catalysis in 1835 in order to rationalize a number of isolated observations, such as the conversion of ethanol to acetic acid, the conversion of starch to sugar by acids, the decomposition of H 2 O 2 by metals, and the reaction between H 2 and O 2 in presence of Pt. He recognized a common feature in these processes but the phenomenon was not properly understood for the next 60 years. W. Ostwald (1853 – 1932), Nobel Prize in Chemistry in 1909, established the kinetic nature of catalysis. In the table below, scientists recognized for works in the field of catalysis are mentioned. Year Scientists Research topic 1909 W. Ostwald For his work on catalysis 1912 P. Sabatier Catalytic hydrogenation 1918 F. Hab er Synthesis of ammonia 1931 C. Bosch, F. Bergius High pressure methods 1932 I. Langmuir Surface chemistry 1963 K. Ziegler, G. Natta Stereospecific polymerization 2001 W.S. Knowles, R. Noyori, K.B. Sharpless Chiral catalysis 2005 Y. Chauvin, R.H. Grub bs, R.R. Schrock Olefin metathesis 2007 G. Eartl Catalytic reactions on surfaces Table 2.4. Nobel Prizes in Catalysis or related topics (Source: Hagen, 1999) The development of the chemical industry in the 20th century was parallel with the evolution of catalysis. Up to about 1940, catalysts were mostly used for the production of basic chemicals and liquid fuels. Significant concepts were introduced by Sabatier (the reactants CHAPTER 2: BACKGROUND Díez Martín, Laura 27 form unstable intermediates with the catalyst) and by Taylor (there are active sites on the catalyst surface, where chemical adsorption occurs) in this period. The basis of catalytic reaction mechanisms was established by Langmuir adsorption isotherm. During the period from 1940 to 1970, the development of hydrocarbon refining and petrochemical industry increased. Catalysts were utilized in synthesis gas, fuel production and selective oxidation processes. In the 1970s years, the legislation about environmental pollution arose promoting the area of catalysis in this field. Important progress was made in the preparation of catalysts and in the understanding of the mechanisms of catalyst deactivation. Moreover, new fields of application emerged, such as photocatalysis and electrocatalysis. In the 1990s, due to the major concern of sustainable development, the concept of "Green Chemistry" appeared. 2.3.2. Introduction to the photochemistry Photochemistry is the discipline that deals with the study of interactions between atoms, small molecules and light (or electromagnetic radiation). The first law of photochemistry, known as the law of Grotthus-Draper, states that light must be absorbed by a chemical substance to generate a photochemical reaction. The second law of photochemistry, the Stark-Einstein law, states that for each photon of light absorbed by a chemical system, only one molecule is activated to produce a photochemical reaction. A chemical reaction required the absorption of electromagnetic radiation with appropriate length by a molecule. When a polychromatic light is passed through an object, it absorbs some wavelengths and transmits the wavelengths that are not absorbed as colours. The wavelength absorbed and the efficiency of absorption will depend on the structure of the molecule and the medium in which it is found. CHAPTER 2: BACKGROUND Díez Martín, Laura 28 In the absorption spectroscopy, the sample absorbs electromagnetic radiation of a suitable source and the amount absorbed can be related with the concentration of the substance that wants to be analyzed in solution. The photochemistry usually works in the following regions of electromagnetic spectrum: - Ultraviolet: 100 – 400 nm - Visible light: 400 – 700 nm - Near infrared: 700 – 1000 nm - Far infrared: 15 – 1000 µm Figure 2.6 . Electromagnetic spectrum (Source: University of Arizona) Photochemistry has numerous applications in air and water purification due to the possibility of degrade chemically pollutants with the presence of light. These reactions of degradation CHAPTER 2: BACKGROUND Díez Martín, Laura 29 take place at low temperatures when photons transfer their energy to transform the reactants directly or through photocatalysts which are not consumed by them. Planck’s law calculates the energy carried by the light to convert the molecules: E = hc/λ Equation 2.1. Planck’s law. h : Planck constant (6,624 ∙10 -34 J∙s) c: speed of light (3∙10 8 m∙s -1 ) λ : wavelength of the radiation 2.3.3. Advanced Oxidation Processes (AOPs) Advanced Oxidation Processes (AOPs) have been proposed in recent years basically as effective alternatives in the purification of air and contaminated waters. The presence of toxic and / or refractory compounds is a major problem for the conventional biological treatments. In addition, the typical separation technologies transfer contamination from one phase to another or create a more concentrated effluent. Furthermore, in recent years, the occurrence of so-called "emerging contaminants" (pesticides, pharmaceuticals ...) creates an additional problem due to the limited information available about its effects on the environment and its interference in the biological processes. For their ability to degrade these pollutants, the AOPs are an attractive option to perform this type of treatment. The AOPs are based on physicochemical processes capable of producing profound changes in the chemical structure of the contaminants. These processes involve the generation of a hydroxyl radical in sufficient amount to interact with the remainder of organic compounds. This radical can be generated by photochemical means (including sunlight) or other forms of energy, and has a high efficiency for the oxidation of the organic matter. AOPs use the high oxidative capacity of hydroxyl radical (HO°) which has very short reaction time. There are several methods depending on the way that generates these radicals. The most common methods use combinations of ozone (O 3 ), hydrogen peroxide (H 2 O 2 ), ultraviolet CHAPTER 2: BACKGROUND Díez Martín, Laura 36 Figure 2.9. Bandgap for metals, semiconductors and insulators. In this situation, the absorption of those photons takes place and electron-hole pairs (e - and h + ) are created in the catalyst surface, which are dissociated in free photo-electrons in the conduction band and photo-holes in the valence band. Figure 2.10. Energetic diagram of a semiconductor during photoexcitation process (Source: Lingsebigler, 1995). Simultaneously an adsorption of reagents is produced and an electron is transferred to an acceptor molecule (Ox 2 ), producing a reduction reaction, while a photo-hole is transferred to a donor molecule (Red 1 ) which will be oxidized. CHAPTER 2: BACKGROUND Díez Martín, Laura 37 Figure 2.11. Global reaction in heterogeneous photocatalysis. (Source: Palmisano et al, 2007). In the figure 2.12, we can observe how the reaction occurs when the radiation with an appropriate wavelength reaches the catalyst surface: Figure 2.12 . Scheme of heterogeneous photocatalytic process (Source: Solar Energy Materials and Devices Group of Renewable Energy laboratory). CHAPTER 2: BACKGROUND Díez Martín, Laura 38 i : UV irradiation of the contaminant with a suitable catalyst (semiconductor) to promote a separation of charges. ii: The migration of electrons that have been seen promoted to the conduction band, occurs and the holes that have been created in the valence band move towards the catalyst surface. iii: The capture of holes and electrons by absorbed species generates highly reactive radicals capable of causing oxidation of polluting compounds. Hydroxyl radicals produce the oxidation of organic compounds and their photocatalytic degradation, obtaining as final reaction products CO 2 and H 2 O. The photo-induced molecular transformations and reactions, involving electron transfer or energy transfer, will take place at the surface of the catalysts solely. Choice of catalyst A good catalyst is one semiconductor particle that meets the following characteristics: - The catalyst is not altered during the process. - The products formed are the desired. - There is a great generation of electron - hole pairs. - It is an exothermic reaction and the final products do not store energy of photons. The table 2.7 shows some semiconductor compounds that can be used in photocatalytic reactions and the maximum wavelength required to activate the catalyst. The wavelength capable of producing the band gap, can be calculated by Planck equation which was explained above. CHAPTER 2: BACKGROUND Díez Martín, Laura 39 Table 2.7. Semiconductors used as catalysts in photocatalytic processes (Source: Ullmann’s Encyclopedia of Industrial Chemistry). A lot of semiconductor substances have been tested for compound degradation. However, the best results have been obtained with TiO 2 catalyst (Andreozzi et al., 1999, Hermann, 1999). TiO 2 is selected as the most suitable substance due to it has a high stability against chemical action and photo-corrosion. It also has a low cost and is safe. In addition, TiO 2 has the advantage of using the solar UV radiation because the separation between valence and conduction band is suitable for these photons, with a less wavelength than 387 nm, that have sufficient energy to excite the catalyst (Hermann, 1999). Photocatalysis with TiO 2 One of the most important properties of TiO 2 is based that upon ultraviolet radiation (λ < 390 nm), titanium dioxide exhibits photocatalytic activity through the action of conduction band electrons and valence band holes photoinduced from the crystal lattice