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REMOVAL OF ANTIBIOTICS FROM WASTEWATER
BY NANOCOMPOSITES AND MEMBRANE HYBRID
TECHNOLOGY
By
AZMAT ULLAH
DEPARTMENT OF CHEMISTRY
UNIVERSITY OF MALAKAND
2019
REMOVAL OF ANTIBIOTICS FROM WASTEWATER
BY NANOCOMPOSITES AND MEMBRANE HYBRID
TECHNOLOGY
By
AZMAT ULLAH
Thesis submitted to the Department of Chemistry, University of Malakand for the
partial fulfillment of the requirement
For the Degree of
DOCTOR OF PHILOSOPHY IN CHEMISTRY
DEPARTMENT OF CHEMISTRY
UNIVERSITY OF MALAKAND
2019
CERTIFICATE
IT IS RECOMMENDED THAT THIS THESIS PREPARED BY MR. AZMAT ULLAH
ENTITLED “REMOVAL OF ANTIBIOTICS FROM WASTEWATER BY
NANOCOMPOSITES AND MEMBRANE HYBRID TECHNOLOGY” BE ACCEPTED
AS FULFILLING THIS PART OF THE REQUIREMENT FOR THE DEGREE OF DOCTOR
OF PHILOSOPHY IN CHEMISTRY.
DR. SULTAN ALAM DR. MUHAMMAD ZAHOOR
Research Supervisor Research Co-Supervisor
DR. MANZOOR AHMAD
Chairman
WE HEREBY APPROVE THE THESIS FOR THE AWARD OF PhD DEGREE
INTERNAL EXAMINER EXTERNAL EXAMINER
To
MY FATHER (LATE)
Whose love, patience, support and encouragement stay with me
throughout my life
(AZMAT ULLAH)
December 2018
ACKNOWLEDGEMENT
All praises to Almighty Allah, who guides us in darkness to light and blessing the
Holy Prophet Muhammad (peace be upon him) who enabled us to recognize our
creator.
I owe a special debt of gratitude to my supervisor, Dr. Sultan Alam, Associate
Professor, Department of Chemistry, and Dr. Muhammad Zahoor, Assistant
Professor, Department of Chemistry, University of Malakand for his proper
guidance, hour-long discussion, sympathetic attitude, constant encouragement,
constructive criticism and valuable advices at the critical junctures during the
course of this work.
I feel great pleasure in expressing heart felt gratitude to my parents, who always
offered humble prayers for my success. Heart felt gratitude is also due to my
brothers and uncles for their continuous encouragements, keen interest,
sympathetic attitude and full financial support, without which this work would
not have been successfully completed.
Thanks to Prof. Dr. Rashid Ahmad, Dean Faculty of Science, University of Malakand,
Dr. Manzoor Ahmad, Chairman Department of Chemistry, Dr. Mumtaz Ali, Dr.
Najeeb, Dr. Mian Mohammad, Dr. Ezzat Khan, Dr. Mohammad Naveed Umar, and
Dr. Mohammad Sadiq, Department of Chemistry, University of Malakand, Prof.
Nawsherwan, Prof. Ali Muhammad, Prof. Riaz Ahmad, Prof. Muhammad Ajmal
Khan, Dr. Waqas, Dr. Hanif, Prof. Hazrat Rahman, Prof. Dr. Nisar , Dr. Nisar, Prof.
Naseeb Rawan, Prof. Rahat Gul Rahat, Dr. Sardar Ahmad, Prof . Khan Bahader, Prof.
Usman and Prof. Rehmat ullah, Mr. Misal Bacha, Mr. Sher Ali Khan, Mr. Mohammad
Ali, Mr. Sardar Ali, Mr. Sher Shah, Mr. Muhammad Irfan, Mr. Waseem Ahamad and
Mr. Abdul Bari Shah (PhD research Scholars at UOM), Muhammad Ali (Lab.
Attendant) for their cooperation.
Azmat Ullah
Table of Contents
S # Content Page
#
List of Figures i
List of Tables vi
List of Abbreviations viii
List of publications
ix
Abstract x
CHAPTER 1.0 INTRODUCTION
1.1 Background 1
1.2 Antibiotics 1
1.3 Types/ classification of antibiotics 2
1.3.1 Beta-lactams 3
a Penicillin 4
b Cephalosporin 4
c Monobactams 4
d Carbapenems 5
1.3..2 Macrolides 5
1.3.3 Tetracyclines 5
1.3.4 Aminoglycosides 6
1.3.5 Sulphonamides 6
1.3.6 Chloramphenicol 7
1.3.7 Quinolones 7
1.3.7.1 History 7
1.3.7.2 Metabolism and excretion 7
1.3.7.3 Applications of FQs 8
1.4 Consumption of antibiotics 8
1.5 The entry sources of antibiotics to the environment 9
1.5.1 Natural sources 9
1.5.2 Pharmaceutical industry 9
1.5.3 Antibiotics consumption 10
1.5.4 Sewage from hospitals and health care centers 10
1.5.5 Veterinary 10
1.5.6 The production of herbal products 10
1.5.7 Aquaculture 11
1.6 Occurrence of antibiotics in the environment 11
1.6.1 Occurrence in wastewater treatment plants (WWTPs) 11
1.6.2 Occurrence in domestic water 12
1.6.3 Rivers, streams and lakes 13
1.6.3.1 Seawater 13
1.6.3.2 Ground water 14
1.6.4 Occurrence in soil and sediments 14
1.6.5 Occurrence in plants and aquatic animals 15
1.7 The effect of antibiotics on the environment 15
1.7.1 The Impacts of Antimicrobials on the (WWTS) Wastewater Treatment System 16
1.7.2 The effect of antibmicrobials on surface water 17
1.7.3 The effect of antibiotics on sediments 17
1.8 Issues related to the presence of antibiotics in the environment 17
1.9 Reasons for treatment of aqueous solutions containing antibiotics 20
1.10 Treatment technologies used for the remediation of antibiotics from aqueous
solutions 20
1.10.1 Photodegradation 20
1.10.2 Membrane technologies 21
a Microfiltration (MF) membranes 22
b Membrane biological reactors (MBR) 22
c Ultrafiltration (UF) membranes 22
d Nanofiltration (NF) membranes 23
e Reverse osmosis (RO) membranes 23
1.10.3 The process of coagulation, flocculation and sedimentation 24
1.10.4 The process of ultrasonic radiations (UR) 24
1.10.5 The advanced oxidation procedure (AOP) 24
1.10.6 Biodegradation 25
1.10.7 Adsorption 26
1.10.8 Membrane processes 29
1.11 Aims and objectives 30
1.12 Hypothesis 31
CHAPTER 2.0 LITERATURE REVIEW
2.1 Literature review 32
Knowledge gaps 58
CHAPTER 3.0 EXPERIMENTAL
3.1 PREPARATION OF MAGNETIC CARBON NANOCOMPOSITES (MCN)
FROM BIOMASS PRECURSORS OF PINEAPPLE AND MANGO 60
Instruments 60
Chemicals and reagents 60
Procedure 60
3.2 CHARACTERIZATION OF MAGNETIC CARBON NANOCOMPOSITES
(MCN) FROM BIOMASS PRECURSORS OF MANGO AND PINEAPPLE 61
3.2.1 BET Surface Area 61
3.2.2 FTIR analysis 61
3.2.3 Elemental analysis or energy dispersive X-Ray (EDX) 62
3.2.4 Scanning electron microscopy (SEM) 62
3.2.5 X-Ray diffraction analysis (XRD) 62
3.2.6 Thermogravimetric and differential thermal analysis (TG/DTA) 62
3.2.7 Zero-point charge (pHpzc) 62
3.2.8 pH 62
3.2.9 Moisture contents 63
3.2.10 Ash contents 63
3.3 FQs antibiotics solution preparation 64
Instruments 64
Chemicals and reagents 64
Procedure 65
3.4 FQs adsorption (batch studies) 67
3.4.1 Adsorption kinetics 68
3.4.2 Adsorption isotherm studies 68
3.4.3 Determination of thermodynamic parameters 68
3.4.4 Effect of the adsorbent dose and pH on FQs removal 69
3.4.5 Effect of humic acid (HA) on FQs removal 69
3.4.6 Effect of ionic strength (sodium chloride) on adsorption capacity of MCN 69
3.4.7 Removal of FQs by membrane process 69
3.4.8 Removal of FQs by membrane hybrid process 70
3.4.9 Reusability/regeneration and recycling of MCN (desorption experiments) 72
Instruments 72
Chemicals and reagents 72
Procedure 72
3.4.10 Determination of drug resistance developed by bacteria found in the industrial
effluents against selected antibiotics 73
CHAPTER 4.0 RESULTS AND DISCUSSION
4.1 Socio-economic impacts of the present research work 74
4.2 Characterization of the nanocomposites 74
4.2.1 Surface area analysis 75
4.2.2 Energy dispersive X-ray (EDX) analysis 78
4.2.3 Scanning electron microscopy (SEM) 79
4.2.4 Thermogravimetric and differential thermal analysis (TG/DTA) 82
4.2.5 X-ray diffraction (XRD) analysis 84
4.2.6 Fourier-transform infra-red (FTIR) analysis 86
4.2.7 Zero point charge (pHpzc) 87
4.2.8 pH of nanocomposites slurry 89
4.2.9 Ash and moisture contents of nanocomposites 89
4.3 Drug resistance developed by streptococci and staphylococci against FQs 89
4.4 Batch adsorption studies 90
4.4.1 Giles isotherm 90
4.4.2 Langmuir isotherm 90
4.4.3 Freundlich isotherm 91
4.4.4 Jovanovich isotherm 92
4.4.5 Tempkin isotherm 93
4.5 Adsorption kinetics 111
4.5.1 Effect of contact time 111
4.5.2 Adsorption kinetic models 111
4.5.2.1 Pseudo 1st and 2nd order kinetic models 111
4.5.2.2 Intraparticle diffusion model 114
4.6 Adsorption thermodynamics 134
4.7 Effect of adsorbent dosage and pH on adsorption of FQs 140
4.8 Effect of humic acid (HA) on FQs removal 150
4.9 Effect of ionic strength (sodium chloride) on FQs removal 156
4.10 Membranes and adsorption/membrane hybrid processes 162
4.10.1 Effect of selected FQs antibiotics (CIP, LEV and ENR) on permeate flux of UF,
NF and RO membranes 162
4.10.2 Improved permeate flux of UF, NF and RO membranes with PAMCN and
MAMCN in hybrid manner 177
4.10.3 Percent retention/rejection of selected FQs antibiotics by membranes and
adsorption/membrane hybrid processes 190
4.10.4 Back wash time of UF, NF and RO membrane systems 206
4.11 Reusability/Regeneration and recycling of MCN (Desorption experiment) 206
4.12 Comparison with other adsorbents 213
CONCLUSIONS 214
REFERENCES 218
i
List of Figures
Figure No Caption Page No.
1.1 Chemical structure of beta-lactam (core structure of Penicillins) 3
1.2 Chemical structure of beta-lactam (core structure of Cephalosporin) 4
1.3 Chemical structure of Tetracycline 6
3.1 Calibration curve of CIP 66
3.2 Calibration curve of LEV 66
3.3 Calibration curvesof ENR 67
3.4 Membrane hybrid plant 71
4.1 Plot of BET surface area of PAMCN sample 76
4.2 Plot of BET surface area of MAMCN sample 76
4.3 BJH pore size distribution plot of PAMCN sample 77
4.4 BJH pore size distribution plot of MAMCN sample 77
4.5 EDX spectra of PAMCN sample 78
4.6 EDX spectra of MAMCN sample 79
4.7a SEM of PAMCN sample 80
4.7b SEM of PAMCN sample 80
4.7c SEM of (PAMCN sample 81
4.8a SEM of MAMCN sample 81
4.8b SEM of MAMCN sample 81
4.8c SEM of MAMCN sample 81
4.8d SEM of MAMCN sample 81
4.8e SEM of MAMCN sample 82
4.8f SEM of MAMCN sample 82
4.9 TG/DTA plot of PAMCN sample 83
4.10 TD/DTA plot of MAMCN sample 83
4.11 XRD diffractogram of PAMCN sample 85
4.12 XRD diffractogram of MAMCN sample 85
4.13 FTIR spectra of PAMCN sample 86
4.14 FTIR spectra of MAMCN sample 87
4.15 Mass titration plot of PAMCN sample for pHpzc 88
4.16 Mass titration plot of MAMCN sample for pHpzc 88
4.17 Adsorption isotherm of CIP onto PAMCN 94
4.18 Langmuir adsorption isotherm model of CIP onto PAMCN 95
4.19 Freundlich adsorption isotherm model of CIP onto PAMCN 95
4.20 Jovanovich adsorption isotherm model of CIP onto PAMCN 96
4.21 Tempkin adsorption isotherm model of CIP onto PAMCN 96
4.22 Adsorption isotherm of LEV onto PAMCN 97
4.23 Langmuir adsorption isotherm model of LEV onto PAMCN 97
4.24 Freundlich adsorption isotherm model of LEV onto PAMCN 98
4.25 Jovanovich adsorption isotherm model of LEV onto PAMCN 98
4.26 Tempkin adsorption isotherm model of LEV onto PAMCN 99
4.27 Adsorption isotherm of ENR onto PAMCN 99
4.28 Langmuir adsorption isotherm model of ENR onto PAMCN 100
4.29 Freundlich adsorption isotherm model of ENR onto PAMCN 100
4.30 Jovanovich adsorption isotherm model of ENR onto PAMCN 101
4.31 Tempkin adsorption isotherm model of ENR onto PAMCN 101
4.32 Adsorption isotherm of CIP onto MAMCN 103
4.33 Langmuir adsorption isotherm model of CIP onto MAMCN 103
4.34 Freundlich adsorption isotherm model of CIP onto MAMCN 104
4.35 Jovanovich adsorption isotherm model of CIP onto MAMCN 104
4.36 Tempkin adsorption isotherm model of CIP onto MAMCN 105
ii
4.37 Adsorption isotherm of LEV onto MAMCN 105
4.38 Langmuir adsorption isotherm model of LEV onto MAMCN 106
4.39 Freundlich adsorption isotherm model of LEV onto MAMCN 106
4.40 Jovanovich adsorption isotherm model of LEV onto MAMCN 107
4.41 Tempkin adsorption isotherm model of LEV onto MAMCN 107
4.42 Adsorption isotherm of ENR onto MAMCN 108
4.43 Langmuir adsorption isotherm model of ENR onto MAMCN 108
4.44 Freundlich adsorption isotherm model of ENR onto MAMCN 109
4.45 Jovanovich adsorption isotherm model of ENR onto MAMCN 109
4.46 Tempkin adsorption isotherm model of ENR onto MAMCN 110
4.47 Adsorption kinetics plot of CIP onto PAMCN 115
4.48 Ct vs t plot of CIP onto PAMCN 116
4.49 Pseudo 1st order kinetic plot of CIP onto PAMCN 116
4.50 Pseudo 2nd order kinetic plot of CIP onto PAMCN 117
4.51 Intraparticle diffusion plot of CIP onto PAMCN 117
4.52 Adsorption kinetics plot of LEV onto PAMCN 118
4.53 Ct vs t plot of LEV onto PAMCN 119
4.54 Pseudo 1st order kinetic plot of LEV onto PAMCN 119
4.55 Pseudo 2nd order kinetic plot of LEV onto PAMCN 120
4.56 Intraparticle diffusion plot of LEV onto PAMCN 120
4.57 Adsorption kinetics plot of ENR onto PAMCN 121
4.58 Ct vs t plot of ENR onto PAMCN 122
4.59 Pseudo 1st order kinetic plot of ENR onto PAMCN 122
4.60 Pseudo 2nd order kinetic plot of ENR onto PAMCN 123
4.61 Intraparticle diffusion plot of ENR onto PAMCN 123
4.62 Adsorption kinetics plot of CIP 40 and 80 mgL-1 onto MAMCN 125
4.63 Ct vs time plot of CIP 40 and 80 mgL-1 onto MAMCN 125
4.64 Pseudo 1st order kinetic plot of CIP 40 and 80 mgL-1 onto MAMCN 126
4.65 Pseudo 2nd order kinetic plot of CIP 40 and 80 mgL-1 onto MAMCN 126
4.66 Intra particle diffusion plot of CIP 40 and CIP 80 mgL-1 onto MAMCN 127
4.67 Adsorption kinetics plot of LEV 20 and 40 mgL-1 onto MAMCN 128
4.68 Ct vs time plot of LEV 20 and 40 mgL-1 onto MAMCN 128
4.69 Pseudo 1st order kinetic plot of LEV 20 and 40 mgL-1 onto MAMCN 129
4.70 Pseudo 2nd order kinetic plot of LEV 20 and 40 mgL-1 onto MAMCN 129
4.71 Intra particle diffusion plot of LEV 20 and 40 mgL-1 onto MAMCN 130
4.72 Adsorption kinetics plot of ENR 50 and 100 mgL-1 onto MAMCN 131
4.73 Ct vs t plot of ENR 50 and 100 mgL-1 onto MAMCN 131
4.74 Pseudo 1st order kinetics plot of ENR 50 and 100 mgL-1 onto MAMCN 132
4.75 Pseudo 2nd order kinetics plot of ENR 50 and 100 mgL-1 onto MAMCN 132
4.76 Intra particle diffusion plot of ENR 50 and 100 mgL-1 onto MAMCN 133
4.77 Vant Hoff plot of CIP onto PAMCN 135
4.78 Vant Hoff plot of LEV onto PAMCN 136
4.79 Vant Hoff plot of ENR onto PAMCN 136
4.80 Van’t Hoff plot of CIP onto MAMCN 137
4.81 Van’t Hoff plot of LEV onto MAMCN 137
4.82 Van’t Hoff plot of ENR onto MAMCN 138
iii
4.83 Effect of PAMCN dosage on CIP removal 141
4.84 Effect of PAMCN dosage on LEV removal 141
4.85 Effect of PAMCN dosage on ENR removal 142
4.86 Effect of MAMCN dosage on CIP removal 142
4.87 Effect of MAMCN dosage on LEV removal 143
4.88 Effect of MAMCN dosage on ENR removal 143
4.89 Mechanism of FQs molecule removal on the surface of nanoomposites 145
4.89a Effect of pH on CIP removal onto PAMCN 146
4.90 Effect of pH on LEV removal onto PAMCN 146
4.91 Effect of pH on ENR removal onto PAMCN 147
4.92 Effect of pH on CIP removal onto MAMCN 148
4.93 Effect of pH on LEV removal onto MAMCN 148
4.94 Effect of pH on ENR removal onto MAMCN 149
4.95 Effect of humic acid (HA) on CIP removal onto PAMCN 152
4.96 Effect of humic acid (HA) on LEV removal onto PAMCN 152
4.97 Effect of humic acid (HA) on ENR removal onto PAMCN 153
4.98 Effect of humic acid (HA) on CIP removal onto MAMCN 155
4.99 Effect of humic acid (HA) on LEV removal onto MAMCN 155
4.100 Effect of humic acid (HA) on ENR removal onto MAMCN 156
4.101 Effect of NaCl on CIP removal onto PAMCN 158
4.102 Effect of NaCl on LEV removal onto PAMCN 158
4.103 Effect of NaCl on ENR removal onto PAMCN 159
4.104 Effect of NaCl on CIP removal onto MAMCN 161
4.105 Effect of NaCl on LEV removal onto MAMCN 161
4.106 Effect of NaCl on ENR removal onto MAMCN 162
4.107 Permeate flux of UF with CIP 40 mgL-1 165
4.108 Permeate flux of NF with CIP 40 mgL-1 165
4.109 Permeate flux of RO with CIP 40 mgL-1 166
4.110 Permeate flux of UF membrane with water and LEV 40 mgL-1 167
4.111 Permeate flux of UF membrane with LEV 40mgL-1 167
4.112 Permeate flux of NF membrane with LEV 40mgL-1 168
4.113 Permeate flux of RO membrane with water and LEV 40 mgL-1 168
4.114 Permeate flux of UF membrane with water and ENR 40 mgL-1 169
4.115 Permeate flux of NF membrane with water and ENR 40 mgL-1 170
4.116 Permeate flux of RO membrane with water and ENR 40 mgL-1 170
4.117 Permeate flux of UF membrane with water and CIP 40 mgL-1 172
4.118 Permeate flux of NF membrane with water and CIP 40 mgL-1 172
4.119 Permeate flux of RO membrane with water and CIP 40 mgL-1 173
4.120 Permeate flux of UF membrane with LEV 40 mgL-1 174
4.121 Permeate flux NF membrane with LEV 40 mgL-1 174
4.122 Permeate flux of RO membrane with LEV 40 mgL-1 175
4.123 Permeate flux of UF membrane with ENR 40 mgL-1 176
4.124 Permeate flux of NF membrane with ENR 40 mgL-1 176
iv
4.125 Permeate flux of RO membrane with ENR 40 mgL-1 177
4.126 Improved permeate flux of UF/PAMCN with CIP 40 mgL-1 178
4.127 Improved permeate flux of NF/PAMCN with CIP 40 mgL-1 179
4.128 Improved permeate flux of RO/PAMCN with CIP 40 mgL-1 179
4.129 Improved permeate flux of PAMCN /UF membrane with LEV 40mgL-1 180
4.130 Improved permeate flux of NF/PAMCN hybrid membrane with LEV
40mgL-1 181
4.131 Improved permeate flux of RO/PAMCN with LEV 40 mgL-1 181
4.132 Improved permeate flux of PAMCN/NF membrane with water and
ENR40 mgL-1 182
4.133 Improved permeate flux of PAMCN/NF membrane with water and
ENR40 mgL-1 183
4.134 Improved permeate flux of PAMCN/RO membrane with water and ENR
40 mgL-1 183
4.135 Improved permeate flux of MAMCN/UF membrane with CIP 40 mgL-1 184
4.136 Improved permeate flux of MAMCN/NF membrane with CIP 40 mgL-1 185
4.137 Improved permeate flux of MAMCN/RO membrane with CIP 40 mgL-1 185
4.138 Improved permeate flux of MAMCN/UF membrane with LEV 40 mgL-1 186
4.139 Improved permeate flux of MAMCN/NF membrane with LEV 40 mgL-1 187
4.140 Improved permeate flux of MAMCN/RO membrane with LEV 40 mgL-1 187
4.141 Improved permeate flux of MAMCN/UF membrane with ENR 40 mgL-1 188
4.142 Improved permeate flux of MAMCN/NF membrane with ENR 40 mgL-1 189
4.143 Improved permeate flux of MAMCN/RO membrane with ENR 40 mgL-1 189
4.144 Percent rejection of CIP onto UF and PAMCN/UF 192
4.145 Percent rejection of CIP onto NF and PAMCN/NF 192
4.146 Percent rejection of CIP onto RO and PAMCN/RO 193
4.147 Percent rejection of LEV onto UF and PAMCN/UF 194
4.148 Percent rejection of LEV onto NF and PAMCN/NF 195
4.149 Percent rejection of LEV onto RO and PAMCN/RO 195
4.150 Percent rejection of ENR 40mgL-1 onto UF and PAMCN/UF 197
4.151 Percent rejection of ENR 40mgL-1 onto NF and PAMCN/NF 197
4.152 Percent rejection of ENR 40mgL-1 onto RO and PAMCN/RO 198
4.153 Percent rejection of CIP 40mgL-1 onto UF and MAMCN/UF 199
4.154 Percent rejection of CIP 40mgL-1 onto NF and MAMCN/NF 200
4.155 Percent rejection of CIP 40mgL-1 onto RO and MAMCN/RO 200
4.156 Percent rejection of LEV 40mgL-1 onto UF and MAMCN/UF 202
4.157 Percent rejection of LEV 40mgL-1 onto NF and MAMCN/NF 202
4.158 Percent rejection of LEV 40mgL-1 onto RO and MAMCN/RO 203
4.159 Percent rejection of ENR 40mgL-1 onto UF and MAMCN/UF 204
4.160 Percent rejection of ENR 40mgL-1 onto NF and MAMCN/NF 205
4.161 Percent rejection of ENR 40mgL-1 onto RO and MAMCN/RO 205
4.162 Regeneration of CIP loaded PAMCN 209
v
4.163 Regeneration of LEV loaded PAMCN 209
4.164 Regeneration of ENR loaded PAMCN 210
4.165 Regeneration of CIP loaded MAMCN 212
4.166 Regeneration of LEV loaded MAMCN 212
4.167 Regeneration of ENR loaded MAMCN 213
4.168 Schematic diagram of MCN 214
vi
List of Tables
Table No Title Page No.
