Removal of Dyes from Contaminated Water Using Low Cost Adsorbents Thesis

REMOVAL OF DYES FROM CONTAMINATED WATER USING LOW COST ADSORBENTS

THESIS

SUBMITTED FOR THE AWARD OF THE DEGREE OF

Doctor of Philosophy IN APPLIED CHEMISTRY

BY SADIA SHAKOOR

UNDER THE SUPERVISION OF DR ABU NASAR

DEPARTMENT OF APPLIED CHEMISTRY ZAKIR HUSSAIN COLLEGE OF ENGINEERING AND TECHNOLOGY ALIGARH MUSLIM UNIVERSITY ALIGARH (INDIA)

2016 DEPARTMENT OF APPLIED CHEMISTRY FACULTY OF ENGINEERING AND TECHNOLOGY ALIGARH MUSLIM UNIVERSITY, ALIGARH-202002 (U.P.) INDIA

Dr. Abu Nasar Telephones Off. : (0571) 2700920-23 Ext: 3002 Ph.D University Fax : (0571) 2700528 Associate Professor E-mail : [email protected] Mob. : +91-9415842475

CERTIFICATE

This is to certify that the thesis entitled “Removal of dyes from contaminated water using low cost adsorbents” is the original contribution of Ms. Sadia Shakoor carried out under my supervision and is suitable for the award of the degree of Doctor of Philosophy in Applied Chemistry from Aligarh Muslim University, Aligarh. This work has neither been submitted nor is being submitted for any other degree.

Dr. Abu Nasar (Supervisor)

Annexure I CANDIDATE’S DECLARATION

I, Sadia Shakoor, Department of Applied Chemistry certify that the work embodied in this Ph.D thesis is my own bonafide work carried out by me under the supervision of Dr. Abu Nasar at Department of Applied Chemistry, Aligarh Muslim University, Aligarh. The matter embodied in this Ph.D thesis has not been submitted for the award of any other degree. I declare that I have faithfully acknowledged, given credit to and referred to the research workers wherever their works have been cited in the text and the body of the thesis. I further certify that I have not wilfully lifted up some other’s work, plan, text, data, result etc. reported in the journals, books, magazines, reports, dissertations, thesis etc., or available at web-sites and included them in this thesis and cited as my own work.

Dated: (Sadia Shakoor)

Annexure II

CERTIFICATE FROM SUPERVISOR

This is to certify that the above statement made by the candidate is correct to the best of my knowledge.

Signature of the Supervisor

Name & designation: Dr. Abu Nasar, Associate Professor

Department: Applied Chemistry

(Signature of the Chairman of the Department with seal)

DEPARTMENT OF APPLIED CHEMISTRY FACULTY OF ENGINEERING AND TECHNOLOGY ALIGARH MUSLIM UNIVERSITY, ALIGARH-202002 (U.P.) INDIA

CHAIRMAN Telephones Off. : (0571) 2700920-23 Extn. : 3000, 3001 University Fax : (0571) 2700528

COURSE/ COMPREHENSIVE EXAMINATION/ PRE-SUBMISSION

SEMINAR COMPLETION CERTIFICATE

This is to certify that Ms. Sadia Shakoor, Department of Applied Chemistry has satisfactorily completed the coursework/comprehensive examination and pre-submission seminar requirement which is part of her Ph.D programme.

Date: Signature of the Chairman of the Department

III

Annexure III

Title of the Thesis: Removal of dyes from contaminated water using low cost adsorbents

Candidate’s Name: Sadia Shakoor

The undersigned hereby assigns to the Aligarh Muslim University, Aligarh copyright that may exist in and for the above thesis submitted for the award of the Ph.D degree.

(Signature of the candidate)

Dedicated

to my parents

Mr. Abdul Shakoor and Mrs. Saeeda Shakoor

ACKNOWLEDGEMENTS

All the praises be to Allah for His immense blessings that He bestowed upon me and gave me the strength and determination to complete my work successfully.

I express my sincere thanks to my supervisor, Dr. Abu Nasar,

Department of Applied Chemistry, for his guidance, suggestions, support and continuous encouragement throughout my PhD work.

I also express my gratitude to Dr. Rifaqat Ali Khan Rao,

Chairman, Department of Applied Chemistry, for providing the necessary facilities to carry out the experimental work.

I sincerely express my heartfelt gratitude to Prof. Ali

Mohammad, for his valuable suggestion, cooperation and constant encouragement during the entire course of study.

It gives me pleasure to extend my sincere thanks to all the members of Teaching and Non-teaching staff of the Department of

Applied Chemistry for their cooperation and help.

I would like to thank all my seniors and lab colleagues Dr.

Nazia Iqbal, Mrs. Samiksha, Mr. Kashif Raees and Mr. Mohd Shaban

Ansari for their help and support during study.

Finally, I reserve my affectionate appreciation to my beloved parents (Mr. Abdul Shakoor and Mrs. Saeeda Shakoor), brothers

(Mohd Shuaib and Mohd. Swaleh), sister-in-law (Rehana Sheikh) and fiancé (Dr. M. Shahnawaz Khan) for their blessings, support and encouragement throughout my work. They have been a constant source of inspiration and motivation for me and have always spurred me towards excellence.

SADIA SHAKOOR

VII

CONTENTS

Page No.

 SUPERVISOR’S CERTIFICATE I  CANDIDATE’S DECLARATION AND CERTIFICATE FROM II SUPREVISOR  COURSE/ COMPREHENSIVE EXAMINATION/ PRE-SUBMISSION III SEMINAR COMPLETION CERTIFICATE  COPYRIGHT TRANSFER CERTIFICATE IV  DEDICATION V  ACKNOWLEDGEMENTS VI  CONTENTS VIII  ABSTRACT XIV  LIST OF TABLES XIX  LIST OF FIGURES XXII

Chapter 1 General introduction 1.1. Introduction 1 1.2. Forms of Environmental pollution 2 1.2.1. Air pollution 2 1.2.2. Water pollution 4 1.2.3. Soil pollution 4 1.2.4. Noise pollution 4 1.3. Water pollution 5 1.3.1. Sources of water pollution 5 1.3.2. Classification of water pollutants 6 1.4. Wastewater treatment 13 1.4.1. Preliminary treatment 13 1.4.2. Primary treatment 13 1.4.3. Secondary treatment 14

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1.4.4. Tertiary treatment 15 1.5. Dyes 17 1.5.1. Classification of dyes 17 1.5.2. Dyes as a source of colour contaminant in water 22 1.5.3. Harmful effects of dyes 22 1.5.4. Methylene blue 23 1.5.4.1. Uses of Methylene blue 23 1.5.4.2. Harmful effects of methylene blue 24 1.5.5. Crystal violet 24 1.5.5.1. Uses of crystal violet 25 1.5.5.2. Harmful effects of crystal violet 25 1.6. Techniques available for removal of dyes from wastewater 25 1.6.1. Biological treatment 26 1.6.2. Chemical treatment 26 1.6.3. Physical treatment 26 1.7. Adsorption 27 1.7.1. Types of adsorption 27 1.7.2. Factors affecting adsorption 28 1.8. Selection of adsorbent 29 1.9. Citrus limetta 35 1.9.1. Plant description 36 1.9.2. Uses 37 1.10. Punica granatum 37 1.10.1. Plant description 38 1.10.2. Uses 39 1.11. Cucumis sativus 39 1.11.1. Plant description 40 1.11.2. Uses 41 1.12. Terminalia arjuna 41 1.12.1. Plant description 41 1.12.2. Uses 42 1.13. Statement of the problem 44 References 46

Chapter 2 Materials and methods 2.1. Chemicals and reagents 56 2.2. Raw materials for adsorbent 56 2.3. Preparation of adsorbent 56 2.4. Characterization of adsorbents 57 2.4.1. Scanning Electron Microscopy 57 2.4.2. Fourier Transform Infra-Red Spectrophotometry 57 2.5. Batch adsorption studies 57 2.5.1. Effect of adsorbent dosage 58 2.5.2. Effect of contact time and initial dye concentration 58 2.5.3. Effect of pH 59 2.5.4. Point of zero charge 59 2.5.5. Effect of particle size 60 2.6. Adsorption isotherms 60 2.6.1. Langmuir adsorption isotherm 60 2.6.2. Freundlich adsorption isotherm 61 2.6.3. Temkin adsorption isotherm 62 2.6.4. Dubinin-Radushkevich (D-R) isotherm 62 2.7. Adsorption kinetics 63 2.7.1. Pseudo-first order kinetic model 63 2.7.2. Pseudo-second order kinetic model 63 2.7.3. Intraparticle diffusion model 63 2.7.4. Elovich model 64 2.8. Thermodynamic studies 64 2.9. Desorption 65 References 66

Chapter 3 Utilisation of Citrus limetta peel for the removal of methylene blue

and crystal violet dyes from aqueous solution

3.1. Introduction 68 3.2. Experimental 70 3.3. Results and discussion 71 3.3.1. Material characterisation 71 3.3.2. Effect of contact time and initial dye concentration 77 3.3.3. Effect of adsorbent dosage 80 3.3.4. Effect of pH 83 3.3.5. Point of zero charge 85 3.3.6. Effect of particle size 86 3.3.7. Adsorption isotherms 87 3.3.8. Adsorption kinetics 92 3.3.9. Adsorption thermodynamics 97 3.3.10. Desorption 101 3.4. Conclusions 102 References 103

Chapter 4 Utilisation of Punica granatum peels for the removal of methylene blue and crystal violet dyes from aqueous solution

4.1. Introduction 110 4.2. Experimental 111 4.3. Results and discussion 112 4.3.1. Material characterisation 112 4.3.2. Effect of contact time and initial dye concentration 118 4.3.3. Effect of adsorbent dosage 121 4.3.4. Effect of pH 124

4.3.5. Point of zero charge 127 4.3.6. Effect of particle size 128 4.3.7. Adsorption isotherms 129 4.3.8. Adsorption kinetics 133 4.3.9. Adsorption thermodynamics 139 4.3.10. Desorption 143 4.4. Conclusions 144 References 145

Chapter 5 Utilisation of Cucumis sativus peels for the removal of methylene blue and crystal violet dyes from aqueous solution

5.1. Introduction 151 5.2. Experimental 152 5.3. Results and discussion 153 5.3.1. Material characterisation 153 5.3.2. Effect of contact time and initial dye concentration 159 5.3.3. Effect of adsorbent dosage 162 5.3.4. Effect of pH 165 5.3.5. Point of zero charge 167 5.3.6. Effect of particle size 168 5.3.7. Adsorption isotherms 169 5.3.8. Adsorption kinetics 174 5.3.9. Adsorption thermodynamics 179 5.3.10. Desorption 183 5.4. Conclusions 184 References 185

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Chapter 6 Utilisation of Terminalia arjuna sawdust for the removal of methylene blue and crystal violet dyes from aqueous solution

6.1. Introduction 190 6.2. Experimental 191 6.3. Results and discussion 192 6.3.1. Material characterisation 192 6.3.2. Effect of contact time and initial dye concentration 198 6.3.3. Effect of adsorbent dosage 201 6.3.4. Effect of pH 204 6.3.5. Point of zero charge 207 6.3.6. Effect of particle size 208 6.3.7. Adsorption isotherms 209 6.3.8. Adsorption kinetics 214 6.3.9. Adsorption thermodynamics 220 6.3.10. Desorption 224 6.4. Conclusions 225 References 226

Appendices Appendix I List of publications 231 Appendix II List of papers presented at conferences 232 Appendix III Reprint of published paper 233

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ABSTRACT

Water pollution has become a plague in our modern society. Rapid increase in industrialisation has resulted in the generation of a variety of toxic pollutants such as detergents, acids, agro-chemicals, heavy metals, dyes, etc. Dyes are an important class of pollutants which are extensively used in various industries like textiles, leather, paper and pulp, pharmaceuticals, paint, cosmetics, plastic, etc. The presence of dyes in water even in trace amounts can be easily recognised and is aesthetically undesirable. Dyes largely affect the photosynthetic activities of aquatic plants by reducing the transmission of sunlight into the water bodies. Moreover, many dyes are toxic and even carcinogenic thus affecting the aquatic biota and human health. Various methods such as adsorption, coagulation, advanced oxidation, ozonation, Fenton’s process, reverse osmosis and biological processes have been used for the removal of dyes from wastewater. Amongst them, adsorption is one of the most effective processes because of the various advantages associated with it such as ease of operation, simple design, avoidance of secondary pollution, low cost, economic feasibility, etc. In recent years, there has been increasing trend in using low cost adsorbents based on agricultural, industrial and domestic wastes. These include peanut hull, olive pomace, spent tea leaves, mango bark, rice husk, coffee husks, peanut husk, orange peel, banana peel, neem leaves, eggshells, lotus leaves, jujube seeds, rice husk, corn cobs, wheat straw, breadfruit, hazelnut shell, garlic peel, jackfruit peel, shaddock peel, cotton stalk, coconut bunch waste, palm kernel fiber, etc. The present work has been planned with the prime objective to utilize and study the effectiveness of four such low cost adsorbents, namely, Citrus limetta peel, Punica granatum peels, Cucumis sativus peels and Terminalia arjuna sawdust, for the removal of methylene blue and crystal violet dyes from artificially contaminated water.

Some of the salient features of the present thesis are:

 Characterisation of the adsorbents to understand their surface morphology, identification of the various functional groups present on its surface and recognition of the functional group involved in dye-adsorbent interaction  Optimisation of the various parameters affecting the adsorption process such as contact time, adsorbent dosage, particle size, pH and temperature  Isotherm and kinetic modeling to understand the nature of dye-adsorbent interaction  Thermodynamic studies to judge the feasibility of the process

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 Investigation of the regenerability of the used adsorbent to ensure its long term reusability to reduce the cost of the process as well as minimizing the disposal problems related to it

The research work presented in this thesis has been divided into six chapters.

Chapter 1 Chapter 1 deals with the basic information regarding pollution with special emphasis on water pollution. The classification of water pollutants has been discussed in detail. Brief description of various wastewater treatment techniques have been given in this chapter. General information about dyes including their classification, sources and harmful effects on living organisms has also been discussed. Specific and harmful effects of methylene blue and crystal violet dyes have been given in detail. This chapter also discusses the description of the various techniques available for the removal of dyes from wastewater with special emphasis on adsorption technique. A literature survey on the adsorptive removal of dyes from wastewater has also been included in his chapter. The chapter ends with the statement of problems which explain the importance of study.

Chapter 2 In this chapter, details of materials used and method employed in the present investigation have been described. The method of preparation of the adsorbents has been discussed. A brief account of the batch adsorption studies carried out in the present investigation has been given along with the experimental method employed to optimise the various parameters affecting the adsorption process. The mathematical equations used for the calculations of adsorption capacities and removal efficiencies of the adsorbents are also given in this chapter. A short description of the various isotherm and kinetic models used in the present work has also been provided. The method to study the regenerability of the used adsorbent in different media (acidic, basic and neutral) under the optimum conditions of adsorbent dose, pH and particle size has been described.

Chapter 3 In this chapter, the utilisation of Citrus limetta peel (CLP) as a low cost adsorbent for the removal of methylene blue (MB) and crystal violet (CV) dyes has been discussed. Batch adsorption studies were conducted to find out how adsorption was affected by various factors like contact time, initial dye concentration, adsorbent dosage, pH and temperature. The

XV experimental data was analysed in the light of Langmuir, Freundlich, Temkin and Dubinin- Radushkevich isotherm models. The data was found to be best represented by Langmuir isotherm for MB-CLP system and Temkin model for CV-CLP system. The data were analysed in the light of different available kinetic models and was observed to be best followed pseudo-second order kinetics for both the systems. Desorption of dye-loaded CLP was studied with various desorbing agents and HCl was found to be most effective desorbing agent among HCl, NaOH, NaCl, CH3COOH and deionised doubly distilled water (DDDW). Results suggest that CLP is a very effective low cost adsorbent for the removal of dyes from wastewater.

Chapter 4 Chapter 4 deals with the removal of MB and CV dyes by using Punica granatum peel (PGP) adsorbent. Batch adsorption studied were conducted to find out how adsorption was affected by different factors such as contact time, initial dye concentration, adsorbent doses, particle size of adsorbent, pH and temperature. Fourier Transform InfraRed analysis was performed to identify the functional groups present in PGP. Surface morphology of PGP before and after adsorption with MB was studied by analysing micrograph images of Scanning Electron Microscopy (SEM). The equilibrium and kinetic data were analysed in the light of different available isotherm and kinetic models. The study was extended for the desorption of MB and CV from the loaded adsorbent. The HCl was observed to be most efficient desorbing agent among HCl, NaOH, NaCl, CH3COOH, deionised doubly distilled water (DDDW) for MB-PGP system whereas NaOH proved to be the best desorbing agent for CV-PGP system.

Chapter 5 In this chapter, the applicability of Cucumis sativus peel (CSP) waste as a low cost adsorbent for the removal of hazardous methylene blue dye from wastewater has been given. The efficacy of dye removal of the adsorbent is determined by investigating the various parameters such as adsorbent dose, contact time, initial dye concentration, particle size, pH and temperature. Characterisation of the adsorbent was done using Scanning Electron Microscopy (SEM) and Fourier Transform Infra Red (FTIR) spectroscopy. The isotherm analysis reveals that the adsorption of MB can be better described by Freundlich adsorption whereas the adsorption of CV obeys Langmuir adsorption isotherm model. Adsorption

XVI kinetics was found to obey pseudo-second order kinetics for both MB-CSP and CV-CSP systems. Thermodynamic data reveals that the adsorption of MB is spontaneous and exothermic in nature while the adsorption of CV is spontaneous and endothermic in nature. For MB-CSP system, the adsorbent regeneration was found to be best obtained in hydrochloric acid whereas for CV-CSP system, sodium chloride was found to the most suitable desorbing agent.

Chapter 6 The utilisation of Terminalia Arjuna sawdust (TASd) as a low cost adsorbent for the removal of MB and CV has been discussed in this chapter. Batch adsorption studies were carried out to find out the effects of various useful parameters such as contact time, initial dye concentration, adsorbent dosage, pH and temperature. The adsorbent was characterised by Scanning Electron Microscopy (SEM) and Fourier Transform Infra-red (FTIR) spectroscopy. The equilibrium time for the adsorption process was determined to be 2 hours for both MB- TASd and CV-TASd systems. The experimental results were analysed in the light of different available isotherm models and were found to be best represented by Langmuir adsorption isotherm with maximum adsorption capacity of 60.6 mg/g for the adsorption of MB. For CV- TASd system, the best model representing the equilibrium data was found to be Freundlich adsorption isotherm model. Pseudo-first-order, pseudo-second-order, intraparticle diffusion and Elovich models were used to describe the kinetic data. It was found that the adsorption kinetics for MB obeys the pseudo-second order kinetic model at all temperatures. However, pseudo-first order kinetic model best represents the kinetic data for CV-TASd system Thermodynamic studies reveal that the adsorption is spontaneous, endothermic and accompanied by an increase in entropy for both the systems. The experimental results have been compared and discussed in the light of those reported by other investigators. Desorption of MB-loaded and CV-loaded TASd was also studied with various desorbing agents viz.

HCl, CH3COOH, NaCl, NaOH and doubly distilled deionised water (DDDW). The recovery of the used adsorbent was best observed in 0.1 M hydrochloric acid for MB and 0.1 M NaOH for CV.

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LIST OF TABLES Page No. Chapter 1

Table 1.1. Some important organic pollutants along with their 8 sources of origin Table 1.2. Some important inorganic pollutants along with their 9 sources of origin Table 1.3. Classification of dyes based on chromophoric group 18 Table 1.4. Summary of the adsorbents used for the removal of dyes 30 from wastewater Chapter 3

Table 3.1a. Isotherm parameters for the adsorption of MB and CV 88

onto CLP Table 3.1b. Langmuir isotherm parameters for the adsorption of MB 90

by different adsorbents

Table 3.2a. Kinetic parameters for the adsorption of MB and CV onto 93 CLP

Table 3.2b. Pseudo-second order rate constant for the adsorption of 96

MB onto different adsorbents

Table 3.2c. Pseudo-second order rate constant for the adsorption of 96 CV onto different adsorbents Table 3.3a. Thermodynamic parameters for the adsorption of MB 98 onto CLP Table 3.3b. Thermodynamic parameters for the adsorption of CV onto 98 CLP Table 3.4. Percentage desorption of MB from MB-loaded CLP in 101 different media

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Chapter 4

Table 4.1a. Isotherm parameters for the adsorption of MB and CV 130 onto PGP Table 4.1b. Freundlich isotherm parameters for the adsorption of CV 133 onto different adsorbents

Table 4.2a. Kinetic parameters for the adsorption of MB and CV onto 135

PGP Table 4.2b. Pseudo-second order rate constant for the adsorption of 137 MB onto different adsorbents Table 4.2c. Pseudo-second order rate constant for the adsorption of 139 CV onto different adsorbents Table 4.3a. Thermodynamic parameters for the adsorption of MB 140 onto PGP Table 4.3b. Thermodynamic parameters for the adsorption of CV onto 140 PGP Table 4.4. Percentage desorption of MB and CV from MB-loaded 143 and CV-loaded PGP in different media

Chapter 5

Table 5.1a. Isotherm parameters for the adsorption of MB and CV 170 onto CSP Table 5.1b. Freundlich isotherm parameters for the adsorption of MB 173 by different adsorbents Table 5.1c. Langmuir isotherm parameters for the adsorption of CV 173 by different adsorbents Table 5.2a. Kinetic parameters for the adsorption of MB and CV onto 175 CSP Table 5.2b. Pseudo-second order rate constant for the adsorption of 178 MB onto different adsorbents Table 5.2c. Pseudo-second order rate constant for the adsorption of 179 CV onto different adsorbents

Table 5.3a. Thermodynamic parameters for the adsorption of MB 180 onto CSP Table 5.3b. Thermodynamic parameters for the adsorption of CV onto 180 CSP Table 5.4. Percentage desorption of MB and CV from MB-loaded 183 and CV-loaded CSP in different media

Chapter 6

Table 6.1a. Isotherm parameters for the adsorption of MB and CV 210 onto TASd Table 6.1b. Langmuir isotherm parameters for the adsorption of MB 212 onto different adsorbents Table 6.1c. Freundlich isotherm parameters for the adsorption of CV 214 onto different adsorbents

Table 6.2a. Kinetic parameters for the adsorption of MB and CV onto 216

TASd Table 6.2b. Pseudo-second order kinetic parameters for the adsorption 219 of MB onto different adsorbents Table 6.2c. Pseudo-first order kinetic parameters for the adsorption of 219 CV onto different adsorbents Table 6.3a. Thermodynamic parameters for the adsorption of MB 221 onto TASd Table 6.3b. Thermodynamic parameters for the adsorption of CV onto 221 TASd Table 6.4. Percentage desorption of MB and CV from MB-loaded 224 and CV-loaded TASd in different media

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LIST OF FIGURES Page No.

Chapter 1

Fig. 1.1. Classification of Water pollutants 7 Fig. 1.2. Methylene blue 23 Fig. 1.3. Crystal violet 24 Fig. 1.4. Citrus limetta fruit 36 Fig. 1.5. Citrus limetta fruit peels 36 Fig. 1.6. Punica granatum fruit 38 Fig. 1.7. Punica granatum fruit peels 38 Fig. 1.8. Cucumis sativus fruit 40 Fig. 1.9. Cucumis sativus fruit peel 40 Fig. 1.10. Terminalia arjuna 42 Fig. 1.11. Terminalia arjuna sawdust 42

Chapter 3

Fig. 3.1a. SEM image of CLP adsorbent 72 Fig. 3.1b. SEM image of MB-loaded CLP 73 Fig. 3.1c. SEM image of CV-loaded CLP 74 Fig. 3.2a. FTIR spectrum of CLP adsorbent 75 Fig. 3.2b. FTIR spectrum of MB-loaded CLP 76 Fig. 3.2c. FTIR spectrum of CV-loaded CLP 76 Fig. 3.3a. Effect of contact time on the adsorption of MB onto CLP at 78 different concentrations Fig. 3.3b. Effect of contact time on the adsorption of CV onto CLP at 79 different concentrations Fig. 3.4a. Effect of adsorbent dosage on removal efficiency and 81 adsorption capacity for the adsorption of MB onto CLP Fig. 3.4b. Effect of adsorbent dosage on removal efficiency and 82 adsorption capacity for the adsorption of CV onto CLP

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Fig. 3.5a. Effect of pH on adsorption of MB on to CLP 83 Fig. 3.5b. Effect of pH on adsorption of CV onto CLP 84 Fig. 3.6. Point of zero charge for CLP 85 Fig. 3.7. Effect of particle size on adsorption of MB and CV onto CLP 86 Fig. 3.8a. Langmuir adsorption plot of MB onto CLP 89 Fig. 3.8b. Temkin adsorption for the adsorption of CV onto CLP 91 Fig. 3.9a. Pseudo-second order kinetic model for the adsorption of MB 94 onto CLP Fig. 3.9b. Pseudo-second order kinetic model for the adsorption of CV 95 onto CLP

Fig. 3.10a. Plot of ln Kc vs 1/T for the adsorption of MB onto CLP 99

Fig. 3.10b. Plot of ln Kc vs 1/T for the adsorption of CV onto CLP 100

Chapter 4

Fig. 4.1a. SEM image of PGP adsorbent 113 Fig. 4.1b. SEM image of MB-loaded PGP 114 Fig. 4.1c. SEM image of CV-loaded PGP 115 Fig. 4.2a. FTIR spectrum of PGP adsorbent 116 Fig. 4.2b. FTIR spectrum of MB-loaded PGP 117 Fig. 4.2c. FTIR spectrum of CV-loaded PGP 117 Fig. 4.3a. Effect of contact time on the adsorption capacity of MB onto 119 PGP at different concentrations Fig. 4.3b. Effect of contact time on the adsorption capacity of CV onto 120 PGP at different concentrations Fig. 4.4a. Effect of adsorbent dosage on removal efficiency and 122 adsorption capacity for the adsorption of MB onto PGP Fig. 4.4b. Effect of adsorbent dosage on removal efficiency and 123 adsorption capacity for the adsorption of CV onto PGP Fig. 4.5a. Effect of pH on adsorption of MB on to PGP 125 Fig. 4.5b. Effect of pH on adsorption of CV on to PGP 126 Fig. 4.6. Point of zero charge for PGP 127 Fig. 4.7. Effect of particle size on adsorption of MB and CV onto PGP 128

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Fig. 4.8a. Temkin isotherm model for the adsorption of MB onto PGP 131 Fig. 4.8b. Freundlich isotherm for the adsorption of CV onto PGP 132 Fig. 4.9a. Pseudo-second order kinetic model for the adsorption of MB 136 onto PGP Fig. 4.9b. Pseudo-second order kinetic model for the adsorption of CV 138 onto PGP

Fig. 4.10a. Plot of ln Kc vs 1/T for the adsorption of MB onto PGP 141

Fig. 4.10b. Plot of ln Kc vs 1/T for the adsorption of CV onto PGP 142

Chapter 5

Fig. 5.1a. SEM image CSP adsorbent 154 Fig. 5.1b. SEM image of MB-loaded CSP 155 Fig. 5.1c. SEM image of CV-loaded CSP 156 Fig. 5.2a. FTIR spectrum of CSP adsorbent 157 Fig. 5.2b. FTIR spectrum of MB-loaded CSP 158 Fig. 5.2c. FTIR spectrum of CV-loaded CSP 158 Fig. 5.3a. Effect of contact time on the adsorption capacity of MB onto 160 CSP at different initial concentrations Fig. 5.3b. Effect of contact time on the adsorption capacity of CV onto 161 CSP at different initial concentrations Fig. 5.4a. Effect of adsorbent dosage on the removal efficiency and 163 adsorption capacity for the adsorption of MB onto CSP Fig. 5.4b. Effect of adsorbent dosage on the removal efficiency and 164 adsorption capacity for the adsorption of CV onto CSP Fig. 5.5a. Effect of pH on the adsorption of MB onto CSP 165 Fig. 5.5b. Effect of pH on the adsorption of CV onto CSP 166 Fig. 5.6. Point of zero charge of CSP 167 Fig. 5.7. Effect of particle size on the adsorption of MB and CV onto 168 CSP Fig. 5.8a. Freundlich adsorption plot of MB onto CSP 171 Fig. 5.8b. Langmuir adsorption plot of CV onto CSP 172 Fig. 5.9a. Pseudo-second order plot for the adsorption of MB onto CSP 176

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Fig. 5.9b. Pseudo-second order plot for the adsorption of CV onto CSP 177

Fig. 5.10a. Plot of ln Kc vs 1/T for the adsorption of MB onto CSP 181

Fig. 5.10b. Plot of ln Kc vs 1/T for the adsorption of CV onto CSP 182

Chapter 6

Fig. 6.1a. SEM image of TASd adsorbent 193 Fig. 6.1b. SEM image of MB-loaded TASd 194 Fig. 6.1c. SEM image of CV-loaded TASd 195 Fig. 6.2a. FTIR spectrum of TASd adsorbent 196 Fig. 6.2b. FTIR spectrum of MB-loaded TASd 197 Fig. 6.2c. FTIR spectrum of CV-loaded TASd 197 Fig. 6.3a. Effect of contact time on the adsorption capacity of MB onto 199 TASd at different concentrations Fig. 6.3b. Effect of contact time on the adsorption capacity of CV onto 200 TASd at different concentrations Fig. 6.4a. Effect of adsorbent dosage on the removal efficiency and 202 adsorption capacity for the adsorption of MB onto TASd Fig. 6.4b. Effect of adsorbent dosage on the removal efficiency and 203 adsorption capacity for the adsorption of CV onto TASd Fig. 6.5a. Effect of pH on the adsorption of MB onto TASd 205 Fig. 6.5b. Effect of pH on the adsorption of CV onto TASd 206 Fig. 6.6. Point of zero charge of TASd 207 Fig. 6.7. Effect of particle size on adsorption of MB and CV onto 208 TASd Fig. 6.8a. Langmuir adsorption plot of MB onto TASd 211 Fig. 6.8b. Freundlich adsorption plot of CV onto TASd 213 Fig. 6.9a. Pseudo-second order kinetic model for the adsorption of MB 217 onto TASd Fig. 6.9b Pseudo-second order kinetic model for the adsorption of CV 218 onto TASd

Fig. 6.10a. Plot of ln Kc vs 1/T for the adsorption of MB onto TASd 222

Fig. 6.10b. Plot of ln Kc vs 1/T for the adsorption of CV onto TASd 223

XXV

Chapter 1

General introduction

CHAPTER 1

General introduction

1.1. Introduction

Since the middle of the 19th century, things have started happening in quite disproportions putting the ecological system out of the balance. The population explosion, prosperous society with an aspiration for a vast array of products, the automobiles, greater energy use leading to increased radiations, increase in food production needs, etc. are some of the potent factors responsible for creating the imbalance. Science and technology brought in the revolutionary change in human life. Modernization made man‘s life more and more comfortable. Today one can travel faster, speak or send a message to distant places through the modern means of communication. Villages have become growing cities as a result of industrialisation. It was the industrial revolution that gave birth to environmental pollution as we know it today.

One of the greatest problems that the world is facing today is the environmental pollution which is increasing with every passing year and causing severe damage to the earth. Today, environmental pollution is occurring on a vast and unprecedented scale globally. The word ―Pollution‖ is derived from a Latin word ―Polluere‖ which means ―to defile‖ or ―to make dirty‖. Pollution is an undesirable change in the physical, chemical or biological characteristics of air, land and water that makes the environment unhealthy to live and creates potential health hazards to living organisms.

The Royal Commission on Environmental Pollution in U.K. in its third report [1] defined the term ―Pollution‖ as ―Introduction by man into the environment of substance or energy liable to cause hazards to human health, harm to living resources

1 and ecological systems, damage to structure or amenity or interference with legitimate uses of the environment.‖

In fact, environmental pollutants are the executing agents of environmental pollution. A pollutant is a substance or energy introduced into the environment that has undesirable effects or adversely affects the usefulness of a resource. Environmental pollutants can be classified into two types – Biodegradable pollutants and non-biodegradable pollutants.

Biodegradable pollutants: Biodegradable pollutants are the ones that can be broken down into simpler, harmless substances in due course of time by the action of microorganisms (like bacteria). For example, domestic wastes, faecal matter, vegetable stuff, etc.

Non-biodegradable pollutants: Non-biodegradable pollutants cannot be broken down into simple and harmless substances by the action of microorganisms. For example, plastics, polythene bags, pesticides, glass, heavy metals, etc.

1.2. Forms of Environmental pollution

The environmental pollution may be classified into different major forms such as air, water, soil, noise pollutions, etc.

1.2.1. Air pollution

Air pollution is the introduction of particulates, biological fragments and other harmful materials into the earth‘s atmosphere resulting in diseases, allergies in living organisms and damage to the natural environment. Sources of air pollution can be natural or anthropogenic. Air pollutants can be classified as primary and secondary.

Primary air pollutants are introduced into the environment by natural sources and human activities as well. Some common examples of primary pollutants are given below.

(a) Carbon monoxide (CO): It is produced by the incomplete combustion of fuels such as natural gas, wood or coal, vehicular emission, cigarette smoking, etc. It is also generated naturally by the plants during the oxidation of methane (swamps, bogs, rice paddies, etc.) and decomposition of chlorophyll.

(b) Sulphur oxides (SOx): Sulphur compounds are commonly emitted into the atmosphere during volcanic eruptions. Sulphur oxides are sprayed out as aerosols from the sea during rough weather. These oxides are also produced during the biogenic decomposition of sulphur-containing organic compounds

on land and in sea. Anthropogenic sources of SOx are burning of fossil fuels (coal, petroleum and its products), smelting of sulphide ores, manufacture of sulphuric acid, etc.