of TiO 2 . In presence of water and oxygen these species produce highly reactive radicals such as OH and O 2 -, on the surface of TiO 2 (case A in the figure 2.13). That enables the oxidative destruction of a wide range of organic compounds on its surface. On the other hand, these materials may also exhibit photocatalytically induced superhydrophilicity that converts the hydrophobic character of the surface to hydrophilic when exposed to UV light (case B in figure 2.13). This causes the formation of uniform CHAPTER 2: BACKGROUND Díez Martín, Laura 40 water films on the surface of these materials, which prevents the adhesion of inorganic or organic components, and thus retains a clean surface on the photocatalyst. Figure 2.13 .Photocatalytic reaction on TiO 2 surface (Source: Research Centre for Nanosurface Engineering) It can be argued that the mechanism of heterogeneous photocatalytic reaction takes place in the following stages: - Transport of reagent in fluid phase to the catalyst surface. - Adsorption of reagents on the catalyst surface. - Photogeneration of electrons and electronic gaps in the catalyst by UV radiation. - Migration of charges into catalyst surface. - Reactions of electrons and electronic gaps with adsorbed species. - Eventual reactions between products adsorbed on the catalyst surface and radical products generated. - Desorption of products. - Transport of products into fluid phase. CHAPTER 2: BACKGROUND Díez Martín, Laura 41 Figure 2.14. Sketch of a photocatalytic process (Source: ExplainThatStuff). Reaction mechanism The azo chromophore –N=Ncan undergo oxidation processes (photogenerated holes) and reduction (photogenerated electrons), besides the interaction with hydroxyl radicals, hence its ease of degradation. The reactions that occur during a photocatalytic process with TiO 2 are detailed below. Following excitation of the TiO 2 molecule with light of appropriate wavelength, with photon energy in excess of the semiconductor band gap (Eg>3,23 eV), an electron/hole pair is generated in the metal oxide particle [Reaction 1]. TiO 2 + hν → TiO 2 (h + + e - ) [Reaction 1] TiO 2 (h VB+ ) + H 2 O → TiO 2 + H + + OH° [Reaction 2] TiO 2 (h VB+ ) + OH - → TiO 2 + OH° [Reaction 3] Hole + Dye solution → Absorbed dye solution [Reaction 4] Hole + H 2 O 2 → H 2 O 2 absorbed [Reaction 5] h + + e - → Heat [Reaction 6] H 2 O 2 + e - → OH° + OH - [Reaction 7] H 2 O 2 + h + → O 2 + 2H + [Reaction 8] H 2 O 2 + OH° → H 2 O + HO 2 ° [Reaction 9] H 2 O 2 + hν → 2OH° [Reaction 10] Dye solution + OH° → Degradation of products [Reaction 11] CHAPTER 2: BACKGROUND Díez Martín, Laura 42 Dye solution + h VB+ → Oxidation of products ( R-COO - + h + → TiO 2 +R°+CO 2 ) [Reaction 12] Dye solution + e CB+ → Reduction of products [Reaction 13] The photogenerated electrons reduce the absorbed dye [Reaction 13] or react with electron acceptors (as H 2 O 2 absorbed on the surface of TiO 2 or dissolved in water), reducing the hydroxyl radical [Reaction 7]. The photogenerated holes can oxidize the organic molecule to form R + [Reaction 12], or reacted with OH - [Reaction 3] or water [Reaction 2] oxidizing into OH° radicals. These, together with other species, are responsible of heterogeneous photodecomposition of dye solutions. For interactions with holes and electrons to be possible, the substrates should be absorbed into the catalyst surface. Dyes and H 2 O 2 undergo a process of physical adsorption [Reactions 4 and 5] to start the reactions mentioned. The process of recombination [Reaction 7] occurs when electrons and holes are not trapped efficiently by absorbed substrates. Then these two species return to their initial state, with a heat generation. The resulting OH° radical is a strong oxidizing agent (standard redox potential 2.8 V) which can oxidize many azo dyes even until full mineralization. Also, it can be observed the pH dependence [Reaction 3], given by the dissociation of water into ions. Kinetics It is assumed that the illuminated area of the reactor is uniform and it is supposed a quasi constant reaction rate which will require the following aspects: - Uniform light scattering. - Absence of mass transfer limitations. - Effective mixing. - Good fluid circulation. CHAPTER 2: BACKGROUND Díez Martín, Laura 43 It should be considered that the reaction volume (V) is not necessarily equal to the irradiated volume (V irr ). Therefore, the conversion for a organic reactant in a specific section of reactor (A irr ) depends on the mixture illuminated and the weight of catalyst (W irr ) that is irradiated. Based on true rate constants (k), for a first order photoconversion, the rate constant can be expressed with apparent rate constants (k app ) by next equation:   = ′  ∙  = ′′  ∙  = ′′′  ∙    Equation 2.2 .Apparent rate constant. The degradation rate of an absorbed substance on catalyst, is identified with the true rate constant of the Langmuir - Hinshelwood kinetic model:  =   =  = −  1 +  Equation 2.3.Degradation rate. Where: r: degradation rate k: degradation rate constant θ: occupation coverage of adsorption sites K: adsorption equilibrium constant (defined by the ratio between adsorption and desorption rate constants K = k ads /k des . C: equilibrium concentration (after adsorption) It is assumed that the term KC is negligible, because at low concentrations kC<<1 and the model follows a first order kinetics, so the integrated reaction rate can be determined by apparent rate constant:     = −  ∙  Equation 2.4 . Integrated rate equation. Where: C 0 : initial concentration of dye solution t : time CHAPTER 2: BACKGROUND Díez Martín, Laura 44 Parameters involved in a photocatalytic process Numerous research works about heterogeneous photocatalysis with TiO 2 have been developed in recent years in order to improve the technology of degradation of organic substances present in industrial wastewater. These works have been performed to study the influence of several parameters involved in photocatalytic processes. Parameters that have been studied in this work, are detailed. Effect of pH The pH affects the properties of catalyst surface and the chemical structure of the compound to degrade, and this is reflected in changes in the degradation rate and the flocculation tendency of the catalyst. When photocatalysis with TiO 2 is applied for the degradation of organic matter, the pH must be optimized because this factor determines the semiconductor surface load and the system capacity to generate oxidant radicals which will allow the substrate to be transformed or mineralized (Zepp et al, 1992). Heterogeneous photacalysis is a process dependent of pH (Khataee et al, 2010, Alinsafi, 2005, Palmisano et al, 2007, Arslan, 2000, Zepp, 1992). When the pH of solution varies, the properties of the solid-liquid interface are modified. Consequently, the adsoption/desorption efficiency and the separation of the electron/hole pair, are affected. For a solution with a upper pH than the isoelectric point of TiO 2 the catalyst surface is negatively charged, while for a lower pH than the isoelectric point the opposite occurs (Guillard,2003). For TiO 2 Millenium – PC500, the isoelectric point (IEP) is situated in 6,2. (Gumy, 2005) . Next, the equilibrium can be seen: pH < IEP : Ti – OH + H + → TiOH 2 + pH > IEP : Ti – OH + OH - → TiO - + H 2 O The change of pH influences the adsorption process of dye molecules on the catalyst surface. CHAPTER 2: BACKGROUND Díez Martín, Laura 45 In alkaline medium, the number of hydroxyl radicals may be increased on the surface of TiO 2 particles, by entrapment of the hydroxyl ions by available photoinduced holes. The holes are considered the most powerful oxidative specie at low pH, while at high or neutral pH hydroxyl radicals are the predominant species. Clearly, when the polluting organic molecule and the catalyst surface have the same load, the adsorption is very low. For these reasons, the photocatalytic activity of anionic azo dyes achieves a maximum under acid conditions followed by a decrease in the range of pH between 7 - 11. Furthermore, the higher degradation rate in acid pH is due to the efficiently process of electron transfer caused by the formation of a complex bond in the surface. Effect of catalyst surface Generally the advantageous features for a photocatalyst are a high surface area, a uniform size distribution of particle, the spherical form of particles and the absence of internal porosity. In photocatalytic processes, usually powders whose particles have micrometric diameters are employed. The photocatalytic degradation with TiO 2 of dye solutions, is influenced by the important role of the photocatalyst surface. Several authors have reported that the photocatalytic process is based mainly on the generation of radicals that occur on the catalyst surface (Fox et al, 1993, Serpone and Pelizzeti, 1989). Studies show that photocatalytic reaction takes place in the adsorption phase on TiO 2 surface, and not in solution (Guillard et al, 2003). The amine groups are mainly transformed into ammonium and nitrate. The azo groups (-N=N-) are mineralized in N 2 . The sulphur atoms in form of sulphite (=S + -) or sulphonates (-SO 3 - ) are mineralized into sulphate. In addition, the concentration of salts and reaction products, may affect the capacity of the catalyst in the photocatalytic process (Guillard et al, 2003). CHAPTER 4: MATERIALS AND METHODS Díez Martín, Laura 52 - Starch from potato → 2,78 mg/l Then, hydrolysis was applied (Alinsafi, 2005). Also, one experience with simulate synthetic textile water