1.1 Recently reported adsorption capabilities in (mgg-1) of antibiotics on
different sorbents in literature 28
3.1 Characteristic properties of the FQs used in this study 64
3.2 Verification of Beer Lambert law for spectrophotometric determination
of FQs 65
3.3 Characteristic properties of UF, NF and RO membranes 70
4.1 Surface parameters of PAMCN and MAMCN samples 77
4.2 Elemental analysis of PAMCN and MAMCN samples 79
4.3 TG analysis of PAMCN and MAMCN samples 84
4.4 FTIR analysis of PAMCN and MAMCN samples 87
4.5 Physical parameters of PAMCN and MAMCN samples 89
4.6 Zone of inhibition of selected antibiotics against bacteria found in FQs
industrial effluents. 90
4.7 Adsorption Isotherm of CIP, LEV and ENR onto PAMCN 94
4.8 Isotherm parameters of CIP, LEV and ENR onto PAMCN 102
4.9 Adsorption Isotherm of CIP, LEV and ENR onto MAMCN 102
4.10 Isotherm parameters of CIP, LEV and ENR onto MAMCN 110
4.11 Adsorption kinetics of CIP 40 and 80 mgL-1 onto PAMCN 115
4.12 Adsorption kinetics of LEV 20 and 40 mgL-1 onto PAMCN 118
4.13 Adsorption kinetics of ENR 50 and 100 mgL-1 onto PAMCN 121
4.14 Adsorption kinetics parameters of CIP, LEV and ENR onto PAMCN 124
4.15 Adsorption kinetics of CIP 40 and 80 mgL-1 onto MAMCN 124
4.16 Adsorption kinetics of LEV 20 and 40 mgL-1 onto MAMCN 127
4.17 Adsorption kinetics of ENR 50 and 100 mgL-1 onto MAMCN 130
4.18 Adsorption kinetics parameters of CIP, LEV and ENR onto MAMCN 133
4.19 Thermodynamic parameters of CIP, LEV and ENR adsorption onto
PAMCN and MAMCN 139
4.20 Effect of dosage of PAMCN on the removal of CIP, LEV and ENR 140
4.21 Effect of dosage of MAMCN on the removal of CIP, LEV and ENR 140
4.22 Effect of pH on the removal of CIP, LEV and ENR onto PAMCN 145
4.23 Effect of pH on the removal of CIP, LEV and ENR onto MAMCN 147
4.24 Effect of Humic Acid (HA) on the removal of CIP, LEV and ENR onto
PAMCN 151
4.25 Effect of Humic Acid (HA) on the removal of CIP, LEV and ENR onto
MAMCN 154
4.26 Effect of ionic strength (NaCl) on the removal of CIP, LEV and ENR onto
PAMCN 157
4.27 Effect of ionic strength (NaCl) on the removal of CIP, LEV and ENR onto
MAMCN 160
vii
4.28 Permeate flux with distilled water 164
4.29 Permeate flux of membranes with CIP 40mgL-1 164
4.30 Permeate flux of membranes with LEV 40mgL-1 166
4.31 Permeate flux of membranes with ENR 40mgL-1 169
4.32 Permeate flux with distilled water 171
4.33 Permeate flux of membranes with CIP 40mgL-1 171
4.34 Permeate flux of membranes with LEV 40mgL-1 173
4.35 Permeate flux of membranes with ENR 40mgL-1 175
4.36 Improved permeate flux with PAMCN/membrane 178
4.37 Improved permeate flux with PAMCN/membrane 180
4.38 Improved permeate flux with PAMCN/membrane 182
4.39 Improved permeate flux with MAMCN/membrane 184
4.40 Improved permeate flux with MAMCN/membrane 186
4.41 Improved permeate flux with MAMCN/membrane 188
4.42 Percent rejection of CIP 40mgL-1 with membrane only 191
4.43 Percent rejection of CIP 40mgL-1 with PAMCN/membrane 191
4.44 Percent rejection of LEV 40mgL-1 with membrane only 193
4.45 Percent rejection of LEV 40mgL-1 with PAMCN/membrane 194
4.46 Percent rejection of ENR 40mgL-1 with membrane only 196
4.47 Percent rejection of ENR 40mgL-1 with PAMCN/membrane 196
4.48 Percent rejection of CIP 40mgL-1 with membrane only 198
4.49 Percent rejection of CIP 40mgL-1 with MAMCN/membrane 199
4.50 Percent rejection of LEV 40mgL-1 with membrane only 201
4.51 Percent rejection of LEV 40mgL-1 with MAMCN/membrane 201
4.52 Percent rejection of ENR 40mgL-1 with membrane only 203
4.53 Percent rejection of ENR 40mgL-1 with MAMCN/membrane 204
4.54 Regeneration of CIP, LEV and ENR loaded PAMCN 208
4.55 Regeneration of CIP, LEV and ENR loaded MAMCN 211
4.56 Comparison with other adsorbents 214
viii
LIST OF ABBREVIATIONS
% R Percent retention/rejection
1/n Freundlich constant
Ao Angstrom
B Adsorption energy
BET Brunauer- Emmett-Teller
BJH Barrett- Joyner- Halenda
C Thickness of boundary layer
Cb Concentration in bulk
Ce Equilibrium concentration
CIP Ciprofloxacin
Cm Centimeter
Cp Concentration in permeate
Ct Concentration at time
CNS Central nervous system
EDX Energy dispersive X-ray
ENR Enrofloxacin
FQs Fluoroquinolones
FTIR Fourier transform infrared
GABA Gamma-aminobutyric acid
HA Humic acid
J Permeate flux
K Freundlich constant
K1 Pseudo 1st order rate constant
K2 Pseudo 2nd order rate constant
Kdiff Intraparticle diffusion rate constant
Kj Jovanovich isotherm constant
KL Langmuir constant
LEV Levofloxacin
MAMCN Mangoes magnetic carbon nanocomposite
MWCO Molecular weight cutoff
NF Nanofiltration
nm Nanometer
P/Po Relative pressure
PAMCN Pineapple magnetic carbon nanocomposite
pzc Point of zero charge
qe Amount adsorbed at equilibrium
qm Maximum adsorption capacity
qmax Maximum adsorption
qt Amount adsorbed at time
R General gas constant
RO Reverse osmosis
SEM Scanning electron microscopy
TG/DTA Thermogravimetric/Differential thermal analysis
UF Ultrafiltration
XRD X-ray diffraction
ΔGo Standard free energy
ΔHo Standard enthalpy
ΔSo Standard entropy
ix
LIST OF PUBLICATIONS
The list of published and accepted publications from this study is as under:
1. A. Ullah, M. Zahoor, S. Alam “Removal of ciprofloxacin from water through
magnetic nanocomposite/membrane hybrid processes” Desalination and Water
Treatment 137, 260-272 (2019)
2. A. Ullah, M. Zahoor, S. Alam “Removal of enrofloxacin from water through
magnetic nanocomposites prepared from pineapple waste biomass” Surface
Engineering and Applied Electrochemistry (Accepted and in press).
3. A. Ullah, M. Zahoor, S. Alam, R. Ullah, A. S. Alqahtani, H. M. Mahmood
“Separation of levofloxacin from industry effluents using novel magnetic
nanocomposite and membranes hybrid processes” BioMed Research
International (Accepted and in press).
x
Abstract
Magnetic Carbon Nanocomposites (MCN) was prepared from pineapple and mango
biomass precursors and then characterized by mean of SEM, XRD, FT-IR, TG/DTA,
EDX, surface area analyzer and pH (PZC). XRD patterns show the presence of Fe3O4
deposited on the surface of carbon materials with cubic crystalline structure at different
2θ values which corresponds to indices planes. SEM images show the mean diameter
of both MCN are around 50-70 nm with equal distribution of white areas in the images
of both MCN show the crystallization of nano-particles of Fe3O4, while black spots
represent the carbon contents. The BET surface area of pineapple and mango MCN are
43 and 51 m2g-1 respectively and BJH pore size distribution are 17.50 and 21.65 m2g-1
respectively, whereas, the total pore volume and pore diameter of both MCN are 0.015
and 0.019 cm3g-1 and 15.05 and 15.03 Ao respectively. The low surface area is due to
impregnation of magnetic particles (Fe3O4), which resulted into pore blockage. The
FTIR spectra of MCN shows peaks at 3470 and 3200 cm-1 which may be due to the
presence of surface groups such as phenol, carboxylic acids, carboxylic acid derivatives
along with physically adsorbed water and surface moisture. The two narrow peaks in
the region of 3000-2800 cm-1 correspond to C-H alkanes, peaks at 1450-1600 cm-1
corresponds to C=C aromatic, peaks at 1300-1000 cm-1 corresponds to -OH alcoholic
and ether, while the peak at 575-580 cm-1 corresponds to Fe-O of magnetite and
maghemite. The pHpzc of pineapple and mango MCN were found to be 7.2 and 7.3
respectively.
The removal of antibiotics such as ciprofloxacin (CIP), levofloxacin (LEV) and
enrofloxacin (ENR) from the water system was carried out by adsorption (adsorption
kinetics and isotherm studies) and MCN-membrane hybrid technology. The adsorption
data shows that the equilibrium was established within 220 min. The adsorption kinetics
xi
data were applied to both 1st, 2nd order pseudo kinetics and intraparticle diffusion
models. Pseudo 2nd order kinetics and intraparticle diffusion models were found best
fits to the adsorption kinetics data. Thermodynamic parameters like rate constant
(K), ∆𝐻°, ∆𝑆° and ∆𝐺° were determined using the Van’t Hoff equation. It was found
that the rate constant increases with rise in temperature. The rate constant (K) trend for
the adsorption of antibiotics was found as: LEV>ENR>CIP. Entropy of activation (ΔSo)
was found to be positive which shows an increase in randomness at the solid-liquid
interface during the adsorption. Enthalpy of activation (∆𝐻°) decreases in the following
order LEV>ENR>>CIP for PAMCN, and ENR>LEV>CIP for MAMCN. ΔSo
decreased in the sequence of, CIP>LEV=ENR for pineapple nanocomposites and
ENR>LEV>CIP for mango nanocomposites respectively. The negative values of ΔG˚
at various temperatures specify the spontaneous nature of the adsorption process and
have a high affinity of antibiotics molecules for both nanocomposites. The intraparticle
diffusion model shows that the adsorption of antibiotics is a diffusion controlled
process. For adsorption isotherm studies the mathematical models like Freundlich,
Langmuir, Jovanovich and Tempkin isotherms were used for the determination of
adsorption parameters. The isotherm data fitted well to Langmuir model for the
adsorption data. The effects of pH, temperature, time, concentration, adsorbent dosage,
humic acid and ionic strength on adsorption process were evaluated. The adsorbent
after use was regenerated using NaOH, methanol and distilled water. The equilibrium
time for both adsorbents at pH 7 was reached in 60-80 min.
Improved permeate fluxes and percent retentions of antibiotics by membranes were
observed for adsorption/membrane hybrid process MCN/UF (magnetic carbon
nanocomposite/Ultrafiltration), MCN/NF (magnetic carbon nanocomposite/
Nanofiltration) and MCN/RO (magnetic carbon nanocomposite/Reverse osmosis
xii
filtration). The percent retention of antibiotics molecules in NF was 96% which
increased to 100% when membrane was used in hybrid manner with MCN. Which is a
great achievement in the present study.
Chapter 1
INTRODUCTION
1
1.1. Background
All forms of life on the earth is possible due to water, a precious resource. In recent
years the accessibility to clean water for every human beings is of great concern.
According to UN report that around one billion peoples in 3rd world do not have an
excess to clean and safe water for drinking [1, 2]. Due to increase in world population,
the need for water consumption also increases. But the scenario of drinking water is not
good. It has been speculated that by year 2025 more than 50% of the world population
will be confronting water crisis [3, 4]. The main causes of the water crisis are (1)
contamination of water reservoirs due to which most of the people have limited
approach to clean and safe water for drinking, (2) use of ground water for watering of
crops, and (3) the local conflicts over water reservoirs etc. The shortage and scarcity of
safe and pure water have also a negative impact on aquatic life and biodiversity on the
earth surface. In the current global perspective, aquatic pollution is a key calamity for
safe drinking water and has even been suggested to be the prominent cause of death and
disease worldwide [5]. In the developed world now, regulations are made for the
governing of the disposal of industrial effluents which contains noxious compounds.
The actual situation in the third world or developing counties is catastrophic. Sensible
people round the globe are also being begged for responsible and sustainable usage of
water for present and future generations, and therefore, a lot of yechnological
improvements are occurred to recycle/treat industrial waste wateror plolluted water
before it is discharged into natural water.
1.2. Antibiotics
The word antibiotic is derived from “antibiosis” which literally means “against life”.
Previously antibiotics were thought of as a group of organic compounds of biological
2
origin synthesized by one microorganism which are harmful to other microorganism
[6, 7]. Antibiotics in low concentration restrain or cancels the growth of other
microorganisms [6]. However, in modern times, this definition is modified as
antimicrobials that are also synthesized partially or completely through synthetic
means. There are some antibiotics which are able to absolutely kill other bacteria
termed as bactericidal, while, other are only able to hinder their growth are termed as
bacteriostatic [8]. Although the general reference of antibiotic generally attributed to
antibacterial. The antibiotics are distinguished as anti-bacterial, anti-fungal and anti-
viral to reflect the group of microscopic organisms they incur [6, 9]. The modern
definition of antibiotic is, an established group of chemotherapeutic agents which are
used to restrain or cancels the growth of micro-organisms [10, 11]. Antibiotics are the
products of modern innovations in the sector of health. The usage of antibiotics has
changed the design of modern living standards. They are excessively utilized in human
beings and animals to cure infectious diseases [10], bee-keeping, growth enhancers in
livestock [10] and aquaculture [12]. Ever since it’s recognition as a medicine to cure
chronic diseases, their market sale has expanded enormously [11]. Penicillin was the
first antibiotic of natural origin produced from genus Penicillium [13], a fungi and
Streptomycin from genus Streptomyces, a bacteria. Nowadays, antibiotics are
synthesized by chemical treatment or through chemical modification in natural
compounds. A large number of antibiotics have relatively small molecules with molar
masses is equal or less than 1000 Da (Daltons) [10].
1.3. Classification of antibiotics
Antibiotics may be classified into different classes by number of ways. The most
common classification schemes are based on their mode of action, molecular structures
3
and spectrum of activity [14]. Others are route of administration (oral, injectable and
topical). Antibiotics within the same class will generally reflect same pattern of toxicity,
effectiveness and allergic potentials of side effects. There are some common
classes/types of antibiotics which are based on chemical or molecular structures that
includes [15-17];
a. Beta-lactams
b. Macrolides
c. Tetracyclines
d. Quinolones
e. Aminoglycosides
f. Sulphonamides
g. Chloramphenicol
1.3.1. Beta-lactams
The members of this class of antibiotics contain a highly reactive 1-nitrogen and 3-
carbon ring. They generally interfere with proteins which are necessary for the
preparation of bacterial cell wall. They either kill or restrain their growth in the process.
The members of this class also interfere with the synthesis of peptidoglycan of bacteria
resulting to split and death of cells.