(c) Nitrogen oxides (NOx): They are produced during thunderstorms and by soil microorganisms. These are also formed by fossil-fuel based power plants and vehicles. (d) Toxic metals: Arsenic, cadmium, lead, mercury, chromium, etc. and their compounds are released in air by industrial and other activities. (e) Volatile organic compounds (VOC): Xylene, toluene, methane, 1,3- butadiene, benzene, formaldehyde, etc. are examples of VOC. Sources of VOC include paints, varnishes, air fresheners, fuel oil, cleaning products, etc. (f) Particulates: These are the tiny particles of solid or liquid suspended in air. They originate from agricultural operations, dust storms, forest and grassland fires, volcanoes, burning of fossil fuels, construction and demolition activities, vehicles and aerosols. (g) Ammonia: Major source of ammonia in the atmosphere is the decay of organic matter and fertilisers. (h) Chlorofluorocarbons (CFCs): These are released into the atmosphere from air conditioners, refrigerators, aerosol, etc.

Secondary air pollutants: These pollutants are not emitted directly into the atmosphere. They are formed in the air when primary air pollutants interact with each other.

(a) Ground level ozone: Ground level ozone is formed due to the reaction of

NOx, carbon monoxide and VOC in the presence of sunlight. (b) Smog: The term ‗smog‘ is derived from two words, namely, smoke and fog. Two different types of smog are caused by the low-pressure gradient weather patterns depending on the kind of emissions and the intensity of radiation. The London smog is formed in winters consisting of a mixture of gaseous and solid aerosols and natural fog. It results from the accumulation of smoke from

coal burning having high sulphur content leading to the production of high concentrations of sulphuric acid in fog droplets. On the other hand, the Los Angeles smog is formed during sunny summer days in regions where automobile emission is very high. It is formed as a result of interactions among nitrogen oxides, reactive hydrocarbons and sunlight.

1.2.2. Water pollution

Water pollution is the contamination of water bodies by the release of industrial wastes, domestic sewage, chemical contaminants, urban and agricultural runoff containing fertilisers and pesticides, eutrophication, littering, etc. Water pollution will be discussed in detail in Section 1.3.

1.2.3. Soil pollution

Soil pollution is the degradation of land in the presence of xenobiotic chemicals or alteration in the natural environment of the soil. It is typically caused by domestic, agricultural and industrial activities and improper disposal of wastes. Some common and harmful soil pollutants are pesticides (herbicides, fungicides, insecticides, etc.), heavy metals (lead, arsenic, mercury, copper, cadmium, etc.), petroleum hydrocarbons, organic solvents and polynuclear aromatic hydrocarbons (naphthalene, benzopyrene, etc.). Crops and plants grown on polluted soil act as media for the transportation of the pollutants to living organisms. Long term exposure of living bodies to such soil can affect their genetic make-up, causing congenital illnesses and chronic health problems that cannot be cured easily. Fungi and bacteria (found in the soil binding it together) begin to decline creating additional problem of soil erosion. The fertility of soil slowly diminishes, making land unsuitable for agriculture and any local vegetation to survive. The death of many soil organisms (e.g. earthworms) in the soil leads to an alteration in soil structure.

1.2.4. Noise pollution

Noise pollution refers to the presence of such levels of noise or sound in the environment that are disturbing, irritating and annoying to living beings. Noise is measured in decibels (dBA). In daily life, people are generally exposed to noise levels ranging from 30–80 dBA. Exposure to noise level greater than 80 dBA leads to stress [2]. Major sources of noise pollution are industries, transport vehicles, household

(televisions, domestic gadgets, air conditioners, vacuum cleaners, etc.), public addressing systems (loud speakers), agricultural machines (tractors, thrashers, tube wells, etc.), defense equipments (artillery, tanks, explosives, etc.), construction works, etc. Noise pollution causes uneasiness and harm living being‘s mental and physical health. It is one of the major causes of deafness. Noise pollution also leads to cardiac disturbance, sleeplessness, headache, irregular blood pressure psychological imbalance, etc.

1.3. Water pollution

Water is one of the world‘s most precious resources without which life is not possible on earth. As stated by philosopher Thales from Miletus, ―Hydor (Water) is the beginning of everything‖. Thales understood that water is life and living organisms cannot survive without it. Over two-thirds of earth‘s surface is covered with water and less than one-third is taken up by land. As the earth‘s population is growing day by day, people are putting ever increasing pressure on the earth‘s water resources. In a sense, our oceans, rivers and other water resources are being squeezed by human activities and also reducing its quality. Today contamination of freshwater systems with a wide variety of pollutants is a subject of great concern.

Water pollution can be defined as the alteration in the physical, chemical or biological characteristics of water which makes it harmful for living organisms and unsuitable for desired usage. Water pollution is a major global problem. It may be caused by natural sources or human activities and can have detrimental effects on aquatic ecosystems as well as other living organisms.

1.3.1. Sources of water pollution

The sources of water pollution can be broadly classified into two categories:

(a) Point sources

In this case, the pollutants are discharged from a single identifiable source. An example of this type is discharge from industries into water, sewage treatment plants, etc. The sources can be easily monitored.

(b) Non-point sources

It refers to the contamination which is spread over a wide area and is not ascribed to a single source. Rain water travelled through the agricultural regions contains mixed pollutants (pesticides, fertilisers, animal manure, etc.) is a most suitable example of this type of pollution. Such pollutants cannot be monitored easily.

However, there is no sharp line of differentiation between point and non-point sources of water pollution. The contamination of groundwater by the leakage of chemicals from the disposal tank of one factory may be a point source of pollution. But, in an industrial area, the leakage of chemicals from the disposal tanks of several factories contaminating the groundwater comes under the category of non-point source of water pollution.

1.3.2. Classification of water pollutants

Water pollutants can be broadly classified into four categories, namely, chemical, physical, physiological and biological pollutants [3].

Schematic diagram showing the detailed classification of water pollutants is presented in Fig. 1.1.

(a) Chemical pollutants

Chemical pollutants can be subdivided into two different types, organic and inorganic pollutants.

Organic pollutants: They include naturally occurring compounds like proteins, fats, carbohydrates, etc. as well as synthetic compounds such as dyes, soaps, detergents, pesticides, etc. Some common organic pollutants along with their source of origin are listed in Table 1.1. When an organic pollutant is discharged into a water body, it is gradually degraded by aerobic bacteria. Thus, complex, hazardous organic compounds are broken down into simple, harmless, inorganic components in the presence of dissolved oxygen. This phenomenon is known as self-purification of water. However, non-biodegradable organic pollutants such as detergents and their aromatic derivatives are resistant to microbial degradation. Their degradation occur extremely slow consuming large amounts of dissolved oxygen.

Inorganic pollutants: They generally originate from industrial wastes. Inorganic acids and alkalis can do extensive damage to a water body by altering its natural buffer system and its normal pH value. Change in pH has a profound effect on aquatic organisms, especially fishes. Some common classes of inorganic pollutants are listed in Table 1.2.

Fig. 1.1. Classification of Water pollutants

Both acids and alkalis kill bacteria and inhibit the self-purification phenomenon of a water body. Self-purification is also hindered by the presence of heavy metal ions in water. These ions terminate the algae and bring about the death of fishes by coagulating the mucous around the gill.

Table 1.1.

Some important organic pollutants along with their sources of origin

Pollutants Sources Representative examples Food processing, cannery waste, Proteins Gelatin, keratin, casein slaughter house waste, tannery waste Fat refining, wool scouring waste, Glycerol palmitate, Fats edible oil waste glycerol stearate Paper and pulp industry, Carbohydrates Starch, cellulose textile industry Paint manufacture, textile Resins Amber, rosin industry, lacquer industry Laundry waste, soap industry, Soaps Sodium palmitate, textile waste, domestic waste potassium stearate, sodium stearate, Laundry waste, textile waste, Sodium lauryl sulphate, Detergents detergent industry, sodium dodecyl benzene domestic waste sulphonate, polyglycol ether Dyeing and printing industry, Fluorescein, magenta, Dyes pulp and paper, leather, methylene blue, textile paint, pharmaceuticals, crystal violet, congo red, carpet, cosmetic industries, etc. malachite green, rhodamine B, metanil yellow Agricultural runoff, Acephate, acetamiprid, Agro-chemicals chemical industry tricyclazole, methomyl, carbaryl, atrazine, diuran, DDT

Table 1.2.

Some important inorganic pollutants along with their sources of origin

Pollutants Sources Representative examples Acids Mine runoff, wool scouring Sulphuric acid, phosphoric waste, acid, nitric acid, iron pickle liquor, industrial hydrochloric acid by-products Alkalis Tannery waste, cotton processing Caustic soda, lime, waste, various industries magnesium hydroxide Heavy metals Industrial and domestic activities, Mercury, cobalt, arsenic, metallurgical operations, cadmium, chromium, nickel, motor vehicles, etc. thallium, lead

(b) Physical pollutants:

Natural qualities of water are also affected when the physical parameters of water are drastically changed. Physical pollutants originate as a secondary consequence of chemical pollution. Physical pollutants include colour, turbidity, suspended matter, froth, radioactivity, thermal pollutants, etc.

Colour: Wastes discharged into the water systems have a distinct colour thereby imparting colour to the water bodies. The colour, in most cases, is due to dyes. For example, fluorescein imparts a characteristic yellow-green colour to water at even a low concentration of 0.025 ppm. Interactions between two different types of wastes in a stream or between an effluent and substances present naturally in a stream can also produce colouration. For example, when effluents from mine runoff, rich in iron content, enter aquatic system containing hard water, a reddish-brown opalescence develops. This colouration is due to ferric hydroxide formed by the interaction of ferric ions present in mine runoff and bicarbonate ions present in hard water.

Turbidity: A distinct physical characteristic of sewage and industrial wastewater is their degree of turbidity which is due to the presence of colloidal matter. Colloidal particles do not settle on standing and, therefore, imparts cloudiness to water. Greater the degree of pollution, more prominent is the turbidity. Turbidity in natural water systems might be due to the presence of small amounts of inert and relatively harmless minerals like clay particles. Colloidal particles which cause turbidity are

9 generally non-toxic. However, these prevent the penetration of sunlight, reduce the extent of photosynthesis, inhibit the growth of submerged aquatic plants and consequently affect the species which are dependent on them.

Suspended matters: Coarse, insoluble matter suspended in water is the most common form of physical pollutant. The particulates tend to cause silting of a watercourse, especially if the stream is slow moving. These cause mechanical injury to the fishes by choking their gills. Further, these reduce the penetration of sunlight in water and restrict photosynthesis.

Froth: Froth consists of a dispersion of gas bubbles in water. The formation of froth is a physical phenomenon arising due to the lowering of the surface tension of water by impurities such as soaps, detergents, etc. Froth restricts photosynthesis by reducing the penetration of sunlight. Also, it is aesthetically unpleasant.

Radioactivite matter: Radioactive pollution is the increase in natural background radiation emerging from the human activities involving the use of naturally occurring or artificially produced radioactive materials. Radioactive substances are those which emit high energy species like α, β particles and gamma rays. Such pollutants are unstable in nature and continuously emit radiations in order to attain stability. Many radioactive elements like uranium, thorium and actinium have always existed in the earth‘s crust. A part of these radionuclides enter the water bodies. The situation will become worse when there is any large scale increase in the radiation due to the development of nuclear fission reactions and also due to the increased use of man- made sources of radioactivity in medicine, industry and research. When these radionuclides are taken up by aquatic organisms, exchange with chemically similar elements already present in the organism‘s body takes place. For example, radioactive strontium-90 and radium-226 replace calcium. Thus, strontium-90 becomes concentrated in scales and bones of fish. Since aquatic flora and fauna can concentrate radioactivity, the possibility exists that those used as food by man could bioaccumulate dangerous amounts of radiations in the human body.

The major sources of radioactive pollution include uranium mining, nuclear fuel production, nuclear power reactors and nuclear tests. Radioactive pollution occurs mostly from the waste products left behind after the use of radioactive substances. A large amount of radioactive waste is generated in nuclear power plants.

Nuclear accidents and nuclear explosions are worst man-made sources of radioactive pollution.

Radioactive pollution is highly dangerous to human health. Exposure of human beings to low levels of radiation causes skin disorders, nausea, vomiting, diarrhoea, loss of hairs and nails. Exposure to high level of radiation can cause leukaemia, tumour, anaemia, haemorrhage, cardiovascular disorders, premature ageing and reduced life span.

Thermal pollutants: Thermal pollution is the degradation of water quality by any process that changes ambient temperature of water. The most common cause of thermal pollution is the use of water as a coolant by power plants and industries. When this water is returned to the natural environment at a higher temperature, the oxygen supply and composition of ecosystem are affected.

The major sources of thermal pollution are nuclear power plants, hydroelectric power plants, coal-fired power plants and industrial effluents. Fishes and other organisms are adapted to live in particular ranges of temperature. They cannot survive when they are exposed to an abrupt change in water temperature (either a rapid increase or decrease). This phenomenon is known as thermal shock. It may change the metabolic responses, diurnal and seasonal behaviour of organisms. The population of aquatic plants is also affected. An increase in temperature causes not only the depletion of dissolved oxygen due to the lower solubility of oxygen at higher temperatures but also an increase in the rate of respiration of the fishes. Also, the toxicity due to pesticides, detergents and other chemicals increases with the increase of temperature. Temperature differences during growth and development of aquatic organisms can also induce morphological changes.

Physiological pollution is a secondary phenomenon arising due to the presence of trace quantities of chemicals. As a result of this, natural water no longer remains tasteless or odourless.

Taste: Industrial wastes contain many chemical compounds which impart characteristic and unpleasant taste to water even if present in extremely small amounts. For example, inky taste arises due to the presence of ferrous ions at even a

11 low concentration of 0.1 ppm in water. If the chlorides in wastewater exceed 500 ppm, it gives a salty taste to water.

Odour: Under the influence of microorganisms, proteins are decomposed giving intermediates having unpleasant odours. For example, sewage possesses unpleasant odour due to the decomposition of proteins into heterocyclic amines (indole and skatole).

(d) Biological pollutants

The undesirable and harmful aquatic organisms, which may sometime multiply excessively, are classified as biological pollutants. These pollutants generally arise as a secondary result of pollution by sewage or industrial wastes. Biological pollutants include weeds, algae, bacteria, viruses, protozoa, worms, etc.

Weeds: Excessive growth of freshwater weeds is because of the discharge of untreated sewage or effluents into water. These weeds cause fish mortality and serve as breeding ground for mosquitoes.

Algae: Algae reproduce at a faster pace causing odours in water. When they die, their cells decompose encouraging the growth of bacteria and fungi which flourish on dead cell components. The decomposition of algae cells consumes oxygen which causes eutrophic conditions in water bodies.

Bacteria: The faecal contamination of water can introduce a variety of pathogenic bacteria. For example- Salmonella can cause acute gastro-entritis with diarrhoea, fever and vomiting. E. coli produces diarrhoea in children.

Viruses: Viruses are introduced into the natural waters through faeces. Although these organisms are present in water in lower numbers, yet they pose a considerable threat to living organisms because they possess a greater resistance to disinfection. For example- Hepatitis A, a form of jaundice, is also transmitted by virus-contaminated water.

Protozoa: Faecal contamination of drinking water is the major source of transmission of pathogenic protozoa. Amoebic dysentery is caused by parasitic protozoa, Entamoeba histolytica.

Worms: Common parasitic worms present in water are roundworms, tapeworms, etc. They are resistant to sewage treatment processes and multiply at a faster rate.

1.4. Wastewater treatment

Before the industrial revolution, natural purification phenomenon was sufficient to provide water of high purity. However, excessive human interference with the environment has pushed the natural purification processes beyond their limits. Hence, a series of purification operations are required to restore the natural qualities of water. Various water treatment plants are developed and used to purify the water before it is discharged from the industries into the freshwater systems. Water is purified in following four successive stages: preliminary, primary, secondary and tertiary treatments [4, 5].

1.4.1. Preliminary treatment

The objective of the preliminary treatment is the removal of suspended coarse solids and other large floating materials often found in wastewater. Removal of these materials is necessary to reduce the maintenance and treatment cost of subsequent treatment units. Suspended matter is removed by screening whereas the floating matter is eliminated by skimming.

In screening, impure water is allowed to pass through screens made of rows of iron bars with a spacing of 1–2 inches. Materials like rags, sticks, polythene bags, wood pieces, papers, etc. are held back by the spacing in the iron bars. Impurities which are lighter than water such as oil, grease, etc. rise to the surface of water and can be removed by mechanical skimming. Skimming technique can also be used to remove grit particles by blowing compressed air in polluted water. The air bubbles that are formed attach themselves to grit particles and lift them to the surface from where they can be skimmed off easily.

1.4.2. Primary treatment

In this stage, colloidal and suspended matters are allowed to settle down as sludge. It involves two methods – sedimentation and flocculation.

Some solids suspended in water are either too fine to be screened out or too heavy to be skimmed off. Such impurities are removed by allowing them to settle

13 down under the influence of gravity. This technique is called sedimentation and is carried out in sedimentation tanks. Polluted water is allowed to remain in tanks for 1– 3 hours. The sludge thus formed undergoes putrefaction and hence should not be left in the sedimentation tanks for too long. The tanks have mechanical gears to remove sludge at regular interval of time.

To get rid of extremely fine particles, flocculation method is used. These particles take very long time to settle down and hence cannot be removed by sedimentation. However, their rate of settlement can be enhanced up to a considerable extent by adding some flocculating agents such as potash alum, ferrous sulphate, ferric chloride, etc. These fine suspended particles in polluted water bear either positive or negative charge. When flocculating agents are added, positive charges are neutralized by sulphate or chloride ions whereas negative charges are neutralized by Al3+, Fe2+ or Fe3+ ions. Once the charges are nullified, the particles come in contact with each other and coalesce and rapidly settle down.

1.4.3. Secondary treatment

Secondary treatment involves the oxidation of dissolved and colloidal organic compounds in the presence of microorganisms. The organic compounds are biodegraded into simpler and harmless compounds with the consumption of oxygen. The aerated conditions are obtained by trickling filters, activated sludge tanks or by oxidation ponds.

Trickling filters consist of circular or rectangular beds packed with stones, gravel, etc. which serve as a habitat for bacteria, fungi and other microoragnisms. A part of the sludge from the primary settling tank is applied to the bed from above and polluted water is allowed to pass over these beds. Gradually with time, a biotic community is established as a gelatinous layer on the surface of bed. This layer contains bacteria, fungi, algae, etc. When water trickles through this biological layer, the organic impurities are broken down in the presence of dissolved oxygen into simpler compounds. Also, the microorganisms already present in water are retained on the beds and supplement the purification phenomenon.

In activated sludge method, water containing organic pollutants is aerated and some amount of sludge settles down. Soon microorganisms start inhabiting the

14 sludge. Nextly, when fresh batch of polluted water is aerated over this sludge, it gets purified more efficiently than the previous one. More and more sludge accumulates and a greater density of microorganisms settles on it. Hence, after each purification slot, the sludge becomes more activated. After each slot, the aeration time is reduced because the purification is achieved in shorter duration.

Oxidation ponds are used in warmer climates to purify polluted water through an interaction between bacteria and algae. Polluted water is made to flow through the ponds (shallow lagoons with an average depth of 1 meter) at a slow speed. The bacteria in the pond decompose the biodegradable organic matter with the consumption of dissolved oxygen generating carbon dioxide, nitrates and phosphates. These nitrates and phosphates are consumed by algae and carbon dioxide is utilized in photosynthesis liberating oxygen. Thus, the dissolved oxygen which was consumed by bacteria is restored and fresh cycle could be started again.

1.4.4. Tertiary treatment

Tertiary treatment of water removes the impurities that remain after the first three stages of purification. These impurities are mainly the soluble inorganic impurities. Different techniques are used in this stage depending on the nature of pollutants.

Chlorination refers to the addition of gaseous chlorine or compounds containing active chlorine such as bleaching powder. It disinfects the pathogenic bacteria by inactivating the enzymes that are essential for the life processes of bacteria. It controls the growth of undesirable algae in the water treatment plants. It also eliminates the odours associated with the anaerobic decomposition of organic matter in water.

The impurities present in water are oxidized to harmless materials using suitable oxidising agents such as hydrogen peroxide. The hydroxyl radical generated by the action of ultraviolet light on H2O2 attacks the inorganic and organic pollutants. The sulphur compounds are oxidised to sulphates, phosphorus compounds to phosphates, cyanides to cyanates and halogen compounds to halides. This method is known as wet oxidation.

In reverse osmosis, impure water is placed above a semi-permeable membrane and is subjected to high pressure. As a result, pure water flows down the semi-permeable membrane and the solute molecules having larger diameters than the pores of the semi-permeable membrane are retained by the membrane.

Electrodialysis technique is used to purify brackish water (water containing higher concentration of ionic impurities). The equipment consists of an electrolytic cell divided into three compartments by two semi-permeable membranes. The orifices on the membrane near the cathode are coated with negatively charged ions. This membrane repels anions but attract cations. Similarly the orifices of the membrane near anode are coated with positively charged ions which repel cations but attract anions. When current is induced, cations present in impure water pass through the cation-permeable membrane and discharge at the cathode. Similarly, anions present in impure water pass through the anion-permeable membrane and discharge at the anode. The central compartment is devoid of any impurity and contains pure water.

During the tertiary stage of water purification, about 1 ppm of fluoride is added, either in the form of sodium fluoride or as sodium hexafluorosilicate (IV). This process is called fluoridation. Fluoride is essential to protect the teeth against dental decay.

The ion-exchange technique is also used for the purification of brackish water. The equipment consists of a cation exchanger coupled with an anion exchanger. Each ion-exchanger contains resin (high molecular weight polymeric material with ionic functional groups). As water containing ionic impurities is passed over these ion exchangers, the functional groups can exchange ions. Impure water is first passed through cation exchanger. The cations present in impure water are exchanged with the H+ ions of the resin (cation exchanger contains ionic sulphonic acid group). When water is passed through anion exchanger (containing quaternary ammonium hydroxide group), the anions present in impure water are exchanged with the hydroxide ions of the resin. The H+ ions and OH- ions combine to form water.

Several compounds which are resistant to biodegradation may persist in water even after primary and secondary treatment. Adsorption technique is used for the elimination such impurities (heavy metals and dyes) from water by passing the water over a bed of granulated active charcoal. When the charcoal becomes saturated with

16 impurities, it is heated at about 1800 K in vacuum to remove impurities from the used adsorbent so that it could be used again.

1.5. Dyes

A dye is a coloured substance that has an affinity for the substrate to which it is being applied. The phenomenon of absorption of light is important for the sensation of colour. However, it was recognized in 1870 that unsaturation is essential for light absorption and hence colour sensation. Otto Witt, a German chemist, put forward his theory of colour and constitution and is known as chromophore-auxochrome theory. The main points of this theory are:

(a) The colour of an organic compound is mainly due to the presence of unsaturated groups known as chromophores (German: Chroma means colour and phorein means to bear). The compound bearing the chromophoric group is called chromogen [6,7]. For example, azo (–N=N–), carbonyl (C=O), methine (–CH=),

and nitro (–NO2) groups, etc. (b) The greater the number of chromophores, the greater is the intensity of colour. (c) Certain substituents fail to produce colour by themselves but they deepen the colour due to the chromophoric group already present. Such groups are called auxochromes (German: auxanein means to increase). Common auxochrome

groups include hydroxyl (–OH), amino (–NR2, –NHR, –NH2) groups, halogens, etc.

1.5.1. Classification of dyes

Dyes can be classified in several ways. Some bases of classification are given below:

. On the basis of source of dyes . On the basis of nature of chromophore . On the basis of application of dyes

(a) Classification based on source of dye

On the basis of the source from which the dye is obtained, dyes can be classified as natural and synthetic.

Natural dyes: These dyes are obtained from natural sources. Most of the natural dyes have plant origin (extracted from leaves, flowers, roots, berries, roots, bark, etc.). Some natural dyes are also obtained from insects and mineral compounds. For example, indigo, madder, saffron, osage orange, safflower, madder, etc. Natural dyes are of two types- additive and substantive dyes. Additive dyes require a mordant to fix to the fiber (For example, madder). Substantive dye does not require the use of any mordant (For example, cochineal and safflower).

Synthetic dyes: Dyes prepared from organic or inorganic compounds are known as synthetic dyes. While searching for a remedy for malaria, William Henry Perkin, an English chemist, serendipitously discovered the first synthetic dye, Mauveine. Since then thousands of different synthetic dyes were manufactured and used due to their low cost and colourfastness. Based on this classification, textile dyes can be categorised into various groups, namely, direct, vat, sulphur, organic pigments, reactive, dispersed, acidic, azoic, basic, oxidative, developed, mordant, and solvents dyes.

(b) Classification based on nature of chromophore

On the basis of the nature of the chromophoric group present in the dye molecule structure, they can be classified into various categories which are listed in Table 1.3.

Table 1.3.

Classification of dyes based on chromophoric group

Dye category Chromophoric Representative example Colour group Acridine dyes

Orange Acridine orange

Anthraquinone dyes

Crimson Alizarin Arylmethane dyes

Yellow

Auramine O

Violet

Crystal violet Azo dyes

–N=N–

Yellow Aniline yellow Nitroso dyes

–N=O

Green

Naphthol green B Xanthene dyes

Yellow fluorescent Rhodamin 6G

Indophenol dyes

Blue

Indophenol blue

On the basis of application, dyes can be classified into 9 categories:

Reactive dyes: These dyes have reactive groups which form covalent bonds with –

OH, –NH2 or –SH groups on the fiber. Reactive dyes are extensively used in the textile industry because of wide variety of colour shades and ease of application. The hydrolysis of the reactive groups in the side reaction lowers the degree of fixation. It is estimated 10–50% does not react with fabric and remain hydrolysed in the water phase. The problem of coloured effluents is, therefore, identified to be mainly because of the use of reactive dyes. For example, Reactive yellow HE6G, Reactive red, Reactive violet C2R, Reactive golden yellow MR, Reactive yellow MGR, etc.

Acid dyes: These are anionic compounds and used for dyeing basic group-containing fabrics like wool, polyamide and silk. These are applied to the fabric under acidic conditions which cause protonation of basic groups. The process is reversible and dyes are removed from fabrics during washing. For example, Acid black, Acid blue S5R, Acid green 20, Acid red 119, etc.

Basic dyes: These are cationic compound that are used for dyeing acid group- containing fibers, usually synthetic fibers like modified polyacryl. They generally give intense shades but have poor light fastness. They are used for dyeing silk and wool directly. For example, Crystal violet, methylene blue, safranin, basic fuschin, etc.

Direct dyes: They dyes have high affinity for cellulose fibers and bind to them through Vander Waals forces. The common salt or Glauber‘s salt is often used with direct dye to promote dyeing process because the presence of excess sodium ions favours the establishment of equilibrium with minimum amount of dye. In this case, the dyeing process is reversible and exhibit poor wash fastness. For example, Direct orange 39, Direct blue 86, Direct red 10, etc.

Mordant dyes: These dyes have poor affinity for the fiber and require pre-treatment of the fiber with the mordant usually metal salts (such as chromium and iron salts). They are used for dyeing wool, leather, silk, paper and modified cellulose fibers. For example, Chrome blue 2K, Alizarin red S, Celestine blue B, Eriochrome cyanine R, etc.

Disperse dyes: They are specifically used to dye synthetic fibers like cellulose acetate, polyester, polyamide, acryl, etc. They are insoluble in water but in the actual fibres themselves. Its diffusion requires swelling of the fiber, either by high temperature (>120˚C) or with the help of chemical softener so that the finely ground particles can penetrate. For example, Disperse red, disperse blue, Disperse violet, Disperse yellow, Disperse green, etc.

Vat dyes: They dyes are insoluble in water but their reduced forms are soluble. These dyes are, therefore, applied in their reduced forms (reduced forms are obtained by treating the dye with some reducing agent such as alkaline sodium dithionite). When the reduced dye is adsorbed on the fiber, the original insoluble dye is reformed upon oxidation with air or chemicals. Vat dyes offer excellent fastness but they are quiet expensive. For example, Vat blue 1, Vat orange 3, Vat yellow 1, etc.

Sulphur dyes: These are polymeric aromatic compounds containing heterocyclic S- ring. They are mainly used for dyeing cellulose fibers. Dyeing process involves reduction and oxidation of the dye. They become soluble when reduced to sodium sulphide and exhibit affinity for cellulose. But on exposure to air, they get oxidised to insoluble dye inside the fiber. For example, sulphur black 1, Sulphur red 1, Sulphur orange 1, Sulphur brown 21, Sulphur green 12, etc.

Solvent dyes: These dyes are non-ionic compounds soluble in organic solvents. They are used as a solution in an organic solvent. For examples, Solvent red 24, Solvent yellow 124, solvent blue 35, Solvent orange 5, Solvent black 3, etc.

1.5.2. Dyes as a source of colour contaminant in water

The discovery of first synthetic dye, Mauveine, in 1856 by William Henry Perkin led the way to the synthesis of a wide variety of dyes to be used for various purposes. There are more than 10,000 commercially available dyes with over 7 x 105 tonnes of dye stuff produced annually [8]. Dyes are widely used in variety of industries such as textiles, rubber, paper, plastics, printing, leather, cosmetics, pharmaceuticals, food, etc., to colour their products. Textile industry is one of the largest sectors globally consuming substantial amounts of water in its manufacturing processes. As a result, a large amount of coloured wastewater is generated which is discharged into the freshwater systems without sufficient treatment. It is estimated that 2 % of dyes produced annually is discharged in effluents from associated industries [9]. Discharge of dye-bearing wastewater into natural streams and rivers poses severe problems to the aquatic life, food web and causes damage to the aesthetic nature of the environment.

1.5.3. Harmful effects of dyes

Colour is the first contaminant to be recognised in wastewater. The presence of even very small amount of dyes in water is highly visible and hence undesirable. Also, dyes have harmful effects on living organisms. Dyes absorb and reflect sunlight entering water and so can interfere with the growth of bacteria and hinder photosynthesis in aquatic plants. The problems become grave due to the fact that the complex aromatic structures of the dyes render them ineffective in the presence of heat, light, microbes and even oxidising agents and degradation of the dyes become difficult [8]. Dyes can cause allergic dermatitis, skin irritation, cancer, mutation, etc. Hence, these pose a serious threat to human health and water quality, thereby becoming a matter of vital concern.

Keeping the essentiality of colour removal, concerned industries are required to treat the dye-bearing effluents before dumping into the water bodies. Thus, the

22 scientific community shoulders the responsibility of contributing to the waste treatment by developing effective dye removal technique.

In the present investigation, removal of two dyes, namely, methylene blue (MB) and crystal violet (CV) from artificially contaminated water was investigated. A brief description of these two dyes has been discussed below.

1.5.4. Methylene blue

Methylene blue is a heterocyclic aromatic compound (a phenothiazine derivative) with the chemical formula C16H18N3SCl. Its IUPAC name is 3,7- bis(Dimethylamino)- phenothiazin-5-ium chloride. The structure of methylene blue is shown in Fig. 1.2. At room temperature it appears as a solid, odourless, dark green powder that yields a blue solution when dissolved in water. It shows maximum absorption of light around 665 nm. Methylene blue was first prepared as a stain in 1876 by German chemist Heinrich Caro. However, it was discovered to be an antidote to carbon monoxide poisoning and cyanide poisoning in 1932 by Matilda Moldenhauer Brooks [10].

Fig. 1.2. Methylene blue

1.5.4.1 Uses of Methylene blue

Methylene blue is mainly used as textile dye for colouring cotton, wool and silk. Its combination with light is known to have virucidal properties and has been used to treat plaque psoriasis [11], hepatitis C [12], adenovirus vectors [13] and to

23 inactivate staphylococcus aureus [14]. It is employed as a medication for the treatment of methemoglobinemia. This is also sometimes used as an antidote to potassium cyanide poisoning. It is used as a redox indicator in analytical chemistry. Being a photosensitiser, it is employed to create singlet oxygen in presence of oxygen and light. In this way it is used in this regard to make organic peroxides by Diels-Alder reaction. In biology, methylene blue is used as a dye for a number of different staining procedures such as Wright's stain and Jenner's stain. Methylene blue is used in aquaculture as a treatment for fungal infections.

1.5.4.2. Harmful effects of methylene blue

Inspite of several advantageous applications, methylene blue dye has a number of harmful effects on human beings. Methylene blue dose of 0.045 to 0.09 mL per pound to body weight is permissible above which some side effects are observed in humans. Most common side effects are abnormal urine and faecal colouration. But, this effect is relatively harmless and stops when the medication is stopped. The severe side effects include nausea, vomiting, stomach pain, chest pain, pale or blue skin, high fever, fast or pounding heartbeats, trouble breathing, mild bladder irritation, dizziness, mental confusion, headache, increased sweating and anemia. Thus, removal of methylene blue from wastewater is essential.

1.5.5. Crystal violet

Crystal violet belongs to triarylmethane group of dyes and has the chemical formula C25H30N3Cl. Its IUPAC name is Tris(4-(dimethylamino)phenyl)methylium chloride. The structure of crystal violet is shown in Fig. 1.3.

Fig. 1.3. Crystal violet

The dye has a violet colour with an absorbance maximum at 590 nm. The dye was first prepared by the German chemists Kern and Caro involved the reaction of dimethylaniline with phosgene to give 4,4′-bis(dimethylamino)benzophenone as an intermediate. This was then reacted with additional dimethylaniline in the presence of phosphorus oxychloride and hydrochloric acid [15].