for DR23 at halved concentration of chemical substances were done to observe the influence of these substances in the photocatalytic reaction. This experience has been called “Simulated Light Dyehouse Effluent”. CHAPTER 4: MATERIALS AND METHODS Díez Martín, Laura 53 4.2. Methods The following actions are needed to evaluate the efficiency of a photocatalytic process: - Effectiveness of a degradation process must be controlled with the monitoring of the kinetics of dye degradation. - The presence of reaction intermediates have to be determined. - The safety of the final effluent should be ensured. From analytical point of view, the task that involves a greater difficulty is the qualitative and quantitative evolution of intermediates or degradation products. As hydroxyl radicals are not selective in its attack, many products are formed in the intermediate stage to the complete mineralization of the dyes initially presents in the water to be treated. Chemical analysis of these complex reaction mixtures is difficult, so the studies focus on monitoring the disappearance of the initial dye (Khataee et al, 2010, Alinsafi, 2005, Vulliet et al, 2003), as well as monitoring of TOC decrease and the appearance of inorganic ions. So, in this way, kinetics of dye degradation and mineralization rate are evaluated during the process. However, it would be necessary to have a better knowledge of intermediate products that are generated, because in many cases these products may be more toxic and persistent than initial compounds (Bianco – Prevot et al, 1999). For this reason, a toxicological evaluation of these processes is also necessary. Then, analytical techniques used in this study are described. 4.2.1. pH The pH indicates if solution is acid or alkaline. This parameter was adjusted depending on the experience to test with sodium hydroxide (NaOH) or hydrochloric acid (HCl). The pH – meter used in the laboratory was Radiometer PHM220 (Paris, France). CHAPTER 4: MATERIALS AND METHODS Díez Martín, Laura 54 4.2.2. UVVisible Spectrophotometry UV-Visible spectrophotometry is an analytical technique used to determine the concentration of compounds, from the measure of its absorbance. Textile effluents contain chromophores that absorb radiation in the visible or ultraviolet. The valence electrons of these groups are transported to the orbitals of higher energy level under the effect of radiation. Physical principle The principle of ultraviolet-visible spectrophotometry involves the absorption of ultravioletvisible radiation by a molecule causing the promotion of an electron from a ground state to an excited state, releasing the excess energy as heat. For this method, the wavelength is comprised between 190 and 800 nm. The molecules that have non-binding valence electrons in there molecular structure, when they are excited by light, emit color. When a UV-Vis radiation passes through a solution containing an absorbent analyte, the beam intensity (I 0 ) is attenuated to I. This fraction of radiation that has failed to pass the sample is called transmittance (T) (T = I / I 0 ) but absorbance (A) is used because it is related lineally with concentration according to the Lambert – Beer equation: A = log (I/I 0 )= ∑ε i ∙l∙c i Equation 4.1. Lambert - Beer Law. Where, ε: molar absorption coefficient l: optical path length c i : concentration of substance The absorbance of a substance at a determined wavelength is the sum of the absorbances of each chromophore group i which absorbs at that wavelength. CHAPTER 4: MATERIALS AND METHODS Díez Martín, Laura 55 Calibration Curve The spectrum of a substance is a graphical representation of the absorbance (A) versus the wavelength (λ). This graph shows waves with peaks and minimum values. For making quantitative determinations, the wavelength corresponding to a maximum value (peak) is chosen because, for that value, the error of measure is minimum and the sensitivity is maximum. To verify the compliance of Beer's law, calibration curve must be performed. So, solutions of substance at known concentrations are prepared and their absorbance, at the chosen wavelength, is measured. If Beer's law is valid for that substance at these concentrations, the relationship should be a straight line. In the Annex II, calibration curves for the studied direct azo dyes are shown at concentrations between 1,5 and 25 mg/l. Experimental procedure In the experiences, the spectrophotometer used was SECOMAM Anthélie Light (Domont, France) which can be seen in figure 4.3 Figure 4.3. Spectrophotometer SECOMAM Anthélie Light. Electromagnetic spectra of dye solutions were measured in a range of 200 to 700 nm. CHAPTER 4: MATERIALS AND METHODS Díez Martín, Laura 56 Solutions were placed in a quartz cuvette, with an optical path of 10 mm, to measure the absorbance and a blank was previously done with distilled water. Once the light has passed through the sample, the spectrophotometer shows a graph with measured absorbance versus wavelength. 4.2.3. Ammonium Ammonium is one of the possible end-products of photocatalysis. For this reason, ammonium was analyzed in final dye solutions. This parameter will be necessary to indicate the efficiency of photocatalytic process. Nessler method was used to determine ammonium in samples. Nessler method To test this procedure samples were collected the end of the photocatalytic process. 10 ml of sample were introduced into a glass tube and then these substances were added: - Two drops of mineral stabilizer (HACH) - Two drops of polyvinyl alcohol dispersant (HACH) - 400 μl of Nessler reactive (HACH) The blank was made with distilled water following the same procedure. Before ammonium measurement, the tubes were shaken to homogenize the sample. Nessler method is based in the generation of a yellow colour when Nessler reagent is decomposed in presence of ammonium ions. To determine ammonium concentration in samples, the absorbance was measured with spectrophotometer HACH DR 2400 at 425 nm. CHAPTER 4: MATERIALS AND METHODS Díez Martín, Laura 57 Figure 4.4. Spectrophotometer HACH DR 2400. The concentration of samples was calculated using calibration curve. Figure 4.5. Calibration curve for ammonium After analysis, chemical wastes were transferred to an appropriate container. y = 3,446x R² = 0,999 0 0,5 1 1,5 2 2,5 3 3,5 0 0,2 0,4 0,6 0,8 1 [N-NH4+] mg/l Absorbance at 425 nm Calibration curve for Ammonium CHAPTER 4: MATERIALS AND METHODS Díez Martín, Laura 58 4.2.4. Total Organic Carbon (TOC) Analysis and quantification of TOC in samples is important because this parameter is commonly used as indicator of water quality and treatment process efficiency. To do this, the amount of organic compounds in initial and treated effluents is studied. The large number of intermediate compounds formed during dye degradation demonstrates the complexity of the photocatalytic process. Due to the high difficulty of tracking all possible intermediate products, it is possible to follow reliably the evolution of photocatalytic process, by TOC monitoring. In short, to monitor the loss of colour is not sufficient. It is also necessary to reach the conversion of a significant percentage of organic carbon in inorganic carbon in the form of CO 2 . The contribution of total carbon (TC) in water samples is made by organic and inorganic substances. Therefore total organic carbon (TOC) and inorganic carbon (IC) must be distinguished. The IC is made up of carbonates and CO 2 dissolved in water, while TOC has two parts: the volatile or purgeable organic carbon (POC) and the non-volatile organic carbon or non-purgeable (NPOC). If the volatile organic portion is negligible, it is assumed that the NPOC is equal at TOC. Non-Purgeable Organic Carbon (NPOC) The method used for TOC analysis is called Non-Purgeable Organic Carbon (NPOC) (Chamorro et al, 2010). In this method, IC is removed from a sample by purging the acidified sample with a purified gas, and then TOC may be determined by means of TC measuring method as TC equal TOC. The method occurs in three stages: - Acidification Addition of acid to removes carbonate ions and converts them into carbon dioxide. CHAPTER 4: MATERIALS AND METHODS Díez Martín, Laura 59 - Oxidation Oxidation of carbon in the remaining sample to generates carbon dioxide and other gases. This oxidation step was performed by combustion. - Detection and Quantification The measurement of generated carbon dioxide is done by a non-dispersive infrared detector (NDIR). The technique used is the total combustion of organic matter into CO 2 and detection of this product with non-dispersive infrared detector. The sample is prepared by acidification and aeration to remove the inorganic carbon. The treated sample is injected into a furnace where water is evaporated and organic carbon generates CO 2 by catalytic combustion. CO 2 is carried by an air stream until the UP detector, which provides a variation of voltage proportional at concentration of total organic carbon (TOC). A TOC Analyzer Shimadzu was used. Figure 4.6. TOC Analyzer Shimadzu. CHAPTER 4: MATERIALS AND METHODS Díez Martín, Laura 60 4.2.5. Ion Chromatography for nitrates and sulphates Technology Ion Chromatography is a variant of High Pressure Liquid Chromatography (HPLC). It is an effective method for separation and determination of ions, based on the use of ion exchange resins. When an ionic sample passes through these columns, the ions experience a separation due to the different retentions they undergo when interacting with the stationary phase of the analytical