Figure 1.1. Chemical structure of beta-lactam [18] (core structure of Penicillins)
4
Figure: 1.2 Chemical structure of beta-lactam [19] (core structure of Cephalosporin)
The most prominent members of the beta-lactam are Penicillins, Cephalosporins,
Monobactams and Carbapenems which are discussed below.
a. Penicillin
Alexander Fleming was the first to discover and report penicillin, later on certain other
antibiotic compounds were also called penicillins. Penicillins are diverse group of
compounds most of which end in the suffix -cillin. They are beta lactam compounds
containing lactam, thiazolidine ring and other ring side chains. Examples of penicillin
class consist of Amoxicillin, Nafcillin, Penicillin G, Penicillin V, Piperacillin,
Mezlocillin, Oxacillin (dicloxacillin), Methicillin and Ampicillin etc. [20].
b. Cephalosporin
They are identical to penicillin in their mode of action and structure. They account for
1/3rd of all antibiotics prescribed and administered by the National Health Scheme in
the United Kingdom (UK) [20]. Cephalosporins are frequently used in the treatment of
infectious diseases and are subdivided from 1-5th generation on the basis of target
organism.
c. Monobactams
Monobactams are part of beta-lactams, but unlike most beta-lactams compounds the
beta lactam ring of monobactams occurs alone and not fused to another ring. The only
5
commercially available monobactams is Aztreonam having a narrow spectrum of
activity and active only against aerobic Gram-negative bacteria such as Pseudomonas
etc.
d. Carbapenems
Carbapenems are important pharmaceutics and play pivotal role in the fight against
bacterial infections. They resist the hydrolytic action of enzyme beta-lactamase. Among
all betalactams, carbapenems possess the broadest spectrum of activity and are effective
against both Gram-positive as well as Gram-negative bacteria, due to which they are
often known as “antibiotics of last resort” [21]. Important examples of carbapenems
are: limipenem, meropenem and ertapenem
1.3.2. Macrolides
J. M. McGuire discovered and isolated the first antibiotic belonging to this class from
a metabolic product of a soil inhabiting fungus. Macrolides have a wider spectrum of
antibiotic activity than Penicillins and they are usually administered to patients allergic
to penicillin [22]. Macrolides effectively inhibiting bacterial protein synthesis.
Macrolides are generally broad spectrum. Low doses of this class of antibiotics are
usually administered due to inflammatory problems. Example of some members are
Clarithromycin, Azithromycin and Erythromycin
1.3.3. Tetracyclines
Benjamin Duggar in 1945 discovered tetracycline from Streptomyces reported by
Sanchez et al.., 2004 [23]. Chlortetracycline (Aureomycin) was the first member of this
class having four hydrocarbon (HCs) rings. Members of this class of antibiotics are
usually grouped into different generations based on the basis of their method of
preparation. 1st generation are those tetracyclines which are obtained by biosynthesis,
6
such as chlortetecycline, oxytetracycline, demeclocycline and tetracycline. 2nd
generation is the derivatives semi-synthesis, such as rolitetracycline, lymecycline,
doxycycline, meclocycline, methacycline and minocycline, while 3rd generation
tetracyclines are the derivatives of total synthesis of tigecycline [24]. In the past,
physicians have frequently administered tetracyclines to patients due to its wide
spectrum antibacterial activity but nowadays these antibiotics are replaced by others
due to numerous bacterial resistance [25].
Figure: 1.3. Chemical structure of Tetracycline [25]
1.3.4. Aminoglycosides
According to Mahajan and Balachandran [26], the first member of Aminoglycosides
class was streptomycin and was successfully used in the treatment of tuberculosis in
humans. They have a wide spectrum of antimicrobial activity and are effective against
aerobic Gram-negative and certain Gram-positive bacteria, but later it was found to be
highly toxic for human beings due to which it was replaced by less toxic and effective
antibiotics against bacteria such as Amikacin, Gentamicin, Neomycin and Tobramycin.
1.3.5. Sulphonamides
The first group therapeutic medicine of antibiotics is sulphonamides. They inhibit
Gram-positive and negative bacteria. Sulphonamides are also capable to impede cancer
7
cell agents [20, 27]. They are broadly utilized in treating a substantial number of
irresistible ailments diseases because of their side effects and toxicity, sulphonamides
are vigilantly managed.
1.3.6. Chloramphenicol
Chloramphenicol is another class of antibiotics. The representative drug of this class is
Chloramphenicol. Their mode of action includes inhibition of DNA replication and
protein synthesis. They are effective in the treatment of grey baby syndrome.
1.3.7. Quinolones (Qs)
1.3.7.1. History
Nalidixic acid was the first discovered Qs antibiotic effective against enterobacteria.
Quionolones are discovered incidentally, as an antimalarial agent by-product. Due to
slender spectrum of action and partial usage the innovative generations of synthetic Qs
were synthesized with modified form by introducing a F-atom at the central carbon ring
and various functional groups. They are named as fluoroquinolones (FQs) having
minimum side effects (toxicity) and broader action against pathogens. The common
FQs are levofloxacin (LEV), ciprofloxacin (CIP), danofoxacin, enrofloxacin (ENR),
marbofloxacin, norfloxacin, amilofloxacin and sarafloxacin. They are comprehensively
used globally.
1.3.7.2. FQs mode of metabolism and excretion
Renal excretion is the major elimination pathway of FQs from the body. They are also
partially metabolized by hepatic system (liver). High concentration of unchanged FQs
and active metabolites of FQs are discharged from human/animal bodies through urine
and bile [28]. For example CIP a FQs antibiotic, is excreted through urine in the range
of 65% and through feces in the range of only 25% [29].
8
1.3.7.3. Application of FQs
In modern world, FQs are one of the larger and established class of antibiotics and are
utilized throughout the world in the cure of a number of infectious diseases of bacterial
emergence such as, urinary tract infections (UTI), nose infections, severe bronchitis,
skin infections and gonorrhea etc. [30, 31]. They are successfully used against gram
negative and positive pathogens. The new generations of FQs have high activity against
anaerobic bacteria as well as against those resistant to and sulfonamides and beta-
lactam antibiotics and are functional in the treatment for a broad range of chronic
ailment [30]. FQs are effective especially against those infections caused by
microorganisms resistive to other classes of antibiotics. Recent studies have shown that
apart from their antimicrobial activity, FQs inhibit some enzymes, due to this inhibition
they are effectively utilized in the development of anticancer as well as in anti HIV
drugs [28].
1.4. Consumption of antibiotics
Antibiotics are used worldwide for the treatment of infectious diseases in human beings
as well as in veterinary medicines. The international data for consumption of antibiotics
is based on estimates so the true figure of agri-food antibiotics are not known and are
conflicting [10]. The estimated consumption of antibiotics throughout the world in 2003
was falling in the range of 1x105 - 2x 106 tons per annum. Global increase of 36% in
antibiotics consumption occured over the last decade, i.e. from 54.10x109 to 73.60x109
standard units have been reported. The amounts of active substances purchased by 26
European countries in 2012, were reported to be3400 for humans and 7982 tons for
breeding animals. In human medicine the use of FQs is 15 to 20% [28, 32]. France have
consumed around 2000 tons of antibiotics in 2005 for veterinary and human medicines
9
amongst the highest in all European countries. The overall consumption percentage of
FQs around the world are 15% amongst all antibiotics. The estimated production and
consumption of Qs in USA, EU and some countries of Asia is ranging from 100 - 120
tons. According to 1998 estimates the per annum consumption of Qs in China as
humans and veterinary medicines were around 1820 tons [33]. The annual sale of Qs
antibiotics as human medicines in USA in 2011 ranges from 0.25 million kg to 0.3
million kg [34]. In USA for the 1st time in 2013, FQs were permitted for food
manufacturing animals and was stated to be 15 x 103 kg. A survey report stated an
annual sale of 136 tons of FQs as veterinary medicine in Europe in 2012 [35]. The usage
of FQs as veterinary medicine was much larger in Europe than USA due to cultural
consumptions and restrictions.
1.5. The Entry sources of antibiotics to the Environment
Generally, there are many sources of antibiotics entrance into environment and can be
categorized into several groups:
1.5.1. Natural sources of antibiotics
There are some antibiotics such as beta lactams, streptomycin, aminoglycosides etc. are
synthesized by bacteria in soil.
1.5.2. Pharmaceutical industry
During the last few decades, the effluents of the pharmaceutical compounds from
industries were not considered as seriously. Recently in some countries of Asia and
some developed countries, the high concentration in mgL-1 of pharmaceutical
compounds has been reported from the pharmaceutics manufacturer. These compounds
are significantly distributed in water reservoirs [36, 37]. These sources can be classified
into several classes;
10
1.5.3. Antibiotics’ consumption
Antibiotics are broadly utilized in human beings for the remedy of incurable illness.
The per capita antibiotics consumption for human use and the administered doses
different in different nations of the world. As they are not totally metabolized in the
bodies of human beings and are therefore discharged through urine and feces into the
environment [38, 39].
1.5.4. Sewage from hospitals and health care centers
Another source of antibiotics introduction into the environment is effluents coming out
from health care centers (HCCs) and hospitals. The wastewater from these spots have
the matching quality as city wastewater. In undeveloped nations where there is no
legitimate system for the gathering of the sewage, therefore they influence the health of
workers, environment and entire society, as these effluents contain harmful and
infective substances [40].
1.5.5. Veterinary
Animal antibiotics such as Enrofloxacin etc. are used in different ways such as for the
treatment of animal diseases and growth supplement [41].
1.5.6. The production of herbal products
Antibiotics have widely been utilized to control and treat bacterial ailments in natural
products such as, fruits, vegetables, and decorative plants. The usage of antibiotics in
the field of agricultural can settle in soil and thus causes environmental pollution [42].
11
1.5.7. Aquaculture
In the field of aquaculture, certain antibiotics such as erythromycin, sulfonamides, and
oxytetracyclines are used as a preventive agent as well as for therapeutic purposes [43,
44].
1.6. The Occurrence of Antibiotics in the Environment
The possible resources of dynamic FQs (antibiotics) and their metabolite in the
environment are manure, bio solids, pharmaceutics manufacturers and wastewater
treatment plants (WWTPs) [45, 46]. The continuous entry of FQs into the ecosystem
even in minute concentration from these sources have a damaging impact on water
quality. The dissociation characteristics of these antibiotics in water (hydrophilicity)
play an important role in their kinesis through the aquatic environment. Some authors
have reviewed the solubility of CIP (30 gL-1) and ENR (130 gL-1) in water [47].
The unchecked utilization of anti-microbial has made their occurrence widespread in
the environment and nearly the entire of the world has recognized their presence in
natural and artificial frameworks. Soil, sludge, sediments, plants, aquatic organisms and
water reservoirs such as groundwater, wastewater, tap water, surface water (lakes,
streams, waterways, ocean), have been accounted for contamination of antibiotics [10,
48]. A point by point explanation about the event of antimicrobials in the environmental
ecology all over the world is given in the subsequent subclasses.
1.6.1. The Occurrence in Watewater Treatment Plants (WWTPs)
In wastewater treatment plants (WWTPs) are the remainder of the spots where anti-
microbial can be dealt with before going into the natural ecosystem. Unfortunately,
none of the WWTPs were designed to target anti-microbial and in this way turned into
the fundamental anthropogenic destinations for the presence of antibiotics. Detailed
12
reports are available on the presence of antibiotics in sewage sludge in many countries
such as China, Canada and USA etc. [49-52]. A few investigations have been done in
China on the event of antibiotics in WWTPs. Amid the examination of 45 WWTPs in
23 urban areas in China, Qs were observed the prominent antibiotic and concentration
were as high as 29647 mgkg-1 in the Shanxi Province [52]. Another investigation of a
metropolitan wastewater recovery plant in Beijing reported the concentration of Qs to
be 4916 ngL-1 [53]. The occurrence of Qs and FQs were analyzed in a metropolitan
sewage treatment plant with depleted levels of oxygen and oxygen consuming treatment
frame works. It was found in the investigation that anti-infection agents interact with
bio solids in these treatment operations, which are thick with microbial territories and
they go about as ordered hindrances to the flat exchange of hereditary material and in
this way, WWTPs have become a notable place for drug resistance societies [54].
1.6.2. The Occurrence in Domestic Water
Trade mark and risk-free drinking water is getting to be uncommon as the large
part/bulk of nations are confronting water quality problems. Unexpectedly, the tap
water which was considered to be a protected and risk-free source of drinking water has
not been saved by the degree of antibiotics pollution. An examination in Madrid
(Spain), asserted tap water contamination with large number pharmaceutics [55]. Some
studies have reported the presence of several FQs antibiotics as contaminants in in tap
water in the ngL-1 range in various cities of China [56]. Ashfaq et al. [57] investigated
different sewage plants for antibiotics effluents in Pakistan, they concluded from their
research that FQs concentration was found maximum amongst all emerging
contaminants.
13
1.6.3. Rivers, streams, and lakes
A significant portion of antibiotics (25-75%) are discharged into rivers, streams and
lakes in unaltered form through feces and urine [58]. Several rivers in Spain were
reported for the presence of a number of FQs antibiotics in the concentration range of
3-1195.5 ngL-1 [55]. The presence of antibiotics were also reported in rivers and streams
of South Korea, USA, Italy, Taiwan, France, Sweden and China, the concentration
range of norfloxacin, ofloxacin, ciprofloxacin in rivers of northern China were 5770,
1290 and 653 ngL-1, respectively [59].
1.6.3.1. Seawater
Coastal areas are considered an ecologically sensitive places, but very little studies have
been reported on analysis of ocean water for contamination of antibiotics. The
concentrations of antibiotics in ocean water were very low (ngL-1) as compared with
WWTPs sludge and river water (mgkg-1 and mgL-1). The main sources of antibiotic
contamination in sea water are direct discharge of sewage and through confluences of
rivers [60, 61]. Some antibiotics are frequently detected in the Beibu gulf. Their
average concentrations were in the range of 0.51–6.30 ngL-1, which may pose a risk to
algae species [62]. East China sea and the Bo sea has been reported for the presence of
antibiotics in concentration range of 0.10–16.6 ngL-1, and can pose serious threat to
aquatic ecology. Sediments Seawater, and aquatic flora in China have been reported for
the presence of antibiotics. Seawater showed about 2.11–9.23 ngL-1 of tetracycline,
whereas concentration of sulfonamides were reported in both the sediments and aquatic
organisms in concentration range of 1.42– 71.32 and 2.18–63.87 mgkg-1, respectively
[60, 63].
14
1.6.3.2. Groundwater
Anthropogenic activities have made urban aquifers vulnerable to antibiotic
contamination. In spite of the fact soil reduces down the movement of contaminants
into the sub surface water, but once contaminated, it is difficult to bring its effects under
control. The main sources of groundwater recharge are considered to be infiltration of
wastewater, natural bank filtrations, and water supply pipes, rainfall, etc., and they also
act as sources of contamination. The presence of emerging contaminants in the
groundwater of the rural and urban areas of Spain have been reported. The study
revealed that WWTPs are the most influential sources of groundwater contamination.
Ciprofloxacin was found to be the highest among all the antibiotics with an average
concentration of 323.75 ngL-1 due to agricultural activities or infiltration of poorly
treated wastewater. In the USA, groundwater samples from 18 states in the year 2000
reported sulfamethoxazole as the most frequently detected pharmaceutic [64]. In
groundwater, antibiotics have been detected with many other organic compounds such
as pharmaceuticals, pesticides, hormones, and (PCPs) personal care products, but the
concentrations are significantly lower than that in WWTPs and rivers [65, 66].
1.6.4. Occurrence in soil and sediments
The natural occurrence of antibiotics is because of the biosynthesis by soil
microorganisms which dwells in soil and residue territories. However, manure and
sludge constitute the major hotspot for the dispersal of most of the antibiotics into the
land, due to continuous manure application antibiotics collects and accumulates in the
soil. Apart from manure and sludge the other prominent sources of the antibiotics are
fish culturing, flooding of surface water, dumping of industrial solid waste on lands etc.
[67, 68].
15
1.6.5. Occurrence in plant and aquatic animals
The presence of antibiotics in aquatic reservoirs, soil and sludge opened their entry into
biota. Antibiotics can be taken up by aquatic plants, animals, vegetables, and crops.
Food safety standards being challenged by the presence of antibiotics in vegetables and
fishes, some researchers have reported the uptake of ciprofloxacin by barley [69, 70].
A study reported the distribution of antibiotics in various parts of plants in the order of:
root < stem < leaf. Winter season is found to be most favorable than summer for
bioaccumulation. Another study reported that celery leaves accumulated ofloxacin,
pefloxacin, and lincomycin in the concentration range of 1.7–3.6, 1.1, and 5–20 mgkg-
1, respectively [71]. Li et al. has reported significant occurrence of quinolone in aquatic
plants (8.37–6532 mgkg-1). Aquatic animals and birds were also detected with
quinolones in the concentrations range of 17.8–167 mgkg-1 [67]. The transfer of
contaminant usually occurs from sludge-modified soils to the plants, via retention by
root surfaces, root uptake, translocation, foliar uptake, and animal intake (soil and
herbage ingestion).
1.7. The Effect of Antibiotics on the Environment
It is challenging to size the complete impacts of antimicrobials on the ecosystem as the
effectiveness of antimicrobials depends on half-life, physico-chemical characteristics
of the medicine, climatic surroundings and other environmental parameters. The cells
of the human body respond with antimicrobials in a very low fundamental level (up to
10-15%). Some authors have reported the excretion of active FQs antibiotics in the
range of 85-90% through feces of poultry birds. These active constituents acutely
affected the non-targeted organisms such as microbial, plant, vertebrate and
invertebrate ecologies [72, 73]. Due to non-biodegradable nature, higher dissociation
16
in water and longer half-life (about 100 days) FQs are considered as one of the emerging
contaminant in ecosystem [10].
As a result, their subsistence in drinking water or food can amplify the levels of these
antimicrobials in the body. They can reach the tissues of the body through the food
chain and make diverse reactions inside the body. Low concentrations can act as a
vaccine for microorganisms (especially bacteria) and make them impervious or
resistant to the antibiotics used in the treatment of a substantial number of reparable
ailments. The bacterial resistance can occur due to the presence of antibiotics in
different environmental compartments. Moreover, the wastewater consisting of
antibiotics, bacterial strains and resistant bacteria would be utilized for watering of
agricultural lands and also large quantities of sludge are used as fertilizer. As a result,
the resistant bacteria directly enter the food chain. The concentrations of antibiotics are
less than that required for the treatment of ailments have an important role in bacterial
resistance and even transmit to the hereditary of bacteria. Reports have demonstrated
that the long term (persistent) impacts of antibiotics are larger than their intense effects
[36, 41, 74].
1.7.1. The Impacts of Antimicrobials on the Wastewater Treatment System
(WWTS)
Antimicrobials have an impact on microbial colonies existing in wastewater systems.
In addition, the presence of antimicrobials in the sewage treatment frameworks,
microbial exercises would be subdued and it can genuinely influence the decay of
carbon based compounds [75, 76].
17
1.7.2. The Impacts of Antimicrobials on the Surface Water
Antimicrobials that have been removed partially from wastewater in treatment
frameworks can enter the surface water repositories and affect various organisms of the
food chain. Algal colonies are more sensitive to different kinds of antimicrobials. Algal
colonies are the motives of food chain. In this manner, the balance of water system is
largely affected by even a partial decline in the inhabitant of algae. Regardless of the
reality the concentration of related antibiotics in water is very low either ngL-I or µgL-
1, their accumulation in plants, poultry, and livestock (as antibiotics are used as feed for
poultry/live stocks, while manure is used worldwide as a source of source of plant
nutrients and also improve soil quality). They enters into the body of human beings
through food chain and cause infective ailments in human beings [77].
1.7.3. The Impacts of Antimicrobials on Sediments
Antimicrobials have an affect on bacterial population living in sediments qualitatively
as well quantitatively, as a result of which disintegration of organic matter is badly
affected. The levels of antimicrobials in sediments can reduces the growth and activity
of various microbes [78].
1.8. Issues related to the presence of antibiotics in the environment
The most important issue of antibiotic release into the environment is related to the
development of antibiotic resistance which has resulted in the reduction of therapeutic
potential against human and animal pathogens. It is not the fact that the presence of
antibiotic resistance was never seen before in the natural environment, but it was
associated only with some bacterial strains, as resistance is an important process of
evolutionary conservation. The resistance is inherited by organisms of the same species
through cell division (vertical resistance transfer), which is known as primary
18
resistance, while the secondary resistance is developed during therapy/contact of micro-
organisms with an antibiotic. Plasmid-mediated resistance is transferable between
micro-organisms and in such cases, extrachromosomal genetic material is transferred
between different bacterial species by conjugation (horizontal resistance transfer) [10].