1.5.5.1. Uses of crystal violet

Crystal violet is not used as a textile dye. Instead, it is used to dye paper and as a component of navy blue and black inks for printing, ballpoint pens and inkjet printers. It is also used to colourise diverse products such as fertilisers, antifreezes, detergents and leather. It is used as a histological stain in Gram staining for classifying bacteria. During gel electrophoresis, crystal violet can be used as a non- toxic DNA stain. In forensics, crystal violet is used to develop fingerprints. It is used as a tissue stain in the preparation of light microscopy sections. It is sometimes used as a cheap way to put identification markings on laboratory mice, since the purple colour stays on their fur for several weeks. It has antibacterial, antifungal, antihelminthic, antitrypanosomal, antiangiogenic and antitumor properties [16, 17].

1.5.5.2. Harmful effects of crystal violet

Harmful effects of crystal violet on living organisms include coughing, chest tightness, feeling of chest pressure, drowsiness, dizziness, disorientation, vertigo and mild skin irritation. Prolonged contact with the dye may cause redness, irritation and dry skin. Repeated exposure to eyes may cause redness, severe irritation, burning, tearing and blurred vision. If it entered into the blood-stream through cuts, abrasions or lesions, it may produce systemic injury with harmful effects.

1.6. Techniques available for removal of dyes from wastewater

The wastewater treatment process has already been discussed in Section 1.4. In this section the available treatment methods will be discussed with special emphasis on dye removal. These techniques can be broadly classified into three categories: Biological, chemical and physical [18].

1.6.1. Biological treatment

In this method, microorganisms such as bacteria, yeasts, fungi and algae are used to degrade different pollutants [19]. Biological methods can be broadly classified into two types- aerobic and anaerobic treatment method. Aerobic method involves the usage of free or dissolved oxygen by microorganisms to decompose the organic matter whereas in anaerobic method, decomposition of the organic wastes occurs in the absence of oxygen. However, the application of biological treatment methods is restricted due to methodological limitations such as requirement of large land area, sensitivity towards diurnal variations, toxicity of some chemicals, less flexibility in design and unsatisfactory colour elimination [20].

1.6.2. Chemical treatment

Chemical methods include coagulation, flocculation, precipitation– flocculation with Fe(II)/Ca(OH)2, electrofloatation, electrokinetic coagulation, conventional oxidation methods by oxidising agents (ozone), electrochemical processes, advanced oxidative processes, etc. The chemical techniques are often expensive, create disposal problems due to accumulation of concentrated sludge and require high input of electrical energy [21,22].

1.6.3. Physical treatment

Different physical methods such as membrane filtration (nanofiltration, reverse osmosis, electrodialysis, etc.) and adsorption techniques are widely used for the removal of dyes from wastewater. The main disadvantage associated with membrane filtration is the limited lifetime of the membrane. Fouling of the membrane occurs after a certain period of time and requires periodic replacement and thereby, reduces the economic viability of the process [23]. To overcome these limitations the adsorption method has been very commonly used. In fact it is one of the most preferred methods used for the removal of dyes from wastewater because of the various advantages such as ease of operation, simplicity of design, avoidance of secondary pollution, insensitivity to toxic pollutants, low cost and economic feasibility, etc. [24, 25].

1.7. Adsorption

Adsorption is a surface phenomenon and may be defined as the ―phenomenon of attracting and retaining the molecules of a substance on the surface of a liquid or a solid resulting into a higher concentration of the molecules on the surface‖. Adsorption process involves two components adsorbent and adsorbate. Adsorbent is the substance on the surface of which adsorption takes place while adsorbate is the substance which is being adsorbed on the surface of adsorbent.

The process of adsorption arises due to presence of unbalanced or residual forces at the surface of liquid or solid phase. In a bulk of material, every molecule is equally attracted from all sides and hence the net force experienced by each molecule in the bulk is zero. However, molecules present on the surface are not wholly surrounded by other molecules and therefore experience a net inward force towards the bulk.

1.7.1. Types of adsorption

There are two types of adsorption processes, namely, physisorption and chemisorption.

(a) Physisorption

It involves the attraction between the adsorbate molecules and the adsorbent surface via weak van der Waals forces. Physical adsorption occurs with the formation of multilayer of adsorbate on adsorbent [26, 27].

Characteristics of physisorption

. It occurs at very low temperatures and its magnitude decreases with the rise in temperature . Heat evolved in physisorption is low, varying between 4–40 kJ/mol . In case of physisorption of gases over solids, the extent of adsorption increases with increase in pressure . It is reversible . It is not specific with respect to adsorbent . The extent of adsorption increases with the increase in surface area of the adsorbent

(b) Chemisorption

Chemisorption is said to have taken place when the affinity between adsorbate and adsorbent is a chemical force or chemical bond. Chemisorption occurs with the formation of monolayer of adsorbte on adsorbent [28].

Characteristics of chemisorption

. Chemisorption occurs at low as well as high temperatures and its magnitude increases with the rise in temperature . Heat of adsorption is very high, varying between 40–400 kJ/mol . The chemisorption is not appreciably affected by small changes in pressure . Chemisorption is irreversible in nature . It is highly specific and occurs only if there is some possibility of chemical bonding between adsorbent and adsorbate . Like physisorption, chemisorption also increases with increase of surface area of the adsorbent

1.7.2. Factors affecting adsorption

Adsorption on a solid surface depends on a number of factors such as [29]:

. Surface area . Nature of the adsorbate . pH of the solution . Temperature . Nature of adsorbate

Surface Area: Adsorption is a surface phenomenon and the extent of adsorption is proportional to specific surface area. Specific surface area can be defined as that portion of the total surface area that is available for adsorption. Thus, if the solid is more finely divided and more porous, the extent of adsorption accomplished per unit weight of solid adsorbent is greater.

Nature of adsorbate: The adsorption is also influenced by the solubility of the adsorbate in the solvent. Generally, the extent of adsorption increases with decrease in solubility due to respective increase in solute-solvent interaction.

28 pH of the solution: The pH of a solution from which adsorption occurs influences the extent of adsorption. Since in most cases, the adsorption occurs via the association of hydronium or hydroxide ions, the process is greatly affected by pH of the medium. Alkaline medium offer favourable condition for the adsorption of cationic dye while anionic dye can be best adsorbed in acidic medium.

Temperature: Since adsorption is accompanied by evolution or absorption of heat depending upon the nature of adsorbent-dye interaction, the magnitude of adsorption is also dependent on temperature.

Nature of adsorbent: The physiochemical nature of the adsorbent imparts profound effects on both rate and capacity for adsorption. Adsorption is affected by the presence of functional groups and other structural characteristics. Different adsorbents adsorb a dye in a different way because of their different characteristic intrinsic nature.

1.8. Selection of adsorbent

Activated carbon has been used as most conventional adsorbent for the treatment of wastewater because of its excellent adsorption ability [30]. However, widespread use of activated carbon is restricted due to its high cost, difficulties in its regeneration and loss of adsorbent during regeneration. Ultimately these factors reduce its economic feasibility [31]. Literature survey reveals that a number of low cost substitutes have successfully been developed and used for the treatment of dyes from aqueous solutions. The materials like chitin, chitosan, modified cotton, keratin, fly ash, oil cakes, fruit peels, barks, seeds, fruit wastes and many more have extensively been used as adsorbents for the removal of dyes from wastewater. Some typical examples [32-106] of such materials are presented in Table.1.4. Since adsorption capacity (defined as the milligram of dye adsorbed per gram of the adsorbent) is a parameter used to represent the extent of adsorption under a given set of conditions, the maximum adsorption capacity of a given adsorbate-adsorbent system, wherever available, is also included in this table.

Table 1.4.

Summary of the adsorbents used for the removal of dyes from wastewater.

Maximum Adsorbent Dye adsorption Reference capacity

qm (mg/g)

Acid-treated pine cone Congo red 40.19 [32] powder

Aleurites Moluccana seeds Rhodamine B 117 [33]

Methylene blue 178 [33]

Avocado seed powder Crystal violet 95.9 [34]

Bamboo leaves Methylene blue 54.17 [35]

Banana fibre Methylene blue * [36]

Biochar-palm bark Methylene blue 2.66 [37]

Biochar-eucalyptus Methylene blue 2.06 [37]

Blast furnace slag Acid red 138 208.3 [38]

Acid green 27 265.2 [38]

Bottom ash Carmoisine A 1.78x 10-5 mol/g [39]

Fast Green FCF 25.05x10-3 mol/g [40]

Breadnut peel Malachite green 353.0 [41]

Canola residues Methylene blue 13.22 [42]

Carbon slurry Methylene blue 126 [43]

Crystal violet 211 [43]

Meldola blue 217 [43]

Chrysoidine G 104 [43]

Carbon slurry Ethyl orange 233 [43]

Adsorbent Dye Maximum Reference adsorption capacity

qm (mg/g)

Carbon slurry Metanil yellow 248 [43]

Acid blue 113 267 [43]

Cerastoderma lamarcki Malachite green 35.84 [44] shell

Citrus limetta peel Eriochrome black 46.512 [45] T

Clay Reactive Red 120 29.94 [46]

Coconut fibre Methylene blue * [36]

Coconut husk-based 2,4,6- 716.10 [47] activated carbon trichlorophenol

Cotton stalk Methylene blue 147.06 [48]

Curcuma angustifolia scales Basic violet 14 208.33 [49]

De-oiled soya Eosin yellow 1.42 x 10-5 mol/g [50]

Carmoisine A 5.62 x 10-5 mol/g [39]

Fast Green FCF 6.57 x 10-3 mol/g [40]

Dicentrarchus labrax scales Acid Blue 121 300.7 [51]

Eucalyptus sawdust Brilliant green 58.48 [52]

Eucalyptus sheathiana bark Methylene blue 45.24 [53]

Fly ash Direct black 76.33 [54]

Giombo persimmon seed Toluidine Blue 34.73 [55]

Hectorite Congo red 182 [56]

Hen feather Amido black 10B 21 [57]

Hen feather Congo red 10.60x10-5 mol/g [58]

Brilliant yellow 1.50 x 10-4 mol/g [59]

Maximum Adsorbent Dye adsorption Reference capacity

qm (mg/g)

Hevea brasiliensis seed Crystal violet 23.81 [60] shell

Illitic clay Methylene blue 24.87 [61]

Jatropha curcas pods Remazol brilliant * [62] blue R

Jujuba seeds Congo red 55.56 [63]

Kaolin-Bentonite mixture Congo red 71.43 [64]

Kaolin Congo red 49.02 [64]

Kenaf fibre Methylene blue 18.18 [65]

Lemna minor biomass Acid blue 113 59.9 [66]

Longan shell Methylene blue 141.04 [67]

Lotus leaf Methylene blue 227.1 [68]

Melaleuca diosmifolia Methylene blue 119.05 [69]

Acridine orange 116.28 [69]

Malachite green 94.34 [69]

Melon peel Methylene blue 333.33 [70]

Mineral waste from coal Aztrazon blue 74.24 [71] mining

Modified natural bentonite Congo red * [72]

Modified sphagnum peat Malachite green 121.95 [73] moss

Montmorillonite Crystal violet 370.37 [74]

Montmorillonite Basic red 18 529.63 [75]

Moroccan clay Malachite green * [76]

Maximum Reference Adsorbent Dye adsorption capacity

qm (mg/g)

Moroccan clay Methylene blue * [76]

Basic red 46 * [76]

Moroccan natural clay Methylene blue 75.18 [77]

Malachite green 156.43 [77]

Methyl orange 82.05 [77]

NaOH-modified rice husk Crystal violet 44.876 [78]

Natural Clay Methylene blue 140.84 [79]

Neem sawdust Malachite green 4.354 [80]

Olive pomace Basic green 4 41.66 [81]

Orange peel Methylene blue 95.4 [82]

Palm kernel fibre Methylene blue 95.4 [83]

Crystal violet 78.9 [83]

Peanut husk Methylene blue 72.13 [84]

Perlite Maxilon Blue 5G * [85]

Pine cone Acid Black 26 62.89 [86]

Acid Green 25 43.29 [86]

Pine cone Acid Blue 7 37.45 [86]

Pine cone powder Congo red 32.65 [32]

Pine tree leaves Basic red 46 71.94 [87]

Pinus radiate Methylene blue 109.89 [88]

Pistachio hull waste Methylene blue 389 [89]

Red mud Acid Blue 15 29.44 [90]

Maximum Adsorbent Dye adsorption Reference capacity

qm (mg/g)

Rejected tea Methylene blue 242.11 [91]

Rice husk Direct Red 31 * [92]

Direct Orange 26 * [92]

River sand Methylene blue * [93]

Rosa canina galls Methylene blue 107.53 [94]

Crystal violet 312.5 [94]

Saklıkent mud Brilliant green 1.18 [95]

Sawdust Methylene blue * [36]

Sepiolite Maxilon red GRL * [96]

Sesame hull Methylene blue 359.88 [97]

Simarouba glauca seed Malachite green 125 [98] shell

Soybean hull Safranin 11.80 [99]

Spent tea leaves Crystal violet 114.94 [100]

Tea dust Crystal violet 175.4 [101]

Water chestnut Rhodamine B 2.97 [102]

Water hyacinth Methylene blue 17.58 [103]

Water hyacinth root Dark blue-GL 60.2 [104]

Wheat bran Reactive red 180 65.79 [105]

Reactive orange 76.3 [105] 16

Reactive black 5 70.4 [105]

Direct red 80 27.3 [105]

Maximum Adsorbent Dye adsorption Reference capacity

qm (mg/g)

Wheat bran Acid red 42 166.6 [105]

Acid yellow 199 96.15 [105]

Zeolite Reactive Red 239 33.0 [106]

Reactive Blue 250 20.63 [106] * Not reported

In the present investigation, four different such low cost adsorbent based on biomass waste have been selected for the treatment of two dyes, namely, methylene blue (MB) and crystal violet (CV). These are:

. Citrus limetta peel (CLP) . Punica granatum peel (PGP) . Cucumis sativus peel (CSP) . Terminalia arjuna sawdust (TASd)

1.9. Citrus limetta

Citrus limetta is a species of citrus, commonly known as sweet lime, sweet lemon, sweet limetta or mosambi. It is native to South and South-east Asia and cultivated in the Mediterranean Basin. It grows in tropical and subtropical climates.

SCIENTIFIC CLASSIFICATION Kingdom : Plantae Division : Tracheophyta Class : Magnoliopsida Order : Sapindales Family : Rutaceae Genus : Citrus Species : C. limetta

1.9.1. Plant description Citrus limetta is a small tree with irregular branches and relatively smooth, brownish-grey bark. It has numerous long thorns. The petioles are narrowly but distinctly winged. Leaves are compound with acuminate leaflets. The plant bears white flowers. Fruits are oval and green, ripening to yellow, having greenish pulp with white pith.

Fig. 1.4. Citrus limetta fruit

Fig. 1.5. Citrus limetta fruit peels

1.9.2. Uses

Citrus limetta fruit is generally taken as a fresh fruit or consumed as juice. Its high vitamin C and essential mineral content makes it an immune boosting food and has a protective effect against damage caused by inflammation of tissues and hence, it can help in conditions like osteoarthritis and rheumatoid arthritis where the immune cells of the body cause inflammation of the tissues. It is also rich in folic acid which plays a role in the health of bones and joints. It is given to the patients suffering from jaundice because it is easy to digest and boosts liver functioning. It is quite popular in the cosmetic industry as well. The extracts of the fruit are used in a lot of products to strengthen hair, treat split ends and dandruff. Its vitamin C content is one of the reasons why it is widely used in skin care products for imparting glowing skin, improving skin tone, reducing acne and blemishes and moisturises the skin.

The peels of the fruit are usually discarded as waste which could be best used as an adsorbent for the removal of dyes from wastewater.

1.10. Punica granatum

Punica granatum is a fruit-bearing deciduous shrub or small tree commonly known as pomegranate or anaar. The pomegranate originated in the region of modern- day Iran and has been cultivated since ancient times throughout the Mediterranean region and northern India [107]. Nowadays, it is widely cultivated throughout the Middle East, North Africa, Tropical Africa, the Indian subcontinent, Central Asia, the drier parts of southeast Asia and parts of the Mediterranean Basin.

SCIENTIFIC CLASSIFICATION Kingdom : Plantae Division : Magnoliophyta Class : Magnoliospida Order : Myrtales Family : Lythraceae Genus : Punica Species : P. granatum

1.10.1. Plant description

A shrub or small tree growing 6 to 10 m high, the pomegranate has multiple spiny branches. Its leaves are opposite or sub-opposite, glossy, narrow and oblong. The flowers are bright red with three to seven petals. The edible fruit is a berry with round shape and reddish skin. Each seed has a surrounding water-laden pulp. The seeds are "exarillate", i.e., unlike some other species in the order, Myrtales, no aril is present. The sarcotesta of pomegranate seeds consists of epidermis cells derived from the integument. The seeds are embedded in a white, spongy, astringent membrane.

Fig. 1.6. Punica granatum fruit

Fig. 1.7. Punica granatum fruit peels

1.10.2. Uses

The pomegranate tree is useful in many ways and almost every part is useful in one way or other. The fruit juice makes an excellent drink which contains potassium, phosphorous and calcium as well as micronutrients like iron, manganese, zinc and copper. The juice stimulates appetite and is used in treatment of stomach disorders. It is well known fruit used for the effective treatment for anaemia. It has also been used in natural and holistic medicines to treat sore throat, cough, urinary infections, digestive disorders, skin disorders and arthritis. The bark of the branches and decoction of the roots contain an alkaloid pellatrierine and tannic acid is used as medicine to get rid of helminthes (the intestinal parasite worms in the human intestine). This decoction is reported to be effective also in the treatment of tuberculosis. Fruit seeds are rich in oil, which have hormone-producing effects and stimulate estrogen hormone. It is also used to prepare cosmetic products. The powder prepared from rind is used to make tooth powder and other cosmetic products. Decoction of the flowers is used to relieve oral and throat inflammation. The peels of Punica granatum fruit are usually rejected as waste which could be well utilised as an adsorbent for the treatment of dye contaminated water.

1.11. Cucumis sativus

Cucumis sativus is a creeping vine that bears cylindrical fruits that are used as culinary vegetables. It, commonly known as cucumbers, is originally from South Asia, but now cultivated on most of the continents. It contains more than 90% water.

SCIENTIFIC CLASSIFICATION Kingdom : Plantae Division : Magnoliophyta Class : Magnoliospida Order : Cucurbitales Family : Cucurbitaceae Genus : Cucumis Species : C. sativus

1.11.1. Plant description

The cucumber grows up trellises or other supporting frames, wrapping around supports with thin, spiraling tendrils. The plant has large leaves that form a canopy over the fruit. The fruit of the Cucumis sativus is cylindrical, elongated with tapered ends. Having an enclosed seed and developing from a flower, botanically speaking, cucumbers are classified as pepoes, a type of botanical berry.

Fig. 1.8. Cucumis sativus fruit

Fig. 1.9. Cucumis sativus fruit peel

1.11.2. Uses

The fruit of cucumis sativus has slightly sweet flavour and is mainly eaten raw in salads or sandwiches or in the form of juice. Raw non peeled cucumber is a good source of potassium, phosphorus, manganese, magnesium, vitamin C and K. It is also used for skin irritations, sunburns, reversing skin tan, hydrates skin and controls the puffiness of eyes. It helps in the elimination of waste substances from the blood stream. This is achieved either through elimination by the urine or skin. It provides sulphur needed for healthy skin cells, hair and nails. Cucumbers are therefore highly recommended for patients suffering from dermatosis, eczema and psoriasis.

The peels of cucumis sativus are usually discarded as waste and can be used as a potential low cost adsorbent to remove dyes from wastewater.

1.12. Terminalia arjuna

Terminalia arjuna is a tree of the genus Terminalia. It is commonly known as arjuna or arjun tree. It is usually grown on river banks in Bangladesh, Pakistan and India [108].

SCIENTIFIC CLASSIFICATION Kingdom : Plantae Division : Magnoliophyta Class : Magnoliospida Order : Myrtales Family : Combretaceae Genus : Terminalia Species : T. arjuna

1.12.1. Plant description

Arjuna is the large size deciduous tree. The height of the tree reaches up to 20–25 meters. It is the evergreen tree with the yellow flowers and conical leaves. It has a smooth gray bark. Fruit is 2.5–3.5 cm long, fibrous woody, glabrous with 5 hard wings, striated with numerous curved veins. It has a buttressed trunk and a vast

41 spreading crown from which the branches drop downwards. Its leaves are dull green above and pale brown beneath.

Fig. 1.10. Terminalia arjuna

Fig. 1.11. Terminalia arjuna sawdust

1.12.2. Uses

The bark of the Arjuna tree contains calcium salts, magnesium salts and glucosides. It has been used in traditional Ayurvedic herbalism. Juice of its leaf is used to cure dysentry and ear ache. It helps in maintaining the cholesterol level at the normal rate, as it contains the antioxidant properties. It strengthens the heart muscles and maintains the proper heart function. It is used for the treatment of coronary artery

42 disease, heart failure, edema, angina and hypercholesterolemia. Its bark power possesses diuretic, prostaglandin-enhancing and coronary risk factor modulating properties. It is also considered as beneficial in the treatment of asthma. It is grown in the cities and towns for the purpose of shade.

The wood of Arjuna tree is used for making carts, agricultural implements, tool handles and other carpentry items [109] which results in the production of a lot of sawdust which could be used as a potential adsorbent for the removal of dyes from wastewater.

1.13. Statement of the problem

Dyes are widely used in various industries such as textile, cosmetics, paper and pulp, leather, food processing, plastics, rubber, printing and dye manufacturing industries, etc. The coloured wastewater generated in these industries is discharged into the freshwater systems without sufficient treatment creates severe pollution problems. It gives an undesirable colour to the water body that will reduce penetration of sunlight thereby affecting photosynthetic activities of aquatic plants. Furthermore, most dyes are toxic, mutagenic and/or carcinogenic thus affecting the aquatic organisms and human health. Hence, the removal of these dyes from the effluents is essential before discharge into the aquatic ecosystem.

Various methods such as coagulation, adsorption, advanced oxidative processes, Fenton‘s process, membrane filtration, etc. are has been reported for the elimination of dyes from wastewater. Adsorption was found to be one of the most effective processes because of its economic feasibility, simple design, ease of operation, and other advantages. Activated carbon has been used conveniently for the treatment of dye-loaded wastewater. But, the use of activated carbon is restricted because of its high cost and difficulties in the regeneration of the used adsorbent which reduces the economic feasibility of the overall process.

The current research is focused on the necessity to develop alternative cost effective adsorbents. Many researchers have reported the feasibility of using various low cost adsorbents derived from natural materials, industrial and agricultural wastes and by-products as potential low cost and efficient adsorbents. A number of review articles [20, 110–112] on the use of a variety of low-cost adsorbents provide extensive information about the removal of dyes from wastewater.

In the light of the above facts and figures, the present investigation were conducted with the prime objective to –

. evaluate the feasibility of four low cost adsorbents, namely, Citrus limetta peel, Punica granatum peel, Cucumis sativus peel and Terminalia arjuna sawdust for the effective treatment of two cationic dyes (Methylene blue and crystal violet) from artificially contaminated water

. characterise the adsorbents in order to understand their surface morphology, identify the various functional groups present on its surface and to recognise the functional group involved in dye-adsorbent interaction . optimise the various parameters affecting the adsorption process such as contact time, adsorbent dosage, particle size, pH and temperature . examine the applicability of the various available isotherm models to understand the nature of dye-adsorbent interaction . study the kinetics of the dye-adsorbent systems by fitting the kinetic data in various available kinetic models. . understand the thermodynamics, determine the thermodynamic parameters and judge the feasibility of the of the adsorption process . investigate the regenerability of the used adsorbents to ensure its long term reusability and easy recovery in order to reduce the cost of the process as well as minimize the disposal problems related to it

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Chapter 2 Materials and

methods

CHAPTER 2

Materials and methods

In this chapter, details of materials used and method implied in the present investigation is briefly discussed. Specific details and concentration ranges for different adsorbate-adsorbent systems will be described in respective chapters.

2.1. Chemicals and reagents

MB and CV dyes obtained from Loba Chemie and Qualigens, India, respectively and were used without further purification. Analytical reagent grade each hydrochloric acid (Merck, Germany), sodium hydroxide (CDH, India), potassium nitrate (CDH, India), sodium chloride (CDH, India) and acetic acid (SD Fine, India) were used in the present investigation.

2.2. Raw materials for adsorbent

In the present work, four different low cost agricultural and domestic wastes were used as adsorbents to study the removal of dyes from aqueous solution. These are:

 Citrus limetta peel (CLP) - collected from local fruit vendors  Punica granatum peel (PGP) - collected from the local fruit stalls  Cucumis sativus peel (CSP) - collected from domestic waste  Terminalia arjuna sawdust (TASd) - collected from local carpentry shop

2.3. Preparation of adsorbent

CLP, as collected, was washed thoroughly by deionised doubly distilled water (DDDW) to remove dust and water soluble impurities from its surface. It was then dried in the sunlight for about 100 hours and then in an air oven at 90 °C for 24 hours

56 until the peels become crispy. The dried peels were pulverised into the fine powder by a mechanical grinder and sieved to pass through 80 BSS (British Standard Sieve) mesh. It was again washed with DDDW till the colour and turbidity of washings were totally disappeared. The washed adsorbent was finally dried in an air oven at 105 °C for about 4 hours. After drying, the mass was crushed again, screened through a set of sieves to get different fractions viz. 80–150, 150–200 and > 200 BSS scales and stored in air tight containers.

In the similar manner, the other adsorbents i.e. PGP, CSP and TASd were prepared.

2.4. Characterisation of adsorbents

All the four adsorbents were characterised by using two techniques: Scanning electron microscopy (SEM) and Fourier Transform Infra-red Sectrophotometry (FTIR).

2.4.1. Scanning Electron Microscopy

The morphological features of all the four adsorbents were analysed using Scanning Electron Microscopy (SEM) (Model: JEOL, JSM6510LV, Japan).

2.4.2. Fourier Transform Infra-Red Spectrophotometry

FTIR spectra of the pure adsorbent, MB-loaded adsorbent and CV-loaded adsorbent were recorded in the spectral range of 4000–400 cm-1 in the solid state.

2.5. Batch adsorption studies

The batch equilibrium experiments were planned to determine the efficiency of the adsorbents for the removal of MB and CV dyes from aqueous solution. 1000 mg/L stock solutions of both MB and CV dyes were prepared by dissolving 1.0 g of the dye in 1000 L DDDW. The solutions of desired concentration were prepared from the stock solution. The adsorption experiments were carried out by taking 25.0 mL of adsorbate solutions with varying initial concentrations (25–250 mg/L for MB and 10– 100 mg/L for CV) in different conical flasks of borosilicate glass. The fixed quantity of adsorbent was added to each flask kept on a shaker and equilibrated for 4 hours. After filtration, the residual concentration of MB and CV was measured by a UV–VIS

57 spectrophotometer at pre-optimised wavelengths (λmax of 665 nm for MB and 590 nm for CV). The extent of dye adsorption can be represented by two adsorption parameters, namely, removal efficiency (also known as percent removal, % R) and adsorption capacity (qe). The amount of dye adsorbed at equilibrium can be calculated by using the following equations:

(2.1)

(2.2)

where, Co and Ce are the initial and equilibrium concentrations (mg/L) of dye, respectively, V is the volume of dye solution (L) and m is the mass of adsorbent (g).

The adsorption capacity at any t time (qt) was calculated using following equation (similar to Eq. 2.1):

(2.3)

Effects of various parameters such as adsorbent dosage, pH, contact time, particle size and temperature on the adsorption were studied.

2.5.1. Effect of adsorbent dosage

The effect of adsorbent dosage was studied by adding varying concentrations of the adsorbent ranging from 0.4 g/L to 10.0 g/L to 25.0 mL of the dye solutions at room temperature. The samples were agitated in a shaker for equilibrium time. Afterwards, the samples were filtered using Whatmann no. 1 filter paper and the residual concentration of the dyes in the filtrate was determined spectrophotometrically at the optimised wavelength, λmax (665 nm for MB and 590 nm for CV). Removal efficiency and adsorption capacity were calculated using Eqs. 2.1 and 2.2.

2.5.2. Effect of contact time and initial dye concentration

A series of 25.0 mL of the dye solutions of a fixed concentration was taken in 100 mL conical flasks and accurately weighed quantity of adsorbent was added to

58 each flask. The residual concentration of dye in each flask was monitored one by one after different pre-determined time intervals (say 5, 10, 15, ---- minutes) under continuous agitation. The adsorption capacity and removal efficiency were calculated using Eqs. 2.1–2.3. The experiments were conducted for different initial concentrations of dye (25, 50,100, 150, 200 and 250 mg/L for MB and 10, 25, 50, 60, 75 and 100 mg/L for CV).

2.5.3. Effect of pH

To study the effect of pH on adsorption, batch experiments were conducted using 25 mL of the dye solution in 100 mL conical flasks. The pH of the dye solutions were adjusted in the range of 2–12. Acidic pHs were adjusted using 0.1 M HCl while the basic pHs were adjusted by adding 0.1 M NaOH dropwise. The optimum dose of the adsorbent was added in each flask and the samples were agitated till the equilibrium is established. Thereafter, the samples were filtered to determine the residual concentration of the dye in the filtrate.

2.5.4. Point of zero charge

The effect of pH on adsorption can be best explained by a parameter, point of zero charge (pHpzc), which describes the condition when electrical charge density on surface becomes zero. It can be defined as the pH at which the surface of the adsorbent has net zero charge. In acidic conditions (i.e. the lower range of pH), the adsorbent surface has positive charge because of the absorption of H+ from the solution (attracting anions). Conversely, above pHpzc, the surface is negatively charged because of the absorption of OH- ions from the solution (attracting cations/repelling anions). The point of zero charge of the adsorbents was determined by the solid addition method [2]. Solutions of different pHs were prepared in 0.1 M

KNO3 solution, adjusting its pH in the range of 2–12 using 0.1M HCl and 0.1 M

NaOH. KNO3 solution (25.0 mL) at each pH was then separately mixed with a pre- weighed adsorbent samples (1.0 g). The solutions were agitated for 48 hours at room temperature and the final pH was recorded using a pH meter. A graph of ∆pH vs pHinitial was plotted and pHpzc of adsorbent was taken as the point at which the line of

∆pH (pHinitial– pHfinal) against pHinitial graph passes through x-axis.

2.5.5. Effect of particle size

The effect of particle size on the adsorption process was studied using three different particle size fractions of adsorbent, namely, 80–150, 150–200 and >200 BSS (British Standard Sieve) mesh. Amongst them, particles of 80–150 BSS mesh size are the largest while those of >200 BSS mesh size are smallest. 25.0 mL of the dye solution was taken in conical flasks and fixed amount of dye (optimum dose) with different particle sizes was added separately. The samples were agitated for equilibrium time and the filtered to determine the residual concentration of the dye after adsorption using Eqs. 2.1–2.2.

2.6. Adsorption isotherms

The equilibrium adsorption isotherm is fundamentally very decisive in the design of any adsorption system. The equilibrium relationships between adsorbent and adsorbate can be described by adsorption isotherms. In the present work, the adsorption data were analysed in the light of four well-known isotherm models, namely, Langmuir, Freundlich, Temkin and Dubinin-Radushkevich adsorption isotherm models.

2.6.1. Langmuir adsorption isotherm

The Langmuir isotherm has been commonly used to discuss various adsorbate- adsorbent combinations for both liquid and gas phase adsorptions [3]. Langmuir adsorption isotherm model is based on the following assumptions:

(a) The surface of the adsorbent available for adsorption is assumed to be uniform, i.e., all the sites available for adsorption are equivalent. (b) There is no sideways interaction between molecules of adsorbate. (c) Only a monolayer is assumed to be formed, i.e. molecules of adsorbate do not deposit on another molecules of adsorbate which are already adsorbed. Instead, they only deposit on the remaining surface available for the adsorption.

This isotherm can be mathematically represented as:

(2.4)

60 where, qm is the maximum adsorption capacity (mg/g) to form a complete monolayer coverage on the surface at high equilibrium adsorbate concentration (Ce) (mg/L) and

KL (L/mg) is Langmuir constant related to affinity between the adsorbate and adsorbent.

The above equation can be rearranged to following linearised form:

(2.5)

Thus, the Langmuir constants qm and KL can calculated from the slope and intercept of plot between 1/qe vs 1/Ce.

The essential characteristics of Langmuir isotherm can be expressed by dimensionless parameter known as separation factor, RL, which is defined as:

(2.6)

where, Co (mg/L) is the initial concentration of dye. The value of RL throws light on the nature of adsorption to be either unfavourable (RL > 1), linear (RL = 1), favourable

2.6.2. Freundlich adsorption isotherm

The Freundlich isotherm is an empirical model that is based on adsorption on a heterogeneous surface [4]. The Freundlich model can be mathematically represented respectively in the non-linear and linear forms as:

(2.7)

(2.8)

1-1/n 1/n where, KF (mg L /g) and n are Freundlich constants related with the adsorption capacity and adsorption intensity, respectively.

2.6.3. Temkin adsorption isotherm

Temkin isotherm is the early model describing the adsorption of hydrogen onto platinum electrodes in acidic solutions [5]. The isotherm contains a factor that explicitly taking into the account of adsorbent–adsorbate interactions. By ignoring the extremely low and large value of concentrations, the model assumes that heat of adsorption (function of temperature) of all molecules in the layer would decrease linearly rather than logarithmically with coverage [6]. The linear form of the Temkin adsorption isotherm is given as:

(2.9) where, B = RT/b, b is Temkin isotherm constant related with heat of adsorption

(J/mol) and KT is the equilibrium binding constant (L/g).