columns. Once separated, the sample flows through a detector which registers the signal obtained with respect to the retention time. The result is a chromatogram where the peak position indicates the type of ion and its area indicates the amount of that ion. Nitrates (NO 3 ) and nitrites (NO 2 ) are oxidation products of nitrogen. Nitrate is more stable and can be transformed into nitrite. Ion chromatography is suitable for measuring the amount of nitrates, nitrites as well as sulphates in solution. Health dangers of nitrates Nitrate is not generally hazardous to health unless it is reduced to nitrite. Nitrate is one of the most common groundwater contaminants. It must be controlled in drinking water because excess levels can cause methemoglobulinemia in babies. Furthermore, the emergence of nitrates in water might indicate the presence of other hazardous pollutants such as bacteria or pesticides. Substance Type of problem Approximate level that would causes problems Nitrate Risk of infant methemoglobulinemia if the water is consumed by young children - Recommended: less than 50 mg/l. - Acceptable: 50 mg/l to 100 mg/l. - No recommended: more than 100 mg/l. Table 4.2. Amount of nitrate that would causes health problems (Source: World Health Organization, 2007). CHAPTER 4: MATERIALS AND METHODS Díez Martín, Laura 61 4.2.6. Toxicity Study Although the purpose of a photocatalytic process is to reach complete mineralization of all organic carbon, in some cases partial degradation of the contaminant may be acceptable if the final product is harmless. The determination of toxicity is essential in determining the efficiency of a photocatalytic process. In the case of treatment of effluents from textile industries, the desired product is an effluent that can be discharged without affecting any of the species of ecosystem. Germination studies are considered short-term and primary assessment methods for acute toxicity effects. For example, plant toxicity studies have been designed to evaluate the phytotoxic effects of dye wastewaters (Palácio et al, 2009), and alfisol soil (J. Celis et al, 2007) and bioremediated explosives (Frische, 2003). In this research project, two toxicity studies were performed. In order to study the toxicity of samples before and after photocatalytic process, a toxicity test with lettuce seeds was made. Furthermore, toxicity studies were realized with six types of different plant seeds to compare the response about toxicity in neutral dyes. Toxicity test with lettuce seeds Toxicity tests with Lactuca sativa L. have been commonly made due to the high sensitivity of lettuce to toxic chemicals (Sobrero and Ronco, 2004, Banks and Schultz, 2005). The acute toxicity test with lettuce seeds is performed to evaluate the adverse effects of a pure compound or a complex mixture in the germination process and in the development of the seedlings during the first days of growth. The inhibition of germination and the elongation of radicle and hypocotyl are determinated to study the response of a toxicity test. CHAPTER 5: INSTALLATION Díez Martín, Laura 68 CHAPTER 5: INSTALLATION At ENSIC in Nancy, a photocatalytic reactor has been previously manufactured by researchers (Khataee, Pons and Zahraa, 2010). The experiences have been developed in a fixed bed reactor where the catalyst is immobilized into a fixed support. Experimental setup The pilot plant of photocatalysis is constituted by a fixed bed reactor (37 o inclination angle), with dimensions of 30x 30 cm 2 , which acts as support of non-woven paper made of cellulose fibres. The catalyst TiO 2 is fixed on the paper. In the next picture, the setup can be seen. Figure 5.1. Experimental installation of photocatalysis 500 ml of dye solution are pumped from a reservoir to the reactor, with a flowrate of 200 ml/min, to ensure a good distribution of liquid. A glass window (30 x 30 cm 2 ) covers the reactor to prevent evaporation of the solution which could occur due to heating by UV / sun. UV radiation is produced by two lamps (Black light Blue, F15T8, BLB 15 W, DUKE (Essen, Germany)), with a power of 15 W which emit at a wavelength of 395 nm, located in parallel to CHAPTER 5: INSTALLATION Díez Martín, Laura 69 the reactor. The solution flows down on the paper and is collected at the bottom. Then, it returns to the reservoir containing the sample to be treated. Flow Diagram Figure 5.2. Flow diagram of photocatalytic reactor. Procedure Previously to the development of experience, the dye solution to be treated is circulated through the reactor during 30 minutes. The first sample is collected at the beginning of the experiment. Next, the UV lamps are activated and samples are taken during the next 8 hours. The collection of final sample is done after 24 hours of process. The reactor is rinsed with ultrapure water under UV radiation between experiences with different dyes. CHAPTER 6: RESULTS AND DISCUSSIONS Díez Martín, Laura 70 CHAPTER 6: RESULTS AND DISCUSSION Four types of direct azo dyes were tested in neutral and hydrolysed solutions. Simulated dyehouse effluents based on these dyes were also studied. 6.1. Applied Method Experiences were made at LRGP in the ENSIC for each type of dye, collecting samples during eight hours. Besides, a last sample was taken 24 hours later of the beginning of the experiment. First, calibration curves were established (Annex II). To do this, dye solutions at different known concentrations were prepared and their absorbance was measured by UVspectrophotometry with a spectrum analysis from 200-700 nm. Following this procedure, maximum wavelength was obtained for each dye. In the figure 6.1, it can be seen the example of the azo dye “Direct Violet 51”: Figure 6.1 . Graph for calibrated of DV51. Then, absorbances at λ max versus dye concentrations were represented, obtaining a linear relationship (Figure 6.2): 0 0,2 0,4 0,6 0,8 1 1,2 200 300 400 500 600 700 Absorbance Wavelength (nm) Graph for calibrated of DV51 1,5 mg/l 2,5 mg/l 5 mg/l 7,5 mg/l 10 mg/L 15 mg/l 20 mg/l 25 mg/l CHAPTER 6: RESULTS AND DISCUSSIONS Díez Martín, Laura 71 Figure 6.2 . Calibration curve for Direct Violet 51. In all cases, calibration curves have shown a linear relationship, with a R 2 value higher than 0,99. Using the mentioned relationships, concentrations were calculated for all experiences by the measure of absorbances by spectrophotometry. Then Ln C 0 /C versus time was represented. The slope of the straight line obtained accounts the apparent constant rate of reaction. In Annex III a table summarizes the experiments. y = 0,0465x - 0,0397 R² = 0,9979 0 0,2 0,4 0,6 0,8 1 1,2 1,4 0 5 10 15 20 25 30 Absorbance at 547 nm Concentration (mg/l) Calibration Curve for Direct Violet 51 CHAPTER 6: RESULTS AND DISCUSSIONS Díez Martín, Laura 72 6.2. Spectrophotometry Photocatalytic reaction follows a first-order kinetic model, as it has been explained. Although neutral dyes achieved complete decolorization, in most experiences with hydrolysed dyes and simulated dyehouse effluents total decolorization not happened. All spectra of dye solutions can be found in Annex IV. Figure 6.3. Samples for Direct Red 23. In an azo dye, the interaction between an azo group (-N=N-) and two aromatic species originates the colour (Khataee et al, 2010). These mentioned aromatic nuclei are: - An acceptor group frequently containing a chromophore (such as –SO 3 - group). - A donor group frequently containing an auxochrome (such as OH group). The mechanism of dye degradation takes place when the fragile groups NH of these dyes loose an H atom by OH radicals (Zahraa et al, 1999). The adsorption of dye solutions, produced by electrostatic attraction, is the first step and it occurs at the surface of TiO 2 . Adsorbed species are mineralized by hydroxyl radicals (Daneshvar, 2003). Therefore, this stage controls the photocatalytic degradation. % =  −    ∙100 Equation 6.1. Percentage of colour removal. CHAPTER 6: RESULTS AND DISCUSSIONS Díez Martín, Laura 73 In the Annex V kinetics results are summarized. Photocatalytic decolorisation of the four dyes in neutral, hydrolysed and simulated dyehouse effluents is shown in the next figures (Figure 6.4, Figure 6.5, Figure 6.6, Figure 6.7) . Figure 6.4. Photocatalytic decolorisation of DY50 solutions. Figure 6.5. Photocatalytic decolorisation of DR81 solutions. 0 10 20 30 40 50 60 70 80 90 100 0 60 120 180 240 300 360 420 480 CR(%) Irradiation time (min) Photocatalytic decolorisation of DY50 solutions Neutral DY50 Hydrolysed DY50 at PH=6 Hydrolysed DY50 at PH=7 Hydrolysed DY50 at PH=8 Simulated Dyehouse Effluent DY50 at PH=6 Simulated Dyehouse Effluent DY50 at PH=7 Simulated Dyehouse Effluent DY50 at PH=8 0 10 20 30 40 50 60 70 80 90 100 0 60 120 180 240 300 360 420 480 CR(%) Irradiation time (min) Photocatalytic decolorisation of DR81 solutions Neutral DR81 Hydrolysed DR81 at PH=5,5 Hydrolysed DR81 at PH=6 Hydrolysed DR81 at PH=7 Hydrolysed DR81 at PH=8 Simulated Dyehouse Effluent DR81 at PH=6 Simulated Dyehouse Effluent DR81 at PH=8 CHAPTER 6: RESULTS AND DISCUSSIONS Díez Martín, Laura 74 Figure 6.6. Photocatalytic decolorisation of DV51 solutions. Figure 6.7. Photocatalytic decolorisation of DR23 solutions. 