Extraordinary high dosages of FQs produces lethal impacts in vertebrate and
invertebrate classes such as hindrance of the neurotransmitter, spasms, visual issues,
joint diseases, dysfunctioning of reproductive, CNS and digestive systems. Exposure
of goldfish, to different concentrations of FQs for different days brought about
noteworthy gonadal DNA harm [79]. Similarly, Exposure of some non-targeted aquatic
organisms to different concentrations for longer period of time to FQs causes lethal
impacts [80]. Wide ranges of FQs concentration are considered hazardous to
microorganisms, vertebrates (frog and fish) and invertebrates [28, 81]. Robinson et al.
evaluated the harmfulness of several FQs on various marine organisms. He concluded
from his studies that cyanobacterium was found to be more sensitive to low
concentration of LEV, while some members of crustaceans exhibited lesser sensitivity
[82]. Identical consequences with levofloxacin and enrofloxacin was repoted by
Gonzalez [83] in aquatic organisms. Contamination with ciprofloxacin also
significantly influened algal growth and the enzymatic levels of zebra fish in fresh water
[84-86].
Fluoroquinolones are regarded as the most persistent type of antimicrobials in soil and
rests for longer time in earth matrixes. Their rate of entering into the environment is
more than its rate of elimination. Therefore, due to their persistent nature, risks to the
environment have been assessed in several studies [87]. The emergence of antibiotic
pollution in the environment is causing potential toxic effects on micro-organisms,
plants, animals, and ultimately humans. In Brazil a livestock is a larger source of
19
income, various types of antibiotics are used for the growth and treatment of livestock.
Various soils in Brazil were analyzed for the presence of antibiotics, after analysis the
concentration of FQs were found much higher in concentration as compared to other
antibiotics. Another report concluded from their study that high amounts of FQs
validates that poultry is a possible cause of ecological pollution [88]. FQs such as
enrofloxacin (ENR) have the capability to relocate himself from soil to different parts
of the plants and enters through food chain posing serious threats to living organisms
[89]. Additionally the presence of antibiotics diminishes the biodegradation capabilities
of plants materials such as roots, leaves and stem, which is a primary nourishment
hotspot of aquatic organisms in water reservoirs [90]. Antibiotics such as tetracyclines,
FQs, and macrolides affect the chloroplastic and mitochondrial protein synthesis in
plants. Fluoroquinolones inhibit DNA synthesis in eukaryotic cells, plastid replication,
and have negative influences on plants morphology and photosynthesis. Streptomycin
inhibits chlorophyll synthesis, sulfadimethoxine and enrofloxacin reduce growth
significantly, ciprofloxacin reduces photosynthesis and hence, growth in plants.
Tetracyclines also have phytotoxic effects which may cause chromosomal aberrations
and inhibition of plant growth. B-Lactams have been considered to be less toxic, but
they also affect the plastid division in lower plants [91, 92]. Tetracyclines,
ciprofloxacin, and erythromycin reduce the content of photosynthetic pigments,
chlorophylls, and carotenoids in plants. Penicillins, cephalosporins, and tetracyclines
affect the photosynthetic electron transport rate. Some researchers have studied the
effect of nine antibiotics on foliage photosynthesis and found that ciprofloxacin and
cephalosporins strongly inhibit the net assimilation rate because of the reduction in
stomatal conductance [93].
20
1.9.Reasons for treatment of aqueous solutions containing Antibiotics
The proposed and necessary reasons for treatment of aqueous solutions containing
antibiotic compounds are mentioned as follow as:
Production and consumption of large amounts of humans and animals’
antibiotics;
Influx of excessive amounts of antibiotics and their metabolites into the
ecosystem through humans/animals’ excretory wastes;
Retention of antibiotics with no running out date, can contaminate the
environmental ecology;
The potential increase of antibiotic remains can gather in food chain or water
reservoirs;
Greater danger of undesired impacts on the environmental ecology;
Dearth of satisfactory statistics on the existence and persistence of antibiotics
in the aquatic setting and its dangers to living organisms [77, 94]
1.10. Treatment technologies used for the remediation of antibiotics from aqueous
solutions
The following technological methods are used for the remediation of antibiotics from
aqueous solution
1.10.1. Photodegradation
The environmental fate of FQs is influence by photodegradation. The process generally
occurs under different experimental conditions [10]. Among FQs, ENR and CIP are
highly photodegradable. The half-lives of these antibiotics depend on the presence of
organic matter, intensity of light, pH, concentration level of antibiotics, time and
phosphorus (P) level. During photodegradation process ENR quickly degrades to CIP
21
in lower light intensity [95], while photodegradation of CIP takes place at acidic pH
[96]. Sun et al. and Zhang et al. [97, 98] successfully removed antibiotics under UV
and sun light. The results of their studies showed that some antibiotics were persistent
under deionized water matrixes, while some antibiotics undergoes direct
phtodegradation.
1.10.2. Membrane technologies
Membrane processes are another example of phase changing technologies with
different applications in the removal of emerging pollutants such as antibiotics etc.
Membranes are synthesized from different materials, depends on the pore size, surface
charge and hydrophobicity of contaminants to be retained on the surface of membranes
[99, 100]. Membrane technologies are based on the use of hydrostatic pressure to
remediate suspended matter and high molecular weight contaminants and allow low
molecular weight solutes and water molecules to pass through. Commercial-scale
operations of membrane technologies have some limitations such as fouling of
membrane surfaces due to deposition of chemicals or development of microbes. To
overcome these problems, an increase in pressure and physicochemical changes in
membrane surfaces are required to maintain improved permeate flux [101]. In reality,
because of the extensive variety of their application and furthermore to enable the kind
and use of membrane technologies. They are classified in to different classes.
Membrane filtration technologies can be classified as microfiltration (MF),
membranous biological reactor (MBR), ultrafiltration (UF), nanofiltration (NF),
reverse osmosis (RO) and forward osmosis (FO).
22
a. Microfiltration (MF) membranes
Microfiltration have wide applications due to its operation at normal atmospheric
pressure. Microfiltration have pore size in the range of 1 - 10 µm. Microbes are
incapable to transfer through these pores. The main disadvantage of MF membranes is
that it can’t remove contaminants (dissolved solids) of size <1 µm [102, 103]. MF
processes are extensively utilized for the removal of foulants with colloidal [104].
b. Membranous biological reactor (MBR)
This apparatus has a compartment in which exclusion of biotic forms are done by a
membrane, viz., MF, having size in the range of 1-10 µm. These compartments are
beneficial in wastewater treatment plants under aerobic as well as anaerobic
circumstances. The quality of the clean water in MBR compartments are similar to MF.
MBR are beneficial for recycle municipal as well as commercial wastewater [105].
c. Ultrafiltration (UF) membranes
Ultrafiltration has been widely used in the removal of emerging contaminants from
aquatic environment and holds particle size smaller than MF (in the range of 0.001-0.1
µm) [106, 107]. This technique is not so active in separation of carbon-based streams.
UF films have the capacity of retaining contaminants having the molecular weight cut
off (MWCO) values in the range of 300 – 500000 Da (Dalton) [104]. Percent removal
of UF films varies widely with membrane and contaminants type [108]. For example,
the removal of bisphenol A from aqueous solution was investigated using two UF
membranes made up of polysulfone a polyvinylidine. The percent retention of the latter
was almost 100%, while that of the former was 75% [108]. The percent retention of
different emerging contaminants such as antipyrene (6-23%), caffeine (2-21%),
ibuprofen (60%) and diclofenac (27-53%) with UF membranes [109]. Generally, more
23
polar and highly water-soluble contaminants are efficiently removed by UF membranes
as compared to non-polar and low water-soluble contaminants.
d. Nanofiltration (NF) membranes
Nanofiltartion membranes are successfully used for the removal of large number of
contaminants due to its smaller pore size in the range of 10-100 Ao [109, 110]. As NF
membranes are operated at a low feed water pressure so, the operational cost of these
membranes are low [109]. The percent retention of NF membranes is much higher than
UF and MF membranes. For example the percent retention of acetaminophen 11-20%
with UF and 18-80% with NF, similarly, the percent retention of caffeine with UF is 2-
21% and with NF is 62-93%, whereas, the percent retention of metronidazole,
naproxen, carbamazepine, sulphmethoxazole, estrone and ibuprofen are 93, 99, 98, 99,
98 and 98% respectively with NF membranes [109]. The membranes materials also
affect the percent efficiency of contaminants, however this trend may not be universal,
as different contaminants having different properties behave differently. NF is not an
efficient film regarding with carbon-based compounds with low molecular weight. NF
provide more optimum condition than other processes used for the decontamination of
antibiotics due to its low price, removal of ions and pore dimensions [104].
e. Reverse osmosis (RO) membranes
Reverse osmosis process uses a semipermeable membrane to separate dissolved solid
substances from water on the basis of osmotic pressure gradient. In RO process
hydraulic pressure is the main driving force for separation. RO process can efficiently
remove particles in the size range of <10Ao. The efficiency of RO membranes increases
significantly for the removal of contaminants with decrease in pore size [109, 111, 112].
RO process is primarily utilized to purify salty water of sea. The noticeable feature of
RO process is the absence of phase alteration and its little energy intake. The normal
24
antibiotics percent removal rate for distilled water and natural water is 90.2 and 90.3%
respectively. Normal percent removal retention of antibiotics can easily be enhanced to
almost 100% by using two or three consecutive RO units. The operational cost of RO
membranes in municipal wastewater treatment plants is too high. Although RO
membranes are often utilized in processing plots, at large, it might be a suitable
technique to decontaminate drinking water from antibiotic compounds [113, 114]. Al-
Rifai et al. [115] reported almost 100% removal of different pharmaceutic compounds
from aqueous solution using RO/MF filters. Similarly Dolar et al. [116] reported the
efficient removal (almost 100%) of FQs, psychiatric drugs, macrolides, β-blockers and
sulphnamides from wastewaters using an integrated RO membrane.
1.10.3. The process of sedimentation, flocculation and coagulation
Sedimentation, flocculation and coagulation are physicochemical filtration methods
used for the removal of antibiotics from aqueous solutions. Choi et al. [117] reported
the efficient removal of seven tetracycline antibiotics using granular activated carbon
in combination with coagulation from synthetic and natural water reservoirs.
1.10.4. The process of ultrasonic radiation (UR)
The term ultrasonic means outside the limit of sound. These are mechanical pulses in
which frequency variation is outside the range of human earshot i.e. from 20 – 2 x103
HZ. They have similar properties like other waves. They are successfully utilized for
pharmaceutical micro-pollutants from aquatic media [117].
1.10.5. The advanced oxidation procedure (AOP)
The main theme of AOP is to convert organic contaminants into reasonably harmless
and eco-friendly inorganic materials such as CO2 and H2O [118]. Innovative oxidation
processes are described by production of an oxidant (a hydroxyl free radical) in
25
relatively high concentrations which have an impact the quality of water. The AOP may
be classified into two subgroups,
1. AOP in the absence of light source (O3, O3/H2O2 and Fe+2/H2O2)
2. AOP in the presence of light source (vacuum UV process, O3/UV process,
O3/H2O2/UV process and H2O2/UV process
Li et al. [119] successfully decontaminated aqueous solution from an emerging
contaminant ENR using IOP method, similarly Bobu et al. [61] studied the removal of
two FQs antibiotics such as CIP and ENR from aqueous solutions using AOP processes.
Nasuhoglu et al. [120] removed LEV antibiotic from wastewater using heterogeneous
IOP method.
1.10.6. Biodegradation
The decomposition of organic materials by the action of microbes is known as
biodegradation. Modification of organic compounds can be intracellular or extra
cellular of microbes; it is the major path way of the degradation by enzymatic
modification under aerobic/anaerobic conditions by microorganisms. However, the
biological decomposition of antibiotics under aerobic conditions assisted by bacteria is
uncommon [121]. Some researchers have assessed the biodegradability test for a
number of antibiotics in the closed vessel test using previous standard guidelines [122].
A few were partially degraded in 28 days. Benzyl penicillin sodium salt was degraded
by 27%, amoxicillin by 5%, nystatin and trimethoprim by 4%, and the rest was reported
to be <4%. Some authors have reported no reduction for CIP and ofloxacin (OFL)
showed only 5% reduction after 40 days [123, 124]. Some have also studied [125] the
inherent biodegradability of 17 antibiotics in a combined test, the Zahn-Wellens test
(test used for determining the inherent biodegradability) and CO2-evolution test also
known as sturm test (method to determine the “ready” ultimate biodegradability of non-
26
volatile chemicals in aqueous media). Benzyl penicillin G was the main biodegradable
compound to the extent of almost 90%. Some were (amoxicillin, imipenem, and
nystatin) viewed as partially biodegradable with the formation of stable metabolites.
Some antibiotics including FQs were completely not biodegraded and hence,
genotoxicity initiated by these composites was also not eliminated [126]. An extremely
low mass change was reported during biodegradation of FQs in a urban sewage
management plant, which again confirmed the point that biodegradation is of negligible
significance in its elimination in WWTPs [11, 127].
1.10.7. Adsorption
Adsorption is a phenomenon in which a various substances (sorbate molecules) are
accumulated on the surface of sorbent through inter and intramolecular forces. Sorption
incorporates the two procedures i.e. absorption and adsorption, while desorption is the
invert procedure of sorption. Absorption is a phenomenon in which one substance
becomes part of another substance through chemical or physical processes [128]. The
evaluation of the fate and transport of antibiotics in the environment is handicapped by
the limited knowledge of the sorption mechanism toward solids. The sorption
phenomenon has been exploited for the removal of antimicrobials in innovative sewage
plants. Carbonaceous materials can be effectively utilized for the decontamination of
different effluents from aquatic environment [117, 129]. Moussavi et al. [130] used
ammonium chloride treated charcoal for the elimination of amoxicilline. Pouretedal and
Sadegh [131] used vine wood activated nanoparticles for the removal of various
antibiotics from aqueous solutions. Chayid et al. [132] used microwave treated carbon
for the removal of antimicrobials from aquatic environment. Marzbali et al. [133] used
phosphoric acid activated carbon prepared from apricot nut shells for the
27
decontamination of tetracycline from wastewater and Ahmad et al. [134] used human
hair porous carbon for the elimination of antibiotics from water. Adsorption by clays
[135, 136], carbon nanotubes [137, 138], ion exchange methods [139] and biochar [140,
141]. Strong sorption for FQs have been reported on clay minerals [142] [143]. The
CIP removal on montmorillonite, illite, and rectorite were 1.19, 0.10 and 0.41 mmolg-
1. Cationic exchange is the main process responsible for CIP removal on these clay
minerals [142]. Jiang et al. studied the adsorption of CIP from aqueous solution onto
brinessite mineral. They confirmed that cation exchange is the main mechanism for CIP
removal [143]. The superiority of adsorption is due to the use of carbon materials,
treated carbon is utilized in pharmaceutic industries for refining of antibiotics. Treated
carbon was efficiently used for the elimination of nitroimidazoles with sorption
capacity of 1–2 mmolg-1. Similarly a number of antibiotics was effectively eliminated
from river water with carbon dosages between 10 and 20 mgL-1 after 4h contact time.
Several antibiotics including FQs were also removed from hospital effluents with
powdered activated carbon at dosages of 20–40 mgL-1 [11, 144-146]. El-Shafey et al.
investigated the adsorption of CIP from aqueous solution onto H2SO4 modified carbon
prepared from date palm leaflets. Maximum removal occurs at nearly neutral pH, above
and below this pH the rate of adsorption decreases. The process of adsorption is
spontaneous and endothermic, the mechanism of adsorption is mainly due to cation
exchange and hydrogen bonding [147]. Muttana et al. investigated the removal of FQs
from aqueous solutions using activated carbon prepared from lignocellulosic biomass
precursors by microwave pyrolysis, the maximum percent adsorption removal of
96.12% for ciprofloxacin and 98.13% for norfloxacin was achieved under the examined
experimental conditions [148]. Lignin based activated carbon was used for CIP and
tetracyclines elimination using batch adsorption studies [149]. However, there are some
28
issues associated with its use like difficulty of its regeneration and large settling time
[150-152]. To overcome this problem, activated carbon is now a days converted into
magnetic nano-composites which are more superior than activated carbon due to its
magnetic character on one hand and have comparable surface area on the other hand
[153-155]. Oladipo and Ifebajo [156] reported the removal of tetracycline and
fluorescent dye from wastewaters onto magnetic biochar prepared from chicken bones,
similarly, Shan and coauthors [157] evaluated the remediation of pharmaceutics from
aquatic environment onto ultrafine magnetic biochar and activated carbon. Saucier et
al. [158] utilized MAC for the decontamination of paracetamol and amoxicillin from
wastewaters. Kong et al. [159] used low cost magnetic herbal biochar for the
remediation of antibiotics from aquatic environment. A summary of some adsorbents
in practical application have been presented in Table 1.1.
Table 1.1. Recently reported adsorption capabilities in (mgg-1) of antibiotics on
different sorbents in literature
S. No. Adsorbent Antibiotic qm (mgg-1) Reference
1 Nano-hydroxy
appetite CIP 1.49 [160]
2 PAC
NOR 1.30
[161]
CIP 237
NOR 289
ENR 275
OFL 230
SAR 236
3 Bamboo biochar ENR 19.9
[162] OFL 19.9
4 Carbon derived from
hazelnut CIP 65 [163]
5 Magnetic carbon CIP 90.10 [164]
6 Magnetic humic acid CIP 101 [165]
29
1.10.8 Membrane processes
Membrane processes like ultrafiltration (UF), nanofiltration (NF) and reverse osmosis
filtration (RO) are the emerging technologies used worldwide for the purification of
potable and industrial water. However, the efficacy of these membranes is affected by
synthetic organic matter [166, 167]. As these substances are get adsorbed on membrane
surface and block the pores, to remove this problem activated carbon can be used in
combination with membrane technology. It was considered that the particles of
activated carbon if enter in membrane system will form porous cake over the membrane
and will not affect the permeate flux [168, 169]. However, latter on it was proved, this
layer also effect the permeate flux. In order to solve this issue, some authors attempted
to prepare magnetic activated carbon and use it in combination with membrane in
hybrid manner and significant results were achieved in this regard. As magnetic
activated carbon can be easily removed from the slurry [170, 171]. Azmat et al. [172]
studied the removal of CIP molecules on the surface of pineapple magnetic carbo
nanocomposites (PAMCN) prepared from low cost biomass precursors of pineapple in
hybrid manner at pH 7, 298K temperature and initial CIP concentration of 40 mgL-1.
Improved permeate fluxes and percent retentions of CIP by membranes (UF, NF and
RO) were observed for adsorption/membrane hybrid process PAMCN/UF,
PAMCN/NF, and PAMCN/RO. The percent retention of CIP molecules in NF was 96%
which increased to 100% when membrane was used in hybrid manner with PAMCN.
No blackening of membrane pipes were observed. Yang et al. [173] utilized a novel all
carbon 3D NF membrane of multi walled carbon nanotube (MWCNTs) interposed
between nano sheets of graphene oxide (GO). The nano channels of prepared membrane
can physically sieve antibiotic molecules through electrostatic forces of attraction. The
thickness of membrane used in the study was 4.26 µm and effectively retain almost
30
100% of tetracycline hydrochloride molecules with water permeate flux of 16.12 Lm-
2h-1bar-1. The prepared NF membrane have broad spectrum application because it
effectively remove methylene blue dye from wastewater.
1.11. Aims and objectives of the present work
The main aim of this study was to prepare magnetic carbon nanocomposites (MCN) on
the surface of low cost biomass precursors of pineapple and mangoe, perform
characterization and evaluate their efficacy for the removal of FQs antibiotics from
aqueous solution through adsorption and membrane hybrid technology.
In meeting the above goal, the following specific objectives are to be apprehended: To
1. Introduce new method for the synthesis of magnetic carbon nanocomposite
(MCN) material.
2. Investigate the characteristics of two magnetic carbon nanocomposites
through surface area analyzer, scanning electron microscopy (SEM), Energy
dispersive X-ray (EDX), X-ray diffraction (XRD), Thermogravimetric/
differential thermal analysis (TG/DTA), Fourier transform infrared
spectroscopy (FT-IR) and Point of zero charge (PZC) using mass titration
method.
3. Optimize various experimental parameters for the removal of Ciprofloxacin
(CIP), Levofloxacin (LEV) and Enrofloxacin (ENR) such as pH, equilibrium
time, initial antibiotics concentration, temperature, doses of MCN, effect of
ionic strength and effect of humic acid.
4. Investigate its potential applications for the removal of FQs group of
antibiotics from wastewater by adsorption studies and hybrid technology.
31
5. Determine the adsorption capacity of each MCN by applying some commonly
used adsorption isotherms and kinetic models.