2.6.4. Dubinin-Radushkevich (D-R) isotherm

Dubinin–Radushkevich isotherm is an empirical model initially conceived for the adsorption of subcritical vapours onto micropore solids following a pore filling mechanism [7]. It is generally applied to express the adsorption mechanism with a Gaussian energy distribution onto a heterogeneous surface [8, 9]. The model has often been successfully fitted to high solute activities and intermediate range of concentrations data well but has unsatisfactory asymptotic properties and does not predict the Henry’s law at low pressure [10]. The approach was usually applied to distinguish the physical and chemical adsorption of metal ions [11]. The linear form of Dubinin-Radushkevich (D-R) isotherm model [12] is given as follows:

(2.10)

(2.11)

where, ε is the polyani potential, β is a constant related to the mean adsorption energy (E) which is given by the following equation:

(2.12) √

2.7. Adsorption kinetics

Kinetic models were used to determine the rate of the adsorption process. The kinetic data for the various adsorbate-adsorbent systems studied in the present work were analysed in the light of four different kinetic models, namely, pseudo-first order, pseudo-second order, intraparticle diffusion and Elovich.

2.7.1. Pseudo-first order kinetic model

The liner form of pseudo-first order kinetic model described by Langergren is given as [13]:

(2.13)

where, k1 is the adsorption rate constant (1/min). A linear plot of ln (qe–qt) against time allows one to obtain the rate constant. If the plot was found to be linear with good correlation coefficient, it indicates that Lagergren’s equation is appropriate for the adsorbate-adsorbent system.

2.7.2. Pseudo-second order kinetic model

Pseudo-second order kinetic model is based on the assumption that chemisorption is the rate-limiting step. Its linear form is represented as [14, 15]:

(2.14)

where, t is time (min) and k2 is the pseudo-second order rate constant (g/mg min). The equilibrium adsorption capacity (qe), and the constant k2 can be determined experimentally from the slope and intercept of plot t/qt versus t.

2.7.3. Intraparticle diffusion model

Intraparticle diffusion model is based on the theory proposed by Weber and Morris which explains the mechanism of adsorption through diffusion and mathematically expressed as [16, 17]:

⁄ (2.15)

1/2 where, kid is intraparticle diffusion rate constant (mg min /g) and C is a constant.

The intraparticle diffusion constant kid can be obtained from the slope of the plot of qt vs t1/2. If the linear plot of intraparticle diffusion model does not pass through the origin, this means that the intraparticle diffusion was not the rate-limiting step of adsorption process and indicates some degree of boundary layer control. This deviation from the origin may be due to difference in the rate of mass transfer in the initial and final stages of adsorption [18].

2.7.4. Elovich model

Elovich model is used to explain the adsorption of gases onto adsorbent. According to this model, due to increase of surface coverage rate of adsorption decreases with increasing time. The linear form of the model may be expressed as [19, 20]:

(2.16)

where, α (mg/g min) is the initial adsorption rate of Elovich model, β (g/mg) is the desorption constant of Elovich model and t (min) is time. Thus, the constants can be obtained from the slope and the intercept of a straight line plot of qt against ln t.

2.8. Thermodynamic studies

To investigate the effect of temperature, the adsorption experiments were performed at 293, 303, 313 and 323 K and the thermodynamic parameters were determined using the following equations [21]:

(2.17)

(2.18)

(2.19)

(2.20)

64 where, ∆G˚ is the Gibbs free energy change (kJ/mol), ∆H˚ is the enthalpy change (J/K mol), ∆S˚ is the entropy change (J/K mol), Kc is the equilibrium constant, R is the gas constant (8.314 J/K mol) and T is the temperature (K). The values of ∆H˚ and ∆S˚ were calculated from the slope and intercept of ln Kc versus 1/T plot.

2.9. Desorption

One of the most important aspects of the adsorbent is its long term reusability and easy recovery which will ultimately reduce the cost of the process and also minimise the disposal problems related to it [22]. The regenerability of the used adsorbent was studied in different media (acidic, basic and neutral) under the optimum conditions of adsorbent dose, pH and particle size. For desorption, the adsorbent was added to 25.0 mL of dye solution and agitated for equilibrium time. Dye-loaded adsorbent particles were separated from the dye solution, washed with DDDW 3–4 times to remove the traces unadsorbed dye molecules and dried in an air oven. This dye-loaded adsorbent was added to 25.0 mL of different desorbing agents

(DDDW and 0.1 M each of HCl, CH3COOH, NaCl and NaOH) and shaken for 6 hours. The percentage desorption (% D) was calculated using the following equation:

(2.21)

References

[1] W.B. James, New approach to high-precision Fourier Transform spectrometer design. Appl. Optics., 1996, 35 (16), 2891–2896. [2] J. Su, H.G. Huang, X.Y. Jin, X.Q. Lu and Z.L. Chen, Synthesis, characterization and kinetic of a surfactant-modified bentonite used to remove As (III) and As (V) from aqueous solution. J. Hazard. Mater., 2011, 185 (1), 63–70. [3] I. Langmuir, The constitution and fundamental properties of solids and liquids. Part I. Solids. J. Am. Chem. Soc., 1916, 38(11), 2221–2295. [4] H.M.F. Freundlich, Über die adsorption in lösungen. Z. Phys. Chem., 1906, 57, 385–470. [5] M.I. Temkin and V. Pyzhev, Kinetics of ammonia synthesis on promoted iron catalyst. Acta Phys. Chim. USSR., 1940, 12, 327–356. [6] C. Aharoni and M. Ungarish, Kinetics of activated chemisorption. Part 2. Theoretical models, J. Chem. Soc. Faraday Trans., 1977, 73, 456–464. [7] M.M. Dubinin and L.V. Radushkevich, The equation of the characteristic curve of the activated charcoal. Proc. Acad. Sci. USSR Phys. Chem. Sect., 1947, 55, 331–337. [8] A. Gunay, E. Arslankaya and I. Tosun, Lead removal from aqueous solution by natural and pretreated clinoptilolite: adsorption equilibrium and kinetics. J. Hazard. Mater., 2007, 146, 362–371. [9] A. Dabrowski, Adsorption—from theory to practice. Adv. Colloid Interf. Sci., 2001, 93, 135–224. [10] O. Altin, H.O. Ozbelge and T. Dogu, Use of general purpose adsorption isotherms for heavy metal–clay mineral interactions. J. Colloid Interf. Sci., 1998, 198, 130–140. [11] M.M. Dubinin, The potential theory of adsorption of gases and vapors for adsorbents with energetically non-uniform surface. Chem. Rev., 1960, 60, 235–266. [12] T.A. Khan, S. Dahiya and I. Ali, Use of kaolinite as adsorbent: Equilibrium, dynamics and thermodynamic studies on the adsorption of Rhodamine B from aqueous solution. Appl. Clay Sci., 2012, 69, 58–66.

[13] S. Lagergren, About the theory of so-called adsorption of soluble substances. Kungliga Svenska Vetenskapsakademiens Handlingar, Band., 1898, 24 (4), 1– 39. [14] Y.S. Ho and M. McKay, Sorption of dye from aqueous solution by peat. Chem. Eng. J., 1998, 70, 115–124. [15] Y.S. Ho and G. McKay, The kinetics of sorption of divalent metal ions onto sphagnum moss peat. Water Res., 2000, 34, 735–742. [16] L. Chen and B. Bai, Equilibrium, kinetic, thermodynamic, and in situ regeneration studies about methylene blue adsorption by the raspberry-like TiO2@yeast microspheres. Ind. Eng. Chem. Res., 2013, 52, 15568–15577. [17] L. Xiong, Y. Yang, J. Mai, W. Sun and C. Zhang, Adsorption behavior of methylene blue onto titanate nanotubes. Chem. Eng. J., 2010, 156, 313–320. [18] D.H.K. Reddy, K. Seshaiah, A.V.R. Reddy, M.M. Rao and M.C. Wang, Biosorption of Pb2+ from aqueous solutions by Moringa oleifera bark: equilibrium and kinetic studies, J. Hazard. Mater., 2010, 174, 831–838. [19] M.J.D. Low, Kinetics of chemisorption of gases on solids. Chem. Rev., 1960, 60, 267–312. [20] S.H. Chien and W.R. Clayton, Application of Elovich equation to the kinetics of phosphate release and sorption in soils. Soil Sci. Soc. Am. J., 1980, 44, 265– 268. [21] M. Auta and B.H. Hameed, Chitosan–clay composite as highly effective and low-cost adsorbent for batch and fixed-bed adsorption of methylene blue, Chem. Eng. J., 2014, 237, 352–361. [22] C. Namasivayam and D. Kavitha, Removal of Congo Red from water by adsorption onto activated carbon prepared from coir pith, an agricultural solid waste. Dyes Pigments., 2002, 54, 47–58.

Chapter 3

Utilisation of Citrus limetta peel for the removal of methylene blue and crystal violet from

aqueous solution

CHAPTER 3

Utilisation of Citrus limetta peel for the removal of methylene blue and crystal violet dyes from aqueous solution

3.1. Introduction

Water is essential for the survival of all living organisms. Today contamination of freshwater systems with a wide variety of pollutants is a subject of great concern. Out of all the contaminants present in industrial effluents, dyes are an important class of pollutants and can be identified even by human eye. Dyes are used as colouring agents in variety of industries such as textiles, food, paper, rubber, plastics, cosmetics, leather, etc. The discharge of wastewater from these industries to water resources causes unavoidable problems due to the toxic and unpleasant nature of dyes. The presence of dyes in water in trace amount is undesirable because most of them are toxic, mutagenic and/or carcinogenic [1]. Dyes also prevent light penetration and thereby reduce photosynthetic activities of water streams and disturb aquatic equilibrium. Thus, removal of dyes from wastewater before discharge is a challenging task.

Methylene blue (MB), a cationic dye, is most commonly used as colouring agent for cotton, wool and silk. It is also used as a staining agent to make certain body fluids and tissues easier to view during surgery and diagnostic examinations. The medical applications of MB also include the treatment of methaemoglobinemia and cyanide poisoning. In spite of several applications, this dye has a number of negative impacts on human beings and animals; such as irritation of mouth, throat, oesophagus and stomach with symptoms of nausea, abdominal discomfort, vomiting and diarrhoea. Skin contact may cause mechanical irritation resulting in redness and itching.

Crystal violet, also known as methyl violet 10B, is a cationic or basic dye. It is used to dye paper and as a component of navy blue and black inks for printing, ballpoint pens and inkjet printers. It is also used as colourant for diverse products such as fertilisers, antifreezes, detergents and leather. It is also used as a histological stain, particularly in Gram staining for classifying bacteria. In forensics, it is used to develop fingerprints. It has antibacterial, antifungal, antihelminthic, antitrypanosomal, antiangiogenic and antitumor properties. It is commonly used for marking the skin for surgery preparation, allergy testing, yeast infections, tinea and ringworm. Overexposure leads to coughing, chest tightness, chest pressure, drowsiness, dizziness, disorientation, vertigo and discomfort. Skin contact causes mild skin irritation. Prolonged contact may cause redness, irritation and dry skin. Eye contact causes serious eye damage, pain and profuse watering of the eyes leading to tissue damage, redness, severe irritation, burning, tearing and blurred vision. Thus, removal of MB and CV dyes from wastewater is of great concern from human and environmental aspects.

Several techniques like flocculation, adsorption, oxidation, electrolysis, biodegradation, ion-exchange, photo catalysis have been employed for the removal of dyes from wastewater [2]. Amongst the various techniques, adsorption has received considerable attention due to its several advantages in terms of cost, ease of operation, insensitivity to toxic pollutants, flexibility and simplicity of design [3, 4]. Among variety of adsorbents, activated carbon may be logically the most preferred adsorbent for the removal of dyes because of its excellent adsorption ability [5]. However, widespread use of activated carbon is restricted because of its high cost [6]. Thus, attention has shifted to find cheaper and efficient alternatives of activated carbon. Natural materials, domestic, agricultural and industrial wastes and bio-sorbents represent potential alternatives. A number of non-conventional and low cost adsorbents have been proposed by many workers for the removal of dyes [7–10]. These include agricultural waste products (saw dust [11], bark [12], orange peel [13]), industrial waste products (metal hydroxide sludge [14], red mud [15], fly ash [16]), clay materials (bentonite [17], diatomite [18]), zeolites [19, 20], siliceous materials (silica beads [21], alunite [22], dolomite [23]), biosorbents (chitosan [24], peat [25], biomass [26, 27]) and others (cyclodextrin [28, 29], starch [30], cotton [31]) etc.

Many low cost adsorbents such as jack fruit peel [32], garlic peel [33], hazelnut shell [34], pine apple stem [35], longan shell [36], spent tea leaves [37] zeolite [38], corn cobs [39], etc. have been reported in literature for the adsorption of methylene blue dye. Similarly, the removal of CV dye from wastewater has been studied by many researchers using many low cost adsorbents such as wheat straw [40], bottom ash [41], de-oiled soya [41], coniferous pinus bark powder [42], grape seed [43], kaolin [44], Eichhornia plant [45], apricot waste [46], coffee waste [47], Syzygium cumini leaves [48], breadfruit [49], algae [50], etc. However, literature survey reveals that so far no considerable effort has been made to study the treatment of MB and CV by citrus limetta peels. Citrus limetta is a species of citrus family, commonly known as sweet lime, sweet lemon or mosambi. It is a native to south and south-east Asia and cultivated in the Mediterranean Basin. In India, it is available throughout the year and abundantly during the months of July and August and also from November to March. It is generally taken as a fresh fruit or consumed as juice. Its juice is commonly sold by roadside stalls and mobile vendors. The peels of citrus limetta are discarded as waste. In view of the above facts, the present investigation was undertaken with the prime objective to explore the feasibility and utilisation of Citrus limetta peel (CLP) for the adsorptive removal of MB and CV dyes. It has also been decided to optimise, wherever possible, the important variables which affect the adsorption capacity.

3.2. Experimental

The batch equilibrium experiments were planned to determine the efficiency of CLP for the removal of MB and CV from aqueous solution. The adsorption experiments were carried out by taking 25 mL of adsorbate solutions with varying initial concentrations (25–250 mg/L for MB and 10–100 mg/L for CV dye) in different conical flasks.

For MB-CLP system, the fixed quantity (0.05 g) of adsorbent was added to each flask kept on a shaker and equilibrated for 4 hours. After filtration, the residual concentration of MB in each flask was measured by a UV-VIS spectrophotometer at a pre-optimised λmax of 665 nm. Experiments were also carried out with CV dye in the similar manner as mentioned above using 0.1 g of CLP adsorbent and the residual concentration of CV dye was measured at λmax of 590 nm. The effects of various

70 parameters affecting adsorption process i.e. contact time, adsorbent dose, pH, particle size and temperature were studied and optimised.

The desorption experiments were conducted in different desorbing media (0.1

M HCl, 0.1 M NaOH, 0.1 M CH3COOH, 0.1 M NaCl and water). 0.5 g adsorbent was treated with 50 mL of 50 mg/L dye solution (i.e. both MB abd CV separately) for 3 hours. The dye-loaded adsorbents were filtered and thoroughly washed several times with deionised doubly distilled water (DDDW) to remove any unadsorbed dye present. The dye-loaded adsorbents were then agitated with 25 mL of different desorbing solutions and equilibrated for 4 hours. The desorbed dye concentration was measured and percent desorption was calculated.

3.3. Results and discussion

3.3.1. Material characterisation

The morphological characteristics of CLP adsorbent before and after adsorption with MB and CV dyes were analysed by Scanning electron microscopy and the micrographs are presented in Figs. 3.1a–3.1c. It can be seen in the micrograph that the surface of CLP adsorbent is highly irregular with cracks and crevices. But after adsorption, the pores of CLP adsorbent were filled with MB (Fig. 3.1b) and CV (Fig. 3.1c) dye molecules.

Fig. 3.1a. SEM image of CLP adsorbent

Fig. 3.1b. SEM image of MB-loaded CLP

Fig. 3.1c. SEM image of CV-loaded CLP

Presence of different functional groups was determined by employing FTIR spectrophotometric method. The FTIR spectra of CLP before and after adsorption with MB are shown in Figs. 3.2a and 3.2b, respectively. The band at 3442 cm-1 might be due to O–H stretching of carboxyl group. The band at 2925 cm-1 might be due to antisymmetric and symmetric stretching of C–H bond of methyl and methylene groups. Sharp band at 1742 cm-1 is due to C=O stretching and strong band at 1643 cm- 1 may be attributed to C=O stretching of carboxylic acid. In MB-loaded CLP, the decrease in peak intensity at 3442cm-1 and 1643 cm-1 indicates the involvement of hydroxyl group and carboxyl group, respectively, in binding with MB during adsorption. Minor changes in other frequencies have also been observed.

In case of CV-loaded CLP, as seen in Figs. 3.2a and 3.2c, shifts in the position of some peaks (1742 cm-1 to 1735 cm-1 and 1643 cm-1 to 1636 cm-1) and change in peak intensity have been appeared. This indicates the involvement of –COOH and – COO groups in binding with the CV dye in the adsorption process.

102 CLP 100

92 % Transmittance %

88 4000 3500 3000 2500 2000 1500 1000 500 wavenumber (cm-1)

Fig. 3.2a. FTIR spectrum of CLP adsorbent

102 MB+CLP 100

94 % Transmittance %

90 4000 3500 3000 2500 2000 1500 1000 500 -1 wavenumber (cm )

Fig. 3.2b. FTIR spectrum of MB-loaded CLP

CV+CLP 100

70 % Transmittance %

4000 3500 3000 2500 2000 1500 1000 500 -1 wavenumber (cm )

Fig. 3.2c. FTIR spectrum of CV-loaded CLP

3.3.2. Effect of contact time and initial dye concentration

The effects of contact time and initial dye concentration on the adsorption capacity as calculated by Eq. 2.3 (Section 2.5, Chapter 2) of CLP at different initial concentrations of MB are shown in Fig. 3.3a. The figure shows that adsorption capacity increases with contact time and reaches to equilibrium after 3 hours. However, the increase is relatively higher during initial 30 minutes. Rapid increase in adsorption during the initial stage may presumably be due to the availability of vacant active sites on the surface of the adsorbent. The slow increase at the later stage is due to the diffusion of dye into the pores of the adsorbent because the external sites are completely occupied. It is also inferred from the figure that the adsorption capacity increases with increasing initial dye concentration at any dye-adsorbent contact time.

As shown in Fig. 3.3b, similar trend was also observed for adsorption of CV dye onto CLP adsorbent but in this case the equilibrium was achieved only after 1 hour. The adsorption capacity also increases with the increase in the initial dye concentration.

120

250 mg/L 80 200 mg/L 150 mg/L 100 mg/L

40 50 mg/L

25 mg/L

Adsorption capacity (mg/g) capacity Adsorption

0 0 50 100 150 200 250 300 t (min)

Fig. 3.3a. Effect of contact time on the adsorption of MB onto CLP at different concentrations (Reaction conditions: Adsorbent dose = 2.0 g/L, Volume of MB solution = 25 mL, Temperature = 298 K and pH = 9.0)

20 100 mg/L 75 mg/L 60 mg/L 50 mg/L 10 25 mg/L

10 mg/L Adsorption capacity (mg/g) capacity Adsorption

0 0 50 100 150 200 250 t (min)

Fig. 3.3b. Effect of contact time on the adsorption of CV onto CLP at different concentrations (Reaction conditions: Adsorbent dose = 4.0 g/L, Volume of CV solution = 25 mL, Temperature = 298 K and pH = 9.0)

3.3.3. Effect of adsorbent dosage

The effect of adsorbent dose on the equilibrium adsorption capacity and removal efficiency (Calculated by using Eqs. 2.1 and 2.2, Section 2.5, Chapter 2) for MB is shown in Fig. 3.4a. It has been observed that as the concentration of CLP adsorbent is increased from 0.4 to 2.0 g/L, removal efficiency is increased rapidly from 94.6% to 97.1%. Thereafter, no significant change has been observed. As the adsorption saturation is reached at adsorbent dose above 2.0 g/L, this concentration was chosen as optimum dose for further studies. The increase in removal efficiency in this range of adsorbent (0.4 – 2.0 g/L) is due to increase in total surface area and the availability of more binding sites for adsorption. The decrease in adsorption capacity with increase in adsorbent dosage might be due to interaction of adsorbent particles like aggregation or agglomeration which resulted to decrease of effective surface area per unit weight of the adsorbent.

In case of adsorption of CV dye, it has been observed that as the concentration of CLP is increased from 0.4 – 4.0 g/L, the removal efficiency increased from 90.0% to 94.9% while the adsorption capacity decreased from 112.5 mg/g to 11.9 mg/g (Fig. 3.4b). No significant change in the adsorption capacity and removal efficiency was observed with further increase in the concentration of CLP. In this case, 4.0 g/L is selected as the optimum dosage for further studies.

98 160

97 120

96 qe 80

95 40

Removal efficiency (% R) (% efficiency Removal Adsorption capacity (mg/g) capacity Adsorption

94 0 0 4 8 12 Adsorbent dosage (g/L)

Fig. 3.4a. Effect of adsorbent dosage on removal efficiency and adsorption capacity

for the adsorption of MB onto CLP (Reaction conditions: Co = 50 mg/L, Adsorbent dose = 2.0 g/L, Volume of MB solution = 25 mL, Temperature = 298 K and pH = 9.0)

98 120

80 94 % R qe 92 40

Removal efficiency (% R) (% efficiency Removal 90 Adsorption capacity (mg/g) capacity Adsorption

88 0 0 4 8 12 Adsorbent dosage (g/L)

Fig. 3.4b. Effect of adsorbent dosage on removal efficiency and adsorption capacity

for the adsorption of CV onto CLP (Reaction conditions: Co = 50 mg/L, Adsorbent dose = 4.0 g/L, Volume of CV solution = 25 mL, Temperature = 298 K and pH = 9.0)

3.3.4. Effect of pH

The effect of pH on removal efficiency of MB and CV dyes by CLP adsorbent is depicted in Figs. 3.5a and 3.5b. The adsorption capacity has been observed to increase drastically with increase in pH of the solution (up to a value of 4.0 for MB and up to pH value 6.0 for CV) after which it remains almost constant with the further increase in pH up to 12.0. In acidic condition i.e. at lower pH, the surface of adsorbent absorbs H+ ions and acquires positive charge resulting in an electrostatic repulsion between positively charged adsorbent and cationic dyes (MB and CV) which reduce the adsorption. Also there exists competition between cationic dye and H+ ions for the adsorption sites on CLP adsorbent. At higher pH, increased adsorption is observed because of the electrostatic attraction between cationic dyes and negatively charged adsorbent (because of the absorption of OH- ions in alkaline medium). The result is in agreement with the existing hypothesis of increasing negatively charged sites/decreasing positively charged sites of adsorbent with increase of pH [51].

92 Removal efficiency (%R) efficiency Removal 90

88 0 5 10 15 pH

Fig. 3.5a. Effect of pH on adsorption of MB on to CLP (Reaction conditions: Co= 50 mg/L, Adsorbent dosage = 2.0 g/L, Volume of MB solution = 25 mL, Temperature = 298 K, pH = 9.0 and Time = 3 hours)

100

Removal efficiency (% R) (% efficiency Removal 88

84 0 5 10 15 pH

Fig. 3.5b. Effect of pH on adsorption of CV onto CLP (Reaction conditions: Co= 50 mg/L, Adsorbent dosage = 4.0 g/L, Volume of CV solution = 25 mL, Temperature = 298 K, pH = 9.0 and Time = 1 hour)

3.3.5. Point of zero charge

The point of zero charge (pHpzc) value of CLP was found to be 8.0 (Fig. 3.6). This indicates that the adsorbent surface has positive charge at pH < 8.0, net zero charge at pH = 8.0 and negative charge at pH > 8.0. Therefore, point of zero charge study reflects that the favourable condition for adsorption of cationic dye by CLP adsorbent is the medium having pH greater than 8.0. Thus a safer pH value of 9.0 was selected for the adsorption studies of MB and CV onto CLP adsorbent.

pHi

0 4 8 12 ∆pH

-2

-4

-6

Fig. 3.6. Point of zero charge for CLP (Reaction conditions: [KNO3] = 0.1 M, Concentration of CLP adsorbent: 0.1 g, Time: 48 hours, Temperature: 298 K)

3.3.6. Effect of particle size

Adsorption of MB and CV dyes on CLP adsorbent was studied using three different size ranges of adsorbent particles (80–150, 150–200 and >200 BSS mesh). Fig. 3.7 shows the effect of particle size on the removal efficiency of MB and CV. It has been observed that as the particle size is decreased, removal efficiency is increased from 93.5% to 98.2% for MB whereas for CV, the removal efficiency increased from 97.3% to 98.7%. It is due to the fact that smaller particle size provides large surface area for adsorption which results in the higher removal of dye. Maximum removal efficiency is associated with mesh size >200. However, because of handling problem accompanying with small particles and for easy separation of solid and liquid phases, particles of 80–150 BSS mesh size range have been chosen throughout.

100

96 MB + CLP CV + CLP 94

Removal efficiency (%R) efficiency Removal 92

90 80-150 150-200 >200 Mesh size

Fig. 3.7. Effect of particle size on adsorption of MB and CV onto CLP (Reaction

conditions for MB-CLP system: Co = 50 mg/L, Adsorbent dose = 2.0 g/L, Time = 3 hours, Temperature = 298 K and pH = 9.0. Reaction conditions

for CV-CLP system: Co = 50 mg/L, Adsorbent dose = 4.0 g/L, Time = 1 hour, Temperature = 298 K and pH = 9.0)

3.3.7. Adsorption isotherms

The experimental results have been fitted on the Langmuir, Freundlich, Temkin and Dubinin-Radushkevich (D-R) isotherm models. For this purpose the linear mathematical forms of these models (as described in Section 2.6, Chapter 2) were used. The values of different isotherm constants for the adsorption of MB and CV onto CLP are listed in Table 3.1a. In the light of relative values of correlation coefficients (R2), Table 3.1a clearly indicates that the isotherm data for MB can be best represented by Langmuir adsorption isotherm model. The linear plot of this model illustrated in Fig. 3.8a has generated following solved equation:

(R² = 0.9787) (3.1)

It is worth to mention here that adsorptive removal of MB dye by other adsorbents obtained from agricultural waste such as wheat straw [52], cotton stalk [53], cucumber peels [54], rice hull ash [55], shaddock peel [56], cottonseed hull [57], banana leaves [58] and Bacillus subtilis [59] and clay [60] has also been found to obey Langmuir isotherm. The values of Langmuir constants as obtained from Eq. 3.1 have been compared with those obtained by above investigators in Table 3.1b. This table clearly indicates that the results obtained in the present study fall within the ranges comparable to those reported earlier.

For the adsorption of CV onto CLP adsorbent, the best model representing the equilibrium data was found to be Temkin adsorption isotherm model (Table 3.1a). The validity of this isotherm in the present case is confirmed by the linear plot shown in Fig. 3.8b with R2 value of 0.9683. The result of Temkin isotherm has been obtained in the form of following mathematical equation:

(R² = 0.9683) (3.2)

The values of Temkin constants have been included in Table 3.1.

Table 3.1a.

Isotherm parameters for the adsorption of MB and CV onto CLP (Reaction conditions for MB-CLP system: Co = 50 mg/L, Adsorbent dose = 2.0 g/L, Time = 3 hours,

Temperature = 298 K and pH = 9.0. Reaction conditions for CV-CLP system: Co = 50 mg/L, Adsorbent dose = 4.0 g/L, Time = 1 hour, Temperature = 298 K and pH = 9.0)

Isotherm models Parameters MB dye CV dye

Langmuir qm (mg/g) 227.3 303.03

KL (L/mg) 0.0289 0.0282

RL 0.4089 0.972

R2 0.9787 0.9183

Freundlich n 1.438 1.2998

1-1/n 1/n KF (mg L /g) 8.758 8.0229

R2 0.9676 0.9288

Temkin b (J/mol) 83.084 339.56

KT (L/g) 0.648 4.2550

R2 0.9756 0.9683

D-R qD (mg/g) 72.457 21.977

2 -8 β 193.4 x 10 2 x 10

R2 0.8815 0.9227

0.1

Langmuir equation

0.08 1/qe= 1/qmKLCe + 1/qm

0.06

e 1 / q / 1 0.04

0.02

0 0 0.1 0.2 0.3 0.4 0.5 0.6

1 / Ce

Fig. 3.8a. Langmuir adsorption plot of MB onto CLP adsorbent (Reaction conditions:

Co = 50 mg/L, Adsorbent dose = 2.0 g/L, Volume of MB solution = 25 mL, Time = 3 hours, Temperature = 298K and pH = 9.0)

Table 3.1b.

Langmuir isotherm parameters for the adsorption of MB by different adsorbents

Systems Langmuir constants R2 Reference KL (L/mg) qm (mg/g)

MB-Wheat straw 0.0036 274.1 0.9984 [52]

MB-Cotton stalk 0.0249 147.1 0.9970 [53]

MB-cucumber peels 0.0573 111.1 0.9991 [54]

MB-rice hull ash 0.606 17.1 0.9987 [55]

MB-Shaddock peel 0.0146 309.6 0.9993 [56]

MB-Cottonseed hull 0.12755 185.2 0.9994 [57]

MB-Banana leaves 0.116 109.9 0.9996 [58]

MB-Bacillus subtilis 0.0164 169.5 0.9884 [59]

MB-Clay 0.022 140.84 0.989 [60]

MB-citrus limetta 0.0289 227.3 0.9787 Present study

Temkin equation

20 qe= B ln Ce + B ln KT

e q 10

0 -1.2 -0.7 -0.2 0.3 0.8 1.3 1.8

ln Ce

Fig. 3.8b. Temkin adsorption for the adsorption of CV onto CLP (Reaction

conditions: Co= 50 mg/L, Adsorbent dose = 4.0 g/L, Volume of CV solution = 25 mL, Time = 1 hour, Temperature = 298K and pH = 9.0)

3.3.8. Adsorption kinetics

The kinetic data have been analysed in the light of different kinetic models, namely, pseudo-first order, pseudo-second order, intraparticle diffusion and Elovich models by employing Eqs. 2.13–2.16 (Section 2.7, Chapter 2). The kinetic parameters associated with these models so obtained are summarised in Table 3.2a. On comparing the values of correlation coefficient, one can infer that the pseudo-second order kinetic model is best one to represent the adsorption results of both dyes i.e. MB and CV. From the linear plots shown in Figs. 3.9a and 3.9b, following mathematical equations have been obtained for the pseudo-second order kinetics for the adsorption of MB and CV by CLP, respectively:

(R² = 0.9999) (3.3)

(R² = 0.9999) (3.4)

Pseudo-second order kinetics have also been observed to be obeyed for the adsorption of MB onto different adsorbents such as wheat straw [52], cotton stalk [53], parsley stalk [54], rice hull ash [55], shaddock peel [56], Arthrospira platensis [61] and coconut bunch waste [62]. The present values of pseudo-second order rate constant and qe,cal as obtained by Eq. 3.3 and those of the above investigators are incorporated in Table 3.2b.

Similarly, the adsorption of CV onto CLP adsorbent have also been found to obey pseudo-second order kinetic model for different adsorbents like palm kernel fibre [63], grapefruit peel [64], rice husk [65], coconut husk [66], cyperus rotundus [67] and Chaetophora elegans alga [50]. (Table 3.2c). Our values of pseudo-second order rate constant and qe,cal (obtained by Eq. 3.4) are compared with literature values in Tables 3.2c. These tables clearly indicate that our results are judiciously comparable with other investigators.

Table 3.2a.

Kinetic parameters for the adsorption of MB and CV onto CLP (Reaction conditions for MB-CLP system: Co = 50 mg/L, Adsorbent dose = 2.0 g/L, Temperature = 298 K and pH = 9.0. Reaction conditions for CV-CLP system: Co = 50 mg/L, Adsorbent dose = 4.0 g/L, Temperature = 298 K and pH = 9.0)

Kinetic models Parameters MB dye CV dye

-1 Pseudo-first order k1 (min ) 0.013 0.0919

qe, exp (mg/g) 23.333 12.189

qe, cal (mg/g) 1.092 1.7192

R2 0.9022 0.9084

Pseudo-second order k2 (g/mg min) 0.057 0.1031

qe, exp (mg/g) 23.333 12.189

qe, cal (mg/g) 23.255 12.3915

R2 0.9999 0.9999

1/2 Intraparticle diffusion Kid (mg min /g) 0.077 0.3465

C 22.22 10.122

R2 0.9657 0.6697

Elovich β (g/mg) 200.0 1.2794

2 5 R 0.9340 1.388 x 10

8 Pseudo-second order equation

2 t/qt= t/qe + 1/k2qe

4 t / q / t

0 0 50 100 150 200 t (min)

Fig. 3.9a. Pseudo-second order kinetic model for the adsorption of MB onto CLP

(Reaction conditions: Co = 50 mg/L, Adsorbent dose = 2.0 g/L, Volume of MB dye = 25 mL, Temperature = 298 K and pH = 9.0)

4 Pseudo-second order equation 3.5 2 t/qt= t/qe + 1/k2qe 3

2.5

2 t / q / t

1.5

0.5

0 0 10 20 30 40 50 t (min)

Fig. 3.9b. Pseudo-second order kinetic model for the adsorption of CV onto CLP (Reaction conditions: Adsorbent dose = 4.0 g/L, Volume of CV dye = 25 mL, Temperature = 298 K and pH = 9.0)

Table 3.2b.