0 10 20 30 40 50 60 70 80 90 100 0 60 120 180 240 300 360 420 480 CR (%) Irradiation time(min) Photocatalytic decolorisation of DV51 solutions Neutral DV51 Hydrolysed DV51 at PH=5,5 Hydrolysed DV51 at PH=6 Hydrolysed DV51 at PH=7 Hydrolysed DV51 at PH=8 Simulated Dyehouse Effluent DV51 at PH=6 Simulated Dyehouse Effluent DV51 at PH=7 Simulated Dyehouse Effluent at PH=8 0 10 20 30 40 50 60 70 80 90 100 0 60 120 180 240 300 360 420 480 CR(%) Irradiation time (min) Photocatalytic decolorisation of DR23 solutions Neutral DR23 Hydrolysed DR23 at PH=6 Hydrolysed DR23 at PH=7 Hydrolysed DR23 at PH=8 Simulated Light Dyehouse Effluent DR23 at PH=7 Simulated Dyehouse Effluent DR23 at PH=6 Simulated Dyehouse Effluent DR23 at PH=7 Simulated Dyehouse Effluent DR23 at PH=8 CHAPTER 6: RESULTS AND DISCUSSIONS Díez Martín, Laura 75 Viewing the previous graphs in which colour removal is represented versus irradiation time, it can be concluded that decolorization of neutral solutions occurred faster than the one of hydrolysed solutions and the latter, faster than the one simulated dyehouse effluents for all dyes that have been tested. Hydrolysis produces a breakdown in a dye molecule which retards the reaction. On the other hand, inorganic salts formed a double lawer in catalyst surface which inhibits the adsoption of dyes. Moreover, it has been observed that decolorization decreases with pH increases (for pH values between 68). The reason for this observation may be attributed at the fact that the catalyst surface is positively charged in acidic solution and negatively charged in alkaline solution, according to the isoelectric point of charge of TiO 2 (Khataee et al 2010, Alinsafi, 2005). Also, in figure 6.8 it can be seen how chemical substance concentration affects in the photocatalytic reaction because an increase of concentration delays decolorization due to the presence of impurities in dye solutions, consume hydroxyl radicals and blocks the light penetration in solution (Guillard et al, 2003). A comparison between different studied neutral azo dyes shows that chemical structure of dyes influences the degradation rate: Table 6.1. Apparent constant rates and structural characteristics of neutral dyes. Analyzing the results, it can be concluded that generally a higher number of H bond acceptor groups (in which chromophore groups are included) in dye molecule implies that photocatalytic reaction happens faster. This fact is related with the negative charge of –SO 3 - groups that capture hydrogens of water, increasing solubility of dye molecule in water. Owing Dye Azo groups (-N=N-) Chromophore (-SO 3 - ) Aromatic rings H Bond Donor H Bond Acceptor k app DY50 2 4 6 2 17 0,0496 DR81 2 2 4 2 12 0,0421 DV51 2 2 5 2 13 0,0308 DR23 2 2 6 5 7 0,0220 CHAPTER 6: RESULTS AND DISCUSSIONS Díez Martín, Laura 76 the increase of solubility, the mass transfer between catalyst surface and dye solution, is improved. In addition, in dyes with the same number of azo and –SO 3 - groups when the number of aromatic rings grows, the photocatalytic reaction is slower because a greater number of bonds have to be degraded. Decolorisation reactions of hydrolysed solutions of Direct Red 23 were the fastest of all hydrolysed solutions. This fact, can be originated because this dye presents the greatest amount of NH fragile groups, which are easier to degrade by hydrolysis. Next, the decolorisation for dyes in different conditions is compared: Figure 6.8. Decolorisation comparison for dye solutions. The decolorisation is larger than 80% in all experiences, except for simulated dyehouse effluent of DV51 at pH =8. 0 10 20 30 40 50 60 70 80 90 100 Neutral Hydrolysed PH=6 Hydrolysed PH=7 Hydrolysed PH=8 Simulated PH=6 Simulated PH=7 Simulated PH=8 Decolorisation (%) DY50 DR81 DV51 DR23 CHAPTER 6: RESULTS AND DISCUSSIONS Díez Martín, Laura 83 Figure 6.14. Average seed length of dye solutions. Relative toxicity only reached a value of 50% in two experiences as it can be seen in figure 6.15. These are the experiences with simulated dyehouse effluents of Direct Red 23 at pH 6 and 8. As it could be expected, at pH=7 usually appeared a less toxicity than at acidic or basic pH due to the addition of chemical substances to adjust the pH. Figure 6.15 . Relative toxicity of dye solutions. 0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5 4,0 4,5 5,0 DY50 DY50H PH=6 DY50H PH=7 DY50H PH=8 DY50SDE PH=6 DY50SDE PH=7 DY50SDE PH=8 DR81 DR81H PH=6 DR81H PH=7 DR81H PH=8 DR81SDE PH=6 DR81SDE PH=8 DV51 DV51H PH=6 DV51H PH=7 DV51H PH=8 DV51SDE PH=6 DV51SDE PH=7 DV51SDE PH=8 DR23 DR23H PH=6 DR23H PH=7 DR23H PH=8 DR23SDE PH=6 DR23SDE PH=7 DR23SDE PH=8 L seed Dye solutions Seed length of dye solutions Initial samples Final samples 0 10 20 30 40 50 60 DY50 DY50H PH=6 DY50H PH=7 DY50H PH=8 DY50SDE PH=6 DY50SDE PH=7 DY50SDE PH=8 DR81 DR81H PH=6 DR81H PH=7 DR81H PH=8 DR81SDE PH=6 DR81SDE PH=8 DV51 DV51H PH=6 DV51H PH=7 DV51H PH=8 DV51SDE PH=6 DV51SDE PH=7 DV51SDE PH=8 DR23 DR23H PH=6 DR23H PH=7 DR23H PH=8 DR23SDE PH=6 DR23SDE PH=7 DR23SDE PH=8 Relative Toxicity Dye solutions Relative Toxicity of dye solutions Initial samples Final samples CHAPTER 6: RESULTS AND DISCUSSIONS Díez Martín, Laura 84 The decrease in relative toxicity was significant in most of dye solutions, although some exceptions appeared which could be due to the emergence of toxic amines during the degradation process of azo dyes. As it would be expected, simulated dyehouse effluents were the most toxic samples in general by the presence of chemical substances on them. In initial samples for neutral dyes, toxicity was attributed at azo dye; but in final samples and hydrolysed solutions toxicity was ascribed at toxic amines that are generated during hydrolysis and photocatalytic process. Although neutral dyes are completely degraded by photocatalytic process, the toxicity of final samples is attributed to the mentioned toxic amines. The percentage of toxicity removal is included in figure 6.16. Direct Red 23 was the dye solution with the greatest toxicity removal. In addition, in photocatalytic process with hydrolysed dyes the highest toxicity removal has been obtained. This fact implies that toxic amines have been reduced in final samples of these solutions. A remarkable point of this study, was that after photocatalytic process not all dyes decreased in toxicity how it can be seen in the figure 6.16. Figure 6.16. Toxicity removal of dye solutions. -40 -20 0 20 40 60 80 100 DY50 DY50H PH=6 DY50H PH=7 DY50H PH=8 DY50SDE PH=6 DY50SDE PH=7 DY50SDE PH=8 DR81 DR81H PH=6 DR81H PH=7 DR81H PH=8 DR81SDE PH=6 DR81SDE PH=8 DV51 DV51H PH=6 DV51H PH=7 DV51H PH=8 DV51SDE PH=6 DV51SDE PH=7 DV51SDE PH=8 DR23 DR23H PH=6 DR23H PH=7 DR23H PH=8 DR23SDE PH=6 DR23SDE PH=7 DR23SDE PH=8 %T REMOVAL Dye solutions Toxicity removal of dye solutions CHAPTER 6: RESULTS AND DISCUSSIONS Díez Martín, Laura 85 From toxicity tests performed, it is not possible establish a relationship between the results obtained for the different dye solutions and the chemical structure dyes. The germination index was higher than 0,8 in all final samples (figure 6.17 ). Figure 6.17. Germination Index of dye solutions. Compared with the positive control seeds with 100% germination index, dye solutions contained some phytotoxicity inhibitions. Dye solutions had a stronger inhibitory effect on root length and germination seed percentage. Generally, a value of germination index below 50% indicates that phytotoxic compounds might have not been metabolized, inhibiting germination (Epstein, 1997). However, in the case of dyehouse effluents, the salt concentrations might have inhibited seed development and thus reduced germination index. On the other hand, in tested samples the inhibition of root growth appeared as more sensitive phytotoxicity indicator than the number of germinated seeds. The higher toxicity of these solutions can be attributed mainly at the combination of several characteristics such as their 0,0 0,2 0,4 0,6 0,8 1,0 DY50 DY50H PH=6 DY50H PH=7 DY50H PH=8 DY50SDE PH=6 DY50SDE PH=7 DY50SDE PH=8 DR81 DR81H PH=6 DR81H PH=7 DR81H PH=8 DR81SDE PH=6 DR81SDE PH=8 DV51 DV51H PH=6 DV51H PH=7 DV51H PH=8 DV51SDE PH=6 DV51SDE PH=7 DV51SDE PH=8 DR23 DR23H PH=6 DR23H PH=7 DR23H PH=8 DR23SDE PH=6 DR23SDE PH=7 DR23SDE PH=8 GI Dye solutions Germination Index of dye solutions Initial samples Final samples CHAPTER 6: RESULTS AND DISCUSSIONS Díez Martín, Laura 86 high salinity and of any excess of organic compounds or ammonium ions (Hoekstra et al.,2002). Analyzing the results obtained in toxicity test, although for the majority of tested dye solutions the decrease in toxicity is achieved, in some experiences a more toxic product was obtained. For this reason, a secondary treatment process should be applied. CHAPTER 6: RESULTS AND DISCUSSIONS Díez Martín, Laura 87 Comparison of plants for germination toxicity tests A comparison study of six types of plants for toxicity was performed with initial and final samples of neutral azo dyes. The samples for Direct Red 23 can be seen in the next figure: Figure 6.18 . Samples of DR23 for comparison toxicity test. The experimental observations of germinating seedlings are shown in figure 6.19 . Figure 6.19. Comparison of germination for neutral dyes. CHAPTER 6: RESULTS AND DISCUSSIONS Díez Martín, Laura 88 For germination test, the plants that have shown an increasing number of germinated seeds were radish, lettuce and cucumber. The seeds of millet have not germinated in any case. The length of seeds was measured for experiences and results are shown in the figure 6.20. Radish, lettuce and watercress provided the best results for toxicity study although radish and watercress seeds were difficult to measure due to the emergence of long radicles into the absorbent paper. Figure 6.20. Comparison of seed length for neutral dyes. Radish and lettuce were seeds that have showed significant sensitivity to azo