6. Calculate the percent retention of each antibiotics and permeate flux of
membrane system.
7. Calculate various thermodynamic parameters.
8. Know the spontaneous and non-spontaneous nature of of adsorption.
9. Degenerate the magnetic carbon nanocomposites.
10. Minimize the concentration of Ciprofloxacin (CIP), Levofloxacin (LEV) and
Enrofloxacin (ENR) antibiotics in the aqueous environment.
It is expected that this research would strengthen the information available on the
removal of FQs antibiotics from aqueous solution. It will enhance the understanding of
adsorption and membrane hybrid technology.
1.12. Hypothesis
In this study waste biomass precursors of pineapples and mangoes that are aboundant
in nature or disposed by the individuals were set up to be used for the preparation of
magnetic carbon nanocomposites with the aim of achieving materials with upgraded
adsorption properties for the removal of FQs antibiotics from aqueous solution.
Chapter 2
LITERATURE REVIEW
32
2.1. Literature review
Extensive efforts have been made to develop low cost-efficient adsorbents for the
removal of antibiotics from aqueous solutions such as biomass precursors of wood and
agricultural waste.
Olivia et al. [171] synthesized magnetite/pectin nanoparticles (MPNPs) and
magnetite/silica/pectin nanoparticles (MSPNPs) utilized it for the adsorption of two
FQs such as Ciprofloxacin (CIP) and Moxifloxacin (MOX) from aqueous solution
under different experimental conditions. A spectrofluorimetric method was devised for
the monitoring of CIP and MOX intact and photodegraded species amounts. The
maximum percentage removal (89%) was achieved as with MSPNPs under optimum
conditions of pH; 7.0, initial sorbate concentration; 5 mg/L, and contact time; 30 min.
The isotherm data were found fitted to Langmuir, Freundlich, and Sips models, and the
best fit with isotherm data was Sips model. To analyze sorption kinetics, pseudo 1st and
pseudo 2nd order kinetic models were employed, and it was found that adsorption of the
investigated FQs followed pseudo 2nd order kinetics. They from conclded from their
work that our synthesized MNPs can be utilized as an effective sorbents for the removal
of FQs and their photodegraded species from aqueous solution.
Caroline et al. [158] prepared two nanocomposites namely activated carbon (AC)/ Co
Fe2O4 (MAC-1 and MAC-2) by pyrolytic method using a mixture of Fe+3/Co+2
benzoates & Fe+3/Co+2 oxalates, respectively, and were efficient used for the removal
of amoxicillin (AMX) and paracetamol (PCT) from wastewaters. The prepared
nanocomposites were characterized using different techniques. The sizes Fe+3/Co+2
benzoates & Fe+3/Co+2 oxalates were in the ranges of 5–80 and 6–27 nm, respectively.
The magnetic nanocomposites can easily be separated from the slurry after adsorption
33
through application of external magnetic field. The maximum sorption capabilities of
AMX on MAC-1 was 280.9 and 444.2 mg g−1 on MAC-2, while for PCT, it was, 215.1
and 399.9 mgg−1 on MAC-1 and MAC2, respectively. Both adsorbents successfully
used for simulated hospital effluents, removing at least 93% by MAC-1 and 96.77% by
MAC-2.
Wang et al. [162] studied the adsorption of widely used FQs antibiotics such as
enrofloxacin and ofloxacin in wastewater using bamboo biochar was investigated.
More than 99% of fluoroquinolone antibiotics were removed from the synthetic
wastewater through adsorption. Adsorption capacities of bamboo biochar slightly
changed when pH increased from 3.0 to 10.0. The adsorption capacity of bamboo
biochar increased sharply when the initial concentration of enrofloxacin or ofloxacin
increased from 1 to 200 mg L−1 and then began to plateau with further increases in
initial concentration. The maximum adsorption capacity (45.88 ± 0.90 mg·g−1) was
observed when the ratio of bamboo biochar to fluoroquinolone antibiotics was 10. The
enrofloxacin adsorption capacity of bamboo biochar decreased from 19.91 ± 0.21
mg·g−1 to 14.30 ± 0.51 mg·g−1 while that of ofloxacin decreased from 19.82 ± 0.22
mg·g−1 to 13.31 ± 0.56 mg·g−1 when the NaCl concentrations increased from 0 to 30
g·L−1. The adsorptions of fluoroquinolone on bamboo biochar have isotherms that
obeyed the Freundlich model (R2 values were in the range of 0.990–0.991).
Balarak et al. [163] investigated the adsorption of Ciprofloxacin (CIP) from aqueous
solutions by hazelnut shell activated carbon (HSAC) in a batch adsorption system.
Factors affecting CIP adsorption such as contact time (10-180 min), initial CIP
concentration (25–200 mg/L), pH (3–11), sorbent dosage (0.3–3.0 g/L) and temperature
(293–323 K) were studied. The adsorption process was relatively fast and equilibrium
was established about 60 min. Maximum adsorption of CIP occurred at around pH 6.
34
A comparison of the kinetic models on the overall adsorption rate showed that the
adsorption system was best described by the pseudo second-order kinetics. The
adsorption equilibrium data fitted best with the Langmuir isotherm and the monolayer
adsorption capacity of CIP was determined as 61.25, 67.39, 73.64 mgg-1 at 273, 298
and 323 K, respectively. Thermodynamic parameters were calculated for the CIP–
HSAC system and the positive value of ∆H0 (3.064 kJmol-1) and negative values of ∆G0
showed that the adsorption was endothermic, spontaneous and physical in nature.
Balarak et al. [174] studied the adsorption of amoxicillin (AMX) onto palm bark from
aqueous solutions using batch adsorption system. Factors influencing AMX adsorption
such as initial AMX concentration (10–100 mgL-1), contact time (10–180 min), and
adsorbent dosage (0.5–5 gL-1) were investigated. The maximum removal efficiency of
AMX was 98.1% under optimum conditions of adsorbent dose 3 gL-1, contact time of
90 min and temperature 298K and initial AMX concentration 10 mgL-1. Adsorption
isotherms models including Langmuir, Freundlich and Tempkin were tested. It was
inferred that the Langmuir models (with very high R2 values) were most suited to
describe the sorption of AMX in aqueous solutions and the monolayer adsorption
capacity of AMX was found to be 35.92 mgg-1.
Nodeh et al. [175] used polyaniline magnetic graphene oxide nanocomposite
(MGO@PANI) for the removal CIP from wastewater. The prepared nanocomposite
was characterized using EDX, FTIR, and FE-SEM methods. Maximum adsorption
(97%) was achieved at pH 6 with sorbent dose of 0.02g and 30 minutes time at room
temperature. The isotherm data fully satisfied the Freundlich model, while kinetics
data obeyed pseudo 2nd order kinetics. From thermodynamic parameter calculation it
was concluded that CIP adsorption onto nanocomposite was endothermic in nature.
35
Yan et al. [176] used pretreated barley straw for the effective removal of norfloxacin
from aqueous solution. The maximum removal of norfloxacin at room temperature and
neutral pH. Various kinetics and isotherm models were applied to know the mechanism
of adsorption. The results also showed that the process of adsorption increases with rise
in temperature.
Yi et al. [177] used different biochars prepared from pretreated pine wood chip for
the removal of levofloxacin using batch adsorption method. Both adsorbents were
characterized using different techniques. They confirmed the chemical adsorption of
levofloxacin from pre and post FTIR spectral analysis of biochars. The sorption data
fully obeyed pseudo 2nd order kinetics, Freundlich and Langmuir models.
Afzal et al. [178] studied the adsorption of ciprofloxacin from aqueous media using
chitosan/biochar hydrogel beads (CBHB). The maximum removal of ciprofloxacin at
initial concentration of 160 mg/L was 76 mgg-1. the adsorption capacity of adsorbent
decreases in the presence of phosphoric acid, while other electrolytes such as NaCl,
NaNO3 and Na2SO4 have little effect on adsorption capacity. The mechanism of
ciprofloxacin removal onto CBHB is due to π-π interaction, hydrogen bonding and
hydrophobic interaction.
Liu et al. [179] used two adsorbents magnetic activated alumina (Al2O3/Fe) and lotus
stalk-based activated carbon (LAC) for the decontamination of norfloxacin from
aqueous environment. Maximum sorption capacity was achieved by the former
adsorbent at pH 6.5, while that of the latter was pH 5.5. The sorption kinetic data fitted
well to pseudo 2nd order model for both adsorbents. The adsorption isotherm data
followed Langmuir model on LAC and Al2O3/Fe obeyed both Langmuir/Freundlich
model pretty well. The dominant mechanism for the removal of norfloxacin on
36
Al2O3/Fe are due to surface complexation and cationic bridging, while that for LAC the
dominant mechanism are hydrophobic interaction, exchange of cationic species and ℼ
electron accepter-donor interaction.
Shi et al. [180] studied the removal of CIP from aquatic environment using magnetic
carbon composite (Fe3O4/C). Maximum adsorption of CIP occurs at nearly neutral pH.
Various kinetic and isotherm models were applied to the adsorption data, the adsorption
kinetic data fitted well to pseudo 2nd order kinetics, while adsorption isotherm data
followed Langmuir model. Due to magnetic character of sorbent (Fe3O4/C), it can easily
be separated from suspension by application of external magnetic field. The Fe3O4/C
was regenerated ten times and percent removal of CIP (85%) clearly suggest the high
efficiency of adsorbent. Due to low cost and easy regeneration of adsorbent makes him
a promising adsorbent in the field of surface chemistry and a promising adsorbent for
decontamination of wastewater.
Wang et al. [181] prepared bamboo based activated carbon (BbAC) from scraps of
bamboo with combined chemical activation phosphoric acid and potassium carbonate.
BbAC was characterized by BET isotherm. The specific surface area and total pore
volume of the prepared adsorbent are 2237 m2g-1 and 1.23 cm3g-1 respectively. The
adsorption experiment was conducted at room temperature. The maximum adsorption
capacity of BbAC was 613 mgg-1.
Mao et al. [182] synthesize MCN (Fe3O4/C) from one step hydrothermal process
followed by thermal activation in an inert atmosphere. The prepared Fe3O4/C was
characterized by various techniques and used for the decontamination of CIP from
aqueous solution. Various factors were optimized for CIP removal. The adsorption data
fully obeyed Langmuir isotherm and pseudo 2nd order kinetic models. The Fe3O4/C was
37
regenerated several times and its adsorption capacity was little affected. They
concluded that modified Fe3O4/C is an excellent and efficient adsorbent for the
decontamination of water.
Danalioglu et al. [169] investigated the removal of different antibiotics (ciprofloxacin,
erythromycin and amoxicillin) on the surface of novel adsorbent (Fe3O4/C/chitosan).
The novel adsorbent was characterized by FTIR, SEM, EDX, VSM, XRD, surface area
analyzer and VSM techniques. The experimental data of all antibiotics fitted well for
Langmuir and pseudo 2nd order kinetics. Fe3O4/C/chitosan (MACC) is a superior
adsorbent due to its magnetic character on one hand and have comparable surface area
on the other hand. MACC can effortlessly be detached by use of exterior magnetic field
from suspension. The maximum sorption capacity of MACC was achieved for
Amoxicillin with 526.31 mg/g.
Badi et al. [183] modified powder activated carbon with magnetite nanoparticles (PAC-
MNPs) by co-precipitation method and used it for the removal of Ceftriaxone (CTX)
from aquatic solution. The optimum condition for CTX (97.18%) were recorded as pH:
3.14, temperature: 298K, equilibrium time: 90 minutes, PAC-MNPs dosage: 1.99 gL-1
and initial CTX concentration: 10 mgL-1. From thermodynamic parameters calculation
the removal of CTX onto PAC-MNPs is a spontaneous and exothermic process. The
removal efficiency of PAC-MNPs decreases only 10% after six rounds of regeneration.
Wang et al. [184] examined the removal of CIP from aqueous media using a novel
magnetic composite. The maximum removal of CIP molecules occurs at pH 6. The
adsorption data fully satisfied pseudo 2nd order and Langmuir models. By application
of external magnetic field, the magnetic adsorbent could easily be removed from
suspension.
38
Li et al. [185] synthesize biochar from tea leaves by process of pyrolysis at 4500C and
used it for the removal of CIP from aqueous environment. The maximum sorption
capacity of was 238.10 mgg-1 at pH 6. The process of CIP adsorption is controlled by
both external and intra-particle diffusion, while the main adsorption mechanisms were
due to ℼ-ℼ interactions, electrostatic attraction and H-bonding.
Menzi et al. [186] used two adsorbents illite and synthetic zeolite for the
decontamination of enrofloxacin from aqueous solutions using batch adsorption
methods under different conditions of pH, time and initial sorbate concentrations. The
optimum pH found for removal of enrofloxacin on the surface of illite was 7 and for
zeolite was 8. The main adsorption mechanisms were cationic exchange and
electrostatic interactions.
Rivagli et al. [187] used different clay minerals for the removal of two veterinary
antibiotics such as enrofloxacin and marbofloxacin as a function of different pH from
aquatic salts solution and tap water. The process of adsorption mechanism was
confirmed from XRD spectra.
Li et al. [188] investigated the adsorption experiments for the removal of ofloxacin onto
the surface of kaolinite as a function of pH and ionic strength. They concluded from
their work that major contributor for ofloxacin removal onto the surface of kaolinite
was cationic exchange and pH value higher than 7.0 is an optimum condition for
adsorption.
Silva et al. [189] tested four different adsorbents (raw and modified forms of clay) for
the efficient removal pharmaceutics (venlafaxine an antidepressant drug) from
wastewater. The adsorption kinetic data of different adsorbents followed Elovich and
39
pseudo 2nd order kinetics, while adsorption isotherm data fully obeyed Langmuir and
Redlich-Peterson’s models.
Jin et al. [190] eliminated levofloxacin from aquatic media using cobalt modified
adsorbent through batch adsorption experiments as a function of pH, time, initial
levofloxacin concentration, sorbent dosage and temperature. The optimum conditions
calculated are; pH 8.5, temperature 303K, sorbent dosage 1 gL-1, and initial LEV
concentration of 119.8 mgL-1. The adsorption rate was fast and reached equilibrium
within 120 minutes. The kinetic data fully obeyed pseudo 2nd order kinetic model
whereas isotherm data followed D-R isotherm. The adsorption energy calculated from
D-R model is 11 kJmol-1 confirms that the process of adsorption is mainly followed by
chemical adsorption. Calculation of various thermodynamic parameters confirms that
the process of adsorption is exothermic and accompanied by decreasing disorder.
Genc [191] investigated kandira stone as adsorbent for the removal of ciprofloxacin
hydrochloride from wastewater through batch adsorption studies. The main mechanism
of adsorption is chemisorption and intraparticle diffusion is a rate controlling process.
The thermodynamic data revealed that the process of adsorption is spontaneous in
nature.
Sayen et al. [192] a cellulosic material derived from wheat bran, an agricultural
precursor was used to test its capability for a FQs antibiotic enrofloxacin as a function
of time, pH and initial concentration. The adsorption data revealed that 100%
enrofloxacin decontamination occurs at pH 6.0 in less than 60 minutes. The adsorption
isotherm data fitted well with Sips model with sorption capacity of 91.5 mgg-1 at pH
6.0.
40
Zhang et al. [193] used batch adsorption studies for enrofloxacin onto bentonite as an
effect contact time, sorbate concentration and temperature from water. The adsorption
equilibrium time for all adsorption studies reached within one-hour time, whereas rise
in temperature increases the rate of adsorption. The process of adsorption is
endothermic and spontaneous.
Chamani et al. [194] prepared a novel magnetic adsorbent and used it for the removal
of enrofloxacin antibiotic from aquatic system as a function of pH and temperature. The
magnetic sorbent was characterized using different techniques. The adsorption kinetic
data fully obeyed the pseudo 2nd order kinetic model.
Sun et al. [195] prepared positively charged novel modified NF membrane for the
successful expulsion of FQs antibiotic from the water. The membrane has adequate
mechanical qualities for the penetration of water under high pressure. The membrane
shows the highest percent retention, least fouling tendency and has a constant permeate
flux over a different pH range. They concluded from their studies that modified NF
membrane has high antifouling capacity and have a great potential for various
industries.
Mona et al. [196] used novel membrane hybrid process (UF/activated
carbon/ultrasound irradiation) process for the effective removal of emerging
contaminants (Diclofenac, Carbamazepine, and Amoxicillin) from wastewater through
single and combine processes. They achieved complete removal of these contaminants
through the application of the hybrid process.
Ming et al. [197] effectively used graphene oxide (GO), activated carbon (AC), carbon
nanotube (CNT) and membrane hybrid processes for the decontamination of
tetracycline hydrochloride (TCH) from water. GO/AC hybrid sheets with 15 µm
41
thickness effectively remove about 99% TCH than other hybrid processes used in the
study.
Ahamad et al. [198] synthesize a low cost and efficient hybrid membrane from the
mixing of alumina powder and activated carbon having a complex network with high
porosity of micro and nano channels and super hydrophilic properties as compared to
membranes of pure alumina. An increase in roughness of membrane surface increases
the percent retention of pollutants to 100%. They concluded from their studies that no
change in efficiency of hybrid membrane occurs under harsh experimental conditions.
Zahoor and Mahramanlioglu [199] designed a hybrid pilot plant (UF/adsorbents) for
the effective removal of 2, 4- Dichloro phenoxy acetic acid from aqueous environment.
Apart improved permeate flux was observed with hybrid membrane system, the percent
retention also increases.
Zahoor [164] focused on limitations of powder activated carbon for fouling control in
membrane processes such as blackening of pipes, backwash time and cake formation
on membrane surface. Due to these secondary problems he designed a hybrid pilot plant
using granular activated carbon (GAC) and ultrafiltration (UF) membrane under batch
adsorption/membrane hybrid process for the decontamination of various pesticides
from wastewaters. 100% retentions were achieved for these pesticides under GAC/UF
hybrid system along with improved permeate fluxes.
Zhang et al. [200] used a hybrid and integrated method using powder activated carbon
(PACs)/ultrafiltration (UF) and reverse osmosis (RO) membranes for the treatment of
wastewater stream coming out of tetracycline (TC) pharmaceutical company. They
used RO membrane alone, for the recovery of TC and COD, results show that the
concentration of TC and COD decreases efficiently from 0.8gL-1 to 0.02gL-1 and
42
0.85gL-1 to 0.07gL-1 respectively accompanied by irreversible fouling (that decreases
the lifetime of a membrane). To overcome irreversible fouling, they used UF in
combination with RO as a result the fouling of RO membrane reduced to greater extent.
To achieve improved, permeate flux and percent retention then they used UF/RO/PACs
in combined manner, the percent retention of TC and permeate fluxes of membrane
increases considerably. They concluded from their work that UF/RO/PACs is a
promising method for the treatment of wastewater and recovery of TC.
Wei et al. [201] used Nanofiltration (NF) membrane for the advanced treatment of
pharmaceutical wastewater streams as a function of membrane fouling and chemical
cleansing. They found from their results that initial fouling of membrane was due to
deposition of sulphate and carbonate ions of calcium while latter fouling was due to
deposition of certain organic and inorganic contaminants on the surface of membrane.
The latter deposited layer forms a denser cake like structure on membrane surface
depends on the efficiency of used cleansing agent. 10 milli moles of EDTA was found
the best cleansing agent with membrane permeate flux of almost 100% as confirmed
by the SEM images and elemental contents of the membrane.
Ahamad et al. [202] synthesized a modified NF membrane from Polyether sulfone
(PES) and Polyvinylpyrrolidone (PVP) for the removal of antibiotics from wastewater
under varying operating conditions of temperature, pH, feed concentration and applied
pressure. The prepared NF membrane was characterized by zeta potential, water contact
angle, ATR-FTIR spectroscopy and scanning electron microscopy (SEM). The percent
retention of antibiotic was 56.49% and the permeate flux of NF membrane was almost
100%. The operating parameters like pH, temperature and pressure have a little effect
on percent retention of antibiotic and permeate flux of NF, while initial feed
concentration have an effect on percent retention/permeate flux of membrane system.
43
The highest percent retention of antibiotic was achieved at pH; 9.0, temperature; 298K,
applied pressure; 2 MPa and initial feed concentration; 20ppm. They recommended the
modified self-made NF membrane for the effective removal of antibiotics from aqueous
environment under low initial feed concentration.