Pseudo-second order rate constant for the adsorption of MB onto different adsorbents

System Pseudo-second order model R2 Reference k2 (g/mg min) qe,cal (mg/g)

MB-Wheat straw 0.4201 280.9 0.9948 [52]

MB-Cotton stalk 0.0519 104.82 0.9998 [53]

MB-parsley stalk 0.00014 83.33 0.9998 [54]

MB-rice hull ash 0.006 23.49 0.9990 [55]

MB-Shaddock peel 0.00005 131.19 0.9998 [56]

MB-Arthrospira platensis 0.0247 27.40 0.998 [61]

MB-Coconut bunch 0.041 34.36 0.991 [62]

MB-Citrus limetta peel 0.057 23.255 0.9999 Present study

Table 3.2c.

Pseudo-second order rate constant for the adsorption of CV onto different adsorbents

System Pseudo-second order model R2 Reference k2 (g/mg min) qe,cal (mg/g)

CV-Palm kernel fibre 0.2003 8.687 0.999 [63]

CV-Grapefruit peel 0.005 24.31 0.992 [64]

CV-Rice husk 0.00234 42.053 0.998 [65]

CV-Coconut husk 0.1878 145.7 0.972 [66]

CV-Cyperus rotundus 0.167 9.52 1.0 [67]

CV-Chaetophora elegans alga 0.117 17.79 0.9993 [50]

CV-Citrus limetta peel 0.1031 12.3915 0.9999 Present study

3.3.9. Adsorption thermodynamics

The free energy change (∆G˚) associated with both MB-CLP and CV-CLP systems were calculated using by Eqs. 2.17 and 2.18 (Section 2.8, Chapter 2) and are listed in Tables 3.3a and 3.3b. The values of enthalpy change (∆H˚) and entropy change (∆S˚) were calculated from the slope and intercept of the linear plot of ln Kc vs 1/T shown in Figs. 3.10a and 3.10b are also included in Tables 3.3a and 3.3b.

The negative values of ∆G˚ indicate that the adsorption of MB onto CLP adsorbent is spontaneous. The trend of free energy with temperature further indicates that the feasibility of the adsorption increases with increase of temperature. The change in enthalpy (∆Hº) was found to be 35.13 kJ/mol (Table 3.3a). The positive value of ∆Hº signifies that the adsorption of MB onto CLP adsorbent is endothermic. Thus, the spontaneity of the adsorption is only due to entropy factor. The entropy change (∆Sº) was found to be 146.7 J/K mol. The positive value of entropy change indicates an increase in randomness at the adsorbate-solution interface during adsorption process. The increase in entropy is presumably due to gain of translational entropy by the dye molecules during adsorption process [68]. In this context, it is relevant to mention here that the increase in randomness i.e. positive entropy change has been reported on a number of adsorbent-adsorbate systems such as MB-Bacillus subtilis [59], MB-Wheat shells [69], MB-Oak sawdust [70], Acid Blue 25-Litchi chinensis [71], Reactive Orange 16-Brazilian-pine fruit shell [72], Supranol yellow 4GL-Bentonite/CTAB [73], MB/Eosin yellow-Tea waste [74], Phenol-OTMAC modified attapulgite [75], Basic yellow-Reed [76], MB-Illitic clay mineral [77], MB Coir pith [78], MB-Flyash [79].

In case of adsorption of CV onto CLP adsorbent, ∆G˚ values were found to be negative indicating that the process is spontaneous, however, the spontaneity decreases with the increase in temperature (Table 3.3b). ∆H˚ and ∆S˚ values were found to be negative indicating that the adsorption process is exothermic accompanied by a decrease in entropy (Table 3.3b). Similar trends in thermodynamics have also been observed for the adsorption of CV on to rice husk [65] and Cyperus rotundus [67].

Table 3.3a.

Thermodynamic parameters for the adsorption of MB onto CLP

(Reaction conditions: Co= 50 mg/L, Adsorbent dose = 2.0 g/L, Volume of MB solution = 25 mL, Time = 3 hours and pH = 9.0)

Temperature (K) ∆G⁰ (kJ/mol) ∆H⁰ (kJ/mol) ∆S⁰ (J/K mol)

293 7.87

303 9.38 35.13 146.69

313 10.49

323 12.41

Table 3.3b.

Thermodynamic parameters for the adsorption of CV onto CLP

(Reaction conditions: Co= 50 mg/L, Adsorbent dose = 4.0 g/L, Volume of CV dye solution = 25.0 mL, Time = 1 hour and pH = 9.0)

Temperature (K) ∆G⁰ (kJ/mol) ∆H⁰ (kJ/mol) ∆S⁰ (J/K mol)

293 9.05

303 8.53 –14.14 –27.9

313 8.34

323 8.21

5 Thermodynamic equation

4.6 ln Kc= -∆H˚/RT + ∆S˚/R

4.2

∆G˚/ RT) ∆G˚/

- (

c c 3.8 ln K ln

3.4

3 3 3.1 3.2 3.3 3.4 3.5 103 / T

Fig. 3.10a. Plot of ln Kc vs 1/T for the adsorption of MB onto CLP (Reaction

conditions: Co = 50 mg/L, Adsorbent dose = 2.0 g/L, Volume of MB dye = 25 mL, pH = 9.0 and Time = 3 hours)

3.8 Thermodynamic equation

ln K = -∆H˚/RT + ∆S˚/R

3.6 c

3.4

∆G˚/ RT) ∆G˚/

(

c c ln K ln 3.2

3 3 3.1 3.2 3.3 3.4 3.5

103 / T

Fig. 3.10b. Plot of ln Kc vs 1/T for the adsorption of CV onto CLP adsorbent.

(Reaction conditions: Co = 50 mg/L, Adsorbent dose = 4.0 g/L, Volume of CV dye = 25 mL, pH = 9.0 and Time = 1 hour)

100

3.3.10. Desorption

To investigate the possibility of regeneration of used CLP, desorption studies were carried out with different desorbing agents (0.1 M HCl, 0.1 M CH3COOH, 0.1 M NaCl, 0.1 M NaOH and DDDW). Percent desorption (%D) was calculated using Eq. 2.21 (Section 2.9, Chapter 2). Table 3.4 shows the percentage desorption efficiency of different reagents with MB and CV-loaded CLP. It was found that HCl is a better desorbing agent for the regeneration of adsorbent for both cases.

Table 3.4.

Percentage desorption of MB from MB-loaded CLP in different media

Desorbing reagent % desorption for MB- % desorption for CV- loaded CLP loaded CLP

0.1 M HCl 32.46 3.60

0.1 M CH3COOH 14.64 2.98

0.1 M NaOH 4.82 2.61

0.1 M NaCl 2.87 0.87

DDDW 2.02 0.59

101

3.4. Conclusions

In the present study, the efficiency of CLP as an adsorbent for the removal of MB and CV was investigated. It was found that adsorption is affected by various parameters like contact time, initial dye concentration, adsorbent dosage, pH and temperature. The equilibrium time for the adsorption of MB onto CLP was found to be 3 hours whereas for CV-CLP system, it was found to be 1 hour. The adsorption study also revealed that the optimum dosage for MB-CLP system was 2.0 g/L and 4.0 g/L for CV-CLP system. In acidic conditions, there is a drastic increase in uptake of dye up to pH = 4.0 and pH = 6.0 for MB and CV, respectively. Thereafter, no significant change was observed. Kinetic study showed that the adsorptive removal of both MB and CV by CLP follow pseudo-second order kinetics. Adsorption isotherm study indicated that the equilibrium data were in agreement with Langmuir model for MB-CLP system and Temkin model for CV-CLP system. The adsorption of MB dye was found to be spontaneous and endothermic accompanied by an increase in entropy whereas the adsorption of CV dye was also found to be spontaneous but exothermic and accompanied by a decrease in entropy. The recovery of CLP from MB-loaded CLP and CV-loaded CLP for reuse was found to be maximum in 0.1 M HCl.

Consequently, it was concluded that CLP is an effective adsorbent for the removal of MB and CV dyes from aqueous solution.

102

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Chapter 4

Utilisation of punica granatum peel for the removal of methylene blue and crystal violet from

aqueous solution

CHAPTER 4

Utilisation of Punica granatum peels for the removal of methylene blue and crystal violet dyes from aqueous solution

4.1. Introduction

Water pollution has become a serious hazard to the environment. With the rapid growth of industrialisation in the past few decades, the release of effluents into the water bodies has increased tremendously. One of the major sources of water contamination worldwide is the textile industries introducing dyes into water bodies. Further, dyes have become indispensable tools for a variety of industries such as food, paint, ceramics, cosmetics, glass, medicine, rubber, printing ink, leather, textiles, paper and pulp, etc. to colour their products. In most cases, the presence of even minute quantity of dye is clearly visible affecting aesthetic nature, thereby, reducing transparency and solubility of gases in water bodies. Photosynthetic activity of the aquatic flora is severely affected due to low penetration of light. Fauna is also extremely affected by the presence of dyes and the extent of damage depends on the concentration of dye as well as on the span of exposure. Also, synthetic dyes and their breakdown products are toxic, carcinogenic and mutagenic and have deteriorating effects on living organisms [1–3]. Thus, the removal of dyes from the industrial effluents before discharge in the freshwater systems has become a challenge for us.

A wide variety of techniques has been developed by researchers for the elimination of dyes from wastewater to reduce their hazardous impacts on the environment. These techniques have already been discussed in Section 1.6 (Chapter 1). Among them, adsorption technique is considered to be preferable due to a number of factors as already discussed (Section 1.6.3, Chapter 1). In fact, adsorption is economically efficient and environmentally benign technique. The economic feasibility of adsorption depends on the choice of the adsorbent. Activated carbon has been most widely used as a conventional adsorbent because of its large surface area,

110 high porosity and high adsorption capacity for a variety of pollutants [4–5]. But, the high cost of production reduces its economic feasibility [6]. Thus, the search of efficient and low cost adsorbents has increased tremendously in the recent years. A literature survey showed that researchers have developed and used a wide variety of low cost adsorbents for the removal of dyes. These include almond shells [7], Arthrospira platensis [8], Bacillus subtilis [9], bark [10], sawdust [11], chaff [12], pine apple stem [13], coconut bunch waste [14], coir pith [15], cottonseed hull [16], cotton stalk [17], egg shells [18], Ephedra strobilacea saw dust [19], garlic straw [20], grass [21], guava leaf powder [22], longan shell [23], Mahogany fruit shell [24], mango seed [25], melon peel [26], neem leaf powder [27], orange peel [28], parsley stalk [29], peanut hull [30], peat [31], platanus leaves [32], pomelo peel [33], rice hull ash [34], sand [35], sepiolite [36], shaddock peel [37], talc [38], Ulva lactuca [39], wheat bran [40] and wheat straw [41] etc.

Punica granatum is a deciduous shrub belonging to family Punicaceae. It is a native from Iran to the Himalayas in northern India and has now been cultivated throughout the Mediterranean region of Asia, Africa and Europe. This fruit, locally known as pomegranate or anaar, is juicy and refreshing with a sub-acid pleasant taste. The fruit juice can be used in soups, jellies, ice creams, cakes, other sweet dishes, etc. The peels of Punica granatum fruit are usually discarded as waste which could be better used as an adsorbent for the purification of water in the water treatment process. Also, literature survey tells that the removal of methylene blue (MB) and crystal violet (CV) dyes have not been studied with Punica granatum peels as adsorbent. Thus, in the present work, the efficacy of Punica granatum peel (PGP) as a non-conventional low cost adsorbent for the removal of MB and CV from aqueous solution has been investigated.

4.2. Experimental

Batch adsorption experiments were carried out in 100 mL conical flasks at room temperature. The equilibrium experiments were conducted to estimate the efficacy of PGP as an adsorbent for the removal of MB and CV dyes from artificially contaminated water. A fixed amount of PGP adsorbent (0.2 g) was added to 25 mL of MB dye solutions with varying initial concentrations (ranging from 25 mg/L to 250 mg/L). The samples were agitated in a rotary shaker at 25˚C for 4 hours and then

111 filtered. The residual concentration of MB dye in the filtrate was determined spectrophotometrically at a wavelength of 665 nm. Similar batch adsorption experiments were performed by using 0.15 g of PGP adsorbent in 25 mL of dye solutions at various initial concentrations of CV (ranging from 10 mg/L to 100 mg/L).

The residual concentration of CV after adsorption was determined at 590 nm (i.e. λmax of CV dye).

The effect of various parameters such as adsorbent dosage, contact time, particle size, pH and temperature were studied in a similar manner and were optimised to obtain the maximum removal of both the dyes. The point of zero charge

(pHpzc) of the adsorbent was determined using solid addition method [42]. In order to understand the thermodynamic behaviour of MB and CV adsorption onto PGP adsorbent, the equilibrium experiments were conducted at four different temperatures, viz. 293, 303, 313 and 323 K.

The adsorption is associated with a secondary task which involves the regeneration of adsorbent and recovery of adsorbate. Dye-loaded PGP was mildly washed with de-ionised doubly distilled water (DDDW) to remove any unadsorbed dye present and dried in an air oven at 30˚C until completely dry. Desorption of dye- loaded PGP was studied with 0.1 M HCl (strong acid), 0.1 M NaOH (strong base), 0.1

M NaCl (neutral salt), 0.1 M CH3COOH (weak acid) and DDDW. Accurately weight amounts of the MB-loaded PGP (0.2 g) and CV-loaded PGP (0.15 g) were added to 25 mL each of the desorbing reagent separately and were left for 6 hours. The samples were filtered and the amount of dye desorbed was determined spectrophotometrically at the respective λmax of both the dyes.

4.3. Results and discussion

4.3.1. Material characterisation

The surface morphology of PGP before and after adsorption of MB and CV dyes was analysed by Scanning electron microscopy. SEM micrograph of PGP shown in Fig. 4.1a indicates that its surface is uneven, porous with fissures and clefts resulting in an amorphous assembly. However, after adsorption, the irregularities and pores on the surface of PGP are filled with the molecules of MB (Fig. 4.1b) and CV (Fig. 4.1c) dyes up to a considerable extent.

112

Fig. 4.1a. SEM image of PGP adsorbent

113

Fig. 4.1b. SEM image of MB-loaded PGP

114

Fig. 4.1c. SEM image of CV-loaded PGP

115

FTIR spectra of PGP before and after adsorption of MB and CV dyes are shown in Figs. 4.2a–4.2c. The strong peak at 3436 cm-1 represents O–H stretching vibration of the carboxylic acid group in the adsorbent whereas the peak at 2916 cm-1 indicates the stretching vibration of aliphatic –CH3 or –CH2 groups. The peaks at 1726 cm-1 and 1618 cm-1 are attributed to C=O stretching vibration of carboxyl group and N–H bending vibration of primary amine, respectively. Sharp peak at 1010 cm-1 might be due to C–O stretch of alcohols or carboxylic acid group. It is clearly seen in Figs. 4.2a and 4.2b that there is a reduction in the peak size at 3436 cm-1 and 1618 cm-1 indicating the involvement of –OH and –NH groups in the adsorption process. In case of CV-loaded PGP, major change in peak intensity at 1618 cm-1 and 1010 cm-1 (Figs. 4.2a and 4.2c) was observed indicating the involvement of respective functional groups in the process of interaction of CV with PGP.

PGP 100

% Transmittance % 85

80 4000 3500 3000 2500 2000 1500 1000 500 wavenumber (cm-1)

Fig. 4.2a. FTIR spectrum of PGP adsorbent

116

102 MB+PGP 100

92 % Transmittance %

88 4000 3500 3000 2500 2000 1500 1000 500 wavenumber (cm-1)

Fig. 4.2b. FTIR spectrum of MB-loaded PGP

100 CV+PGP

60 % Transmittance %

4000 3500 3000 2500 2000 1500 1000 500 wavenumber (cm-1)

Fig. 4.2c. FTIR spectrum of CV-loaded PGP

117

4.3.2. Effect of contact time and initial dye concentration

The variation of adsorption capacity, calculated by using Eq. 2.3 (Section 2.5, Chapter 2), with time for the adsorption of MB and CV onto PGP is shown in Figs. 4.3a and 4.3b, respectively. It is evident from the figures that the adsorption capacity first rises rapidly in the early stage (0–30 minutes), gradually slows down after 30 minutes and lastly becomes constant after 3 hours for MB whereas in case of CV dye, the adsorption capacity becomes almost constant after about 1 hour. Rapid increase in adsorption in the initial stage is due to the accessibility of a large number of active sites on the peripheral surface of the adsorbent on which dye molecules get adsorbed through boundary layer adsorption [43]. As the time is increased, the surface of the adsorbent gets saturated progressively with dye molecules. In the later stage, dye molecules get diffused into the pores of PGP which slows down the process of adsorption [44]. The equilibrium time for the MB-PGP and CV-PGP systems were taken to be 3 and 1 hours, respectively. It is also concluded from Figs. 4.3a and 4.3b that the adsorption capacity increases with the increase in the concentration of MB (from 25 mg/L to 250 mg/L) and CV (from 10 mg/L to 100 mg/L).

118

25 250 mg/L 200 mg/L 20 150 mg/L 100 mg/L 15 50 mg/L

10 25 mg/L Adsorption capacity (mg/g) (mg/g) capacity Adsorption 5

0 0 50 100 150 200 250 t (min)

Fig. 4.3a. Effect of contact time on the adsorption capacity of MB onto PGP at different concentrations (Reaction conditions: Adsorbent dose = 8.0 g/L, Volume of MB solution = 25 mL, Temperature = 298 K and pH = 7.0)

119

12 100 mg/L 75 mg/L 60 mg/L 8 50 mg/L 25 mg/L

4 10 mg/L Adsorption capacity (mg/g) capacity Adsorption

0 0 50 100 150 200 250

t (min)

Fig. 4.3b. Effect of contact time on the adsorption capacity of CV onto PGP at different concentrations (Reaction conditions: Adsorbent dose = 6.0 g/L, Volume of CV solution = 25 mL, Temperature = 298 K and pH = 7.0)

120

4.3.3. Effect of adsorbent dosage

The effect of adsorbent dosage on the adsorption of MB and CV dyes was studied for different quantities of PGP (0.4–10.0 g/L) and the values of equilibrium adsorption capacity and removal efficiency, as determined by using Eqs. 2.1 and 2.2 (Section 2.5, Chapter 2), are plotted in Figs. 4.4a and 4.4b, respectively. It can be clearly seen from the Fig. 4.4a that the removal efficiency for MB dye increases from 37.2% to 76.5% with the increase in PGP dosage from 0.4 to 8.0 g/L. Subsequently, there is no major change in the removal efficiency with further increase in adsorbent dosage. The optimum adsorbent dosage for MB-PGP system was found to be 8.0 g/L. However, in case of CV-PGP system, the removal efficiency increases from 82.6% to 91.4% on increasing the PGP dosage from 0.4 to 6.0 g/L (Fig. 4.4b) and hence, 6.0 g/L was selected as optimum dosage for further adsorption studies. The increase in removal efficiency for both the dyes with the increase in adsorbent dosage is due to the availability of large number of active sites and large surface area [45].

Conversely, the reverse trend was observed in the case of variation of adsorption capacity with adsorbent dosage. This behaviour might be due to the saturation of the adsorption sites because of particulate interactions such as aggregation which results in a decrease in effective surface area per unit weight of the adsorbent [46].

121

90 100

80 75

60 %R

qe 40 Removal efficiency (%R) efficiency Removal

45 Adsorption capacity (mg/g) capacity Adsorption

30 0 0 2 4 6 8 10 12 Adsorbent dosage (g/L)

Fig. 4.4a. Effect of adsorbent dosage on removal efficiency and adsorption capacity

for the adsorption of MB onto PGP (Reaction conditions: Co = 100 mg/L, Volume of MB solution = 25 mL, Temperature = 298 K, Time = 3 hours and pH = 7.0)

122

92 120

100 90

80 88 % R

qe 60

40 Removal efficiency (% R) (% efficiency Removal 84 (mg/g) capacity Adsorption 20

82 0 0 2 4 6 8 10 12 Adsorbent dosage (g/L)

Fig. 4.4b. Effect of adsorbent dosage on removal efficiency and adsorption capacity

for the adsorption of CV onto PGP (Reaction conditions: Co = 50 mg/L, Volume of CV solution = 25 mL, Temperature = 298 K, Time = 1 hour and pH = 7.0)

123

4.3.4. Effect of pH

pH is an important factor which affects the process of adsorption. Fig. 4.5a shows the effect of pH on the adsorption of MB by PGP at 100 mg/L initial MB concentration. It can be seen from the figure that the adsorption of MB is 54.9% at pH value 2.0. The removal efficiency increased with the increase in the solution pH and reached up to 83.5% at pH = 7.0. However, there is no further increase in the removal efficiency above this pH value. Similar trend was observed in case of adsorption of CV onto PGP adsorbent at 50 mg/L CV concentration (Fig. 4.5b). In this case, removal efficiency increased from 83.6% (at pH 2.0) to 91.7% (at pH 7.0). Subsequently, there is no further increase removal efficiency afterwards with increase in pH. At low pH values, the surface of the adsorbent becomes positively charge by the absorption of H+ ions leading to repulsion between cationic dyes and positively charged adsorbent. Also, there is competition between H+ and MB molecules for the active sites on PGP. On the contrary, in basic medium, due to the presence of OH˗ ions in excess, the surface of PGP becomes negatively charged. This results in electrostatic attraction between cationic dyes and negatively charged PGP surface leading to enhanced adsorption in basic pH.

124

60 Removal efficiency (%R) efficiency Removal

50 0 2 4 6 8 10 12 14

Fig. 4.5a. Effect of pH on adsorption of MB on to PGP (Reaction conditions: Co= 100 mg/L, Adsorbent dosage = 8.0 g/L, Volume of MB solution = 25 mL, Temperature = 298 K and Time = 3 hours)

125

86 Removal efficiency (% R) (% efficiency Removal

82 0 2 4 6 8 10 12 14 pH

Fig. 4.5b. Effect of pH on adsorption of CV on to PGP (Reaction conditions: Co= 50 mg/L, Adsorbent dosage = 6.0 g/L, Volume of CV solution = 25 mL, Temperature = 298 K and Time = 1 hour)

126

4.3.5. Point of zero charge

The point of zero charge for the PGP adsorbent was found to be 5.7 (Fig. 4.6).

For pH < pHpzc, the surface of the PGP adsorbent acquires positive charge whereas, at pH > pHpzc, the surface acquires a negative charge [47]. This indicates that the surface of PGP adsorbent would become negatively charged (favourable for cationic dye adsorption) only at pH higher than 5.7.

∆ pH ∆ pHi 0 0 2 4 6 8 10 12

-1

-2

-3

Fig. 4.6. Point of zero charge for PGP (Reaction conditions: [KNO3] = 0.1 M, Concentration of PGP adsorbent = 0.1 g, Time = 48 hours and Temperature = 298 K)

127

4.3.6. Effect of particle size

The effect of particle size of the adsorbent on MB and CV adsorption in the form of bar graph is shown in Fig. 4.7. The removal efficiency of PGP increases from 84.1% to 92.7% for MB (91.5% to 95.2% for CV) on decreasing the particle size ranging from 80–150 to >200 BSS (British Standard Sieve) mesh. The reason for this behaviour might be the increase in surface area of the adsorbent and availability of a large number of active sites for adsorption [48]. But, due to the handling difficulties accompanying smaller particle size, particles of intermediate size range (80–150 BSS) were selected for MB-PGP as well as CV-PGP adsorption studies.

88 MB + PGP CV + PGP 84

Removal efficiency (%R) efficiency Removal 80

76 80-150 150-200 >200

Mesh size

Fig. 4.7. Effect of particle size on adsorption of MB and CV onto PGP (Reaction

conditions for MB-PGP system: Co = 100 mg/L, Adsorbent dosage = 8.0 g/L, Time = 3 hours, Temperature = 298 K and pH = 7.0. Reaction conditions for

CV-PGP system: Co = 50 mg/L, Adsorbent dose = 6.0 g/L, Time = 1 hour, Temperature = 298 K and pH = 7.0)

128

4.3.7. Adsorption isotherms

The results has been analysed in the light of four common isotherm models, namely, Langmuir, Freundlich, Temkin and Dubinin-Radushkevich. Attempts have been made to fit generated data in the linear form of these models (Section 2.6, Chapter 2). The values of different isotherm parameters for the adsorption of MB and CV onto PGP thus obtained are presented in Table 4.1a. The Langmuir adsorption isotherm model does not fit the experimental data and is inadequate to be used because values of qm were found to be negative in both the cases. A similar result was also observed in the case of uranium (VI) - Aspergillus fumigatus [49]. Table 4.1a distinctly tells that the Temkin model is most suited to represent the adsorption of MB by PGP. The Temkin plot for the adsorption of MB onto PGP is shown in Fig. 4.8a and the resulting solution of Temkin equation for this system is given as:

2 (R = 0.9872) (3.1)

According to this isotherm there is a high probability that the active sites on the surface of the unmodified natural adsorbent might be energetically non- equivalent. Accordingly, the more energetic active sites of the adsorbent are occupied first in the process of adsorption [50]. It is worth to mention here that adsorptive removal of MB dye by other adsorbents obtained from agricultural waste such as coir pith [15] and platanus leaves [32] have also found to obey Temkin adsorption isotherm.

129

Table 4.1a.

Isotherm parameters for the adsorption of MB and CV onto PGP (Reaction conditions for MB-PGP system: Co = 100 mg/L, Adsorbent dose = 8.0 g/L, Time = 3 hours,

Temperature = 298 K and pH = 7.0. Reaction conditions for CV-PGP system: Co = 50 mg/L, Adsorbent dose = 6.0 g/L, Time = 1 hour, Temperature = 298 K and pH = 7.0)

Isotherm models Parameters MB dye CV dye

Freundlich n 0.1543 0.8274

1-1/n 1/n -7 KF (mg L /g) 1.384 x 10 1.0117

R2 0.8172 0.9824

Temkin b (J/mol) 37.3341 371.205

KT (L/g) 0.0763 0.7326

R2 0.9872 0.9061

D-R qD (mg/g) 391.7406 10.7467

β 2 x 10-4 1 x 10-6

R2 0.8958 0.8488

130

30 Temkin equation

25 qe= B ln Ce + B ln KT

e q 15

0 2.5 2.6 2.7 2.8 2.9 3 3.1 ln C e

Fig. 4.8a. Temkin isotherm model for the adsorption of MB onto PGP (Reaction

conditions: Co = 100 mg/L, Adsorbent dose = 8.0 g/L, Time 3 hours, Temperature = 298K and pH = 7.0)

131

Based on the correlation coefficient values for all the three models, the best model fitting the equilibrium data was found to be Freundlich adsorption isotherm for CV dye removal (Table 4.1a). In the Freundlich isotherm, the factor, 1/n, was found to be greater than unity suggesting that the adsorption of CV onto PGP is cooperative (Fig. 4.8b). This indicates that the adsorbed adsorbate has an effect on the adsorption of new adsorbate molecules. From the isotherm plot shown in Fig. 4.8b following Freundlich isotherm equation has been established for this system:

(R2 = 0.9824) (3.2)

The removal of CV dye by groundnut shell [51], bean pod [51] and citrullus lanatus rind [52] were also found to obey Freundlich adsorption isotherm. The values of the various Freundlich parameters reported by the investigators for the above mentioned adsorbents are compared with the present investigation in Table 4.1b.

Freundlich equation 2.5

ln qe = 1/n ln Ce + ln KT

e 1.5 ln q ln

0.5

0 0 0.5 1 1.5 2 2.5

ln Ce

Fig. 4.8b. Freundlich isotherm for the adsorption of CV onto PGP (Reaction

conditions: Co = 50 mg/L, Adsorbent dose = 6.0 g/L, Time 1 hour, Temperature = 298K and pH = 7.0)

132

Table 4.1b.

Freundlich isotherm parameters for the adsorption of CV onto different adsorbents

System Freundlich constants R2 Reference 1-1/n 1/n KF (mg L /g) n

CV-Groundnut shell 0.00465 0.542 0.805 [54]

CV-Bean pod 0.000479 0.403 0.886 [54]

CV-Citrullus lanatus 4.82 0.702 0.900 [55]

CV-Punica granatum peel 1.0117 0.8274 0.9824 Present study

4.3.8. Adsorption kinetics

For understanding the kinetics of MB-PGP and CV-PGP systems, the experimental data were analysed in the light of pseudo-first order, pseudo-second order, Elovich and intraparticle diffusion models. The values of the various constants for these kinetic models as calculated from respective equations (Eqs. 2.13–2.16, Section 2.7, Chapter 2) are summarised in Table 4.2a.

For MB-PGP system, pseudo-first order kinetic model is not obeyed as the data does not fall on the straight line. The values of qe,cal and qe,exp show marked differences and the value of correlation coefficient is comparatively low. Thus, pseudo-first order kinetic model is inapt for this system. For the pseudo-second order kinetic model, the values of theoretical qe value (qe,cal) and experimental qe value

(qe,exp) are very close to each other. Also, the value of correlation coefficient is found to be close to 1 (R2 = 0.9998). The plot of intraparticle diffusion model did not pass through origin signifying that intraparticle diffusion is not the only rate-limiting step and some other mechanism is involved in the MB adsorption process. For Elovich model, the value of the coefficient of correlation (R2) is 0.9528. The values of α and β are given in Table 4.2a. By comparing the R2 values for the various models, it is concluded that the best fit kinetic model for the adsorption of MB onto PGP is pseudo-second order model (R2 = 0.9998). The pseudo-second order kinetic plot as illustrated in Fig. 4.9a, has resulted the following linear equation for the adsorption of MB onto PGP:

133

(R² = 0.9998) (3.3)

Pseudo-second order kinetics have also been observed to be obeyed for the adsorption of MB onto different adsorbents such as Arthrospira platensis [8], coconut bunch waste [14], cotton stalk [17], parsley stalk [29], rice hull ash [34], shaddock peel [37], Bacillus subtilis [9], Ulva lactuca [39], Mahogany fruit shell [24], melon peel [26] and wheat straw [41]. The values of pseudo-second order rate constant as obtained by the above investigators are summarised in Table 4.2b. This table clearly indicates that the values as generated in present investigation are in judiciously comparable ranges of other. However, close agreement is not possible because different investigator used different adsorbent and each adsorbent has its specific characteristics.

For CV-PGP system, on the basis of comparison of the correlation coefficients (R2), the best model representing the equilibrium data was again found to pseudo- second order kinetic model with R2 = 0.9997 (Fig. 4.9b). The values of the various parameters of the above mentioned kinetic models for CV-PGP system are given in Table 4.2a. Following mathematical equation for pseudo-second order kinetics has been obtained from Fig. 4.9b:

(R² = 0.9997) (3.4)

Pseudo-second order kinetics have also been observed to be obeyed for the adsorption of CV onto different adsorbents such as palm kernel fiber [53], grapefruit peel [54], rice husk [55], coconut husk [56], cyperus rotundus [57], Chaetophora elegans alga [58]. The values of pseudo-second order rate constant as obtained by the above investigators are compared in Table 4.2c.

134

Table 4.2a.

Kinetic parameters for the adsorption of MB and CV onto PGP (Reaction conditions for MB-PGP system: Co = 100 mg/L, Adsorbent dose = 8 g/L, Temperature = 298 K and pH = 7. Reaction conditions for CV-PGP system: Co = 50 mg/L, Adsorbent dose

= 6.0 g/L, Temperature = 298 K and pH = 7.0)

Kinetic models Parameters MB dye CV dye

-1 Pseudo-first order k1 (min ) 0.0273 0.0734

qe, exp (mg/g) 10.5929 7.5773

qe, cal (mg/g) 2.2042 2.0450

R2 0.9768 0.9511

Pseudo-second order k2 (g/mg min) 0.0337 0.0746

qe, exp (mg/g) 10.5929 7.5773

qe, cal (mg/g) 10.730 7.7821

R2 0.9998 0.9997

1/2 Intraparticle diffusion Kid (mg min /g) 0.1904 0.3305

C 8.4204 5.4495

R2 0.9124 0.9215

5 Elovich α (mg/g min) 1.179 x 10 804.322

β (g/mg) 1.6157 1.4287

2 R 0.9528 0.973

135

16 Pseudo-second order equation

14 2 t/qt= t/qe + 1/k2qe 12

t t

8 t /q t

0 0 50 100 150 200 t (min)

Fig. 4.9a. Pseudo-second order kinetic model for the adsorption of MB onto PGP (Reaction conditions: Adsorbent dose = 8.0 g/L, Volume of MB dye = 25 mL, Temperature = 298 K and pH = 7.0)

136

Table 4.2b.

Pseudo-second order rate constant for the adsorption of MB onto different adsorbents

System Pseudo-second order model R2 Reference

k2 (g/mg min) qe,cal (mg/g)

MB-Arthrospira platensis 0.0247 27.40 0.998 [8]

MB-Bacillus subtilis 0.028 19.57 0.9998 [9]

MB-Coconut bunch 0.041 34.36 0.991 [14]

MB-Cotton stalk 0.0519 104.82 0.9998 [17]

MB-Mahogany fruit shell 0.0026 12.64 0.991 [24]

MB-Melon peel 0.015 22.22 0.999 [26]

MB-parsley stalk 0.00014 83.33 0.9998 [29]

MB-rice hull ash 0.006 23.49 0.9990 [34]

MB-Shaddock peel 0.00005 131.19 0.9998 [37]

MB-Ulva lactuca 0.040 16.75 1.000 [39]

MB-Wheat straw 0.4201 280.9 0.9948 [41]

MB-Punica granatum peels 0.0337 10.7296 0.9998 Present study

137

Pseudo-second order equation 6

2 t/qt= t/qe + 1/k2qe 5

t / q / t 3

0 0 10 20 30 40 50

t (min)

Fig. 4.9b. Pseudo-second order kinetic model for the adsorption of CV onto PGP (Reaction conditions: Adsorbent dose = 6.0 g/L, Volume of CV dye = 25 mL, Temperature = 298 K and pH = 7.0)

138

Table 4.2c.