dyes. According to the ease of procedure, lettuce seeds are the best plant to use for germination toxicity studies. This type of seed is sensitive to the pollutant and is relatively easy to enumerate. Other comparison studies of plants for germination toxicity tests have indicated the same (Banks and Schultz). CHAPTER 7 Díez Martín, Laura 89 CHAPTER 7: CONCLUSIONS AND PERPECTIVES Photocatalytic decolorisation and mineralization of four direct azo dyes, with two azo groups, in neutral, hydrolysed solutions and simulated textile effluents has been tested in presence of immobilized TiO 2 nanoparticles on non-woven paper under UV radiation. Results have shown that decolorisation was complete in neutral solutions, but not in the majority of hydrolysed solutions and simulated effluents. It has been mentioned that the adsorption takes place at catalyst surface. With regard to the pH of solution, for pH between 6 and 8, it has been observed that dye degradation was favored at acidic pH, which can be attributed at the positively charge of catalyst surface under those conditions. So, the adsorption occurs faster due to the anionic charge of dye molecule. On the other hand, the effect of inorganic salts in simulated dyehouse effluents could be attributed to the formation of a double layer of these salts at catalyst surface which produces the inhibition in the adsorption of solutions. It can also be concluded that degradation rate at catalyst surface depends on the type of catalyst employed, the characteristics of degraded sample and the chemical structure of dye involved in solutions. For example, it has been seen that in neutral dyes with a great number of sulfates in their structure, degradation was faster. In the same way, neutral dyes with the same number of sulfate groups in their structure were degraded more slowly when this structure had more aromatic rings. The first aspect can be explained because a greater number of sulfates in dye molecule, implies an increase in anionic charge of dye. The second one can be due to the fact that the dye molecules with more aromatic rings have a higher value of molecular weight. However, in hydrolysed solutions and simulated effluents this behavior did not happened since dye molecules were broken into smaller ones by hydrolysis and also some inorganic substances were added. In hydrolysed dyes, degradation was favored in dyes with more amide groups and less sulfate groups. The previous aspect can be attributed to the ease of degradation of amides by hydrolysis in carboxylic acids and the substitution between sulfate ions and hydroxyl radicals. In addition, it would be necessary to know thoroughly the mechanisms that take place during hydrolysis in order to understand clearly CHAPTER 7 Díez Martín, Laura 90 how degradation phenomenon is produced and how inorganic salts acts in the reactions. This is a difficult task by the complexity to study how light interfere to degrade dye solutions. By photocatalytic procedures, the degradation of all dye solutions was not achieved within the 24 hours of the experiment because in some experiences TOC was not removed, and in others the removal was rather low. Under acidic conditions, a greater TOC removal occurred due to the positively charge of catalyst surface at these conditions, and therefore, the increase of OH radicals to oxidize organic carbon. For ammonium and nitrates, in practically all experiences the measured amount was less than expected. It could be due to the formation of N 2 over ammonium. Concerning to the toxicity, final samples of dye solutions had acceptable germination index but, in some cases, there was not any toxicity removal. In conclusion, in most cases, heterogeneous photocatalysis is a good treatment for textile wastewaters allowing practically total adsorption of dyes. However, TOC results showed that organic compounds remained in the solution. For this reason, and to decrease the toxicity of final samples, a secondary treatment process, possibly a biological treatment, should be applied. The fact that the textile wastewater can be treated with solar irradiation would eliminate major operational costs making this methodology an attractive alternative treatment process. REFERENCES Díez Martín, Laura 91 REFERENCES Alinsafi, A.: 2005, “Traitabilité de Rejets Liquides de l’Industrie Textile”. Doctoral Thesis. National Polytechnic Institute of Lorraine (ENSIC Group, Nancy, France) and University of Cadi Ayyad (Marraketch). Anastas, P., Wagner, J.: 1998, “Green Chemistry: Theory and Practice” p. 30. Andreozzi, R., Caprio, V., Insola, M., Marotta, R.: 1999, “Advanced oxidation processes (AOP) for water purification and recovery”. Catalysis Today. Volume 53, Issue 1: 51 – 59. Arslan I., Bahnemann D.W., Balcioglu A.I.: 2000, “Heterogeneous photocatalytic treatment of simulated dyehouse effluents using novel TiO2 – photocatalysts”. Applied catalysis B: Environmental (26) : 193-206. Banks, M.K. and Schultz, K.E.: 2005, “Comparison of plants for germination toxicity tests in petroleum-contaminated soils”. Water, Air and Soil Pollution (2005) 167: 211 – 219. Bianco – Prevot, A., Fabbri, D., Promauro, E., Morales – Rubio, A., de la Guardia, M.: 2010. “Contonuous monitoring of photocatalytic treatments by flow inyection. Degradation of dicamba in aqueous TiO2 dispersions”. Chemosphere 44 (2001): 249 – 255. Candal, R.J., Bilmes, S.A., Blesa, M.A.: 2001, “Semiconductores con actividad fotocatalítica”. Eliminación de contaminantes por Fotocatálisis Heterogénea. Chapter 4: 79 – 102. Celis, J., Sandoval, M. and Briones, M.: 2007, “Bioensayos de fitotoxicidad de residues orgánicos en lechuga y ballica anual realizados en un suelo alfisol degradado”. R.C. Suelo Nutr. Veg., Vol.7, n.3 : 51 – 60. Chamorro, X., Rodríguez, G., Enríquez, A.L.: 2010, “Montaje y validación del método de análisis por combustión y detección por IND del COT en agua”. LunAzul Sciencific Journal 30/01/2010. Chen, H.Y., Zahraa, O., Bouchy, M.: 1997, “Inhibition of the adsorption and photocatalytic degradation of an organic contaminant in an aqueous suspension of TiO2 by inorganic ions”. Journal of Photochemistry and Photobiology A: Chemistry: 37 – 44 Chung, A., Gilks, B., Dai, J.: 1999, “Introduction of fibrogenic mediators by fine and ultrafine titanium dioxide in rat tracheal explants”. AJP – Lung Physiol November 1.1999 Vol 277 no. 5 L975 – L982. Cooper, S.G.: 1978, “The textile industry. Environmental control and energy conservation” p. 385. Daneshvar, N., Salari, D.et al.:2003, “Photocatalytic degradation of azo dye acid red 14 in water: investigation of the effect of operational parameters”. Journal of Photochemistry and Photobiology A: Chemistry 157 (1): 111 - 116 98 CALIBRATION CURVE FOR DIRECT YELLOW 50 For Direct Yellow 50 dye, the absorbance peak appears at a maximum wavelength of 395 nm. 0 0,2 0,4 0,6 0,8 1 1,2 200 300 400 500 600 700 Absorbance Wavelength (nm) Graph for calibrated of Direct Yellow 50 1,5 mg/l 2,5 mg/l 5 mg/l 7,5 mg/l 10 mg/l 15 mg/l 20 mg/l 25 mg/l y = 0,0198x + 0,0047 R² = 0,9992 0 0,1 0,2 0,3 0,4 0,5 0,6 0 5 10 15 20 25 30 Absorbance at 395 nm Concentration (mg/l) Calibration Curve for Direct Yellow 50 99 CALIBRATION CURVE FOR DIRECT RED 23 For Direct Red 23 dye, the absorbance peak appears at a maximum wavelength of 503 nm. 0 0,2 0,4 0,6 0,8 1 1,2 200 300 400 500 600 700 Absorbance Wavelength (nm) Graph for calibrated of Direct Red 23 1,5 mg/l 2,5 mg/l 5 mg/l 7,5 mg/l 10 mg/l 15 mg/l 20 mg/l 25 mg/l y = 0,032x + 0,0046 R² = 0,9951 0,0000 0,1000 0,2000 0,3000 0,4000 0,5000 0,6000 0,7000 0,8000 0,9000 0 5 10 15 20 25 30 Absorbance at 503 nm Concentration (mg/l) Calibration Curve for Direct Red 23 100 CALIBRATION CURVE FOR DIRECT RED 81 For Direct Red 81 dye, the absorbance peak appears at a maximum wavelength of 510 nm. 0 0,2 0,4 0,6 0,8 1 1,2 200 300 400 500 600 700 Absorbance Wavelength (nm) Graph for calibrated of Direct Red 81 1,5 mg/l 2,5 mg/l 5 mg/l 7,5 mg/l 10 mg/l 15 mg/l 20 mg/l 25 mg/l y = 0,0456x + 0,0046 R² = 0,9977 0,0000 0,2000 0,4000 0,6000 0,8000 1,0000 1,2000 1,4000 0 5 10 15 20 25 30 Absorbance at 510 nm Concentration (mg/l) Calibration Curve for Direct Red 81 101 ANNEX III: Summary table about studied experiences DYE TYPE OF SOLUTION PH NAME DY50 NEUTRAL DY50 HYDROLYSED 6 DY50H at pH = 6 HYDROLYSED 7 DY50H at pH = 7 HYDROLYSED 8 DY50H at pH = 8 SIMULATED DYEHOUSE EFFLUENT 6 DY50SDE at pH = 6 SIMULATED DYEHOUSE EFFLUENT (Test 1) 7 DY50SDE at pH = 7 SIMULATED DYEHOUSE EFFLUENT (Test 2) 7 DY50SDE at pH = 7 SIMULATED DYEHOUSE EFFLUENT 8 DY50SDE at pH = 8 DR81 NEUTRAL DR81 HYDROLYSED 5,5 DR81H at pH = 5,5 HYDROLYSED 6 DR81H at pH = 6 HYDROLYSED 7 DR81H at pH = 7 HYDROLYSED 8 DR81H at pH = 8 TEXTIL SYNTHETIC WATER 6 DR81SDE at pH = 6 TEXTIL SYNTHETIC WATER 8 DR81SDE at pH = 8 DV51 NEUTRAL DV51 HYDROLYSED 5,5 DV51H at pH = 5 HYDROLYSED 6 DV51H at pH = 6 HYDROLYSED 7 DV51H at pH = 7 HYDROLYSED 8 DV51H at pH = 8 SIMULATED DYEHOUSE EFFLUENT 6 DV51SDE at pH = 6 SIMULATED DYEHOUSE EFFLUENT 7 DV51SDE at pH = 7 SIMULATED DYEHOUSE EFFLUENT (Test 1) 8 DV51SDE at pH = 8 SIMULATED DYEHOUSE EFFLUENT (Test 2) 8 DV51SLDE at pH = 8 DR23 NEUTRAL DR23 HYDROLYSED 6 DR23H at pH = 6 HYDROLYSED 7 DR23H at pH = 7 HYDROLYSED 8 DR23H at pH = 8 TEXTIL SYNTHETIC WATER 6 DR23SDE at pH = 6 TEXTIL SYNTHETIC WATER 7 DR23SDE at pH = 7 TEXTIL SYNTHETIC WATER 8 DR23SDE at pH = 8 SIMULATED LIGHT DYEHOUSE EFFLUENT 7 DR23SLDE at pH = 7 102 ANNEX IV: Dye spectra DIRECT YELLOW 50 NEUTRAL DY50 SAMPLE S1 S2 S3 S4 S5 S6 S7 Time (min) 0 15 30 45 60 75 90 Absorbance at λ máx 