Nalan kaby and Merek Bryjak [203] have focused on membrane hybrid processes. They
concluded that membrane hybrid processes are superior to conventional separation
processes due to lower energy consumption, highest yields, and sustainability. They
recommended such systems an alternative ways of cleansing environmental effluents.
Shatalebi et al. [204] evaluated the removal of amoxicillin (AMX) from pharmaceutics
effluents on spiral polyamide NF membrane as a under the influence of flow rate,
applied pressure and initial feed concentration of AMX and COD. The % retention of
AMX and COD was 97 and 40% respectively, whereas the permeate flux (J) of NF was
1.5 Lmin-1m-2. The rise in applied pressure improved the transport of solvents, while J
increases with increase in flow rate. They concluded from experimental work that high
retention of AMX is due to polarization and improved J of membrane showed a
potential application of pharmaceutical wastewater treatment.
Dinesh et al. [205] prepared magnetic activated carbon (MASAC) from the mixing of
activated carbon with an aqueous suspension of ferrous/ferric ions followed by sodium
hydroxide treatment for the removal of trinitrophenol (TNP) from aqueous streams.
They used both MASAC and nonmagnetic activated carbon (ASAC) in their studies.
They determined the surface morphologies of both adsorbents. Various kinetics and
isotherm models were evaluated for both adsorbents. Desorption experiments were
conducted with hot water and methanol.
44
Mehta et al. [206] have focused on the need of new adsorbents. As adsorption process
play an important role in the treatment of wastewater coming from various industries
such as dyes, pharmaceutics etc. due to some obstacles the conventional adsorbents
have nowadays being replaced by new adsorbents having magnetic character one hand
and have comparable surface area on the other hand can successfully be used for the
treatment aquatic pollutants.
Kumari et al. [207] prepared magnetite adsorbent using a simple method with ferric salt
an iron precursor for the effective remediation of lead and chromium ions as a function
of pH and temperature etc. from aquatic environment. The optimum pH Cr+6 and Pb+2
was 4.0 and 5.0 respectively. The used adsorbents can effortlessly be detached from
aqueous suspension through use of magnet and can easily be regenerated.
Xiangdong et al. [208] synthesize magnetic and novel carbon nanocomposite from
waste biomass precursors with high saturation magnetization under normal conditions
and effectively used it for the removal of dyes from wastewater. The magnetic
adsorbent can easily be removed from the suspension by application of external
magnetic field.
Thines et al. [209] reviewed the synthesis of magnetic biochar from agro based
precursors. The conversion of agro based precursors into more productive materials has
decreases their disposal issues. Magnetic biochar derived from waste biomass
precursors has good adsorbent capabilities on one hand and has a remarkable magnetic
property on the other hand. Due to their high surface area and magnetic character,
magnetic biochar exhibits excellent applications in the field wastewater treatment
processes and polymer industries.
45
Thines et al. [210] synthesize a novel magnetic biochar from waste biomass precursors
of durian fruits (king of fruits) in the presence of iron oxide using pyrolytic method
under optimum temperature of 800oC, pyrolysis time in a muffle furnace 25 minutes
and sonication frequency 70 HZ. The magnetic biochar effectively removed Congo red
from wastewater.
Danna et al. [157] used two magnetic adsorbents biochar/Fe3O4 and activated carbon/
Fe3O4 hybrid materials for the decontamination of tetracycline (TC) and carbamazepine
(CBZ) by using adsorption and degradation methods. The adsorption capacities of
biochar/Fe3O4 and activated carbon/ Fe3O4 were higher for CBZ than TC. The
adsorption data fitted well for Langmuir model. Solution pH have no effect on
adsorption of CBZ while the adsorption of TC is slightly affected by pH. The used
adsorbents with adsorbed TC and CBZ on its surface were degraded
mechanochemically, after three hour of degradation process about 97% adsorbed TC
was degraded while 50% CBZ was remain undegraded. The use of quartz sand in
combination with biochar/Fe3O4 have greatly improved the CBZ degradation from 50%
to 98.4%. They concluded from their research work that such kind of ultrafine magnetic
sorbents can be effectively used for the purification of pharmaceutical effluents from
water/wastewater through adsorption process and degradation using ball milling.
Sandip et al. [211] evaluated superheated steam activated mung bean husk (SMBB) for
the decontamination of ranitidine hydrochloride (RH) from wastewater using
breakthrough column studies as a function of bed depth, initial RH concentration and
flow rate. The optimum sorption capacity of SMBB was achieved at bed height of 3
cm, RH concentration of 200 mgL-1 and flow rate of 2 mlmin-1.
46
Wang et al. [212] synthesized a variety of activated magnetic biochar (AMB) from
waste biomass precursors of corn stalks, red stalks and willow branches. They used
AMB for the decontamination of norfloxacin from aquatic media. The data of AMB
fully obeyed with pseudo 2nd order kinetic and Langmuir isotherm model. Adsorption
of norfloxacin onto AMB was spontaneous and an endothermic process. The maximum
sorption capacity 6.6249 mg/g was achieved with corn AMB.
Lin et al. [213] studied the combined effect of salts and organic matter on the adsorption
of ibuprofen and sulfamethazole using different biochar and activated carbon using
reclaimed water of RO membrane concentrate/synthetic solutions. The removal of
pharmaceutical effluents in RO concentrate is pH dependent, whereas presence of
electrolytes in RO concentrate increases the rate of adsorption on one hand while
presence of humic acid and carbonates decreases the rate of adsorption on the other
hand.
Alvarez-Torrellas et al. [214] used different activated carbon for the removal of non-
biodegradable pharmaceutics such as CIP and CBZ in ultrapure water as isolated
compounds and mixture of both. As a real pharmaceutic effluents higher removal of
both CIP and CBZ occurs at activated carbon with maximum sorption capacities of 264
mg/g and 242 mg/g respectively under neutral pH and 303K. The adsorption capacity
of CBZ decreases enormously when mixture of CBZ-CIP was used.
Zahoor and Mahramanlioglu [151] investigated the adsorption of imidacloprid onto
powder activated carbon (PAC) and magnetic activated carbon (MAC12) as a function
of contact time, initial sorbate concentration, solution pH and temperature from aqueous
media. The adsorption kinetic data of PAC and MAC12 followed PSEUDO 2nd order
kinetics, whereas, equilibrium data fitted well to Langmuir model for both adsorbents.
47
The rate of adsorption decreases with rise in temperature for both adsorbents, while
solution pH has no effect on the removal of imidacloprid.
Kim et al. [215] focused on the use and application of magnetic carbon nanocomposites
(MCN) for the decontamination processes of aquatic media, as these composites have
relatively low settling time and can easily be separated from aqueous media through
application of external magnetic field. They concluded from their work that MCN is an
alternative adsorbent for the removal of large number of emerging aquatic effluents and
can easily replace the conventional adsorbents like activated carbon in the field of
surface chemistry. These adsorbents can easily be used in hybrid processes in
combination with membrane systems in a specially designed reactors and significant
results were achieved.
Robert et al. [216] synthesize magnetic carbon nanocomposites (iron oxide/carbon
nanocomposites) through an environmental friendly combustion method in an inert
atmosphere of N2 gas using citric acid as fuel and used it for the removal of
anionic/cationic dyes under different experimental conditions from aquatic
environment. The kinetic data is well explained by pseudo 2nd order kinetics, while
equilibrium experimental data fitted well with Langmuir model. The spent adsorbent
was regenerated 5 times. The adsorption of these dyes is highly pH dependent and
mechanism of dyes removal onto nanocomposites is controlled by electrostatic forces
of attraction. They concluded from their work that MCN is an excellent alternative
material of activated carbon for the purification of wastewaters.
Wang et al. [217] used magnetic ion exchange (MIEX) resins for the effective removal
of different antibiotics from aqueous solutions using batch experiments. The adsorption
capacities of MEIX for TC, SMX and AMX were 443.18, 789.32 and 155.15 μg/ml
48
respectively at room temperature, which were very much higher than activated carbon
indicating the superiority of magnetic sorbents over conventional carbonaceous
adsorbents. Solution pH play an important role for the sorption of antibiotics. The resins
were easily regenerated with NaCl solution. They concluded from their work that
magnetic resins have potential applications for the decontamination of antibiotics from
aquatic environment.
Paredes-Laverde et al. [218] successfully used rice husk (RH) and coffee husk (CH)
biomass precursors for the removal of broad spectrum, non-biodegradable antibiotic
(FQs) from aquatic media under variable solution pH and particle size of adsorbents.
Various isotherm models were to the adsorption data, Langmuir and Redlich-
Peterson models were fitted well to the adsorption isotherm data, while adsorption
kinetic data fully fitted with pseudo 2nd order kinetic model. The adsorption of FQs
antibiotic occurs at the surface and within the pores of RH and CH. Thermodynamic
studies confirm that the process of adsorption is physical and spontaneous in nature.
The removal of antibiotic on the surface of RH mainly through intermolecular
interactions, while in case of CH hydrogen bonding is the significant contributor.
Dolor et al. [219] studied the removal of photodegradable products of light sensitive
drugs such as FQs through application of membrane systems (RO and NF) under the
effect of solution pH. The presence of photodegradable products in aquatic system
results in the formation of new generation products which are more harmful to the
natural ecosystem than the parent compound, therefore it necessary to locate and
identify such products and successfully remove them before entering the water streams.
Membrane systems (RO and NF) are the irreplaceable technologies for the removal of
such kind of compounds from aquatic media. They successfully removed the
photodegraded products and parent compound (ENR) almost completely by RO and
49
tight NF membranes, while the % retention of ENR with loose NF reaches almost 92%.
The % retention of smaller photodegradable products loose NF membrane is almost
37% at slightly basic pH.
Sturini et al. [220] investigated the removal of FQs an important emerging micro
pollutants such as enrofloxacin (ENR) and marbofloxacin (MAR) through photo
chemical degradation process on the surface of clay minerals as a function of
irradiation time through high performance liquid chromatography (HPLC). They
concluded from their experimental work that the use of sunlight has completely
degraded ENR and MAR on the surface as well as in inner spacing of the clay minerals.
Ashrafi et al. [221] evaluated the removal of ENR from aqueous solutions using
modified rice husk as a function of solution pH, sorbate concentration, temperature and
adsorbent dosage. The optimum condition obtained for ENR (92.25%) removal are;
0.69g/L adsorbent dose, pH 5.11, initial ENR concentration 25.02 mg/L and
temperature 36.43oC.
Zhao et al. [222] compared the activities of different NF membranes for the rejection
of different pharmaceutical effluents from wastewaters. They concluded from their
studies that high pressure membranes like NF-90 and NF-270 have an excellent
rejection capability for the removal of contaminants from water reservoirs.
Zahoor and Khan [163] synthesized MCN from waste biomass precursors of maize and
characterized it through EDX, FTIR, SEM, TG/DTA, XRD and surface area analyzer.
They used it for the removal of Aflatoxin B1 as a function of solution pH, time and
temperature. The optimum equilibrium time achieved at pH 7 and pH 3 was 96 and 180
minutes, respectively. The adsorption kinetic data fitted well to pseudo 1st order kinetic
50
model. Various thermodynamics parameters were also determined using Van’t Hoff
equation.
Grenni et al. [223] reviewed the presence of different pharmaceuticals (micro
contaminants) in environment. These contaminants have greatly affected human beings
as well as other organisms. They have an adverse effect on natural microbial
communities, various methods are used for the decontamination of theses micro
contaminants from aquatic media. These antibiotics develop antibiotic resistance gene
(ARGs), which acts as an emerging contaminant (naturally present in chromosomal
DNA of bacteria).
Li et al. [224] investigated the removal of chloramphenicol (CAP) on modified
activated carbon prepared from Typha orientalis as a function of contact time, solution
pH, ionic strength and initial concentration of CAP from aqueous solution. The kinetic
data fitted well with pseudo 2nd order kinetic model while adsorption isotherm data
followed Freundlich isotherm. The adsorption process is a chemical controlling
process. The maximum sorption capacity of adsorbent is 0.424 mmolg-1. Both ionic
strength pH has a little effect on CAP removal. The possible removal mechanisms of
CAP on activated carbon were π-π interaction, hydrogen bonding and hydrophobic
phenomenon.
Jalil et al. [225] have used four different types of pillared clays for the effective removal
of emerging contaminants such as CIP from aqueous solution under different
experimental condition. The highest sorption capacity CIP was achieved at Silicon
(100.6 mg/g) and Iron (122.1mg/g) pillared clays. The possible mechanism of CIP
removal onto pillared clays were van der Waals interaction and inner sphere complex
formation.
51
Dogan [226] studied the removal of CIP (10 mgL-1) from aqueous solution using six
types of different (loose and tight) NF membranes as a function of transmembrane
pressure (TMP), membrane type and pH from aqueous solutions. The CIP retention
varied with type of membrane and solution pH. The highest retention of CIP was
achieved with tight NF90 membrane at pH value 5.65 and applied pressure of 10 bar.
Wang et al. [227] investigated the removal of pharmaceuticals and personal care
products (PPCP) in hybrid manner using membrane bioreactor (MBR) in combination
with RO and NF membranes from municipal wastewaters. The percent retention of
MBR lies in between 40-95%, while the % retention of MBR-NF/RO hybrid system
showed an efficiency above 95%. The hybrid MBR-NF successfully removed 13
compounds while hybrid MBR-RO successfully remove 20 compounds below
detection limits.
Gholami et al. [228] removed ampicillin and amoxicillin from artificial wastewater
using low pressure RO membranes as a function solution pH, initial antibiotic
concentration, temperature and membrane operating pressure. The percent rejection for
both antibiotics lies from 73-99%. The antibiotics rejection mechanism was due to size
exclusion. The permeate flux (J) for both antibiotics was lie in between 12-18.73 Lm-2
h and largely affected by the operating pressure and solution pH. They recommended
the used RO membranes for effective removal of antibiotics from wastewater.
Ming et al. [229] compare the treatment capability of forward osmosis (FO) and
membrane distillation (MD) hybrid system for the removal of trace organic
contaminants (TrOCs) from wastewater. The hybrid system percent rejection ranges
from 91 to 98%. In order avoid the decrease in permeate flux of membrane system, the
contaminants were treated with granular activated carbon before feeding into
52
membrane system and resulted in almost 100% rejection of TrOCs without
accumulation in the draw solution.
Long et al. [230] utilized two NF membranes for the removal of estradiol, estrone,
testosterone and progesterone (natural steroid hormones). The dominant mechanism for
the removal of hormones in the initial stage of filtration is adsorption of hormones to
the polymer of membrane, while, the latter filtration stage mechanism is governed by
size exclusion mechanism. The diffusion of hormones into membrane matrixes mainly
depends on size of hormones molecules, hydrogen bonding, functional groups and
hydrophobic interactions of hormones with membrane polymer.
Lubomira et al. [231] used a plot scale project for the removal of hospital wastes (micro
contaminants) with membrane bioreactor (MBR), post treatment methods such as PAC,
O3, low pressure UV light in the presence of and absence TiO2. They successfully
purified the hospital wastewater from micro contaminants.
Liu et al. [232] checked the potential of NF membranes using model as well as real
secondary effluents of antibiotics (FQs and macrolides) from wastewater as a function
of MWCO (molecular weight cut off), applied pressure and different feeding solutions.
The percent rejection of the model solutions of antibiotics under applied pressure of
0.2MPa were almost 100%. They also achieved high percent rejection with secondary
effluents with less permeate flux (J) decline.
Mehrdad et al. [233] focused their study on emerging pharmaceutically active species
present in water reservoirs affecting drinking water standards and aquatic ecology.
Various methods are used for the removal of these species which includes adsorption
and membrane systems. They reviewed their focus on the use of membrane separation
methods for the removal of such species, as membrane process are generally used for
53
the purification of good quality drinking and potable water. RO membranes are 100%
efficient for the decontamination of all pharmaceutical effluents but the use of RO is
limited by their cost, while, NF membrane separation is largely effected by hydrophobic
and electrostatic interactions. The efficacy of membrane bioreactors (MBR) is a
complicated one. To improve the effectiveness of membrane technology, they suggest
the need for hybrid system (combination of membrane/activated carbon).
Dinh et al. [234] investigated hospital and domestic effluents in water reservoirs for the
presence of antibiotics, they found eight classes of antibiotics with different
concentration range i.e. from the limit of low concentration to 50 micro gram per liter.
The compounds which often detected the most in effluents were FQs (enrofloxacin,
flumequine, ofloxacin, norfloxacin, ciprofloxacin, lomefloxacin and enoxacin),
sulfonamides and macrolides. The concentration of antibiotics is much higher in
hospital effluents (0.04-17.9 μg L-1) than those measured for domestic effluents (0.03-
1.75 μgL-1), their contribution to waste water treat plants for antibiotic inputs is about
90%.
Sun et al. [235] prepared magnetic and non-magnetic adsorbents from the biomass
precursors of a submerged aquatic plant (Vallisneria natans). The magnetic adsorbent
was prepared by simple co-precipitation method using ferric chloride hexahydrate and
ferrous sulphate hepta hydrate as iron source. They investigated both adsorbents for the
removal of methylene blue (MB) from aqueous solution. The adsorption kinetic data
fitted well for pseudo 2nd order kinetics, while isotherm data followed DR model. The
process of adsorption was spontaneous and exothermic in nature. The maximum
sorption capability of MB on magnetic and non-magnetic adsorbents were 473.93 mgg-
1 and 657.9 mgg-1 respectively at 30oC.
54
Zhang et al. [236] prepared magnetic activated carbon (MAC) from bituminous coal
and used it for the removal of organic contaminants using batch adsorption method as
a function of contact time and MAC dose. The removal efficiency for the organic
contaminants ranges from 71.4 -100%. The MAC was regenerated through magnetic
separators.
Guo et al. [237] synthesize magnetic activated carbon (MAC) from biomass precursors
of peanut using ferric chloride hexahydrate as magnetite/iron source. MAC was
modified in an atmosphere of CO2. The modified MAC was characterized and use for
the removal of dyes from aquatic environment. The spent MAC were separated from
aqueous suspension by application of external magnetic field. The adsorption data fully
explained by PSO and Freundlich model.
Arbabi et al. [238] synthesized magnetic activated carbon (MAC) from almond biomass
precursors and used it successfully for the removal of nitrate ions from aqueous solution
as a function of solution pH, contact time, initial concentration of NO3-1 and MAC dose.
Fatemeh et al. [239] prepared magnetic carbon nanocomposites (MCNC) by simple
precipitation method and successfully utilized for the adsorption of melanoidin (a by-
product of bioethanol) under optimum conditions of MCNC dose, contact time, pH, and
temperature. The adsorption data fully obeyed PSO and Langmuir isotherm models.
The percent removal efficiency of melanoidin on MCNC is about 81%.
Wang and Ma [240] synthesize a number of low cost magnetic porous carbon (MPCs)
from waste biomass precursors of peanut shells (carbon source) and hydrochloric acid
picking wastewater (magnetic source) via pyrolytic process. The MPCs were
characterized and used it for the adsorption of nitrobenzene (NB) from wastewater
55
streams. The possible mechanism for NB adsorption on MPCs were π-π, hydrogen bond
and electrostatic interactions.
Madeeha et al. [241] synthesize a low-cost and effective magnetic adsorbent from the
used tea impregnated with magnetite (Fe3O4) and successfully utilized it for the
removal hazardous metal As (III) from wastewater reservoirs as a function of initial
sorbate concentration, solution pH and temperature. Using DR-model various
thermodynamic parameters were calculated. The thermodynamic values confirmed
that the process of adsorption is spontaneous and exothermic in nature.
Tomaszewska and Mozia [242] prepared a model solution of HA and phenol. The
model solution was allowed to pass through UF membrane and UF/PAC in cross flow
system to check the percent retention of phenol, backwashing time and decline in
permeate flux using pilot plant. The use of PAC produces a small decline in permeate
flux of UF membrane. The particles of PAC if enters into membrane system during
pumping are too large to block the pores of UF membrane, they form a porous cake
on membrane surface. They concluded from their results that backwashing applied in
PAC/UF hybrid system was effective at PAC dose less than 20 mg/L. The permeate
flux (J) was maintained at 1m3m-2d-1. The 100% retention of phenol was achieved in
hybrid system at PAC dose of 100 mgL-1.