Pseudo-second order rate constant for the adsorption of CV onto different adsorbents

Systems Pseudo-second order model R2 Reference

k2 (g/mg min) qe, cal (mg/g)

CV-Palm kernel fiber 0.2003 8.687 0.999 [53]

CV-Grapefruit peel 0.005 24.31 0.992 [54]

CV-Rice husk 0.00234 42.053 0.998 [55]

CV-Coconut husk 0.1878 104.82 0.972 [56]

CV-Cyperus rotundus 0.167 12.64 1.0 [57]

CV-Chaetophora elegans alga 0.117 22.22 0.9993 [58]

CV-Punica granatum peels 0.0746 7.7821 0.9997 Present study

4.3.9. Adsorption thermodynamics

The results of the thermodynamic studies for MB-PGP system indicate that the removal efficiency increases from 67.2% to 86.4% on increasing the temperature from 293 K to 323 K. Rate of diffusion of MB molecules through the peripheral boundary layer and into the pores the adsorbent is enhanced by increasing the temperature [59]. The values of free energy change at different temperature as calculated by employing Eqs. 2.17 and 2.18 (Section 2.8, Chapter 2) for both MB- PGP and CV-PGP systems are incorporated in Tables 4.3a and 4.3b, respectively.

The values of ∆H˚ and ∆S˚ were obtained from the slope and intercept of ln Kc versus 1/T plots (Figs. 4.10a and 4.10b) and are also included in above tables. For both the systems, negative values of ∆G˚ signify that the adsorption process is feasible and spontaneous within the temperature range selected in the present investigation. Tables 4.3a and 4.3b further indicates that the thermodynamic nature of adsorptive removal by PGP is same for both dyes. Positive values of ∆H˚ show that the reaction is endothermic in nature. Positive value of ∆S˚ indicates the increase in the randomness at the adsorbate/solution interface during adsorption [60]. The increase in entropy might be due to increasing the translational energy of the dye molecules. The increase

139 in entropy has also been reported in the literature for the adsorption of MB onto Bacillus subtilis [9], coir pith [15], fallen leaves of Platanus [32], illitic clay mineral [60], wheat shells [61], oak sawdust [62], tea waste [63] and flyash [64].

Table 4.3a.

Thermodynamic parameters for the adsorption of MB onto PGP

(Reaction conditions: Co= 100 mg/L, Adsorbent dose = 8.0 g/L, Volume of solution = 25 mL, Time = 3 hours and pH = 7.0)

Temperature (K) ∆G⁰ (kJ/mol) ∆H⁰ (kJ/mol) ∆S⁰ (J/K mol)

293 1.74

303 2.96 31.3 113.1

313 4.54

323 4.95

Table 4.3b.

Thermodynamic parameters for the adsorption of CV onto PGP

(Reaction conditions: Co= 50 mg/L, Adsorbent dose = 6.0 g/L, Volume of MB solution = 25 mL, Time = 1 hour and pH = 7.0)

Temperature (K) ∆G⁰ (kJ/mol) ∆H⁰ (kJ/mol) ∆S⁰ (J/K mol)

293 4.75

303 5.06 7.32 41.06

313 5.48

323 5.99

140

2.5

Thermodynamic equation 2

ln Kc= -ΔH˚/RT + ΔS˚/R

1.5

∆G˚/ RT) ∆G˚/

( c c

1 ln K ln

0.5

0 3.05 3.1 3.15 3.2 3.25 3.3 3.35 3.4 3.45

103/T

Fig. 4.10a. Plot of ln Kc vs 1/T for the adsorption of MB onto PGP (Reaction

conditions: Co : 100 mg/L, Adsorbent dose = 8.0 g/L, Volume of MB dye = 25 mL, pH = 7.0 and Time = 3 hours)

141

2.3

Thermodynamic equation

2.2 ln Kc= -ΔH˚/RT + ΔS˚/R

2.1

∆G˚/ RT) ∆G˚/

(

c c ln K ln

1.9 3.05 3.1 3.15 3.2 3.25 3.3 3.35 3.4 3.45

103/T

Fig. 4.10b. Plot of ln Kc vs 1/T for the adsorption of CV onto PGP (Reaction

conditions: Co = 50 mg/L, Adsorbent dose = 6.0 g/L, Volume of CV dye = 25 mL, pH = 7 and Time = 1 hour)

142

4.3.10. Desorption

The study of desorption process helps to understand the mechanism of adsorption and also the possibility of retrieval of adsorbate as well as the adsorbent. The treatment process will become economically advantageous if the adsorbent could be regenerated successfully. Desorption of MB-loaded PGP and CV-loaded PGP was studied in five desorbing reagent and the percentage desorption for each of them is given in Table 4.4.

It was found that the highest desorption takes place in 0.1 N HCl (30.16%) followed by 0.1 N CH3COOH (21.91%) and least desorption is found in DDDW (5.14%) for MB-PGP system. Thus, it was inferred that HCl is the most appropriate desorbing reagent which enabled reusability of PGP making the overall process more economical.

In case of CV-PGP system, highest desorption was observed in 0.1 N NaOH (4.97%) whereas least desorption was observed in DDDW (0.45%). Thus, sodium hydroxide was found to be the most appropriate desorbing agent for the regeneration of used PGP in the CV-PGP system. However, further work is needed to increase the desorption efficiency.

Table 4.4.

Percentage desorption of MB and CV from MB-loaded and CV-loaded PGP in different media

Desorbing reagent % desorption for MB- % desorption for CV- loaded PGP loaded PGP

0.1 M HCl 30.16 1.31

0.1 M CH3COOH 21.90 1.24

0.1 M NaOH 5.45 4.97

0.1 M NaCl 20.09 0.50

DDDW 5.14 0.44

143

4.4. Conclusions

In the present study, the effectiveness of PGP for the adsorptive removal of MB and CV in batch method was investigated. Batch adsorption studies reveal that adsorption of MB and CV onto PGP is affected by various parameters such as contact time, pH, adsorbent dosage, particle size of adsorbent and temperature.

For MB-PGP system, the equilibrium was attained in 3 hours. The optimum dosage of PGP for the adsorption was found to be 8.0 g/L. The optimum pH was found to be 7.0 which is verified by the point of zero charge experiment (pHpzc = 5.7). The adsorption of MB onto PGP was best described by Temkin adsorption isotherm model whereas for CV-PGP system, the isotherm data was best described by Freundlich adsorption isotherm model. The kinetic data were found to be in good agreement with pseudo-second order kinetic model for both the systems. Thermodynamic studies revealed that the adsorption of MB and CV onto PGP is feasible, spontaneous and endothermic accompanied by an increase in entropy. Regeneration of the used PGP was successfully achieved in 0.1 M HCl in MB-PGP system whereas 0.1 M NaOH was found to be the better desorbing agent for CV-PGP system.

Thus, it was concluded that PGP, which is a waste material and is easily available, can be used for the removal of dyes from contaminated water.

144

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150

Chapter 5

Utilisation of Cucumis sativus peel for the removal of methylene blue and crystal violet from

aqueous solution

CHAPTER 5

Utilisation of Cucumis sativus peels for the removal of methylene blue and crystal violet dyes from aqueous solution

5.1. Introduction

Rapid increase in industrialisation in the recent years has resulted in the generation of numerous kinds of toxic pollutants. These pollutants are considered to be the major cause of water pollution worldwide. Many industries like textiles, paper and pulp, paint, food processing, tanneries, cosmetics, etc. consume dyes to colour their products, thereby, creates large amounts of dye contaminated wastewater. Release of this coloured wastewater into the aquatic ecosystem without sufficient treatment creates major problems because of the detrimental effects of dyes to all forms of life [1–3]. Harmful effects of dyes have already been discussed in Section 1.5.3 (Chapter 1). Consequently, there is a significant requirement to eliminate these toxic dyes from the effluents before they discharged into the freshwater systems. Researchers have made several efforts to develop appropriate methods for the removal of dyes from the contaminated water. Adsorption method has been the preferred choice in terms of cost, ease of operation, simplicity of design, high efficiency and economic feasibility [4]. Activated carbon is the preferred adsorbent but their use is restricted because of its high cost, necessity of regeneration and loss of adsorbent during regeneration [5]. Thus, there have been many endeavors in search of inexpensive and easily available adsorbents for the removal of dyes from wastewater. Agricultural waste products are available in large quantities and are usually discarded. Grass waste [6], jute waste [7], neem leaf powder [8], banana stalk waste [9], pineapple stem waste [10], banana peel [11], coffee husk [12], rice husk [13], garlic peel [14], orange peel [15], coconut bunch [16], palm kernel fibre [17], papaya seeds [18], wheat straw [19,20], phoenix tree leaves [21], jackfruit peel [22], peanut hull [23], grass [24], sepiolite [25], Cucumber peels [26], cotton stalk [27], rice hull ash

151

[28], shaddock peels [29], cottonseed hull [30], banana leaves [31], Bacillus subtilis [32], parsley stalk [26], Arthrospira platensis [33], etc. have been effectively employed for the elimination of dyes from wastewater.

Methylene blue (MB) and crystal violet (CV) are two cationic dyes which are commonly used for dying cotton, wool, silk and in printing inks, paints and textiles. The uses and harmful effects of these dyes have already been discussed in Sections 1.5.4 and 1.5.5 (Chapter 1). Because of the various detrimental effects of MB and CV, removal of these dyes from wastewater before discharge is a subject of great concern.

Cucumis sativus, commonly known as cucumber, is an annual climber belonging to family Cucurbitaceae. It is originally from southern Asia but now grows on most continents. The fruit of Cucumis sativus has slightly sweet flavour and is mainly eaten raw in salads or sandwiches. Raw non peeled cucumber is a good source of potassium, phosphorus, manganese, magnesium, vitamin C and K. They contain more than 90% water, thereby, keeping the body hydrated and help in the elimination of toxins from the body. It is also used for skin irritations, sunburns, reverse skin tanning, hydrates skin and controls the puffiness of eyes. The peels of cucumis sativus are usually discarded as waste and could be used as a potential low cost adsorbent for the treatment of dye-loaded wastewater. So far, the removal of MB and CV dyes from wastewater has not been investigated using Cucumis sativus peels (CSP) as adsorbent. Hence, in the present investigation, CSP has been used to study the removal of MB and CV dyes from wastewater.

5.2. Experimental

Batch adsorption experiments were carried out to estimate the efficiency of CSP for the removal of MB and CV from artificially contaminated water. A 1000 mg/L stock solution of the dye was prepared by dissolving accurately weighed (1.0 g) amount of dye in 1 L deionised doubly distilled water (DDDW) from which the solutions of desired concentrations were prepared by dilution.

For MB-CSP system, a fixed amount (0.1 g) of CSP was added to 25 mL of MB solutions with varying initial concentrations (25–250 mg/L) and agitated continuously in a thermostatic water bath shaker at 298 K until the establishment of equilibrium. After equilibration, the samples were filtered and the residual i.e.

152 remaining concentration of MB was studied at λmax = 665 nm. Similar batch experiments were carried out to study the adsorptive behaviour of CV in the concentration range of 10 mg/L to 100 mg/L using 0.125 g of CSP adsorbent. The residual concentration of the filtrate was determined at the pre-determined λmax of CV (590 nm). The effects of contact time, initial dye concentration, adsorbent dose, pH and temperature on the adsorption of MB and CV on to CSP were studied and optimised. The effect of temperature was studied by adding optimum dose of CSP to 25 mL each of 100 mg/L MB dye solution and 50 mg/L CV dye in a temperature- controlled water-bath shaker at 293, 303, 313 and 323 K for equilibrium time.

Desorption studies were carried out to discover reusability of the used adsorbent to make the whole process more economical. For this, the dye-loaded adsorbent was added to 25 mL each of the various desorbing reagents– 0.1 M HCl,

0.1 M NaOH, 0.1 M CH3COOH, 0.1 M NaCl and DDDW in 100 mL conical flasks for 6 hours. The desorbed dye concentration was measured and percent desorption was calculated.

5.3. Results and discussion

5.3.1. Material characterisation

SEM micrographs of CSP before and after adsorption with MB and CV were recorded at 2000 magnification and are presented in Figs. 5.1a–5.1c. It can be clearly seen that the surface of the adsorbent is highly porous, rough and irregular (Fig. 5.1a). This surface was completely modified after the adsorption process and it is covered with molecules of MB (Fig. 5.1b) and CV (Fig. 5.1c) dyes.

153

Fig. 5.1a. SEM image CSP adsorbent

154

Fig. 5.1b. SEM image of MB-loaded CSP

155

Fig. 5.1c. SEM image of CV-loaded CSP

156

To elucidate the possible nature of adsorbate-adsorbent interaction and identify the various functional groups involved in this interaction, FTIR spectrophotometric analysis of CSP, MB-loaded CSP and CV-loaded CSP was done and the spectra are shown in Figs. 5.2a–5.2c. Strong peak at 3434 cm-1, indicating the presence of hydroxyl group, is due to the stretching vibration of O–H bond. The -1 presence of aliphatic groups (–CH3 or –CH2) is confirmed by the peak at 2925 cm due to the stretching vibrations of C–H bonds. Peak at 1642 cm-1 is attributed to the C=O stretching vibration. It can be clearly seen that the reduction in peak size at 3434 cm-1 indicates the involvement of hydroxyl group in the MB-CSP interaction (Figs. 5.2a and 5.2b). In the spectrum of CV-loaded CSP, change in the peak intensity at 3434 cm-1 and 1642 cm-1 was observed (Figs. 5.2a and 5.2c) which suggests the involvement of –OH and –COO groups in the interaction of CV with CSP.

CSP

100

90 % Transmittance %

85 4000 3500 3000 2500 2000 1500 1000 500 -1 wavenumber (cm )

Fig. 5.2a. FTIR spectrum of CSP adsorbent

157

102 MB+CSP

100

94 % Transmittance %

90 4000 3500 3000 2500 2000 1500 1000 500 -1 wavenumber (cm )

Fig. 5.2b. FTIR spectrum of MB-loaded CSP

100 CV+CSP

60 % Transmittance %

40 4000 3500 3000 2500 2000 1500 1000 500 -1 wavenumber (cm )

Fig. 5.2c. FTIR spectrum of CV-loaded CSP

158

5.3.2. Effect of contact time and initial dye concentration

The effect of contact time on the adsorption capacity of MB and CV dyes by CSP at 298 K as calculated by using Eq. 2.3 (Section 2.5, Chapter 2) is shown in Figs. 5.3a and 5.3b. It has been observed that the adsorption capacity of both MB and CV initially increases rapidly with the increase in contact time (initial 30 minutes) and finally becomes almost constant with the attainment of equilibrium for all the selected concentrations. Afterwards, the adsorption continues sluggishly at a slower rate and finally equilibrium was attained within 1 hour. The rapid uptake of dye at the early stage might be due to the availability of unoccupied binding sites on the surface of the adsorbent [34]. As the contact time increases, more and more sites are occupied which results in the saturation of the adsorbent surface leading to slower rate of adsorption in the middle stage. Finally, when all the sites are occupied, no further adsorption occurs. Also, as the initial concentration of MB and CV dyes were increased (25 mg/L to 250 mg/L for MB and 10 mg/L to 100 mg/L for CV), increase in the adsorption capacity was observed. This result may be ascribed to the availability of large number of dye molecules in the solution phase favouring the interaction between the dye molecules and CSP. With the increase in the dye concentration, concentration gradient of dyes also rises, thereby, strengthening the thermodynamic driving force which overcomes the mass transfer resistance of the MB and CV molecules from aqueous solution to CSP. Consequently, the probability of collision of dye molecules and CSP active sites increases and hence the adsorption capacity also increases [35].

159

250 mg/L 40 200 mg/L 150 mg/L 30 100 mg/L 50 mg/L 20

25 mg/L Adsorption capacity (mg/g) capacity Adsorption

0 0 50 100 150 200 250

t (min)

Fig. 5.3a. Effect of contact time on the adsorption capacity of MB onto CSP at different initial concentrations (Reaction conditions: Adsorbent dose = 4.0 g/L, Volume of MB dye solution = 25 mL, Temperature = 298 K and pH = 7.0)

160

100 mg/L 15 75 mg/L 60 mg/L 50 mg/L 10 25 mg/L 10 mg/L

Adsorption capacity (mg/g) capacity Adsorption 5

0 0 50 100 150 200 250

t (min)

Fig. 5.3b. Effect of contact time on the adsorption capacity of CV onto CSP at different initial concentrations (Reaction conditions: Adsorbent dose = 5.0 g/L, Volume of CV dye solution = 25 mL, Temperature = 298 K and pH = 7.0)

161

5.3.3. Effect of adsorbent dosage

The effect of adsorbent dose on the equilibrium adsorption capacity and removal efficiency (calculated by using Eqs. 2.1 and 2.2, Section 2.5, Chapter 2) is presented in Figs. 5.4a and 5.4b. It can be clearly seen that for the adsorption of MB, removal efficiency increases from 49.0% to 81.4% on increasing the adsorbent dosage from 0.4 g/L to 4.0 g/L. Afterwards, there is no major variation in the removal efficiency with further increase in adsorbent dose. But, the adsorption capacity follows the reverse trend i.e. the adsorption capacity decreases from 122.4 mg/g to 20.4 mg/g by increase in adsorbent dose from 0.4 to 4.0 g/L (Fig. 5.4a). The increase in removal efficiency with the increase in adsorbent dosage might presumably be due to the accessibility of vacant active sites on the surface of the adsorbent. However, the decrease in adsorption capacity can be attributed to the particulate interaction such as aggregation at higher adsorbent dosage, thereby, decreasing the effective surface area per unit mass of adsorbent and an increase in the diffusional path length [36, 37]. An optimum dose of 4.0 g/L is selected for further studies.

In case of CV-CSP system, similar trend in the removal efficiency and equilibrium adsorption capacity was observed. The removal efficiency increased from 92.3% to 96.5% and the adsorption capacity decreased from 115.4 mg/g to 9.6 mg/g on increasing the CSP dose from 0.4 g/L to 5.0 g/L (Fig. 5.4b). Subsequently, no major changes were observed with further increase in the CSP dose. Hence, 5.0 g/L was selected as optimum dosage for further studies.

162

95 140

120

100

75 % R 80 qe 60 65

Removal efficiency (% R) (% efficiency Removal 55 20 (mg/g) capacity Adsorption

45 0 0 2 4 6 8 10 12 Adsorbent dosage (g/L )

Fig. 5.4a. Effect of adsorbent dosage on the removal efficiency and adsorption

capacity for the adsorption of MB onto CSP (Reaction conditions: Co = 100 mg/L, Volume of MB solution = 25 mL, Temperature = 298 K, Time = 1 hour and pH = 8.0)

163

98 140

120

100 96

80 95 qe 60 % R 94

Removal efficiency (%R) efficiency Removal Adsorption capacity (mg/g) capacity Adsorption 93 20

92 0 0 2 4 6 8 10 12 Adsorbent dosage (g/L)

Fig. 5.4b. Effect of adsorbent dosage on the removal efficiency and adsorption

capacity for the adsorption of CV onto CSP (Reaction conditions: Co = 50 mg/L, Volume of CV solution = 25 mL, Temperature = 298 K, Time = 1 hour and pH = 8.0)

164

5.3.4. Effect of pH

pH is an important parameter affecting the adsorption process by influencing the surface charge of the adsorbent. The effects of pH on the adsorption of MB and CV onto CSP are shown in Figs. 5.5a and 5.5b. It has been observed that the removal efficiency increased from 50.0% to 78.3% on increasing the pH from 2.0 to 8.0 for MB-CSP system. Afterwards, there is no major change in the removal efficiency with further increase in pH (Fig. 5.5a). However, in case of adsorption of CV dye, removal efficiency increased from 83.5% to 96.2% on increasing the pH from 2.0 to 8.0 (Fig. 5.5b). Hence, 8.0 was selected as optimum pH for further adsorption studies on both MB and CV dyes.

Removal efficiency (%R) efficiency Removal 55

45 0 2 4 6 8 10 12 pH

Fig. 5.5a. Effect of pH on the adsorption of MB onto CSP (Reaction conditions: Co = 100 mg/L, Adsorbent dose = 4.0 g/L, Volume of MB solution = 25 mL, Temperature = 298 K and Time = 1 hour)

165

Removal efficiency (%R) efficiency Removal 86

82 0 2 4 6 8 10 12 14

Fig. 5.5b. Effect of pH on the adsorption of CV onto CSP adsorbent (Reaction

conditions: Co = 50 mg/L, Adsorbent dose = 5.0 g/L, Volume of CV solution = 25 mL, Temperature = 298 K and Time = 1 hour)

166

5.3.5. Point of zero charge

The dependence of adsorption on pH can also be interpreted in terms of point of zero charge (pHpzc) of the adsorbent. The pHpzc of CSP adsorbent was determined using solid-addition method [38,39]. The point of zero charge (pHpzc) for CSP was found to be 6.0 (Fig. 5.6). At pH < 6.0, the surface of CSP carries positive charge due to the protonation in the presence of H+ ions whereas at pH > 6.0, the surface becomes negatively charged due to deprotonation in the presence of large number of OH- ions [39]. For adsorption of cationic MB and CV dyes to occur, the adsorbent surface should preferentially have negative charge. Thus, this study further indicates that pH of the medium for favourable adsorption of cationic dyes (MB and CV) must be larger than 6.0.

2 ∆pH 1

pHi 0 0 2 4 6 8 10 12 14

-1

-2

Fig. 5.6. Determination of point of zero charge of CSP (Reaction conditions: [KNO3] = 0.1 M, Concentration of CSP adsorbent = 0.1 g, Time = 48 hours and Temperature = 298 K)

167

5.3.6. Effect of particle size

Particle size is an important parameter affecting the rate of adsorption. The effect of particle size of CSP on the adsorption of MB and CV dyes is illustrated in Fig. 5.7. It was found that as the particle size range is decreased from 80–150 BSS to > 200 BSS mesh, the removal efficiency increases from 80.3% to 85.2% for MB dye and from 95.7% to 98.0% for CV dye. It may be attributed to the fact that with the decrease in particle size, surface area of the adsorbent increases and large number of active sites are available for adsorption [40]. However, due to the difficulties in handling the smaller particle size, particles of 80–150 BSS mesh range were selected for the adsorption studies on both the dyes.

100

60 MB + CSP CV + CSP 40

Removal efficiency (% R) (% efficiency Removal 20

0 80-150 150-200 >200 Mesh size

Fig. 5.7. Effect of particle size on the adsorption of MB and CV onto CSP (Reaction

conditions for MB-CSP system: Co = 100 mg/L, Adsorbent dose = 4.0 g/L, Time = 1 hour, Temperature = 298 K and pH = 8.0. Reaction conditions for

CV-CSP system: Co = 50 mg/L, Adsorbent dose = 5.0 g/L, Time = 1 hour, Temperature = 298 K and pH = 8.0)

168

5.3.7. Adsorption isotherms

Langmuir, Freundlich, Temkin and Dubinin-Radushkevich isotherm models were used to describe MB-CSP and CV-CSP systems. The values of the various isotherm parameters as calculated from Eqs. 2.4 – 2.12 (Section 2.6, Chapter 2) for the adsorption of MB and CV onto CSP are presented in Table 5.1a.

For MB-CSP system, the Langmuir adsorption isotherm model was found to be inadequate as the value of qm was found to be negative. Similar result was also observed in case of uranium(VI)- Aspergillus fumigatus [41]. Table 5.1a indicates that the best model representing the adsorption of MB by CSP is Freundlich isotherm. The Freundlich plot shown in Fig. 5.8a exhibits good linearity with an R2 = 0.9784. This suggests that the surface of CSP is heterogeneous and favours the multilayer adsorption of MB dye. The solution of Freundlich equation generated from the ln qe vs ln Ce plot (Fig. 5.8a) of MB-CSP system is expressed as:

(R2 = 0.9784) (5.1)

It is worth to mention here that adsorptive removal of MB dye by other adsorbents obtained from agricultural waste such as parsley stalks [26], Rosa canini galls [42] and peach shell [43] has also been found to obey Freundlich isotherm. The values of Freundlich constants so obtained are compared with those obtained by other investigators are compared in Table 5.1b.

In case of CV-CSP system, based on the value of correlation coefficient, the best model fitting the equilibrium data was found to be Langmuir adsorption isotherm 2 model (R = 0.9944). The maximum adsorption capacity, qm, was found to be 149.3 mg/g. The value of RL was found to be less than unity indicating that adsorption is favourable. Fig. 5.8b clearly indicates that the isotherm data i.e. variation of 1/qe against 1/Ce exhibit very good linear plot and the solution of Langmuir equation is given as:

(R² = 0.9944) (5.2)

169

Literature survey reveals that the adsorption of CV onto wheat straw [44], grapefruit peel [45], kaolin [46], Eichhornia plant [47], coffee waste [48], Artrocarpus altilis skin [49] and Calotropis procera leaf [50] were also found to obey Langmuir adsorption isotherm and the values of the Langmuir constants have been compared to those obtained in the present work in Table 5.1c.

Table 5.1a. Isotherm parameters for the adsorption of MB and CV onto CSP (Reaction conditions for MB-CSP system: Co = 100 mg/L, Adsorbent dose = 4.0 g/L, Time = 1 hour,

Temperature = 298 K and pH = 8.0. Reaction conditions for CV-CSP system: Co = 50 mg/L, Adsorbent dose = 5.0 mg/L, Time = 1 hour, Temperature = 298 K and pH = 8.0)

Isotherm models Parameters MB dye CV dye

Langmuir qm (mg/g) –17.7825 149.254

KL (L/mg) –0.0254 0.0282

RL –0.649 0.4149

R2 0.9394 0.9944

Freundlich n 0.6100 1.1514

1-1/n 1/n KF (mg L /g) 0.1539 4.1916

R2 0.9784 0.9701

Temkin b (J/mol) 78.5110 –5.9585 x 10-3

-11 KT (L/g) 0.1213 6.7824 x 10

R2 0.9485 0.8937

D-R qD (mg/g) 45.5176 13.7535

β 3 x 10-5 3 x 10-7

R2 0.9413 0.9063

170

4.5 Freundlich equation 4

ln qe= 1/n ln Ce + ln KF

3.5

e 3 ln q ln 2.5

1.5

1 2 2.5 3 3.5 4

ln Ce

Fig. 5.8a. Freundlich adsorption plot of MB onto CSP adsorbent (Reaction

conditions: Co = 100 mg/L, Adsorbent dose = 4.0 g/L, Time = 1 hour, Temperature = 298 K and pH = 8.0)

171

0.6 Langmuir equation 0.5

1/qe = 1/qmKLCe + 1/qm

0.4

0.3 1 / q / 1

0.2

0.1

0 0 0.5 1 1.5 2 2.5 1 / C e

Fig. 5.8b. Langmuir adsorption plot of CV onto CSP (Reaction conditions: Co = 50 mg/L, Adsorbent dose = 5.0 g/L, Time = 1 hour, Temperature = 298 K and pH = 8.0)

172

Table 5.1b.

Freundlich isotherm parameters for the adsorption of MB by different adsorbents

System Freundlich parameters R2 Reference 1-1/n 1/n kF (mg L /g) n

MB-Parsley stalks 2.47 1.326 0.9987 [26]

MB-Rosa canina galls 51.32 2.12 0.99 [42]

MB-Peach shell 52.6 2.9 0.9966 [43]

MB-Cucumis sativus 0.1539 0.61 0.9990 Present study peels

Table 5.1c.

Langmuir isotherm parameters for the adsorption of CV by different adsorbents

System Langmuir parameters R2 Reference kL (L/mg) qm (mg/g)

CV-Wheat straw 0.1719 227.27 0.9988 [44]

CV-Grapefruit peel 0.131 249.68 0.994 [45]

CV-Kaolin 0.25 47.27 0.99 [46]

CV-Eichhornia plant 0.36 58.13 0.96 [47]

CV-Coffee waste 0.047 125.0 0.985 [48]

CV-Artrocarpus altilis skin 0.03 145.84 0.9922 [49]

CV-Calotropis procera leaf 0.114 4.14 * [50]

CV-Cucumis sativus peels 0.0282 149.25 0.9944 Present study * Not reported

173

Tables 5.1b and 5.1c clearly indicate that there is wide disagreement in the isotherm constants for the removal of both MB and CV dyes by different adsorbents. This is due to fact that the adsorption characteristics are strongly dependent on the nature of adsorbent.

5.3.8. Adsorption kinetics

Pseudo-first order, pseudo-second order, intraparticle diffusion and Elovich models were used to study the kinetics of MB-CSP and CV-CSP system. Various kinetic model parameters for both the systems, as computed by using Eqs. 2.13 – 2.16 (Section 2.7, Chapter 2), are presented in Table 5.2a. The comparison of correlation coefficients for the above mentioned models clearly indicates that the kinetic data obtained are in good agreement with pseudo-second order kinetic model (R2 = 0.9981 for MB and R2 = 0.9999 for CV). The plots of pseudo-second order kinetic for the adsorption of MB and CV onto CSP adsorbent are presented in Figs. 5.9a and 5.9b, respectively. The mathematical solutions of pseudo-second order kinetic model generated for MB-CSP (Eq. 5.3) and CV-CSP (Eq.5.4) as obtained from respective t/qt vs t plots (Figs. 5.9a and 5.9b) are given as:

(R² = 0.9981) (5.3)

(R² = 0.9999) (5.4)

The calculated values of adsorption capacity (qe,cal) for both the dyes are in very good agreement with those obtained experimentally (qe,exp). This further indicates the validity of pseudo-second order kinetic model. Pseudo-second order kinetics have also been observed to be obeyed for the adsorption of MB onto different adsorbents such as wheat straw [20], parsley stalk [26], cotton stalk [27], rice hull ash [28], shaddock peel [29], Arthrospira platensis [33] and coconut bunch waste [16]. Also, the adsorption of CV dye onto grapefruit peel [49], palm kernel fiber [51], rice husk [52], coconut husk [53], cyperus rotundus [54], Chaetophora elegans alga [55] have also found to obey pseudo-second order kinetic model. The values of pseudo- second order rate constants as obtained by the above investigators have been

174 compared with the values obtained in the present investigation in Tables 5.2b and 5.2c. Our values are judiciously comparable with those of other investigators.

Table 5.2a.

Kinetic parameters for the adsorption of MB and CV onto CSP

(Reaction conditions for MB-CSP system: Co = 100 mg/L, Adsorbent dose = 4.0 g/L,

Temperature = 298 K and pH = 8.0. Reaction conditions for CV-CSP system: Co = 50 mg/L, Adsorbent dose = 5.0 g/L, Temperature = 298 K and pH = 8.0)

Kinetic models Parameters MB dye CV dye

-1 Pseudo-first order k1 (min ) 0.0995 0.1094

qe,exp (mg/g) 20.1410 9.6061

qe,cal (mg/g) 10.0925 1.0941

R2 0.9153 0.9343

Pseudo-second order k2 (g/mg min) 0.0148 0.2056

qe,exp (mg/g) 20.141 9.6061

qe,cal (mg/g) 21.459 9.7087

R2 0.9981 0.9999

-1/2 Intraparticle diffusion Kid (mg min /g) 1.3390 0.1295

C 11.6690 8.7872

R2 0.9431 0.9436

Elovich α (mg/g min) 89.5233 2.1 x 1013

β (g/mg) 0.3577 3.7216

R2 0.9663 0.9567

175

2.5 Pseudo-second order equation

2 2 t/qt= t/qe+ 1/k2qe

1.5

t t/q 1

0.5

0 0 10 20 30 40 50 t (min)

Fig. 5.9a. Pseudo-second order plot for the adsorption of MB onto CSP (Reaction

conditions: Co = 100 mg/L, Adsorbent dose = 4.0 g/L, Temperature = 298 K and pH = 8.0)

176

5 Pseudo-second order equation

2 4 t/qt= t/qe +1/k2qe

t t/q 2

0 0 10 20 30 40 50 t (min)

Fig. 5.9b. Pseudo-second order plot for the adsorption of CV onto CSP (Reaction

conditions: Co = 50 mg/L, Adsorbent dose = 5.0 g/L, Temperature = 298 K and pH = 8.0)

177

Table 5.2b.

Pseudo-second order rate constant for the adsorption of MB onto different adsorbents

System Pseudo-second order model R2 Reference

k2 (g/mg min) qe,cal (mg/g)

MB-Coconut bunch 0.041 34.36 0.991 [16]

MB-Wheat straw 0.4201 280.9 0.9948 [20]

MB-parsley stalk 0.00014 83.33 0.9998 [26]

MB-Cotton stalk 0.0519 104.82 0.9998 [27]

MB-rice hull ash 0.006 23.49 0.9990 [28]

MB-Shaddock peel 0.00005 131.19 0.9998 [29]

MB-Bacillus subtilis 0.028 19.57 0.9998 [32]

MB-Arthrospira platensis 0.0247 27.40 0.998 [33]

MB-Cucumis sativus peels 0.0148 21.4592 0.9981 Present study

178

Table 5.2c.

Pseudo-second order rate constant for the adsorption of CV onto different adsorbents

System Pseudo-second order model R2 Reference

k2 (g/mg min) qe,cal (mg/g)

CV-Grapefruit peel 0.005 24.31 0.992 [49]

CV-Palm kernel fiber 0.2003 8.687 0.999 [51]

CV-Rice husk 0.00234 42.053 0.998 [52]

CV-Coconut husk 0.1878 104.82 0.972 [53]

CV-Cyperus rotundus 0.167 12.64 1.0 [54]

CV-Chaetophora elegans alga 0.117 22.22 0.9993 [55]

CV-Cucumis sativus peels 0.2056 9.7087 0.9999 Present study

5.3.9. Adsorption thermodynamics

The standard free energy change of a process is an essential tool to judge the feasibility of a process against any environment. The values of ∆G˚ associated with the adsorption of MB and CV by CSP were calculated by employing Eqs. 2.17 and 2.18 (Section 2.8, Chapter 2) and are presented in Tables 5.3a and 5.3b. The respective values of enthalpy change and entropy change (Eqs. 2.19 and 2.20, Section 2.8, Chapter 2) as obtained from linear plots shown in Figs. 5.10a and 5.10b are also included in Tables 5.3a and 5.3b.