0,5092 0,2308 0,1255 0,0567 0,0179 0,0031 -0,0013 Concentration (mg/l) 25,48 11,42 6,10 2,63 0,67 -0,08 -0,30 Ln (C 0 /C) 0,0000 0,8025 1,4294 2,2723 3,6434 - - 0,0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1,0 200 300 400 500 600 700 Absorbance Wavelength (nm) Spectrum - Neutral DY50 S1_Time0min S2_Time15min S3_Time30min S4_Time45min S5_Time60min S6_Time75min S7_Time90min y = 0,0496x + 0,0095 R² = 0,9971 0,00 0,40 0,80 1,20 1,60 2,00 2,40 0 10 20 30 40 50 Ln Co/C Time (min) Ln Co/C vs Time (Pseudo - first order kinetics) 103 HYDROLYSED DY50 AT PH = 6 SAMPLE S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 Time (min) 0 60 120 180 240 300 360 420 480 1440 Absorbance at λ máx 0,415 0,286 0,239 0,193 0,150 0,115 0,117 0,094 0,069 0,005 Concentration (mg/l) 20,72 14,22 11,82 9,53 7,36 5,55 5,67 4,52 3,23 0,04 Ln (C 0 /C) 0,000 0,377 0,561 0,777 1,035 1,317 1,296 1,522 1,859 6,373 0,0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1,0 200 300 400 500 600 700 Absorbance Wavelength (nm) Spectrum - Hydroluysed DY50 at pH = 6 S1_Time0min S2_Time60min S3_Time120min S4_Time180min S5_Time240min S6_Time300min S7_Time360min S8_Time420min S9_Time480min S10_Time1440min y = 0,0042x + 0,0509 R² = 0,9914 0,00 0,40 0,80 1,20 1,60 0 50 100 150 200 250 300 350 Ln Co/C Time (min) Ln Co/C vs Time (Pseudo - first order kinetics) 104 HYDROLYSED DY50 AT PH = 7 SAMPLE S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 Time (min) 0 60 120 180 240 300 360 420 480 1440 Absorbance at λ máx 0,397 0,334 0,279 0,244 0,209 0,179 0,156 0,116 0,117 0,009 Concentration (mg/l) 19,82 16,65 13,83 12,08 10,33 8,81 7,64 5,66 5,67 0,23 Ln (C 0 /C) 0,000 0,174 0,359 0,495 0,651 0,810 0,953 1,253 1,251 4,446 0,0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1,0 200 300 400 500 600 700 Absorbance Wavelength (nm) Spectrum - Hydrolysed DY50 at pH = 7 S1_Time0min S2_Time60min S3_Time120min S4_Time180min S5_Time240min S6_Time300min S7_Time360min S8_Time420min S9_Time480min S10_Time1440min y = 0,0027x + 0,0139 R² = 0,9981 0,00 0,40 0,80 1,20 0 50 100 150 200 250 300 350 Ln Co/C Time (min) Ln Co/C vs Time (Pseudo - first order kinetics) 105 HYDROLYSED DY50 AT PH = 8 SAMPLE S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 Time (min) 0 60 120 180 240 300 360 420 480 1440 Absorbance at λ máx 0,428 0,329 0,274 0,235 0,198 0,162 0,139 0,116 0,095 0,006 Concentration (mg/l) 21,38 16,36 13,58 11,61 9,74 7,95 6,78 5,63 4,56 0,07 Ln (C 0 /C) 0,000 0,268 0,454 0,611 0,787 0,989 1,149 1,335 1,546 5,712 0,0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1,0 200 300 400 500 600 700 Absorbance Wavelength (nm) Spectrum - Hydrolysed DY50 at pH = 8 S1_Time0min S2_Time60min S3_Time120min S4_Time180min S5_Time240min S6_Time300min S7_Time360min S8_Time420min S9_Time480min S10_Time1440min y = 0,0031x + 0,0496 R² = 0,9974 0,00 0,40 0,80 1,20 1,60 2,00 0 100 200 300 400 500 600 Ln Co/C Time (min) Ln Co/C vs Time (Pseudo - first order kinetics) 106 SIMULATED DYEHOUSE EFFLUENT DY50 AT PH = 6 SAMPLE S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 Time (min) 0 60 120 180 240 300 360 420 480 1440 Absorbance at λ máx 0,505 0,444 0,399 0,349 0,299 0,265 0,239 0,176 0,168 0,013 Concentration (mg/l) 25,28 22,18 19,90 17,43 14,84 13,17 11,83 8,66 8,23 0,43 Ln (C 0 /C) 0,000 0,131 0,239 0,372 0,532 0,652 0,759 1,071 1,123 4,064 0,0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1,0 200 300 400 500 600 700 Absorbance Wavelength (nm) Spectrum - Simulated Dyehouse Effluent DY50 at pH = 6 S1_Time0min S2_Time60min S3_Time120min S4_Time180min S5_Time240min S6_Time300min S7_Time360min S8_Time420min S9_Time480min S10_Time1440min y = 0,0022x - 0,0074 R² = 0,9974 0,00 0,20 0,40 0,60 0,80 0 50 100 150 200 250 300 350 Ln Co/C Time (min) Ln Co/C vs Time (Pseudo - first order kinetics) 113 HYDROLYSED DR81 AT PH = 7 SAMPLE S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 Time (min) 0 30 60 90 120 150 180 210 240 270 Absorbance at λ máx 1,199 1,090 0,987 0,903 0,822 0,745 0,690 0,595 0,548 0,528 Concentration (mg/l) 26,20 23,80 21,55 19,69 17,92 16,24 15,04 12,94 11,92 11,48 Ln (C 0 /C) 0,000 0,096 0,196 0,286 0,380 0,478 0,555 0,705 0,787 0,825 0,0 0,2 0,4 0,6 0,8 1,0 1,2 1,4 200 300 400 500 600 700 Absorbance Wavelength (nm) Spectrum - Hydrolysed DR81at pH = 7 S1_Time0min S2_Time30min S3_Time60min S4_Time90min S5_Time120min S6_Time150min S7_Time180min S8_Time210min S9_Time240min S10_Time270min S11_Time300min S12_Time1440min y = 0,0033x - 0,0059 R² = 0,9946 0,00 0,40 0,80 1,20 1,60 2,00 0 50 100 150 200 250 300 350 Ln Co/C Time (min) Ln Co/C vs Time (Pseudo-first order kinetics) 114 HYDROLYSED DR81 AT PH = 8 SAMPLE S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 Time (min) 0 60 120 180 240 300 360 420 480 1440 Absorbance at λ máx 1,058 0,883 0,762 0,685 0,612 0,571 0,517 0,464 0,421 0,061 Concentration (mg/l) 23,09 19,27 16,62 14,92 13,31 12,42 11,23 10,08 9,12 1,23 Ln (C 0 /C) 0,000 0,181 0,329 0,437 0,551 0,620 0,721 0,829 0,929 2,936 0,0 0,2 0,4 0,6 0,8 1,0 1,2 1,4 200 300 400 500 600 700 Absorbance Wavelength (nm) Spectrum - Hydrolysed DR81 at pH = 8 S1_Time0min S2_Time60min S3_Time120min S4_Time180min S5_Time240min S6_Time300min S7_Time360min S8_Time420min S9_Time480min S10_Time1440min y = 0,0018x + 0,069 R² = 0,9864 0,00 0,40 0,80 1,20 1,60 2,00 0 100 200 300 400 500 600 Ln Co/C Time (min) Ln Co/C vs Time (Pseudo-first order kinetics) 115 SIMULATED DYEHOUSE EFFLUENT DR81 AT PH = 6 SAMPLE S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 Time (min) 0 60 120 180 240 300 360 420 480 1420 Absorbance at λ máx 1,128 1,016 0,941 0,882 0,819 0,777 0,724 0,655 0,588 0,147 Concentration (mg/l) 24,63 22,19 20,53 19,24 17,86 16,94 15,79 14,27 12,80 3,12 Ln (C 0 /C) 0,000 0,104 0,182 0,247 0,321 0,374 0,445 0,546 0,654 2,066 0,0 0,2 0,4 0,6 0,8 1,0 1,2 1,4 200 300 400 500 600 700 Absorbance Wavelength (nm) Spectrum - Simulated Dyehouse Effluent DR81 at pH = 6 S1_Time0min S2_Time60min S3_Time120min S4_Time180min S5_Time240min S6_Time300min S7_Time360min S8_Time420min S9_Time480min S10_Time1440min y = 0,0014x + 0,0106 R² = 0,9883 0,00 0,20 0,40 0 50 100 150 200 Ln Co/C Time (min) Ln Co/C vs Time (Pseudo-first order kinetics) 116 SIMULATED DYEHOUSE EFFLUENT DR81 AT PH = 8 SAMPLE S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 Time (min) 0 60 120 180 240 300 360 420 480 1440 Absorbance at λ máx 1,084 0,989 0,937 0,864 0,803 0,731 0,689 0,636 0,597 0,195 Concentration (mg/l) 23,67 21,59 20,44 18,85 17,50 15,94 15,02 13,84 12,99 4,18 Ln (C 0 /C) 0,000 0,092 0,147 0,228 0,302 0,395 0,455 0,537 0,600 1,734 0,0 0,2 0,4 0,6 0,8 1,0 1,2 1,4 200 300 400 500 600 700 Absorbance Wavelength (nm) Spectrum - Simulated Dyehouse Effluent DR81 at pH = 8 S1_Time0min S2_Time60min S3_Time120min S4_Time180min S5_Time240min S6_Time300min S7_Time360min S8_Time420min S9_Time480min S10_Time1440min y = 0,0013x + 0,0049 R² = 0,9984 0,00 0,20 0,40 0,60 0,80 1,00 0 100 200 300 400 500 600 Ln Co/C Time (min) Ln Co/C vs Time (Pseudo-first order kinetics) 117 DIRECT VIOLET 51 NEUTRAL DV51 SAMPLE S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 Time (min) 0 30 60 90 150 180 210 270 330 400 1320 Absorbance at λ máx 1,023 0,394 0,196 0,070 0,017 0,008 0,001 0,001 0,006 0,004 -0,004 Concentration (mg/l) 21,40 7,68 3,38 0,64 -0,53 -0,73 -0,88 -0,87 -0,76 -0,79 -0,97 Ln (C 0 /C) 0,000 1,024 1,846 3,512 - - - - - - - 0,0 0,2 0,4 0,6 0,8 1,0 1,2 200 300 400 500 600 700 Absorbance Wavelength (nm) Spectrum - Neutral DV51 S1_Time0min S2_Time30min S3_Time60min S4_Time90min S5_Time150min S6_Time180min S7_Time210min S8_Time270min S9_Time330min S10_Time400min S11_Time1320min y = 0,0308x + 0,0338 R² = 0,996 0,00 0,50 1,00 1,50 2,00 0 10 20 30 40 50 60 70 Ln Co/C Time (min) Ln Co/C vs Time (Pseudofirst order kinetics) 118 HYDROLYSED DV51 AT PH = 5,5 SAMPLE S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 Time (min) 0 30 60 120 180 240 300 360 420 480 510 1440 Absorbance at λ máx 1,033 0,569 0,431 0,298 0,217 0,178 0,143 0,102 0,099 0,077 0,059 0,006 Concentration (mg/l) 23,07 13,09 10,11 7,27 5,52 4,68 3,93 3,05 2,97 2,51 2,14 0,98 Ln (C 0 /C) 0,000 0,567 0,825 1,155 1,430 1,594 1,769 2,0243 2,049 2,218 2,378 3,160 0,0 0,2 0,4 0,6 0,8 1,0 1,2 1,4 1,6 1,8 200 300 400 500 600 700 Absorbance Wavelength (nm) Spectrum - Hydrolysed DV51 at pH = 5,5 S1_Time0min S2_Time30min S3_Time60min S4_Time120min S5_Time180min S6_Time240min S7_Time300min S8_Time360min S9_Time420min S10_Time480min S11_Time510min S12_Time1440min y = 0,0137x + 0,0515 R² = 0,9553 0,00 0,50 1,00 0 10 20 30 40 50 60 70 Ln Co/C Time (min) Ln Co/C vs Time (Pseudo - first order kinetics) 119 HYDROLYSED DV51 AT PH = 6 SAMPLE S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 Time (min) 0 60 120 180 240 300 360 420 480 1440 Absorbance at λ máx 0,9741 0,5202 0,3921 0,3259 0,2679 0,2421 0,1897 0,1599 0,1493 0,0295 Concentration (mg/l) 21,80 12,04 9,29 7,86 6,62 6,06 4,93 4,29 4,06 1,49 Ln (C 0 /C) 0,0000 0,5937 0,8535 1,0199 1,1927 1,2803 1,4860 1,6251 1,6797 2,6845 0,0 0,2 0,4 0,6 0,8 1,0 1,2 1,4 200 300 400 500 600 700 Absorbance Wavelength (nm) Spectrum - Hydrolysed DV51 at pH = 6 S1_Time0min S2_Time60min S3_Time120min S4_Time180min S5_Time240min S6_Time300min S7_Time360min S8_Time420min S9_Time480min S10_Time1440min y = 0,0071x + 0,0557 R² = 0,9515 0,00 0,40 0,80 1,20 0 20 40 60 80 100 120 140 Ln Co/C Time (min) Ln Co/C vs Time (Pseudo - first order kinetics) HYDROLYSED DV51 SAMPLE S1 S2 Time (min) 0 60 Absorbance at λ máx 0,995 0,610 Concentration (mg/l) 22,25 13,97 Ln (C 0 /C) 0,000 0,465 0,0 0,2 0,4 0,6 0,8 1,0 1,2 1,4 200 300 