Heo et al. [108] examined the adsorption and retention of micro pollutants such as
Bisphenol A (BPA) and 17β-estradiol (E2) using different commercially available UF
membranes. A continuous stirred reactor operated at dead end was employed to check
the percent retention of micro pollutants and permeate flux of membrane in the presence
and absence of natural organic matter (NOM) and carbon nanotubes. The results
suggested that the transport of micropollutants were greatly affected by NOM resulting
56
in fouling of membranes through cake formation which blocks the pores of UF
membranes. Excellent decline in permeate flux and percent retention of micropollutants
were observed when UF membranes were operated in hybrid manner and in absence of
NOM.
Lowenberg et al. [243] used a two hybrid UF membrane (PAC/UF pressurized) and
(PAC/UF submerged) for the removal of micro-contaminants from WWTP effluents
for period six months. Both hybrid membranes excellent results. SEM images of both
membranes confirms the degeneration of membranes after operation of six months
period. The percent retention of micro-contaminants for both hybrid UF membranes
ranges from 60-95% at PAC dose of 20 mgL-1.
Lowenberg et al. [244] utilized three distinctive pre-treatment advancements such as
powder activated carbon (PAC) adsorption, coagulation and UF prior to RO membrane
for desalination of a cooling tower blow down (CTBD) was explored. Unique
consideration was paid to the capacity of the pre-treatment for the removal dissolved
organic matter (DOM). The PAC/UF pre-treatment bring about the least fouling of
membrane systems.
Zahoor [245] designed a pilot plant (GAC/UF hybrid plant), fixed bed methods and
adsorption method for the decontamination of different surfactants from aquatic
environment for fouling control of UF membrane. The adsorption equilibrium data
fitted well to Langmuir model. In membrane study he used UF membrane alone and
GAC/UF hybrid technology. He evaluated the membrane parameters like percent
removal of the selected foulants and the declines in permeate flux. Highest percent
retention was achieved for triton x-100 with UF and GAC/UF hybrid due to its
hydrophilic nature. No blackening of pipes and flowmeters were observed with GAC.
57
Zahoor [246] have devised a pilot plant for the production of drinking water with low
concentration of carbon-based matter using granular activated carbon
(GAC)/Ultrafiltration (UF) hybrid membrane system. First of all, he determined the
adsorption parameters of GAC using batch adsorption and fixed bed column methods.
For evaluation of membrane parameters like percent retention of foulants, permeate
flux of membrane and backwashing time, he used GAC filter in combination with UF
membrane in hybrid manner for the removal of HA from aqueous solution. Higher
percent retention (17.5%) of HA and improved permeate flux was observed with
GAC/UF than UF alone in dead end mode with transmembrane pressure of 0.8 bar.
Similarly, the back-washing time for GAC/UF membrane in hybrid manner was much
lower than UF membrane alone.
Zahoor and Mahramanlioglu [247] have prepared magnetic activated carbon (MAC)
and compared its efficiency with powder activated carbon (PAC) for fouling control in
membrane system. The adsorption parameters of both sorbents were determined using
batch adsorption methods for the remediation of phenolic substances from aquatic
media. The data fully obeyed with Langmuir model and pseudo 2nd kinetic model. The
membrane parameter like percent retention and flow rate of both adsorbents were
almost the same in MAC/UF and PAC/UF membrane systems, but the problem
associated with PAC like blackening of pipes and flow meters was not observed with
MAC, as MAC particles was easily removed from the slurry though application of an
external magnetic field.
Zahoor [152] have prepared powder magnetic activated carbon composite (MAC13)
and compared its efficiency with powder activated carbon (PAC) for fouling formation
in membrane system. The adsorption parameters of both PAC and MAC13 were
determined using batch adsorption methods for the decontamination of surfactants from
58
wastewaters. The adsorption data fitted well with Langmuir model. The membrane
parameter like percent retention and permeate flux were determined using pilot plant
(PAC/UF and MAC13/UF in hybrid manner), although the percent retention of
PAC/UF membrane was much higher than MAC13/UF but improved permeate flux
was observed with the latter. The problem associated with PAC like blackening of pipes
and cake formation on membrane surface was not observed with MAC13, as MAC13
particles was easily removed from the slurry though application of an external magnetic
field.
Xu et al. [248] investigated the removal of NOM in membrane systems fouling control
using magnetic resins in combination with membrane processes as a function of trans-
membrane pressure and preventing fouling. The pretreatment of foulants could
effectively remove most of the organic matter hydrophobic as well as hydrophilic. The
pore blocking and cake formation on membrane surface was reduced with magnetic
resins and enhanced production of water was achieved membrane hybrid process.
Zahoor [164] used GAC/UF hybrid technology for the removal of pesticides from
aquatic media. The adsorption parameters of GAC was determined using batch
adsorption method. The adsorption data obeyed Langmuir model. The percent retention
of 2, 4-D was 100% in GAC/UF hybrid system. Controlled fouling, improved permeate
flux and high percent retention was observed.
Knowledge gaps
Based on the literature review, there is an incentive to develop cost-effective and high
performance magnetic adsorbents from biomass precursors of pineapple and mango for
removal of FQs antibiotics from waste water through adsorption and membrane hybrid
technology. The Knowledge gaps for this purpose were identified as follows:
59
1. Magnetic nanocomposites (adsorbents) made from biomass precursors of
pineapple and mango has not been synthesized and characterized.
2. Magnetic nanocomposites (adsorbents) made from biomass precursors of
pineapple and mango has not been utilized for removal of FQs antibiotics from
waste water.
3. Impacts of operating parameters such as temperature, solution pH, initial
adsorbate concentration, ionic strength, HA, dosage and contact time on
elimination of FQs antibiotics from water using pineapple and mango magnetic
carbon nanocomposites have not been explored previously.
4. Equilibrium isotherms and kinetic models for adsorption of FQs antibiotics
from water pineapple and mango magnetic carbon nanocomposites needs to be
investigated.
5. Thermodynamic analysis of FQs antibiotics adsorption on pineapple and mango
magnetic carbon nanocomposites has not been conducted up till now.
6. Desorption and reuse of adsorbents made of pineapple and mango magnetic
carbon nanocomposites loaded with FQs antibiotics has not been explored
previously.
7. The effect of pineapple and mango magnetic carbon nanocomposites on
reduction of backwashing of membranes has not been explored previously.
8. The effect of pineapple and mango magnetic carbon nanocomposites on
permeate flux of membranes has not been explored previously.
9. The effect of pineapple and mango magnetic carbon nanocomposites on percent
rejection of FQs antibiotics has not been explored previously.
Chapter 3
EXPERIMENTAL
60
3.1. PREPARATION OF MAGNETIC CARBON NANOCOMPOSITES (MCN)
FROM BIOMASS PRECURSORS OF PINEAPPLE AND MANGO
Instruments
Magnetic stirrer Model PC-220 (China), pH meter PHS-3C (China), Microwave oven,
Digital analytical balance Sartorius (Germany) JT3003B and Centrifuge CN; FUJ 4000
r min-1 (China)
Chemicals and reagents
All the chemicals used in this study were of analytical grade. Ferric chloride
hexahydrate, ferrous sulphate, sodium hydroxide, hydrochloric acid (Sigma–Aldrich).
Procedure
Waste biomass precursors of pineapple and mangoe were collected from local market
in Swat, KP (Pakistan). The biomass precursors were washed with hot water to remove
dust. The samples were then dried in shade for several days and used to synthesize
pineapples and mangoes based MCN. A solution of FeCl3.6H2O (0.05mol) and
FeSO4.7H2O (0.025mol) were prepared in water (200 mL) at room temperature in
separate containers. The obtained mixed suspension of Fe+3 and Fe+2 was added to the
dried powder of pineapple and mangoes separately, and the mixture was stirred rapidly
for 5 min at 70oC. After this, 5molL-1 NaOH solution was added dropwise to the
mixture, for the adjustment of pH to approximately pH 10 with constant stirring for 50
min, and the resulting mixture was cooled. The mixture along with biomass was then
charred and ignited in a specially designed chamber for ten hours at 250oC under
nitrogen atmospher separately. In order to attain the neutral pH, the final product was
washed with 0.1 molL-1 HCl solution and washed with deionized water several times.
The final product of both precursors were oven dried at 70oC.
61
3.2. CHARACTERIZATION OF MAGNETIC CARBON NANOCOMPOSITES
(MCN) FROM BIOMASS PRECURSORS OF PINEAPPLE AND MANGO
3.2.1 BET Surface Area
BET-N2 adsorption-desorption experiments were carried out manometrically at -196oC
using Quantachrome NOVA 2200 surface area and pore size volume analyzer. Surface
area was obtained by applying the standard BET equation to the adsorption data. The
values of 0.81 g cm-3 and 16.2 × 10-20 m2 were used for the density of liquid nitrogen
and the molecular area of adsorbate nitrogen at -196oC, respectively. The pore size
distribution were determined by BJH method using the NovaWin2 data analysis
software.
3.2.2. FTIR analysis
A transmission infrared spectrum of the MCN samples were obtained by using 8201PC
Shimadzu, Japan, Fourier Transform Infrared Spectrophotometer along with FTCOM-
1 computer control disc unit. The KBr pellet technique was used. Potassium bromide
(KBr) Spectrosol BDH was well dried and stored in a vacuum desiccator before use.
The sample was dried. Various ratios of MCN samples and KBr were tried until
spectrum with an acceptable resolution was obtained. In the procedure the MCN
samples of approximately 3-5 mg was correctly weighed and then mixed with KBr.
This mixture was finely pulverized in porcelain container after which the pellet of
weighing 70 ±2 mg was hard-pressed in a 13 mm die for 5 minutes under a load of 10
tons. The resulting pellet was 0.5 mm thick. Since KBr is hygroscopic, the pellet was
dried in a vacuum oven (110 oC, 10 torr). It was found that drying the pellet for 12 hours
removed all detectable traces of water. The pellet was dried overnight and kept in a
vacuum desiccator to keep away from any moisture absorption. The IR absorption
62
bands of the MCN samples were obtained in the region ranging from 450 to 4000 cm-
1.
3.2.3 Elemental analysis or Energy Dispersive X-Ray (EDX)
The elemental analysis of the pineapples and mangoes MCN were carried out by EDS
X-sight apparatus (INCA 200 Oxford Instruments).
3.2.4. Scanning Electron Microscopy (SEM)
The surface morphology of MCN samples were determined using SEM at accelerating
voltage of 20 KV.
3.2.5. X-Ray Diffraction (XRD) analysis
MCN samples were characterized by XRD with Nickel filter using monochromatic Cu
Kα rays having wave length of 1.5418 Ao. The X-ray generator was operated at
generator current of 30 mA and voltage 40 KV. The scanning speed and scanning range
were selected at 10 min-1 and 2θ/θ respectively.
3.2.6. Thermogravimetric and Thermal Differential Analysis (TG/DTA)
TGA and DTA was performed for both MCN samples with diamond series TG/DTA
Perkin Elmer, US analyzer using alumina (Al2O3) as a reference, under N2 atmosphere.
The starting temperature for both nanocomposites were ranged from 50 to 600oC.
3.2.7. Zero point charge (pHpzc)
Zero Point charge (pHpzc) of PAMCN and MAMCN was determined using mass
titration method.
3.2.8. pH
One gram of the MCN samples were taken in a 100 cm3 conical flask and added 50 cm3
of freshly boiled CO2 free double distilled water and cooled to room temperature. The
suspension was uniformly mixed by stirring using magnetic stirrer. The samples were
allowed to stabilize. The pH of the suspension was measured by pH meter with
63
combined glass electrode. The same procedure was repeated in triplicate and the mean
value of pH was noted for each MCN sample individually.
3.2.9. Moisture contents
One gram (weighed in triplicate) of MCN sample of both nanocomposites were set in
in a separate, dried and pre weighed crucible. The crucibles are covered with a watch
glass and then dried in an oven at 105 ± 2 oC for 240 minutes [249]. Each sample was
cooled in a desiccator and weighed. The procedure was repeated in triplicate until a
constant equilibrium weight was attained. The percent weight loss was then calculated
as percent free moisture using the following equation;
Moisture (%) =Loss in mass on drying (g)
Mass of MCN (g) X 100 … … . 3.1
3.1.10. Ash contents
Standard test method (ASTM D2866-94) was used for the determination of ash content
of MCN nanocomposites. The empty porcelain crucibles were preheated in at 600oC in
a Muffle furnace. Crucibles are cooled in a desiccator and weighed. One gram of MCN
nanocomposites were taken in each rucible and reweighted. The crucibles containing
MCN nanocomposites were then placed in a cooled Muffle furnace and the temperature
was allowed to rise to 600oC with the door partially open (for the entrance of O2 for
oxidation of nanocomposites), to provide good circulation of air until the MCN sample
has been completely ignited. After ignition the crucibles were allowed to cool in the
furnace and then transferred to a desiccator and reweighed. The procedure was repeated
till a constant equilibrium weight was obtained. The percent ash contents of both
samples were then calculated using the following equation;
Ash (%) =Ash weight (g)
Furnace dried weight (g) X 100 … … . 3.2
64
3.3 FQs antibiotics solution preparation
Instruments
UV/VIS spectrophotometer (Shimadzu, Japan)
Chemicals and reagents
CIP, LEV and ENR antibiotics were collected from Swat Pharma, District Swat
(Pakistan). The characteristic properties of CIP, LEV and ENR antibiotics are given in
Table.3.1. Double distilled water was used throughout the experimental work.
Table. 3.1. Characteristic properties of the FQs used in this study
Structural formula of Ciprofloxacin
Molar mass 331.346 gmol-1
Appearance White crystalline
Dissociation constant 6.09-8.74 (at 298 K)
Solubility Water soluble
Structural formula of Levofloxacin
0.5 H20
Chemical formula C18H20FN3O4
IUPAC name (-)-(S)-9-fluoro2,3dihydro-3-methyl-10-(4-methyl-1-
piperazinyl)-7-oxo-7H-pyrido[1,2,3-de]-nzoxazine-6-
carboxylic acid hemihydrate
Molecular mass 370.38 gmol-1
Appearance Yellowish white
Dissociation constant 6.24 (carboxylic acid moiety)
Solubility Water soluble
Structural formula of Enrofloxacin
Chemical formula of Enrofloxacin C19H22FN3O3
IUPAC name Enrofloxacin 1-cyclopropyl-7-(4-ethylpiperazin-1-yl)6-fluoro-4-
oxoquinolone-3-carboxylic acid
Molecular mass 359.401 gmol-1
Appearance Pale yellow crystals
Dissociation constant 6.24 (carboxylic acid moiety)
Solubility Water soluble
65
Procedure
In the present study, stock solutions of FQs (CIP, LEV and ENR) were prepared by
dissolving known amounts of FQs antibiotics in double distilled water at room
temperature. Working solutions with desired concentration (1 -10 mgL-1) of CIP, LEV
and ENR were obtained by dilution method. Concentration of CIP, LEV and ENR were
determined at 275 nm (λmax), 280 nm (λmax) and 271 nm (λmax) respectively.
Calibration (standard) curves of CIP, LEV and ENR are given in figure 3.1, 3.2 and 3.3
respectively, while absorbance is given in table 3.2.
Table 3.2. Verification of Beer Lambert law for spectrophotometric determination of
FQs
CIP
Conc. (mgL-1) Absorbance
LE
V
Absorbance
EN
R
Absorbance
1 0.05 0.055 0.200
2 0.08 0.095 0.290
3 0.12 0.145 0.420
4 0.15 0.200 0.530
5 0.17 0.250 0.670
6 0.21 0.300 0.840
7 0.25 0.355 0.970
8 0.28 0.410 1.080
9 0.32 0.460 1.240
10 0.35 0.520 1.380
Slope 0.0355 0.051 0.1375
R2 0.993 0.999 0.996
66
Figure: 3.1. Calibration curve of CIP
Figure: 3.2. Calibration curve of LEV
y = 0.0355x
R² = 0.993
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0 2 4 6 8 10 12
Ab
sorb
ance
Concentration (mgL-1)
y = 0.051x
R² = 0.9986
0
0.1
0.2
0.3
0.4
0.5
0.6
0 2 4 6 8 10 12
Ab
sorb
ance
Concentration (mgL-1)
67
Figure: 3.3. Calibration curve of ENR
3.4 FQs adsorption (Batch studies)
The general methodology used in this study was to allow a specified amount of MCN
in 100 ml flasks, each containing 50 mL FQs solution having the desired concentration
according to the requirement of an experiment. In order to correct for any sorption of
FQs due to container walls, control experiments were conducted without MCN, and
there was negligible adsorption by the container walls. All the determinations were
carried out in triplicate, the mean values were determined and plotted. The flasks were
placed in a rotary shaker and were shaken at a speed of 150 r.min-1 for a specified
interval of time. The temperature was adjusted to the desired value (298K). The solution
pH was adjusted using 0.1 molL-1 HCl and 0.1 molL-1 NaOH solutions as reported by
Mao et al. [180]. The MCN was removed from solutions through a magnetic bar. The
FQs solution in the flasks was then filtered through Whatman filter paper No. 1. The
filtrates were checked for FQs concentration using UV/Visible spectrophotometer at
275 nm, 280 nm and 271 nm for CIP, LEV and ENR respectively. The amount of FQs
adsorbed at the surface of MCN samples qe (mg g-1) were calculated using the following
relation:
y = 0.1375x
R² = 0.9962
0
0.3
0.6
0.9
1.2
1.5
0 2 4 6 8 10 12
Ab
sorb
ance
Concentration (mgL-1)
68
𝑞𝑒 = (𝐶0 − 𝐶𝑒)𝑉
𝑊 ……….. 3.3
Where Co is initial FQs concentration in (mg dm-3), Ce is the FQs concentration (mg
dm-3) after certain interval of time, qe is the amount of FQs adsorbed on the surface of
MCN in (mg g-1), V is the volume of FQs solution in dm3 and W is weght in grams of
the MCN. The percent removal (% R) was calculated using the following relation:
% Removal = (𝐶𝑜−𝐶𝑒
𝐶𝑜) 100 …… 3.4
3.4.1 Adsorption kinetics
For the adsorption kinetics studies, 0.04 g of MCN was added to 50 mL FQs solution
in 100 mL flasks. The contact time was changed from 0 to 240 minutes. The flasks
containing FQs solution were shaken at 150 r.min-1 and 298K. Pseudo 1st, pseudo 2nd
order and intraparticle diffusion kinetic models were used to analyze the adsorption
kinetic data.
3.4.2 Adsorption isotherm studies
50 mL of FQs solutions of different concentration were taken in a series of flasks each
containing 0.04 g of MCN. The flasks were shaken at 298K for a specific intervals of
time. The MCN was removed from solution using a magnetic bar. The FQs solution in
flasks was then filtered through Whatman N0. 1 filter paper and the supernatants were
checked for FQs concentration using UV/Visible spectrophotometer. Langmuir,
Freundlich, and Tempkin isotherm models equations were applied to the adsorption
isotherm experimental data.
3.4.3 Determination of thermodynamic parameters
About 0.05 g of MCN was added to 50 mL of known concentrations FQs solution in
100mL flasks. All the flasks were placed on shaker with a speed of 150 r.min-1 at 25,
40 and 60˚C each for 80 minutes. The MCN was then separated from the solution using
69
magnetic bar, filtered the solution through Whatman filter paper No. 1 and analyzed for
FQs concentration by UV-Visible spectrophotometer as discussed above.
3.4.4 Effect of the adsorbent dose and pH on FQs removal
The effect of adsorbent dosage i.e. from 0.01 – 0.06 g at initial FQs concentration (CIP
= 30 mgL-1, LEV = 20 mgL-1 and ENR = 40 mgL-1) were determined at 298K.
The effect of pH i.e. from 3 – 11 at initial FQs concentration (CIP = 40 mgL-1, LEV =
30 mgL-1 and ENR = 20 mgL-1) were determined at 298K. The solution pH was adjusted
using 0.1M NaOH and 0.1M HCl solutions, as reported by Otker et al. [250] and Mao
et al. [180].
3.4.5 Effect of Humic acid (HA) on FQs removal
The effect of HA was determined using a different concentration of HA i.e. from 0- 80
mgL-1 in combination with initial FQs concentration (CIP = LEV = ENR = 30 mgL-1)
using 0.06g MCN at 298K for 240 minutes of shaking.