The decrease in the negative value of the free energy with increasing temperature indicates that adsorption is favoured at the lower temperature for the adsorption of MB onto CSP. Thus feasibility of the process decreases with temperature. However, the reverse trend of feasibility with temperature has been observed in case of adsorption of CV by CSP.

179

Table 5.3a.

Thermodynamic parameters for the adsorption of MB onto CSP

(Reaction conditions: Co= 100 mg/L, Adsorbent dose = 4.0 g/L, Volume of MB solution = 25 mL, Time = 1 hour and pH = 8.0)

Temperature (K) ∆G⁰ (kJ/mol) ∆H⁰ (kJ/mol) ∆S⁰ (J/K mol)

293 5.42

303 4.64 –26.0 –70.4

313 4.03

323 3.28

Table 5.3b.

Thermodynamic parameters for the adsorption of CV onto CSP

(Reaction conditions: Co= 50 mg/L, Adsorbent dose = 5.0 g/L, Volume of CV solution = 25 mL, Time = 1 hour and pH = 8.0)

Temperature (K) ∆G⁰ (kJ/mol) ∆H⁰ (kJ/mol) ∆S⁰ (J/K mol)

293 7.98

303 8.62 7.6 53.4

313 9.09

323 9.60

180

2.4 Thermodynamic equation 2.2

ln Kc= -∆H˚/RT + ∆S˚/R

1.8

∆G˚/RT)

- (

c c 1.6 ln K ln 1.4

1.2

1 3.05 3.1 3.15 3.2 3.25 3.3 3.35 3.4 3.45

103/T

Fig. 5.10a. Plot of ln Kc vs 1/T for the adsorption of MB onto CSP (Reaction

conditions: Co = 100 mg/L, Adsorbent dose = 4.0 g/L, Volume of MB dye = 25 mL, pH = 8.0 and Time = 1 hour)

181

3.6

3.55 Thermodynamic equation

3.5 ln Kc = -∆H˚/RT + ∆S˚/R

3.45

∆G˚/RT)

- (

c c 3.4 ln K ln

3.35

3.3

3.25 3.05 3.1 3.15 3.2 3.25 3.3 3.35 3.4 3.45 103/T

Fig. 5.10b. Plot of ln Kc vs 1/T for the adsorption of CV onto CSP (Reaction

conditions: Co = 50 mg/L, Adsorbent dose = 5.0 g/L, Volume of CV dye = 25 mL, pH = 8.0 and Time = 1 hour)

182

5.3.10. Desorption

An efficient adsorbent for the removal of dyes is the one which has high removal efficiency as well as good desorption characteristics so that it could be used again. Five desorbing reagents- HCl, NaOH, CH3COOH, NaCl (0.1 M each) and DDDW were investigated and percent desorption is given in Table 5.4.

Table 5.4 shows that 0.1 M HCl is most medium for desorption of MB from

CSP adsorbent with desorption of 63.6% followed by 0.1 M CH3COOH (55.4% desorption) whereas DDDW was found to be least effective with only 3.4% desorption.

However, in case of desorption of CV dye, 0.1 M NaCl is found to be most suitable desorbing agent (17.1% desorption). Negligible adsorption was observed in

0.1 M CH3COOH and DDDW.

Table 5.4.

Percentage desorption of MB and CV from MB-loaded and CV-loaded CSP in different media

Desorbing reagent % desorption for MB- % desorption for CV- loaded CSP loaded CSP

0.1 M HCl 63.62 2.49

0.1 M CH3COOH 55.38 0.33

0.1 M NaOH 9.26 2.44

0.1 M NaCl 56.65 17.14

DDDW 3.40 0.28

183

5.4. Conclusions

CSP adsorbent was found to be an effective low cost adsorbent for the removal of MB and CV dyes from aqueous solution. Various parameters, namely, adsorbent dose, pH, contact time, initial dye concentration and temperature have been optimised. An optimum contact time of 1 hour was required for the attainment of equilibrium for both MB-CSP and CV-CSP systems. The optimum adsorbent dosage for the adsorption of MB dye was found to be 4.0 g/L and 5.0 g/L for the adsorption of CV dye. Isotherm studies revealed that Freundlich adsorption isotherm was found to be validated with the experimental data indicating heterogeneous surface of CSP for the adsorption of MB dye. However, in case of CV dye, the experimental data was found to be in good agreement with Langmuir adsorption isotherm model indicating homogeneous surface of CSP. This signifies that different dyes that were used in the present investigation behave differently with same adsorbent. Kinetic data were found to obey pseudo-second order kinetics with R2 = 0.9981 for MB and R2 = 0.9999 for CV. Thermodynamic study revealed that the adsorption of MB by CSP is spontaneous, exothermic and associated with decrease of entropy. However, the adsorption CV is endothermic and accompanying with increase of entropy. Desorption studies revealed that the used adsorbent could be successfully regenerated in hydrochloric acid with 63.62% desorption in case of MB-CSP system whereas for CV-CSP system, sodium chloride is found to the most suitable desorbing agent with 17.1% desorption. The present investigation suggests that CSP is an efficient low cost and economically viable adsorbent for the removal of dyes from wastewater.

184

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189

Chapter 6

Utilisation of Terminalia arjuna peel for the removal of methylene blue and crystal violet from

aqueous solution

CHAPTER 6

Utilisation of Terminalia arjuna sawdust for the removal of methylene blue and crystal violet dyes from aqueous solution

6.1. Introduction

The global problem of water pollution has been worsened through discharge of untreated industrial effluents. Several industrial processes utilise toxic chemicals for the manufacture of their products. Discharge of industrial effluents containing hazardous contaminants, such as toxic heavy metals and dyes, has severe destructive effects on the environment. Out of the various contaminants, dyes are an important class of pollutants which are discharged into the freshwater systems through various industries like textile, leather, paints, paper, plastic, cosmetics, pharmaceuticals, dye manufacturing, etc. The dyes have several harmful impacts on the environment which have been discussed in Section 1.5.3 (Chapter 1). Hence, the removal of dyes from industrial effluents before discharge into the water resources is a subject of serious concern for the environmentalists.

Several techniques have been described in the literature for the removal of dyes from wastewater (discussed in Section 1.6, Chapter 1). Most of these techniques have some downsides such as the formation of by-products, high operational cost, low selectivity and inadequate dye removal [1]. Adsorption was found to be the most promising technique amongst them because of its efficacy, simple design, ease of operation, low cost and avoidance of secondary pollution [2]. Activated carbon, the most conventional adsorbent, has shown remarkable performance for the removal of dyes. But, there are limitations in its application (Section 1.8, Chapter 1) which reduces its economic feasibility [3]. Therefore, the attention has shifted to the development of efficient low cost adsorbents for the removal of dyes from wastewater.

190

Various low cost adsorbents have been developed and used by the researchers for the removal of dyes from wastewater. These include jackfruit peel [4], pineapple stem waste [5], grass waste [6], banana leaves [7], rejected tea [8], Ephedra strobilacea sawdust [9], egg shells [10], shaddock peel [11], cotton stalk [12], avocado seed [13], garlic straw [14], longan shell [15], cottonseed hull [16], peanut hull [17], illitic clay [18], orange peel [19], wheat straw [20], cucumber peels [21], rice hull ash [22], Bacillus subtilis [23], parsley stalk [21], Arthrospira platensis [24], coconut bunch waste [25], bamboo leaves [26], Pistachio hull waste [27], kenaf fibre [28], melon peel [29], neem sawdust, [30], etc.

Terminalia arjuna is a tree belonging to genus Terminalia and commonly known as arjuna tree. It is usually grown in different parts of India and Bangladesh. The bark of arjuna tree contains flavonoids, tannins, saponin and gallic acid. It is rich in calcium, magnesium, zinc and copper. It also contains a lot of phytosterols which helps in the prevention and treatment of cardiovascular diseases. Flavonoids help reduce inflammation and affect cognitive function, improve heart and blood vessels. This plant is also used to treat kidney, liver and gall bladder problems. It helps to prevent blood loss through wounds and helps in blood clotting. The wood of arjuna tree is dark brown, very hard, lustrous and coarse-textured. It is used for making carts, agricultural implements, tool handles and other carpentry items which results in the production of a lot of sawdust which is usually rejected as waste. This waste sawdust could be used as a potential adsorbent to study the removal of dyes from wastewater.

In the present investigation, Terminalia arjuna sawdust (TASd) is employed to study the removal of methylene blue (MB) and crystal violet (CV) dyes from aqueous solution in batch mode as no significant effort has been made to study the removal of these dyes using TASd adsorbent.

6.2. Experimental

The batch adsorption experiments were carried out by adding a fixed amount (0.15 g) of TASd to 25 mL of aqueous solutions of dyes with varying initial concentrations (25–250 mg/L for MB and 10–100 mg/L for CV) in 100 mL conical flasks. The samples were agitated in a thermostatic water bath shaker at 298 K for 4 hours in order to ensure the establishment of equilibrium. The samples were filtered after the establishment of equilibrium and the residual concentration of the dye was

191 determined at their respective λmax values (665 nm for MB and 590 nm for CV). Various adsorption parameters such as adsorbent dosage, pH, contact time, particle size and temperature were optimised in batch method. Point of zero charge (pHpzc) of TASd was determined by solid addition method [31].

To investigate the adsorption kinetics, the residual concentration of dyes was monitored at different time interval by employing procedure similar to those of equilibrium experiments. Thermodynamics of the adsorption of MB and CV onto TASd was studied by conducting the batch equilibrium experiments at 293, 303, 313 and 323 K.

The regenerability of the used TASd was studied in different media (acidic, basic and neutral) under the optimum conditions of adsorbent dose (0.15 g), pH (7.0) and particle size (80–150 BSS mesh). For desorption, 0.15 g of the TASd was added to 25 mL of dye solution and agitated for 2 hours. Dye-loaded TASd particles were separated from the dye solution, washed 3–4 times with deionised doubly distilled water (DDDW) to remove traces of unadsorbed dye molecules and then dried in an air oven. This dye-loaded TASd was added to 25 mL of different desorbing agents

(DDDW and 0.1 M each of HCl, CH3COOH, NaCl and NaOH) and shaken for 6 hours. The desorbed dye concentration was measured and percent desorption was calculated.

6.3. Results and discussion

6.3.1. Material characterisation

The SEM images of TASd, MB-loaded TASd and CV-loaded TASd are shown in Figs. 6.1a–6.1c. SEM micrograph of TASd, shown in Fig. 6.1a, indicates that its surface is highly irregular and porous. The vessels on the surface of the TASd can be clearly seen as small hole-like structures. This irregular and porous morphology of the adsorbent offers a large surface area for the dye-adsorbent interaction. However, after adsorption, the pores on the surface of TASd are filled with layers of MB (Fig. 6.1b) and CV (Fig. 6.1c) dye molecules up to a considerable extent.

192

Fig. 6.1a. SEM image of TASd adsorbent

193

Fig. 6.1b. SEM image of MB-loaded TASd

194

Fig. 6.1c. SEM image of CV-loaded TASd

195

FTIR analysis was done in order to identify the different functional groups present on the surface of the adsorbent. The FTIR spectra of TASd (before and after dye adsorption) are presented in Figs. 6.2a–6.2c. The spectral band at 3414 cm-1 might be due to the stretching vibration of H-bonded –OH and –NH groups in the adsorbent [32]. The sharp peak observed at 2918 cm-1 is assigned to asymmetric stretching of –CH group. The strong peak at 1735 cm-1 is due to the C=O vibration of the carbonyl group and the band at 1636 cm-1 indicates the presence of C=C bond. The peaks at 1247, 1027 and 605 cm-1 are assigned to C=C aromatic bending, C–C stretching and C–H bending, respectively. It was observed that some major shifting in the peaks from 3414 to 3441 cm-1 and 1636 to 1594 cm-1 appeared in the spectrum of MB-loaded TASd (Fig. 6.2a and 6.2b) signifying the involvement of hydroxyl and C=C in binding with the MB dye in the adsorption process. In case of CV-loaded TASd, change in the peak intensities at 1735 cm-1 and 1636 cm-1 was observed (Fig 6.2a and 6.2c) indicating that respective functional groups of TASd might be involved in the interaction with CV dye.

100

94 % Transmittance % 92 TASd

90 3500 3000 2500 2000 1500 1000 500 -1 wavenumber (cm )

Fig. 6.2a. FTIR spectrum of TASd adsorbent

196

100

96 % Transmittance % 94 MB+TASd

92 4000 3500 3000 2500 2000 1500 1000 500 -1 wavenumber (cm )

Fig. 6.2b. FTIR spectrum of MB-loaded TASd

100

60 % Transmittance %

50 CV+TASd

40 4000 3500 3000 2500 2000 1500 1000 500 wavenumber (cm-1)

Fig. 6.2c. FTIR spectrum of CV-loaded TASd

197

6.3.2. Effect of contact time and initial dye concentration

The variation of adsorption capacity versus contact time (Calculated using Eq. 2.3, Section 2.5, Chapter 2) at room temperature for the adsorption of MB and CV dyes are shown in Figs. 6.3a and 6.3b, respectively. It can be clearly seen in the figures that the adsorption of dyes increased swiftly in the initial 30 minutes followed by a slow dye uptake and finally attaining equilibrium at around 2 hours. The rapid adsorption of dye in the primary stage might probably be due to the availability of a large number of vacant binding sites on the surface of TASd. However, with the increase in contact time, more and more binding sites were gradually occupied resulting in the saturation of adsorbent surface. Lastly, when all the sites are occupied, no further adsorption takes place with a subsequent increase in contact time [33]. Hence, the equilibrium time for the adsorption of MB and CV onto TASd adsorbent is taken to be 2 hours. It is also inferred from Figs. 6.3a and 6.3b that the adsorption capacity increases with the increase in the concentration of MB and CV dyes. Also, with the increase in the concentration of dyes, the adsorption capacity was found to increase. Such behaviour may presumably be due to the presence of the large number of dye molecules in the solution for adsorption. A high concentration gradient is established providing a thermodynamic driving force which overcomes the mass transfer resistance of dye molecules from aqueous solution on the solid phase. In other words, with the increase of dye concentration, the probability of collision of dye molecules with the binding sites of the adsorbent also increases, resulting in higher adsorption capacity [34].

198

30 250 mg/L

25 200 mg/L

20 150 mg/L

(mg/g)

e 100 mg/L q 15 50 mg/L

10 25 mg/L

0 0 50 100 150 200 250 Time (min)

Fig. 6.3a. Effect of contact time on the adsorption capacity of MB onto TASd at different concentrations (Reaction conditions: Adsorbent dose = 6.0 g/L, Volume of MB solution = 25 mL, Temperature = 298 K and pH = 7.0)

199

14 100 mg/L 12 75 mg/L

10 60 mg/L

(mg/g)

t 8 50 mg/L q 25 mg/L 6 10 mg/L 4

0 0 50 100 150 200 250 Time (min)

Fig. 6.3b. Effect of contact time on the adsorption capacity of CV onto TASd at different concentrations (Reaction conditions: Adsorbent dose = 6.0 g/L, Volume of CV solution = 25 mL, Temperature = 298 K and pH = 7.0)

200

6.3.3. Effect of adsorbent dosage

It is important to optimise the adsorbent dose in order to make the overall adsorption process cost effective. Smaller adsorbent dose accompanied by large adsorbate removal from aqueous solution is our motive. The effect of adsorbent dosage on the equilibrium adsorption capacity and removal efficiency of MB and CV (Calculated using Eqs. 2.1 and 2.2, Section 2.5, Chapter 2) onto TASd adsorbent was studied at room temperature with different amounts of TASd (0.4–10.0 g/L) in 25 mL dye solution and the results are presented in Figs. 6.4a and 6.4b. It is evident from the Fig. 6.4a that for the adsorption of MB dye, the removal efficiency increased from 53.3 % to 85.1 % and the adsorption capacity decreased significantly from 133.3 mg/g to 14.2 mg/g on increasing the TASd dose from 0.4 to 6.0 g/L. For CV-TASd system, the removal efficiency is increased promptly from 92.0% to 95.6% and the adsorption capacity (qe) decreased from 46.0 to 8.0 mg/g on increasing the dose of TASd from

0.4–6.0 g/L (Fig. 6.4b). Thereafter, there is no major change in % R or qe with further increase in TASd dose has been observed. An optimum dosage of 6.0 g/L was thoughtfully selected for further adsorption studies. The increase in removal efficiency with increasing dose might possibly be due to the increase in the number adsorption sites [35]. Conversely, the decrease in the adsorption capacity at higher adsorbent dosage might be due to the particulate interactions (aggregation) resulting in an increase in diffusional path length and reduction in the effective surface area per unit mass of the adsorbent [36].

201

90 140

85 120

80 100

75 % R 80 70 qe 60 65

Removal efficiency (% R) R) (% efficiency Removal Adsorption capacity (mg/g) capacity Adsorption 55 20

50 0 0 2 4 6 8 10 12 Adsorbent dose (g/L)

Fig. 6.4a. Effect of adsorbent dosage on the removal efficiency and adsorption

capacity for the adsorption of MB onto TASd (Reaction conditions: Co = 100 mg/L, Volume of MB solution = 25 mL, Temperature = 298 K, Time = 2 hours and pH =7.0)

202

96 50

95 40

94 30 % R qe 93 20

Removal efficiency (%R) efficiency Removal 92 10 Adsorption capacity (mg/g) capacity Adsorption

91 0 0 2 4 6 8 10 12 Adsorbent dosage (g/L)

Fig. 6.4b. Effect of adsorbent dosage on the removal efficiency and adsorption

capacity for the adsorption of CV onto TASd (Reaction conditions: Co = 50 mg/L, Volume of CV solution = 25 mL, Temperature = 298 K, Time = 2 hours and pH =7.0)

203

6.3.4. Effect of pH

pH plays an important role in the adsorption process by affecting the surface charge of the adsorbent via protonation and de-protonation. The effect of pH on the removal efficiency for the adsorption of MB and CV dyes onto TASd (as calculated using Eq. 2.2, Section 2.5, Chapter 2) was investigated in the pH range of 2–12 and the results obtained are presented in Figs. 6.5a and 6.5b. It can be clearly seen in the figures that the removal efficiency increased from 55.4% to 90.7% for MB and from 82.1% to 95.3% for CV on respective increase in pH from 2.0 to 6.0 and 2.0 to 5.6. Afterwards there is no major variation in removal efficiency with further increase in pH. The result can be explained by the protonation and de-protonating of the dye as well as the adsorbent surface. In acidic medium, the surface of the adsorbent carries a positive charge on its surface due to the absorption of H+ form the solution. This leads to electrostatic repulsion between the cationic MB and CV dyes and positively charged adsorbent surface. On the contrary, in alkaline medium, due to the presence of OH˗ ions in excess, the surface of TASd carries a negative charge. This results in electrostatic attraction between cationic MB and negatively charged TASd surface leading to enhanced adsorption at higher pH values.

204

100

Removal efficiency (%R) efficiency Removal 60

50 0 2 4 6 8 10 12 14 pH

Fig. 6.5a. Effect of pH on the adsorption of MB onto TASd (Reaction conditions: Co = 100 mg/L, Adsorbent dosage = 6.0 g/L, Volume of MB solution = 25 mL, Temperature = 298 K and Time = 2 hours)

205

Removal efficiency (%R) Removal efficiency 84

80 0 2 4 6 8 10 12 14 pH

Fig. 6.5b. Effect of pH on the adsorption of CV onto TASd (Reaction conditions: Co = 50 mg/L, Adsorbent dosage = 6.0 g/L, Volume of CV solution = 25 mL, Temperature = 298 K and Time = 2 hours)

206

6.3.5. Point of zero charge

The effect of pH on the adsorption of MB and CV dyes can also be explained on the basis of point of zero charge (pHzpc) of TASd. The pHzpc of TASd was found to be 5.0 (Fig. 6.6) indicating that at this pH value the adsorbent has neutral charge on its surface. At pH< pHzpc, the surface of TASd gets protonated resulting in an electrostatic repulsion between hydrogen ions and cationic dyes whereas at pH > pHzpc, TASd surface becomes negatively charged leading to electrostatic attraction between TASd and cationic dyes molecules and an enhanced removal efficiency. Thus, a thoughtful pH value of 7.0 was selected for the adsorption studies of cationic MB and CV dyes onto TASd.

2 ∆pH 1

pHi 0 0 2 4 6 8 10 12 14

-1

-2

Fig. 6.6. Determination of point of zero charge of TASd (Reaction conditions:

[KNO3] = 0.1 M, Concentration of TASd adsorbent = 0.1 g, Time = 48 hours and Temperature = 298 K)

207

6.3.6. Effect of particle size

The effect of particle size of TASd on the adsorption of MB and CV is shown in Fig. 6.7. It was observed that as the particle size of TASd is decreased from range 80–150 to > 200 BSS (British Standard Sieve) mesh, removal efficiency increased from 88.9% to 94.5% for MB dye and from 96.0% to 97.5% for CV dye. The reason for this behaviour might be the increase in surface area of the adsorbent and availability of a large number of active sites for adsorption. But, due to the handling difficulties accompanying smaller particle size, particles of intermediate size range (80–150 BSS) were selected for MB-TASd as well as CV-TASd adsorption studies.

100 MB + TASd CV + TASd

Removal efficiency (%R) efficiency Removal 84

80 80-150 150-200 >200 Mesh size

Fig. 6.7. Effect of particle size on adsorption of MB and CV onto TASd (Reaction

conditions for MB-TASd system: Co = 100 mg/L, Adsorbent dosage = 6.0 g/L, Time = 2 hours, Temperature = 298 K and pH = 7.0. Reaction conditions

for CV-TASd system: Co = 50 mg/L, Adsorbent dose = 6.0 g/L, Time = 2 hour, Temperature = 298 K and pH = 7.0)

208

6.3.7. Adsorption isotherms

The experimental adsorption data were analysed in the light of Langmuir, Freundlich, Temkin and Dubinin-Radushkevich (D-R) isotherm models. Various isotherm parameters calculated for the above mentioned models using Eqs. 2.4–2.12 (Section 2.6, Chapter 2) for MB-TASd and CV-TASd systems are listed in Table 6.1a. For MB-TASd system, based on the correlation coefficient values, the best model representing the equilibrium data was found to Langmuir adsorption isotherm model. The Langmuir plot of 1/qe vs 1/Ce for this system presented in Fig. 6.8a has resulted in the following solved equation:

(R² = 0.9931) (6.1)

The value of RL was found to be less than one approving the applicability of

Langmuir isotherm for this system. The maximum adsorption capacity (qm) was found to be 60.6 mg/g. This indicates that there is homogeneous distribution of active sites onto TASd surface.

In this context it is worth to mention here that the adsorptive removal of MB by other similar adsorbents such as banana leaves [7], shaddock peel [11], cotton stalk [12], cottonseed hull [16], wheat straw [20], cucumber peels [21], rice hull ash [22], bacillus subtilis [23] etc. has been testified to obey Langmuir isotherm. The values of Langmuir constants so reported for the above mentioned adsorbents by various investigators are presented in Table 6.1b. This table clearly shows that the constants obtained in the present investigations fall within ranges comparable to those reported earlier.

209

Table 6.1a.

Isotherm parameters for the adsorption of MB and CV onto TASd

(Reaction conditions for MB-TASd system: Co = 100 mg/L, Adsorbent dose = 6.0 g/L, Time = 2 hour, Temperature = 298 K and pH = 7.0. Reaction conditions for CV-

TASd system: Co = 50 mg/L, Adsorbent dose = 6.0 mg/L, Time = 2 hour, Temperature = 298 K and pH = 7.0)

Isotherm models Parameters MB dye CV dye

Langmuir qm (mg/g) 60.606 –31.25

KL (L/mg) 0.0241 –0.933

RL 0.2926 –0.2728

R2 0.9931 0.9918

Freundlich n 1.3798 0.909

1-1/n 1/n KF (mg L /g) 2.0222 3.3902

R2 0.9845 0.9964

Temkin b (J/mol) 254.7658 378.845

KT (L/g) 0.4326 1.9726

R2 0.9457 0.9239

3 D-R qD (mg/g) 6.927 x 10 7.8091

β 2 x10-7 –9 x 10-9

R2 0.9371 0.6745

210

0.3

Langmuir equation 0.25

1/qe= 1/qmKLCe + 1/qm

0.2

0.15 1 / q / 1

0.1

0.05

0 0 0.1 0.2 0.3 0.4

1 / Ce

Fig. 6.8a. Langmuir adsorption plot of MB onto TASd (Reaction conditions: Co = 100 mg/L, Adsorbent dose = 6.0 g/L, Time = 2 hour, Temperature = 298 K and pH = 7.0)

211

Table 6.1b.

Langmuir isotherm parameters for the adsorption of MB onto different adsorbents

Systems Langmuir constants R2 Reference KL (L/mg) qm (mg/g)

MB-Banana leaves 0.116 109.9 0.9996 [7]

MB-Shaddock peel 0.0146 309.6 0.9993 [11]

MB-Cotton stalk 0.0249 147.1 0.9970 [12]

MB-Cottonseed hull 0.12755 185.2 0.9994 [16]

MB-Wheat straw 0.0036 274.1 0.9984 [20]

MB-Cucumber peels 0.0573 111.1 0.9991 [21]

MB-Rice hull ash 0.606 17.1 0.9987 [22]

MB-Bacillus subtilis 0.0164 169.5 0.9884 [23]

MB-Terminalia arjuna 0.0241 60.6 0.9931 Present study sawdust

For CV-TASd system, the Langmuir adsorption isotherm model does not fit the experimental data and is inadequate to be used in this case as qm was found to be negative. A similar result was also observed in the case of uranium (VI) - Aspergillus fumigatus [37]. Based on the correlation coefficient values for all the three models, the best model fitting the equilibrium data was found to be Freundlich adsorption isotherm. The factor, 1/n, was found to be greater than unity suggesting that the adsorption of CV onto TASd is cooperative (Table 6.1a). This indicates that the adsorbed adsorbate has an effect on the adsorption of new adsorbate molecules [38,

39]. The Freundlich plot of ln qe vs ln Ce for the adsorption of CV onto TASd is shown in Fig. 6.8b and the solution of the Freundlich equation generated for this system is given as:

(R2 = 0.9964) (6.2)

212

The removal of CV dye TASd has been compared with similar other non- conventional low-cost adsorbents such as groundnut shell [40], bean pod [40], citrullus lanatus rind [41], Fugas sawdust [42] palm kernel fiber [43] and cyperus rotundus [44] which were also found to obey Freundlich adsorption isotherm. The values of the Freundlich parameters for the adsorption of CV by different adsorbent as reported by other investigators along with the present values are compiled in Table 6.1c.

3 Freundlich equation 2.5

ln qe= 1/n ln Ce + ln KF 2

1.5

e ln q ln 1

0.5

0 -1 -0.5 0 0.5 1 1.5 2

ln Ce

Fig. 6.8b. Freundlich adsorption plot of CV onto TASd (Reaction conditions: Co = 50 mg/L, Adsorbent dose = 6.0 g/L, Time = 2 hour, Temperature = 298 K and pH = 7.0)

213

Table 6.1c.

Freundlich isotherm parameters for the adsorption of CV onto different adsorbents

System Freundlich constants R2 Reference 1-1/n 1/n KF (mg L /g) n

CV-Groundnut shell 0.00465 0.542 0.805 [40]

CV-Bean pod 0.000479 0.403 0.886 [40]

CV-Citrullus lanatus 4.82 0.702 0.900 [41]

CV-Fugas sawdust 1.263 2.375 0.9815 [42]

CV-Palm kernel fiber 5.10 1.70 0.991 [43]

CV-Cyperus rotundus 13.27 0.74 0.97 [44]

CV-Terminalia arjuna 3.3902 0.909 0.9931 Present study sawdust

6.3.8. Adsorption kinetics

In order to understand the mechanism of adsorption and estimate the rate of adsorption, the experimental data were analysed in the light of pseudo-first-order, pseudo-second-order, Elovich and intraparticle diffusion models. The various kinetic parameters calculated using Eqs. 2.13–2.16 (Section 2.7, Chapter 2) for MB-TASd and CV-TASd systems are listed in the Table 6.2a.

On comparison of the R2 values it can be inferred that pseudo-second-order model (R2 = 0.9996) best represents the kinetics associated with the adsorption of MB onto TASd. The experimental value of qe is found to be in close agreement with that calculated for the pseudo-second-order kinetic model for MB-TASd system. However, for the pseudo-first-order kinetic model, these values were found to be markedly different. The linear plot of t/qt vs t is shown in Fig. 6.9a and the solution of the pseudo-second order equation obtained for this system is expressed as:

(R² = 0.9996) (6.3)

214

Pseudo-second-order kinetic model have also been found to be obeyed by various adsorbents as shaddock peel [11], cotton stalk [12], wheat straw [20], parsley stalk [21], rice hull ash [22], Arthrospira platensis [24] and coconut bunch waste [25] for the adsorption of MB dye. The values of the pseudo-second order rate constant obtained in the case of above mentioned adsorbents have been reported in the Table 6.2b.

For CV-TASd system, on the basis of comparison of the R2 values, it can be inferred that pseudo-first order model (R2 = 0.9936) is the best one representing the kinetic behaviour associated with the adsorption of CV onto TASd. The experimental value of qe is found to be in close agreement with that calculated for the pseudo-first order kinetic model. The plot of ln (qe–qt) vs t for this system is shown in Fig. 6.9b and the solution of pseudo-first order kinetic equation is expressed as:

2 (R = 0.9936) (6.4)

In literature, the majority of work on different adsorbate-adsorbent systems reports the validity of pseudo-second-order kinetics. However in the present case the pseudo-first-order kinetic model has been observed to be validated. In this context it is worth relevant to mention here that the adsorption of CV on to various similar adsorbents (calotropis procera [45], carbonaceous slurry [46], sagan sawdust [47], etc.) have also been found to follow pseudo-first order kinetic model. The values of the rate constants reported by these investigators are listed in Table 6.2c.

215

Table 6.2a.

Kinetic parameters for the adsorption of MB and CV onto TASd

(Reaction conditions for MB-TASd system: Co = 100 mg/L, Adsorbent dose = 6.0 g/L, Temperature = 298 K and pH = 7.0. Reaction conditions for CV-TASd system:

Co = 50 mg/L, Adsorbent dose = 6.0 g/L, Temperature = 298 K and pH = 7.0)

Kinetic models Parameters MB dye CV dye

-1 Pseudo-first order k1 (min ) 0.042 0.0567

qe, exp (mg/g) 15.192 7.969

qe, cal (mg/g) 7.5255 9.2027

R2 0.9678 0.9936

Pseudo-second order k2 (g/mg min) 0.0158 0.0042

qe, exp (mg/g) 15.192 7.969

qe, cal (mg/g) 15.625 10.06

R2 0.9996 0.988

1/2 Intraparticle diffusion Kid (mg min /g) 0.5994 0.8061

C 9.5631 0.7099

R2 0.9356 0.9049

Elovich α (mg/g min) 157.78 0.9229

β (g/mg) 0.5999 0.4412

2 R 0.9904 0.979

216

8 Pseudo-second order equation 7 2 t/qt= t/qe + 1/k2qe 6

4 t / q / t

0 0 20 40 60 80 100 120 t (min)

Fig. 6.9a. Pseudo-second order kinetic model for the adsorption of MB onto TASd

(Reaction conditions: Co = 100 mg/L, Adsorbent dose = 6.0 g/L, Volume of MB dye = 25 mL, Temperature = 298 K and pH = 7.0)

217

1 t (min)

) t

q 0 20 40 60 80 100 120

e -1

ln (q ln -2

-3 Pseudo-first order equation

-4 ln(qe-qt) = -kt +ln qe -5

Fig. 6.9b. Pseudo-first order kinetic model for the adsorption of CV onto TASd

(Reaction conditions: Co = 50 mg/L, Adsorbent dose = 6.0 g/L, Volume of CV dye = 25 mL, Temperature = 298 K and pH = 7.0)

218

Table 6.2b.

Pseudo-second order kinetic parameters for the adsorption of MB onto different adsorbents

System Pseudo-second order model R2 Reference k2 (g/mg min) qe,cal (mg/g)

MB-Shaddock peel 0.00005 131.19 0.9998 [11]

MB-Cotton stalk 0.0519 104.82 0.9998 [12]

MB-Wheat straw 0.4201 280.9 0.9948 [20]

MB-Parsley stalk 0.00014 83.33 0.9998 [21]

MB-Rice hull ash 0.006 23.49 0.9990 [22]

MB-Arthrospira platensis 0.0247 27.4 0.998 [24]

MB-Coconut bunch 0.041 34.36 0.991 [25]

MB-Terminalia arjuna 0.0158 15.625 0.9996 Present sawdust study

Table 6.2c.

Pseudo-first order kinetic parameters for the adsorption of CV onto different adsorbents

System Pseudo-first order model R2 Reference -1 k1 (min ) qe,cal (mg/g)

CV-Calotropis procera 0.0322 * 0.9998 [45]

CV-Carbonaceous slurry 0.227 * 0.995 [46]

CV-Sagaun sawdust 0.0972 * * [47]

CV-Terminalia arjuna 0.0567 9.2027 0.9936 Present sawdust study * Not reported.