Absorbance 0,00 0,40 0,80 1,20 0 Absorbance Ln Co/C vs Time (Pseudo 120 DV51 AT PH = 7 S3 S4 S5 S6 S7 S8 120 180 240 300 360 420 0,453 0,350 0,301 0,243 0,209 0,174 10,59 8,37 7,32 6,09 5,35 4,60 0,743 0,978 1,112 1,296 1,423 1,576 400 500 600 700 Wavelength (nm) Spectrum - Hydrolysed DV51 at pH = 7 y = 0,0053x + 0,0649 R² = 0,9729 50 100 150 Time (min) Ln Co/C vs Time (Pseudo - first order kinetics) S9 S10 480 1440 0,143 0,022 3,92 1,32 1,737 2,828 S1_Time0min S2_Time60min S3_Time120min S4_Time180min S5_Time240min S6_Time300min S7_Time360min S8_Time420min S9_Time480min S10_Time1440min y = 0,0053x + 0,0649 200 121 HYDROLYSED DV51 AT PH = 8 SAMPLE S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 Time (min) 0 60 120 180 240 300 360 420 480 1440 Absorbance at λ máx 1,003 0,614 0,503 0,434 0,376 0,337 0,292 0,245 0,229 0,087 Concentration (mg/l) 22,43 14,05 11,68 10,18 8,94 8,11 7,13 6,12 5,77 2,73 Ln (C 0 /C) 0,000 0,468 0,653 0,790 0,920 1,018 1,146 1,299 1,357 2,107 0,0 0,2 0,4 0,6 0,8 1,0 1,2 1,4 200 300 400 500 600 700 Absorbance Wavelength (nm) Spectrum - Hydrolysed DV51 at pH = 8 S1_Time0min S2_Time60min S3_Time120min S4_Time180min S5_Time240min S6_Time300min S7_Time360min S8_Time420min S9_Time480min S10_Time1440min y = 0,0043x + 0,0943 R² = 0,9157 0,00 0,20 0,40 0,60 0,80 1,00 0 50 100 150 200 Ln Co/C Time (min) Ln Co/C vs Time (Pseudo - first order kinetics) 122 SIMULATED DYEHOUSE EFFLUENT DV51 AT PH = 6 SAMPLE S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 Time (min) 0 60 120 180 240 300 360 420 480 1440 Absorbance at λ máx 1,108 0,733 0,629 0,520 0,459 0,411 0,360 0,329 0,286 0,056 Concentration (mg/l) 24,69 16,61 14,40 12,05 10,74 9,69 8,60 7,94 7,01 2,06 Ln (C 0 /C) 0,000 0,396 0,539 0,718 0,833 0,935 1,054 1,134 1,259 2,484 0,0 0,2 0,4 0,6 0,8 1,0 1,2 1,4 200 300 400 500 600 700 Absorbance Wavelength (nm) Spectrum - Simulated Dyehouse Effluent DV51 at pH = 6 S1_Time0min S2_Time60min S3_Time120min S4_Time180min S5_Time240min S6_Time300min S7_Time360min S8_Time420min S9_Time480min S10_Time1440min y = 0,0033x + 0,0997 R² = 0,9392 0,00 0,40 0,80 1,20 0 50 100 150 200 250 300 Ln Co/C Time (min) Ln Co/C vs Time (Pseudo - first order kinetics) 129 HYDROLYSED DR23 AT PH = 8 SAMPLE S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 Time (min) 0 60 120 180 240 300 360 420 480 1440 Absorbance at λ máx 0,753 0,461 0,323 0,222 0,167 0,118 0,087 0,062 0,054 0,017 Concentration (mg/l) 23,39 14,27 9,95 6,79 5,08 3,53 2,59 1,80 1,54 0,38 Ln (C 0 /C) 0,000 0,494 0,855 1,237 1,527 1,891 2,202 2,566 2,720 4,117 0,0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1,0 200 300 400 500 600 700 Absorbance Wavelength (nm) Spectrum - Hydrolysed DR23 at pH = 7 S1_Time0min S2_Time60min S3_Time120min S4_Time180min S5_Time240min S6_Time300min S7_Time360min S8_Time420min S9_Time480min S10_Time1440min y = 0,006x + 0,0933 R² = 0,9948 0,00 0,50 1,00 1,50 2,00 2,50 3,00 0 50 100 150 200 250 300 350 400 Ln Co/C Time (min) Ln Co/C vs Time (Pseudo-first order kinetics) 130 SIMULATED DYEHOUSE EFFLUENT DR23 AT PH = 6 SAMPLE S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 Time (min) Absorbance at λ máx Concentration (mg/l) Ln (C 0 /C) 0,0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 200 300 400 500 600 700 Absorbance Wavelength (nm) Spectrum - Simulated Dyehouse Effluent DR23 at pH = 6 S1_Time0min S2_Time60min S3_Time120min S4_Time180min S5_Time240min S6_Time300min S7_Time360min S8_Time420min S9_Time480min S10_Time1440min y = 0,0024x - 0,0045 R² = 0,9968 0,00 0,40 0,80 1,20 1,60 0 100 200 300 400 500 600 Ln Co/C Time (min) Ln Co/C vs Time (Pseudo-first order kinetics) 131 SIMULATED DYEHOUSE EFFLUENT DR23 AT PH = 7 SAMPLE S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 Time (min) 0 60 120 180 240 300 360 420 480 1440 Absorbance at λ máx 0,829 0,705 0,638 0,557 0,501 0,450 0,414 0,360 0,313 0,047 Concentration (mg/l) 25,78 21,89 19,78 17,27 15,50 13,92 12,79 11,11 9,62 1,31 Ln (C 0 /C) 0,000 0,163 0,265 0,400 0,509 0,616 0,701 0,841 0,985 2,979 0,0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1,0 200 300 400 500 600 700 Absorbance Wavelength (nm) Spectrum - Simulated Dyehouse Effluent DR23 at pH = 7 S1_Time0min S2_Time60min S3_Time120min S4_Time180min S5_Time240min S6_Time300min S7_Time360min S8_Time420min S9_Time480min S10_Time1440min y = 0,002x + 0,0269 R² = 0,9964 0,00 0,40 0,80 1,20 0 100 200 300 400 500 600 Ln Co/C Time (min) Ln Co/C vs Time (Pseudo-first order kinetics) 132 SIMULATED DYEHOUSE EFFLUENT DR23 AT PH = 8 SAMPLE S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 Time (min) 0 60 120 180 240 300 360 420 480 1440 Absorbance at λ máx 0,826 0,725 0,656 0,609 0,559 0,519 0,483 0,437 0,388 0,110 Concentration (mg/l) 25,68 22,52 20,36 18,88 17,34 16,09 14,94 13,51 11,98 3,29 Ln (C 0 /C) 0,000 0,131 0,232 0,307 0,393 0,468 0,542 0,642 0,762 2,054 0,0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1,0 200 300 400 500 600 700 Absorbance Wavelength (nm) Spectrum - Simulated Dyehouse Effluent DR23 at pH = 8 S1_Time0min S2_Time60min S3_Time120min S4_Time180min S5_Time240min S6_Time300min S7_Time360min S8_Time420min S9_Time480min S10_Time1440min y = 0,0015x + 0,0289 R² = 0,9941 0,00 0,20 0,40 0,60 0,80 1,00 0 100 200 300 400 500 600 Ln Co/C Time (min) Ln Co/C vs Time (Pseudo-first order kinetics) 133 LIGHT SIMULATED DYEHOUSE EFFLUENT DR23 AT PH = 7 SAMPLE S1 S2 S3 S4 S5 S6 S7 S8 S9 Time (min) 0 60 120 180 240 300 360 420 480 Absorbance at λ máx 0,799 0,631 0,509 0,427 0,343 0,293 0,287 0,278 0,291 Concentration (mg/l) 24,83 19,57 15,76 13,21 10,57 9,00 8,83 8,54 8,93 Ln (C 0 /C) 0,000 0,238 0,455 0,631 0,854 1,015 1,034 1,068 1,022 0,0 0,2 0,4 0,6 0,8 1,0 1,2 200 300 400 500 600 700 Absorbance Wavelength (nm) Spectrum - Simulated Light Dyehouse Effluent DR23 at pH = 7 S1_Time0min S2_Time60min S3_Time120min S4_Time180min S5_Time240min S6_Time300min S7_Time360min S8_Time420min S9_Time480min y = 0,0034x + 0,0251 R² = 0,9969 0,00 1,00 2,00 0 50 100 150 200 250 300 350 Ln Co/C Time (min) Ln Co/C vs Time (Pseudo-first order kinetics) 134 ANNEX V: Kinetic results DYE NAME k app (min -1 ) % ADSORPTION DY50 DY50 0,0496 100 DY50H at pH = 6 0,0042 99,83 DY50H at pH = 7 0,0027 98,83 DY50H at pH = 8 0,0031 99,67 DY50SDE at pH = 6 0,0022 98,28 DY50SDE at pH = 7 (Test 1) 0,0017 98,19 DY50SDE at pH = 7 (Test 2) 0,0024 100 DY50SDE at pH = 8 0,0019 93,27 DR81 DR81 0,0421 100 DR81H at pH = 5,5 0,0092 99,39 DR81H at pH = 6 0,0068 98,74 DR81H at pH = 7 0,0033 91,49 DR81H at pH = 8 0,0018 94,69 DR81SDE at pH = 6 0,0014 87,32 DR81SDE at pH = 8 0,0013 82,34 DV51 DV51 0,0308 100 DV51H at pH = 5,5 0,0137 95,76 DV51H at pH = 6 0,0071 93,17 DV51H at pH = 7 0,0053 94,08 DV51H at pH = 8 0,0043 87,63 DV51SDE at pH = 6 0,0033 91,65 DV51SDE at pH = 7 0,0031 82,13 DV51SDE at pH = 8 (Test 1) 0,0023 79,77 DV51SDE at pH = 8 (Test 2) 0,0022 78,05 DR23 DR23 0,022 100 DR23H at pH = 6 0,0137 100 DR23H at pH = 7 0,0093 99,08 DR23H at pH = 8 0,0066 98,37 DR23SLDE at pH = 7 0,0033 98,5 DR23SDE at pH = 6 0,0024 97,24 DR23SDE at pH = 7 0,0022 94,92 DR23SDE at pH = 8 0,0017 87,17 135 ANNEX VI: COT Results DYE NAME TOC INITIAL (mg/l) TOC FINAL (mg/l) % TOC Removal DY50 DY50 4,821 1,648 65,82 DY50H at pH = 6 5,018 1,358 72,94 DY50H at pH = 7 4,932 3,831 22,32 DY50H at pH = 8 5,100 4,586 10,08 DY50SDE at pH = 6 5,211 1,205 76,88 DY50SDE at pH = 7 (Test 1) 4,358 3,606 85,93 DY50SDE at pH = 7 (Test 2) 5,669 1,330 76,54 DY50SDE at pH = 8 5,660 2,610 53,89 DR81 DR81 7,320 2,726 62,76 DR81H at pH = 5,5 8,569 0,399 95,34 DR81H at pH = 6 8,079 1,392 82,77 DR81H at pH = 7 7,896 2,542 67,81 DR81H at pH = 8 6,961 3,363 51,69 DR81SDE at pH = 6 7,416 4,020 45,79 DR81SDE at pH = 8 7,918 5,736 27,56 DV51 DV51 4,431 1,342 69,71 DV51H at pH = 5,5 7,101 3,204 54,88 DV51H at pH = 6 6,912 2,196 68,23 DV51H at pH = 7 6,821 8,370 -22,71 DV51H at pH = 8 3,488 4,080 -16,97 DV51SDE at pH = 6 4,394 3,455 21,37 DV51SDE at pH = 7 3,006 5,647 -87,86 DV51SDE at pH = 8 (Test 1) 3,070 5,061 -64,85 DV51SDE at pH = 8 (Test 2) 3,533 5,379 -52,25 DR23 DR23 3,446 1,382 59,90 DR23H at pH = 6 5,612 1,020 81,82 DR23H at pH = 7 3,991 1,042 73,89 DR23H at pH = 8 5,130 2,024 60,55 DR23SLDE at pH = 7 4,879 1,996 59,09 DR23SDE at pH = 6 4,709 2,511 46,68 DR23SDE at pH = 7 5,268 2,556 51,48 DR23SDE at pH = 8 4,902 3,837 21,73 136 ANNEX VII: Ammonium and nitrates results DYE NAME AMMONIUM (μmol/l) NITRATES (μmol/l) TOTAL IONS(μmol/l) EXPECTED IONS(μmol/l) DR23 DR23 5,36 7,85 13,21 92,16 DR23H at pH = 6 9,21 4,42 13,63 92,16 DR23H at pH = 7 3,14 3,14 92,16 DR23H at pH = 8 4,66 4,66 92,16 DR23SLDE at pH = 7 13,33 13,33 92,16 DR23SDE at pH = 6 6,48 6,48 92,16 DR23SDE at pH = 7 6,88 6,88 92,16 DR23SDE at pH = 8 10,78 10,78 92,16 DV51 DV51 13,76 8,89 22,64 34,70 DV51H at pH = 5,5 19,12 10,78 29,90 34,70 DV51H at pH = 6 4,46 6,43 10,90 34,70 DV51H at pH = 7 11,59 5,73 17,31 34,70 DV51H at pH = 8 36,88 36,88 34,70 DV51SDE at pH = 6 11,99 11,99 34,70 DV51SDE at pH = 7 42,44 42,44 34,70 DV51SDE at pH = 8 (Test 1) 35,97 35,97 34,70 DV51SDE at pH = 8 (Test 2) 37,63 37,63 34,70 DY50 DY50 1,88 10,04 11,92 52,26 DY50H at pH = 6 2,11 4,86 6,97 52,26 DY50H at pH = 7 2,33 6,03 8,36 52,26 DY50H at pH = 8 1,72 9,39 11,11 52,26 DY50SDE at pH = 6 0,94 0,94 52,26 DY50SDE at pH = 7 (Test 1) 2,11 2,11 52,26 DY50SDE at pH = 7 (Test 2) 2,48 2,48 52,26 DY50SDE at pH = 8 2,37 2,37 52,26 DR81 DR81 1,44 8,77 10,21 37,00 DR81H at pH = 5,5 5,17 5,17 37,00 DR81H at pH = 6 1,92 1,92 37,00 DR81H at pH = 7 5,93 5,93 37,00 DR81H at pH = 8 10,02 10,02 37,00 DR81SDE at pH = 6 22,94 22,94 37,00 DR81SDE at pH = 8 45,88 45,88 37,00