219

6.3.9. Adsorption thermodynamics

The values of different thermodynamic parameters calculated using Eqs. 2.16– 2.20 (Section 2.8, Chapter 2) for MB-TASd and CV-TASd systems are presented in Table 6.3a and 6.3b. Negative values of ∆G˚ show the spontaneous nature of MB- TASd adsorption. However, the spontaneity was found to increases with the increase in temperature (as the negative value of ∆G˚ increases with increase in temperature). A positive value of ∆H˚ suggests that the process is endothermic in nature and positive value of ∆S˚ indicates that the adsorption process is accompanied by an increase in randomness at the solid-liquid interface [48]. The plot of ln Kc vs 1/T for this system is presented in Fig. 6.10a.

For CV-TASd system, ∆G˚ values are found to be negative indicating the feasibility of the adsorption process (Table 6.3b). It can be clearly seen that with the increase in temperature, the value of ∆G˚ becomes more and more negative indicating that the process becomes more feasible at higher temperature. ∆H˚ and ∆S˚ values are found to be positive indicating that the reaction is endothermic accompanied by an increase in entropy. The plot of ln Kc vs 1/T for this system is presented in Fig. 6.10b.

220

Table 6.3a.

Thermodynamic parameters for the adsorption of MB onto TASd

(Reaction conditions: Co= 100 mg/L, Adsorbent dose = 6.0 g/L, Temperature = 298 K and pH = 7.0)

Temperature (K) ∆G⁰ (kJ/mol) ∆H⁰ (kJ/mol) ∆S⁰ (J/K mol)

293 5.6284

303 6.7324 36.5 143.5

313 8.3764

323 9.8809

Table 6.3b.

Thermodynamic parameters for the adsorption of CV onto TASd

(Reaction conditions: Co= 50 mg/L, Adsorbent dose = 6.0 g/L, Temperature = 298 K and pH = 7.0)

Temperature (K) ∆G⁰ (kJ/mol) ∆H⁰ (kJ/mol) ∆S⁰ (J/K mol)

293 6.67

303 7.20 10.3 57.9

313 7.68

323 8.45

221

3.8

3.6 Thermodynamic equation 3.4

ln K = -∆H˚/RT + ∆S˚/R 3.2 c

∆G˚/RT)

- (

c c 2.8

ln K ln 2.6

2.4

2.2

2 3.05 3.1 3.15 3.2 3.25 3.3 3.35 3.4 3.45

103/T

Fig. 6.10a. Plot of ln Kc vs 1/T for the adsorption of MB onto TASd (Reaction

conditions: Co = 100 mg/L, Adsorbent dose = 6.0 g/L, Volume of MB dye = 25 mL, pH = 7.0 and Time = 2 hour)

222

3.2

Thermodynamic equation 3.1

ln Kc = -∆H˚/RT + ∆S˚/R

∆˚G/RT)

- (

c c 2.9 ln K ln

2.8

2.7 3.05 3.1 3.15 3.2 3.25 3.3 3.35 3.4 3.45 103/T

Fig. 6.10b. Plot of ln Kc vs 1/T for the adsorption of CV onto TASd (Reaction

conditions: Co = 50 mg/L, Adsorbent dose = 6.0 g/L, Volume of MB dye = 25 mL, pH = 7.0 and Time = 2 hour)

223

6.3.10. Desorption

One of the most important aspects of the adsorbent is its long term reusability and easy recovery which will ultimately reduce the cost of the process as well as minimise the disposal problems related to it. The desorption studies were conducted using five different solvents namely, 0.1 M HCl, 0.1 M CH3COOH, 0.1 M NaCl, 0.1 M NaOH and DDDW. The desorption potential of these agents have been given in Table 6.4. This table clearly shows that hydrochloric acid is the most suitable desorbing agent for the MB-TASd system and the most effective desorbing agent for CV-TASd system is NaOH.

Table 6.4.

Percentage desorption of MB and CV from MB-loaded and CV-loaded TASd in different media

Desorbing reagent % desorption of MB-loaded % desorption of MB- TASd loaded TASd

0.1 M HCl 18.96 1.04

0.1 M CH3COOH 11.76 1.85

0.1 M NaOH 15.58 2.86

0.1 M NaCl 3.23 0.99

DDDW 1.35 1.00

224

6.4. Conclusions

In this work, TASd has been proved to be an efficient adsorbent for the removal of MB and CV dyes from artificially contaminated water. Batch adsorption studies were carried out to find out the effects of various useful parameters such as contact time, initial dye concentration, adsorbent dosage, pH and temperature. Equilibrium time for both MB-TASd and CV-TASd systems was found to be 2 hours. Optimum TASd dosage for both the systems was found to be 6.0 g/L. Amongst the four isotherms that were used to analyse the data, Langmuir adsorption isotherm was 2 found to be most suitable with a correlation coefficient (R ) of 0.9931 and qm = 60.6 mg/g. However, for the adsorption of CV onto TASd, the best model representing the equilibrium data was found to be Freundlich adsorption isotherm model with R2 = 0.9964. The adsorption kinetics for MB-TASd system was found to be in good agreement with pseudo-second-order kinetic model with a rate constant of 0.0158 g/mg min whereas pseudo-first order kinetic model best represents the kinetic data for CV-TASd system (rate constant =0.0567 min.-1) with R2 = 0.9936. Thermodynamic studies reveal that the adsorption process is spontaneous, endothermic and accompanied by an increase in entropy for both the systems. Further, the recovery of the used adsorbent was best observed in 0.1 M hydrochloric acid for MB and 0.1 M NaOH for CV.

225

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230

Appendix I

LIST OF PUBLICATIONS

1. Sadia Shakoor, Abu Nasar, “Removal of methylene blue dye from artificially contaminated water using citrus limetta peel waste as a very low cost adsorbent”, J. Taiwan. Inst. Chem. Eng. 2016, 66, 154–163. (Published, IF= 2.848)

2. Sadia Shakoor, Abu Nasar, “Treatment of crystal violet dye from artificially contaminated water using Terminalia arjuna sawdust waste as a low cost adsorbent”, RSC Adv. (Under review, IF= 3.289)

231

Appendix II

LIST OF PAPERS PRESENTED AT CONFERENCES

1. Sadia Shakoor, Abu Nasar, “Removal of methylene blue dye from artificially

contaminated water using low-cost adsorbents”, International Conference on

“Aligarh Nano-V and STEMCON-16”, Aligarh Muslim University, Aligarh,

March 12-15, 2016.

(Poster presentation)

2. Abu Nasar*, Sadia Shakoor, “Adsorptive removal of methylene blue dye

from artificially contaminated water using citrus limetta peel waste as a very

low cost adsorbent”, International Conference on “Biomedical Engineering &

Supportive Technologies”, Bundelkhand Institute of Engg. & Technology,

Jhansi, September 02-03-2015.

(Oral presentation)

232

Appendix III Reprint of published

paper

233

Journal of the Taiwan Institute of Chemical Engineers 66 (2016) 154–163

Contents lists available at ScienceDirect

Journal of the Taiwan Institute of Chemical Engineers

journal homepage: www.elsevier.com/locate/jtice

Removal of methylene blue dye from artiﬁcially contaminated water using citrus limetta peel waste as a very low cost adsorbent

∗ Sadia Shakoor, Abu Nasar

Department of Applied Chemistry, Faculty of Engineering and Technology, Aligarh Muslim University, Aligarh 202 002, India

a r t i c l e i n f o a b s t r a c t

Article history: In the present work, the potential of citrus limetta peel (CLP) as a low cost adsorbent for the removal of Received 21 December 2015 Methylene blue (MB) dye was investigated. Batch adsorption studies were conducted to ﬁnd out how ad-

Revised 14 May 2016 sorption was affected by various factors like contact time, initial dye concentration, adsorbent dosage, pH Accepted 9 June 2016 and temperature. The experimental data was analysed in the light of Langmuir, Freundlich and Temkin Available online 2 July 2016 isotherm models. The data was found to be best represented by Langmuir adsorption isotherm with max- Keywords: imum adsorption capacity for monolayer coverage was found to be 227.3 mg/g. The data were analysed in Adsorption the light of different available kinetic models and was observed to be best followed pseudo-second order Citrus limetta peel kinetics. Wastewater Desorption of MB-loaded CLP was studied with various desorbing agents and HCl was found to be Water treatment most effective desorbing agent among HCl, NaOH, NaCl, CH 3 COOH and deionised doubly distilled water Dye removal (DDDW). Results suggest that CLP is a very effective low cost adsorbent for the removal of dyes from Methylene blue wastewater. © 2016 Taiwan Institute of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

1. Introduction dye has a number of negative impacts on human beings and animals; such as irritation of mouth, throat, oesophagus and stomach Water is essential for the survival of all living organisms. To- with symptoms of nausea, abdominal discomfort, vomiting and di- day contamination of freshwater systems with a wide variety of arrhoea. Skin contact may cause mechanical irritation resulting in pollutants is a subject of great concern. Out of all the contami- redness and itching. Thus, removal of MB dye from wastewater is nants present in industrial effluents, dyes are an important class of great concern from human and environmental point of view as of pollutants and can be identified by even human eye. Dyes are well. used as colouring agents in a variety of industries such as textiles, Several techniques like flocculation, adsorption, oxidation, elec- food, paper, rubber, plastics, cosmetics, leather, etc . The discharge trolysis, biodegradation, ion-exchange, photo catalysis have been of wastewater from these industries to water resources causes un- employed for the removal of dyes from wastewater [2] . Amongst avoidable problems due to the toxic and unpleasant nature of dyes. the various techniques, adsorption has received considerable atten- The presence of dyes in water in trace amount is undesirable be- tion due to its several advantages in terms of cost, ease of opera- cause most of them are toxic, mutagenic and carcinogenic [1] . Dyes tion, flexibility and simplicity of design and insensitivity to toxic also prevent light penetration and thereby reduce photosynthetic pollutants [3,4] . Among the variety of adsorbents, activated car- activities of water streams and disturb the aquatic equilibrium. bon may be logically the most preferred adsorbent for the removal Thus, removal of dyes from wastewater before discharge is a chal- of dyes because of its excellent adsorption ability [5] . However, lenging task. widespread use of activated carbon is restricted because of its high Methylene blue (MB), a cationic dye, is most commonly used cost [6] . Thus, attention has shifted to find cheaper and efficient as the colouring agent for cotton, wool and silk. It is also used as alternatives of activated carbon. Natural materials, agricultural and a staining agent to make certain body fluids and tissues easier to industrial wastes and bio-sorbents represent potential alternatives. view during surgery and diagnostic examinations. The medical ap- A number of non-conventional and low cost adsorbents have been plications of MB also include the treatment of methaemoglobine- proposed by many workers for the removal of dyes [7–10] . These mia and cyanide poisoning. In spite of several applications, this include agricultural waste products (saw dust [11] , bark [12] , orange peel [13] ), industrial waste products (metal hydroxide sludge [14] , red mud [15] , fly ash [16] ), clay materials (bentonite [17] , di- ∗ Corresponding author. Tel.: + 91 571 2700920; fax: + 91 571 2700528. atomite [18] ), zeolites [19,20] , siliceous materials (silica beads [21] , E-mail address: [email protected] (A. Nasar). http://dx.doi.org/10.1016/j.jtice.2016.06.009 1876-1070/© 2016 Taiwan Institute of Chemical Engineers. Published by Elsevier B.V. All rights reserved. S. Shakoor, A. Nasar / Journal of the Taiwan Institute of Chemical Engineers 66 (2016) 154–163 155 alunite [22] , dolomite [23] ), biosorbents (chitosan [24] , peat [25] , given as: biomass [26,27] ) and others (cyclodextrin [28,29] , starch [30] , cot- C o − C e ton [31] ) etc . q e = V (1) m Many low cost adsorbents such as jack fruit peel [32] , garlic peel [33] , hazelnut shell [34] , pine apple stem [35] , longan shell where, C o and C e are the initial and equilibrium concentrations [36] , spent tea leaves [37] zeolite [38] , corn cobs [39] have been (mg/L) of MB, respectively, V is the volume of solution (L) and m is reported in literature for the adsorption of methylene blue dye. the mass of adsorbent (g). However, literature survey reveals that so far no considerable ef- The percentage removal of MB (% R ) was calculated using the fort has been made to study the treatment of MB dye by citrus equation: limetta peels. Citrus limetta is a species of citrus, commonly known C o − C e as sweet lime, sweet lemon or mousambi. It is a native to south % R = × 100 (2) C and south-east Asia and cultivated in the Mediterranean Basin. In o India, it is available throughout the year and abundantly during the The equilibrium data so obtained have been made to anal- months of July and August and also from November to March. It is yse in the light of different available isotherm models. The Lang- generally taken as a fresh fruit or consumed as juice. Its juice is muir isotherm [40] has been commonly used to discuss various commonly sold by roadside stalls and mobile vendors. The peels adsorbate–adsorbent combinations for both liquid and gas phase of citrus limetta are discarded as waste. In view of the above facts, adsorptions. This isotherm may be represented as: the present investigation was undertaken with the prime objective q m K L C e to explore the feasibility and utilization of CLP for the adsorptive q e = (3) 1 + K C removal of MB dye. It has also been decided to optimize, wher- L e ever possible, the important variables which affect the adsorption where, q m is the maximum adsorption capacity (mg/g) to form a capacity. complete monolayer coverage on the surface bound at high equilibrium adsorbate concentration ( C e ) (mg/L) and K L (L/mg) is Lang- 2. Materials and methods muir constant related to affinity between the adsorbate and adsorbent. 2.1. Materials The Langmuir equation can be arranged to following linearised form: Analytical reagent grade each MB dye (Loba Chemie, India), HCl 1 1 1 = + (Merck, Germany), NaOH (CDH, India), NaCl (CDH, India), KNO (4) 3 q e q m K L C e q m

(CDH, India) and CH3 COOH (SD Fine, India) were used in the present investigation. The water used was puriﬁed by deionisation The essential characteristics of Langmuir isotherm can be ex- followed by double distillation. This doubly distilled deionised wa- pressed by dimensionless parameter known as separation factor, ter (DDDW) was used throughout the experiment. RL , which is deﬁned as: 1 = 2.2. Preparation and characterization of CLP adsorbent R L (5) 1 + K L C o

CLP waste was collected from local fruit stall, washed thor- where, C o (mg/L) is the initial concentration of MB dye. The value oughly by DDDW to remove dust and water soluble impurities of RL throws light on the nature of adsorption to be either un- > = < < from its surface and dried in the sunlight for about 4 days and favourable (RL 1), linear (RL 1), favourable (0 RL 1), or irre- = then in an air oven at 90 °C for 24 h until the peels become crisp. versible (RL 0). The dried mass was pulverised into the fine powder by a mechan- Freundlich model is an empirical isotherm commonly used to ical grinder and then sieved to pass through 80 BSS mesh. It was describe heterogeneous system. The model is represented in linear then washed with DDDW till the colour and turbidity of wash- form as: ings were completely removed. The washed adsorbent was finally 1 ln q e = ln C e + ln K (6) dried in an air oven at 105 °C for about 4 h. After drying, the mass n F was crushed again, screened through a set of sieves to get differ- − where, K (mg 1 1/nL 1/n/g) and n are Freundlich constants related ent fractions, namely, 80–150, 150–20 0 and > 20 0 BSS scales and F with the adsorption capacity and adsorption intensity, respectively stored in air tight containers. [41] . The surface morphology of CLP before and after adsorption Another model, Temkin is also used to fit the experimental data. was analysed by Scanning electron microscopy (JEOL, JSM6510LV, This model assumes that heat of adsorption on the surface de- Japan). Fourier Transform Infrared spectrometer (FTIR) was used to creases linearly with the coverage adsorbate–adsorbent interaction analyse the functional groups on the surface of CLP in the spectral [42] . The linear form of the Temkin adsorption isotherm is given range of 40 0 0 to 400 cm ¯1. as:

2.3. Batch equilibrium studies q e = B ln C e + B ln K T (7)

= The batch equilibrium experiments were planned to determine where, B RT/b, b is Temkin isotherm constant related with heat of the efficiency of CLP for the removal of MB from aqueous so- adsorption (J/mol) and KT is the equilibrium binding constant (L/g). lution. The adsorption experiments were carried out by taking 25 mL of adsorbate solutions with varying initial concentrations 2.4. Adsorption kinetics (25–250 mg/L) in different conical flasks of borosilicate glass. The fixed quantity of adsorbent (0.05 g) was added to each flask kept In order to understand the kinetics behind the MB removal pro- on a shaker and equilibrated for 3 h. After filtration, the resid- cess, the extent of adsorption was monitored as function of time. ual concentration of MB was measured by a UV–vis spectropho- The method was similar to that employed for the equilibrium stud- tometer at a pre-optimised λmax of 665 nm. The amount of MB ies. The samples from the reaction flasks were withdrawn at the dye adsorbed at equilibrium is expressed by a factor q e (mg/g) pre-planned time intervals and the residual concentrations of MB 156 S. Shakoor, A. Nasar / Journal of the Taiwan Institute of Chemical Engineers 66 (2016) 154–163 were measured. The amount of MB at time t , q t (mg/g) was cal- a culated by using the equation, which is mathematically similar to Eq. (1) .

C o − Ct qt = V (8) m where, C t is the residual concentration of MB at time t . The kinetic data were analysed in the light of pseudo-ﬁrst order [43–45] , pseudo-second order [46,47] , intraparticle diffusion [48–51] and Elovich [52–54] models. The linear form of pseudo-ﬁrst order kinetic model is given as: ln ( q e − qt ) = ln q e − k 1 t (9) where, qt is the amount of MB adsorbed at time t (mg/g) and k1 is the adsorption rate constant (min −1 ). Pseudo-second order kinetic model is based on the assumption b that chemisorption is the rate-limiting step. Its linear form is represented as: t 1 t = + (10) 2 qt k2 qe qe where, t is time (min) and k2 is the pseudo-second order rate constant (g min/mg). Intraparticle diffusion model is based on the theory proposed by Weber and Morris which explains the mechanism of adsorption through diffusion and mathematically expressed as: / = 1 2 + qt kid t C (11) 1/2 where, kid is intraparticle diffusion rate constant (mg min /g) and Fig. 1. SEM images of (a) CLP adsorbent and (b) MB-loaded CLP. C is a constant. Elovich model is used to explain the adsorption of gases onto where, m and m are the amounts of MB desorbed (mg/L) and adsorbent. According to this model, due to increase of surface cov- d a adsorbed (mg/L), respectively. erage rate of adsorption decreases with increasing time. The linear form of the model may be expressed as: 3. Results and discussion ln ( αβ) 1 qt = + ln t (12) β β 3.1. Material characterisation where, α (mg/g min) is the initial adsorption rate of Elovich model, β (g/mg) is the desorption constant of Elovich model and t (min) The morphological features and surface characteristics of CLP is time. adsorbent samples before and after adsorption by MB were ex- amined using SEM and depicted in Fig. 1 (a) and (b), respectively. 2.5. Adsorption thermodynamics Fig. 1 (a) shows that that the surface of the untreated CLP is irregular and contains pores of different sizes and shapes which provide The thermodynamic parameters associated with the adsorption large surface area for MB-surface interaction. The surface of dye process, viz. free energy change ( ࢞G °) (kJ/mol), enthalpy change loaded adsorbent as shown in Fig. 1 (b), however, clearly exhibits ( ࢞H °) (kJ/mol) and entropy change ( ࢞S °) (J/K mol) were deter- that the surface of CLP is saturated i.e. covered by MB molecules. mined by using the equations: FTIR spectroscopy was used in order to determine the presence of different functional groups on the surface of CLP adsorbent. The G = − RT ln K c (13) FTIR spectra of CLP before and after adsorption with MB is shown −1 G ◦ H ◦ S ◦ in Fig. 2. The band at 3442 cm might be presumably due to O–H −1 ln K c = − = − + (14) stretching of carboxyl group. The band at 2925 cm might be due RT RT R to antisymmetric and symmetric stretching of C –H bond of methyl where, R, Kc and T are gas constant (8.314 J/K mol), equilibrium and methylene groups. Sharp band near 1742 cm −1 is due to C = O constant and temperature (K) respectively. stretching and strong band near 1643 cm −1 may be attributed to = 2.6. Desorption studies C O stretching of carboxylic acid. In MB-loaded CLP, the decrease in peak intensity at 3442 cm −1 and 1643 cm −1 indicates the in-

The desorption experiments were carried out in batch with dif- volvement of hydroxyl group and carboxyl group, respectively, in

binding with MB during adsorption. Minor changes in other fre- ferent media such as 0.1 M HCl, 0.1 M NaOH, 0.1 M CH3 COOH, 0.1 M

NaCl and water. 0.5 g adsorbent was treated separately with 50 mL quencies are also observed. of 50 mg/L dye solution for 3 h. The dye-loaded adsorbents were thoroughly washed several times with DDDW to remove any unad- 3.2. Effect of contact time and initial concentration of dye sorbed dye present. The dye-loaded adsorbents then agitated with

25 mL of different desorbing solutions and equilibrated for 4 h. The The effect of contact time and initial dye concentration on the desorbed dye concentration was measured and percent desorption adsorption capacity of CLP at different initial concentrations of MB was calculated by using the equation: is shown in Fig. 3. The ﬁgure shows that adsorption capacity increases with contact time and reaches to equilibrium after 3 h. m % Desorption = d × 100 (15) However, the increase is relatively higher during initial 30 min. m a S. Shakoor, A. Nasar / Journal of the Taiwan Institute of Chemical Engineers 66 (2016) 154–163 157

above 2 g/L, this concentration was chosen as optimum dose for further studies. The increasing removal eﬃciency in this range of adsorbent (0.4–2 g/L) is due to increase in surface area and the availability of more binding sites for adsorption. The decrease in adsorption capacity ( q e ) with increase in adsorbent dosage might be due to interaction of adsorbent particles like aggregation or agglomeration which resulted in decrease of the total surface area.

3.4. Effect of pH

The effect of pH on removal of MB dye by CLP adsorbent is depicted in Fig. 6 . The adsorption capacity has been observed to increase drastically with increasing in pH of the solution. How- ever, the increase is more pronounced in the lower pH range. In acidic conditions ( i.e. the lower range of pH), the adsorbent surface has positive charge resulting an electrostatic repulsion with cationic MB dye. With the increase of pH, the adsorption capacity increases due to decrease of repulsive force between adsorbent– Fig. 2. FT-IR spectrum of CLP and MB-loaded CLP. adsorbate system. The ﬁnding is in agreement with the existing hypothesis of increasing negatively charged sites/decreasing posi-

Rapid increase in adsorption during the initial stage may presum- tively charged sites of adsorbent with increase of pH [55]. ably be due to the availability of vacant active sites on the surface In fact the effect of solution pH on the dye uptake can be best of the dye. The slow increase at the later stage is due to the dif- explained on the basis of point of zero charge (pHpzc ). It is a confusion of dye into the pores of the adsorbent because the external venient and useful parameter of surface to judge when it becomes sites are completely occupied. It is also inferred from Fig. 3 that positively or negatively charged as function of pH. The point of the adsorption capacity increases with increasing initial dye con- zero charge (pHpzc ) value of CLP was found to be 8.0 (Fig. 7). This < centration at any dye-adsorbent contact time. The values of equi- indicates that the adsorbent surface has positive charge at pH 8, = > librium adsorption capacity ( i.e. for the contact time of 180 min.) net zero charge at pH 8 and negative charge at pH 8. Thus, the have been plotted in Fig. 4 against equilibrium dye concentration favourable condition for adsorption of any cationic dye such as MB for different initial dye concentration as labelled on each point. The by the surface of CLP is the medium having pH greater than 8. This

ﬁgure clearly indicates that the equilibrium adsorption capacity in- is because of the fact that the surface of CLP adsorbent becomes creases with increasing equilibrium dye concentration irrespective negatively charged and favours the uptake of cationic dye. of the initial dye concentration. 3.5. Effect of particle size

3.3. Effect of adsorbent dosage Adsorption of MB dye on CLP adsorbent was studied using three different size fractions of adsorbent particles (80–150, 150–200 The effects of adsorbent dose on the removal efficiency ( i.e. per and > 200 BSS mesh). Fig. 8 shows the effect of particle size on the cent adsorption) and adsorption capacity are shown in Fig. 5 . It has removal efficiency of MB. It has been observed that as the parti- been observed that as the concentration of CLP adsorbent is in- cle size is decreased, removal efficiency is increased from 93.5% to creased from 0.4 to 2.0 g/L, removal efficiency is increased rapidly 98.2%. It is due to the fact that smaller particle size provides large from 94.6% to 97.1%. Thereafter, no significant change has been ob- surface area for adsorption which results in the higher removal served. As the adsorption saturation is reached at adsorbent dose of dye. Maximum removal efficiency is associated with mesh size

Fig. 3. Effect of contact time on the adsorbent capacity of MB at different concentrations. 158 S. Shakoor, A. Nasar / Journal of the Taiwan Institute of Chemical Engineers 66 (2016) 154–163

Fig. 4. Effect of equilibrium concentration of MB concentration on adsorption of MB for its different initial concentration.

Fig. 5. Effect of adsorbent dosage on removal eﬃciency and adsorption capacity.

> 200. However, because of handling problem accompanying with banana leaves [62] and Bacillus subtilis [63] has also been found to small particles and for easy separation of solid and liquid phases, obey Langmuir isotherm. The values of Langmuir constants as eval- particles of 80–150 mesh size have been chosen throughout. uated by these investigators are compared with those of present study Table 2 . This table clearly indicates that the values of Lang- 3.6. Adsorption isotherms muir constants obtained in the present study fall within the ranges comparable to those of reported earlier. The experimental results have been fitted on the Langmuir, Freundlich and Temkin isotherm models. The values of different 3.7. Adsorption kinetics isotherm constants for the adsorption of MB onto CLP are listed in Table 1 . In the light of relative values of R 2 , Table 1 clearly in- Kinetic parameters for all the four kinetic models are reported dicates that the data can be best represented by Langmuir adsorp- in Table 3 . On the basis of comparison of the values of the cor- tion isotherms ( Fig. 9 ). It is worth to mention here that adsorptive relation coefficient, it was found that pseudo-second order kinetic removal of MB dye by other adsorbents obtained from agricultural model ( Fig. 10 a and b) fits the experimental data perfectly. waste such as wheat straw [56] , cotton stalk [57] , cucumber peels Pseudo-second order kinetics have also been observed to be [58] , rice hull ash [59] , shaddock peel [60] , cottonseed hull [61] , obeyed for the adsorption of MB onto different adsorbents such as S. Shakoor, A. Nasar / Journal of the Taiwan Institute of Chemical Engineers 66 (2016) 154–163 159

Fig. 6. Effect of pH on adsorption of MB.

Fig. 7. Determination of point of zero charge for CLP adsorbent.

Table 1 Table 2 Isotherm parameters for the adsorption of MB onto Langmuir isotherm parameters for the adsorption of MB by different adsor-

CLP (Reaction conditions: C o = 50 mg/L, Adsorbent bents. = = = = dose 2 g/L, t 3 h, Temperature 298 K, pH 9). System Langmuir constants R 2 Reference

Isotherm models Parameters Values R 2 K L q m Langmuir q 227.3 0.9787 m MB-wheat straw 0.0036 274.1 0.9984 [56] K 0.0288 L MB-cotton stalk 0.0249 147 .1 0.9970 [57] R 0.4089 L MB-cucumber peels 0.0573 111.1 0.9991 [58] Freundlich n 1.438 0.9676 MB-rice hull ash 0.606 17.1 0.9987 [59] K 8.758 F MB-shaddock peel 0.0146 309.6 0.9993 [60] Temkin b 83.084 0.9756 MB-cottonseed hull 0.12755 185 .2 0.9994 [61] K 0.648 T MB-banana leaves 0.116 109.9 0.9996 [62] MB-Bacillus subtilis 0.0164 169.5 0.9884 [63] MB-citrus limetta 0.0289 227.3 0.9787 Present study wheat straw [56] , cotton stalk [57] , parsley stalk [58] , rice hull ash [59] , shaddock peel [60] , Arthrospira platensis [64] and coconut 3.8. Adsorption thermodynamics bunch waste [65] . The values of pseudo-second order rate constant as obtained by the above investigators are incorporated in Table 4 . For the adsorption of MB onto CLP adsorbent, the values of Our results are judiciously comparable with those of other investi- Gibbs free energy ( ࢞G °) was found to be ̶ 7.87, ̶ 9.38, ̶ 10.49 and ̶ gators. 12.41 kJ/mol at 293, 303, 313 and 323 K, respectively ( Table 5 ). The 160 S. Shakoor, A. Nasar / Journal of the Taiwan Institute of Chemical Engineers 66 (2016) 154–163

Fig. 8. Effect of particle size on adsorption of MB.

Fig. 9. Langmuir adsorption for the adsorption of MB onto CLP adsorbent at 298 K.

Table 3 negative value of Gibbs free energy indicates that the adsorption of Kinetic study for the adsorption of MB onto CLP adsorbent MB onto CLP adsorbent is spontaneous. Since the negative value of = = (Reaction conditions: Co 50 mg/L, Adsorbent dose 2 g/L, Gibbs free energy decreases with temperature, it may be inferred = = Temperature 298 K, pH 9). that adsorption becomes more feasible at higher temperatures. The

Kinetic models Parameters Values R 2 increase of feasibility with temperature clearly indicates the pre- dominant role of entropy factor. Pseudo-ﬁrst order k 0.013 0.9022 1 The values of ࢞H ° and ࢞S ° were calculated from the slope q e , exp 23.333

q e , cal 1.092 and intercept of ln kc vs 1/T plot (Fig. 11). The change in en- Pseudo-second order k 2 0.057 0.9999 thalpy ( ࢞H °) was found to be 35.13 kJ/mol. The positive value

qe , exp 23.333 of ࢞H ° signiﬁes that the adsorption of MB onto CLP adsorbent

qe,cal 23.255 is endothermic. Thus, the spontaneity of the adsorption is only Intraparticle diffusion K 0.077 0.9657 id ࢞ C 22.22 due to entropy factor. The entropy change ( S°) was found to be Elovich β 200.0 0.9340 146.7 J/K mol. The positive value of entropy change indicates an S. Shakoor, A. Nasar / Journal of the Taiwan Institute of Chemical Engineers 66 (2016) 154–163 161

Fig. 10. (a) Pseudo-second order kinetic model for the adsorption of MB onto CLP adsorbent (for 50 mg/L). (b) Pseudo-second order kinetic model for the adsorption of MB onto CLP adsorbent at different concentrations of MB.

Table 4 Pseudo-second order rate constant for the adsorption of MB onto different adsorbents.

System Pseudo-second order model R 2 Reference

k 2 q cal

MB-wheat straw 0.4201 280.9 0.9948 [56] MB-cotton stalk 0.0519 104.82 0.9998 [57] MB-parsley stalk 0.0 0 014 83.33 0.9998 [58] MB-rice hull ash 0.006 23.49 0.9990 [59] MB-shaddock peel 0.0 0 0 05 131 .19 0.9998 [60] MB-Arthrospira platensis 0.0247 27.40 0.998 [64] MB-coconut bunch 0.041 34.36 0.991 [65] MB-citrus limetta peel 0.057 23.255 0.9999 Present study

increase in randomness at the adsorbate-solution interface during as Bacillus subtilis -MB [63] , Wheat shells - Methylene blue [67] , Oak adsorption process. The increase in entropy is presumably due to sawdust-MB [68] , Litchi chinensis -Acid Blue 25 [69] , Brazilian-pine gain of translational entropy by the dye molecules during adsorp- fruit shell-Reactive Orange 16 [70] , CTAB Bentonite-Supranol yel- tion process [66] . In this context, it is relevant to mention here low 4GL [71] , Tea waste-MB [72] , Phenol-OTMAC modiﬁed atta- that the increase in randomness i.e. positive entropy change has pulgite [73] , Reed-Basic yellow [74] , Illitic clay mineral-MB [75] , been reported on a number of adsorbent–adsorbate systems such Coir pith-MB [76] , Flyash-MB [77] . 162 S. Shakoor, A. Nasar / Journal of the Taiwan Institute of Chemical Engineers 66 (2016) 154–163

Fig. 11. Plot of ln k c vs 1/ T for the adsorption of MB onto CLP adsorbent.

Table 5 isotherm study indicated that the equilibrium data were in agree-

Thermodynamic parameters for the adsorption of MB onto CLP (Reac- ment with Langmuir isotherm model. Maximum adsorption capac- tion conditions: C o = 50 mg/L, Adsorbent dose = 2 g/L, t = 3 h, pH = 9). ity ( q m ) was found to be 227.3 mg/g. The adsorption process was Temperature (K) ࢞G ° (kJ/mol) ࢞H ° (kJ/mol) ࢞S ° (J/K mol) found to be spontaneous and endothermic accompanied by an increase in entropy. The recovery of CLP from MB-loaded CLP for 293 −7.87

303 −9.38 35.13 146.7 reuse was found to maximum in 0.1 M HCl. 313 −10.49 Thus, it was concluded that CLP is an effective adsorbent for 323 −12.41 the removal of MB from aqueous solution. Also, CLP adsorbent is cheap and available in abundance throughout the year. Being a Table 6 waste product, it resolves waste management issues as well. Percentage desorption of MB from MB- loaded CLP in different media. Acknowledgements Desorbing reagent % desorption The authors are grateful to the Chairman, Department of Ap-

0.1 M HCl 32.46 plied Chemistry, Faculty of Engineering and Technology, Aligarh 0.1 M CH COOH 14.64 3 0.1 M NaOH 4.82 Muslim University for providing necessary laboratory facilities. 0.1 M NaCl 2.87

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