3.4.6 Effect of ionic strength (sodiumchloride) on adsorption capacity of MCN
The effect of ionic strength was determined at different concentrations of NaCl i.e. from
0-0.2 ML-I in combination with initial FQs concentration (CIP = LEV = ENR = 30 mgL-
1) using 0.06 g MCN at 298K for 240 minutes time of shaking.
3.5 Removal of FQs by membrane process
Three membranes UF, NF and RO were used in this study in order to determine the %
retention of selected antibiotic by each membrane and their consequent effect on
permeate flux. The characteristic properties of these membranes are given in Table 3.3.
Membranes were firstly washed with distilled water as instructed by the manufacturer.
A solution of known concentration of FQs was prepared in distilled water. All samples
were equilibrated to room temperature, at pH 7 and applied pressure was kept at 1.0 bar
70
throughout the experimental cycle. The rejection of FQs and the decline in the flow rate
by the selected membrane alone were determined.
Table 3.3. Characteristic properties of UF, NF and RO membranes
UF membrane NF membrane (DOW Film Tec 2.5 x
40)
RO membrane (DOW FILMTEC ECO
PRO 400i)
Parameters Specification Parameters Specification Parameters Specification
Material Polyether sulfone Model NF 270-2540 Model RO 270-2540
Type Capillary multi
bores x 7 Permeate Flow
rate
850 gallons/day
(3.2 m3/day) Membrane type
Thin film
composite
(Filmtech)
Diameter bores
ID 0.9 mm Active surface
area 28 ft2 (3.2 m2) Permeate Flow
rate
850 gallons/day
(3.2 m3/day)
Diameter fiber
OD 4.2mm Applied
pressure 4.8 bar Active surface
area 28 ft2 (3.2 m2)
Stabilized salt
rejection 10-20%
Stabilized salt
rejection > 97%
Stabilized salt
rejection 100%
Surface area 50 m2 Surface area 3.2 m2 Surface area 3.2 m2
Maximum
temperature 40oC Maximum
temperature 40-180oC Maximum
temperature 40-180oC
Maximum
pressure 109 psi
Maximum
pressure 100-1000 psi Maximum
pressure 100-1000 psi
Membrane back
wash pressure 0.5-1bar
Membrane back
wash pressure 50-800 psi Membrane back
wash pressure 50-800 psi
Operator pH
range 3-10
Operator pH
range 3-10 Operator pH
range 3-10
Back wash pH
range 1-13 Back wash pH
range 1-12 Back wash pH
range 1-12
Disinfection
chemicals
Hypo chloride and
Hydrogen
peroxide
Disinfection
chemicals
Hydrogen
peroxide and
peracetic acid
Disinfection
chemicals
Hydrogen
peroxide and
peracetic acid
MWCO 100KD MWCO 0.3-1KD MWCO 0.1-1KD
Pore size 5-20 nm Pore size 1-5 nm Pore size 1-5 nm
3.5.1 Removal of FQs by membrane hybrid process
The resulting decline in permeate flux due to blockage of membrane pore by antibiotic
when operated without the aid of adsorbent was compensated through the use of MCN
adsorption. This operation was termed as membrane hybrid processes. A specially
designed pilot plant was used for this purpose (Figure 3.4).
71
Figure: 3.4. Membrane hybrid plant
The membranes were washed with distilled water and water permeate flux was noted.
The test solutions were taken in 12 L container and passed through UF/NF/RO
membranes using the multispeed water pump. The membranes were, then used in
combination with the continuous stirred reactor, where MCN (0.4 gL-1) was added to
the FQs solution in a single dose. In a specially designed container equipped with the
magnetic arrangement for the separation of MCN after use, the FQs solution were
mixed with MCN for one hour which was then fed to membrane system as feed
contaminated water at a pressure of 1bar in case of UF and 5bar pressure in case of NF
and RO membranes. The UF membrane system was operated in dead-end mode. The
membrane parameter like percent retention of FQs and their effect on permeate flux
were determined.
The percent retention of the solute R was determined by using the following relation:
𝑅 = 100 (1 −𝐶𝑝
𝐶𝑏) ………….. 3.5
Where Cp is the concentration of solute in permeate (after feeding through membrane)
and Cb is the solute concentration in bulk (before feeding through membrane).
72
The permeate flux of membranes (J) L m-2 h-1 was calculated at different time of
filtration using the following relation:
J =1
𝐴
𝑑𝑣
𝑑𝑡 ……………… 3.6
Where A is area of membrane (m2), V is permeate volume (L) and t is filtration time
(h).
Backwashing of 60 minutes was applied to each membrane after each successive
experimental period.
In similar way the NF and RO membranes were operated in hybrid manner as described
above and membrane parameters like percent retention of selected antibiotics and their
effect on permeate flux were determined.
3.6 Reusability/Regeneration and recycling of MCN (Desorption experiment)
For the economical point of view, in adsorption process regeneration of adsorbent is
very important.
Instruments
UV/VIS spectrophotometer (Shimadzu, Japan)
Chemicals and reagents
NaOH analytical grade (Sigma Aldich), CH3OH analytical grade (Sigma Aldich) and
double distilled water
Procedure
First, 0.150 g of both nanocomposites i.e. PAMCN and MAMCN was added to 50 mL
initial CIP concentration of 80 mgL-1 and initial concentration of LEV = ENR = 40
mgL-1 at pH 7.0 . The reaction was oscillated at 150 rmin-1 in a 25 °C water bath for six
hours. The remaining concentration of each antibiotic in the filtrate was measured using
a UV/Visible double beam spectrophotometer, and the adsorption capacity was
calculated. The PAMCN/CIP, PAMCN/LEV, PAMCN/ENR and MAMCN/CIP,
73
MAMCN/ENR loaded complexes were isolated from the reaction mixture with a
magnet, and the solid was washed several times with a 3% NaOH solution, methanol
and double distilled water. At last the washed samples was individually oven dried in
an oven at 70oC for five hours. The collected adsorbent was reintroduced into 50 mL
solution of initial concentration of selected antibiotics at pH 7.0, and the regeneration
performance of both samples were investigated under the same conditions. The same
experiment was carried out six times under the same conditions Desorption experiments
were also carried out with photodegradation process (by exposing the FQs loded
nanocomposites to UV- visible light for eight hours).
3.7 Determination of drug resistance developed by bacteria found in the industrial
effluents against selected antibiotics
Industrial effluents were collected from local FQs industry at District Swat. The
effluents were spread on sterilized nutrient agar plates and incubated for twenty-four
hours. Gram staining technique was used to identify the bacteria present in the effluents.
Streptococci and staphylococci were detected. Both strains were incubated into tubes
containing nutrient broth in order to proliferate them. In order to determine the drug
resistance developed by both these strains, petri plates and nutrient agar was sterilized
at 121°C in autoclave. One plate was inoculated with streptococci using cotton swab
while the other with staphylococci. In both the plates three holes were made at equal
distances through cork borer. The holes were filled with CIP, LEV and ENR (20 mgL -
1 solution of each antibiotic was prepared in sterile distilled water and stored at -20°C),
incubated for 24 hours. The zone of inhibition formed around each hole were measured.
The zone of inhibitions of all these three standard antibiotics were compared to
conclude whether the drug resistance has been developed by these bacteria against ENR
or not.
Chapter 4
RESULTS AND DISCUSSION
74
4.1 Socio-economic impacts of the present research work
As a practice activated carbon or other adsorbents are used to detoxify different
pollutants (organic/inorganic) in the environment. Definitely antibiotics will
contaminate the environment and will reach to human body through food chain. Thus
in present study magnetic carbon nanocomposite (MCN) have been synthesized from
biomass precursors of pineapples and mangoes, and were used to remove CIP, LEV
and ENR from aqueous solution through adsorption/membrane hybrid technology.
Their presence in environment give rise to drug resistance in bacteria. The prepared
composites have magnetic character on one hand and have comparable surface area to
that of activated carbon on the other hand. After use, they can easily be collected from
the slurry through external magnetic process and can be regenerated/recycled easily.
The prepared nanocomposites are more effective and eco-friendly. If the antibiotics are
released from industry unchecked, they will enter into water bodies where a number of
bacteria are living there. Their concentration in vast water bodies will be lower than the
bactericidal concentration, so they will not kill the bacteria, however if bacteria grows
in such environment of antibiotic they will develop drugs resistance, which will result
the ineffectiveness of the antibiotics and will lead to huge economic losses. Thus their
removal with effective technology is the need of the day.
4.2 Characterization of the nanocomposites
The composites (PAMCN and MAMCN) were prepared on a surface carbonaceous
material. After the synthesis, magnetic bar were applied to the materials in order to find
whether the resulting material is magnetic or not. The material completely adhered to
the magnetic bar. This clearly showed that the prepared pineapple and mango (wastes)
based nanocomposites were magnetite in nature.
75
4.2.1 Surface area analysis
The BET surface area and BJH pore size distribution plots of both nanocomposites
(PAMCN and MAMCN) are given in Figure 4.1, 4.2, 4.3 and 4.4 respectively. While
results of different surface parameters are given in Table 4.1. The BET surface area of
PAMCN and MAMCN are lower in comparison with activated carbon. The reduction
in surface area of PAMCN and MAMCN were due to impregnation of magnetic
particles (Fe3O4), which resulted in pore blockage [245, 251, 252]. The other reason for
lesser surface area is pyrolysis of the samples was not performed at elevated
temperature [253]. The BET surface area of PAMCN and MACN were 43 and 51 m2g-
1 respectively. The lower BET surface area of the former was due to greater
impregnation of Fe3O4 particles in to the pore and is also confirmed from the percent
ash contents, specific gravity (Table 4.3) and elemental analysis Table 4.2. Although,
they are comparable to those reported by Mao et al. [180] 17.743 and 79 m2g-1, Tu et
al. [254] 46.5 and 16.6 m2g-1, Zahoor et al. [163, 255] 97 and 70.50 m2g-1.
The BJH pore size distribution surface area of PAMCN and MAMCN were 17.50 and
21.65 m2g-1 respectively, whereas, the total pore volume and pore diameter of PAMCN
and MAMCN were 0.015 and 0.019 cm3g-1 and 15.05 and 15.03 Ao respectively. The
micropore volumes and pore diameters of both nanocomposites were again much
smaller than that of activated carbon, the reason for this might be due to considerable
amount of the iron oxide (Fe3O4) in magnetic nanocomposites, which thus have smaller
surface areas and abundant temporary tiny holes. The micropore volume reported by
Oliveira et al. [252] for different magnetic composites were 0.172 and 0.177 cm3g-1 and
according to Anyika et al. [256] were; 0.09 and 0.18 cm3g-1.
76
Figure: 4.1. Plot of BET surface area of PAMCN sample
Figure: 4.2. Plot of BET surface area MAMCN sample
77
Figure: 4.3. BJH pore size distribution plot PAMCN sample
Figure: 4.4. BJH pore size distribution plot of MAMCN sample
Table 4.1 Surface parameters of PAMCN and MAMCN samples
Sample
BET surface
area
(m2g-1)
BJH surface
area
(m2g-1)
Total pore
volume
(cm3g-1)
Average pore
diameter
(Ao)
PAMCN 43 17.50 0.015 15.05
MAMCN 51 21.65 0.019 15.03
78
4.2.2 Energy dispersive X-ray (EDX) analysis
The elemental analysis of both nanocomposites (PAMCN and MAMCN) are given in
Figure 4.5 and 4.6. The proximate elemental analysis are given in Table 4.2. Lower
carbon contents (25.33%) was estimated in PAMCN versus MAMCN (32.62%) which
were attributed to greater impregnation of Fe3O4 in tiny holes on the surface confirmed
by both BET surface area and percent weight of Fe (41.00%). The higher loading of
iron particles onto the surface of carbonaceous materials was reported previously by
Oliveira et al. [252] and Mohan et al. [205]. Other major percentages of elements
present in both nanocomposites were oxygen and nitrogen, while lower percentages of
other elements (S, Si, Na etc.) were also present.
Figure: 4.5. EDX spectra of PAMCN sample
79
Figure: 4.6. EDX spectra of MAMCN sample
Table 4.2 Elemental analysis PAMCN and MAMCN samples
Sample Element Weight (%) Sample Element Weight (%)
PAMCN
C 25.33
MAMCN
C 32.62
O 22.76 O 23.97
N 8.00 N 12.04
Fe 41.00 Fe 20.17
Others 2.95 Others 11.20
4.2.3 Scanning electron microscopy (SEM)
Apparent morphology play a significant role in the interaction of adsorbent and
adsorbate molecules. SEM images (Figure 4.7 and 4.8) of PAMCN and MAMCN
shows a porous surface with somewhat disorganize structural morphology. SEM
observations for both PAMCN (Figure 4.7 a-c) and MAMCN (Figure 4.8 a-f) shows
differences in sizes and shapes of the composite materials. The images show the mean
diameter of both nanocomposites are around 50-70 nm. The white areas in the images
of both nanocomposites show the crystallization of samples and nano-particles of
Fe3O4, while black spots represents the carbon contents. The white areas were equally
80
distributed in to the carbon matrixes of both nanocomposites. Homogenous distribution
of white areas on the surface of both adsorbents making easy removal/separation by
application of external magnetic field [157]. The micrographs of PAMCN shows some
morphological changes due to greater impregnation of Fe3O4 in the pores of carbon
matrix, due to which the surface area is less than that of MAMCN. Impregnation of iron
on the surfaces of both nanocomposites are porous and spongy like. The spongy nature
of porous surfaces suggest a homogenous dispersion Fe3O4 nano-particles, which
resulted in lower surface area of nanocomposites. The lower surface area of magnetic
activated carbon is reported by Oliveira et al. [252] and Zahoor et al. [163]. It was also
observed from the images that the crystalline structure of Fe3O4 is somewhat cubic in
nature.
Figure: 4.7 a SEM of PAMCN
Figure: 4.7 b SEM of PAMCN
81
Figure: 4.7 c SEM of PAMCN
Figure: 4.8 a SEM of MAMCN
Figure: 4.8 b SEM of MAMCN
Figure: 4.8 c SEM of MAMCN
Figure: 4.8 d SEM of MAMCN
82
Figure: 4.8 e SEM of MAMCN
Figure: 4.8 f SEM of MAMCN
4.2.4 Thermogravimetric/Differential thermal (TG/DTA) analysis
Thermogravimetric analysis (TGA) is a technique utilized to determine the variation in
weight loss of a material under controlled atmosphere as a function of temperature. The
thermal stability of both samples (PAMCN and MAMCN) can be observed using TG
analysis. Figure 4.9 and 4.10 describes the thermogram of both nanocomposites at a
starting temperature of 35oC to 600oC. Table 4.3 briefly outline the temperature,
percent weight loss and PAMCN/MAMCN residuals after each decomposition phase.
Figure 4.9 and 4.10 explains that both (PAMCN and MAMCN) has really good thermal
stability as it can resist very high temperature. At the early stage, 45-100oC a loss of
9.70 and 6.22% in total weight of PAMCN and MAMCN occurs was due to dehydration
or loss of moisture. At around 100-370oC for PAMCN and 100-250oC for MAMCN
another weight loss stage is observed which is attributed to the dehydration of
physically adsorbed and rigidly bound water to the surfaces of both samples. The 2nd
weight loss stage of both samples are similar to that reported by Zahoor et al. [163, 255]
and Anyika et al. [256]. Both samples were continuously experiencing weight losses
up to temperature range of 550oC. These weight losses in both samples were due to the
decomposition of volatile organic matter, combustion of carbon and phase transition
83
from Fe3O4 to FeO, because FeO is thermodynamically stable above 570°C [257].
Above 550oC both samples showed sufficient thermal stability and no further weight
loss were observed. The final residue is a mixture of ash and char.
Figure 4.9 and 4.10 also illustrates the DT analysis of PAMCN and MAMCN. DTA
curves of both PAMCN and MAMCN showed three endothermic peaks in the
temperature range of 30 to 490oC.
Figure: 4.9 TG/DTA plot of PAMCN sample
Figure: 4.10 TG/DTA plot of MAMCN sample
84
Table 4.3 TG analysis of PAMCN and MAMCN samples
Sample
Temperature
(oC)
Weight
loss
(%)
Residual
(%)
Sample
Temperature
(oC)
Weight
loss
(%)
Residual
(%)
PAMCN
45-100 9.70 90.30
MAMCN
45-100 6.22 93.78
100-370 16.66 83.33 100-250 18..33 81.66
370-500 27.50 72.50 250-370 18.36 81.64
500-550 6.90 93.10 370-430 12.50 87.5
….. ….. ….. 430-550 42.85 57.13
4.2.5 X-ray diffraction (XRD) analysis
XRD is an established and an important analytical method utilized to recognize the
crystalline structure and particle size of a substance. In order to accurately prove the
crystalline state of Fe3O4 in both PAMCN and MAMCN samples, they were analyzed
using powder XRD analysis. Figure 4.11 and 4.12 illustrates the XRD diffractogram
patterns of Fe3O4 in PAMCN and MAMCN extracted from Fe+3/Fe+2 solutions. Both
diffractogram patterns showed the presence of Fe3O4 deposited on the surface of carbon
materials. The characteristics diffraction peaks of Fe3O4 crystals with cubic crystalline
structure in the PAMCN and MAMCN are obvious from the 2θ values at 30o, 35.7o,
44o, 53o, 57.95o and 62.5o, which correspond to indices planes of (220), (311), (400),
(422), (511) and (400). These values of diffraction peaks corresponds to the cubic
crystalline structure of magnetite form of iron, which has been previously reported by’
Zahoor et al. [151, 255] Tu et al. [254], Mohan et al. [205], Mao et al. [182], Zhang et
al. [258], Oliveira et al. [252], Anyika et al. [256] and Depci et al. [259]. The other
diffraction peaks at 2θ may correspond either to other forms of iron such as hematite
and maghemite or Fe3O4 may have changed to Fe3C/Fe [182]. Iron and iron
85
nanocomposites have advantages for the removal of CIP from aqueous media [182], on
one hand it has increased the mass of the particles due to which it can easily settle down
due to gravity and on the other hand it has magnetic character due to which it can easily
be collected after use through magnetic process [151, 255].
Figure. 4.11 XRD diffractogram pattern of PAMCN sample
Figure. 4.12 XRD diffractogram pattern of MAMCN sample
86
4.2.6 Fourier transform infra-red (FTIR) analysis
FTIR is a technique used for the determination of surface functional groups on the
surface of adsorbent. These groups shows a positive or negative impact on the removal
of any adsorbate. The prepared nanocomposites were characterized using FTIR
spectroscopy. The spectra of PAMCN and MAMCN are shown in Figure 4.13 and 4.14
respectively. The spectra of MCN shows characteristic peaks with broad bands between
3470 and 3200 cm-1 in the spectrum which may be attributed to stretching vibrations of
–OH groups in phenol, carboxylic acids or carboxylic acid derivatives, as well as the
existence of tangibly adsorbed water on the surface of MCN. The two narrow peaks in
the region of 3000-2800 cm-1 correspond to C-H alkanes, peaks at 1450-1600 cm-1
corresponds to C=C aromatic, peaks at 1300-1000 cm-1 corresponds to -OH alcoholic
and ether, while the peak at 575-580 cm-1 corresponds to Fe-O of magnetite and
maghemite (Table 4.4) [151, 170 and 182]. From the present study of surface functional
groups it was find out that these groups enhance the adsorption of all three types of
antibiotics. The earlier investigators Mao et al. [182] and Badi et al. [183] also studied
the impact of these groups on the removal of antibiotics.
Figure: 4.13 FTIR spectra of PAMCN sample
87
Figure: 4.14 FTIR spectra of MAMCN sample
Table 4.4 FTIR analysis of PAMCN and MAMCN samples
Sample Functional group Wave number Sample Functional group Wave number
PAMCN
-OH phenolic, -COOH,
-CONH-, adsorbed H2O
3470-3200 cm-1
MAMCN
-OH phenolic, -COOH,
-CONH-, adsorbed H2O
3470-3200 cm-1
-CH alkanes 3000-2800 cm-1 -CH alkanes 3000-2800 cm-1
C = C aromatic 1600-1450 cm-1 C = C aromatic 1600-1450 cm-1
-OH alcoholic,
C-O-C 1300-1000 cm-1
-OH alcoholic,
C-O-C 1300-1000 cm-1
Fe-O Magnetite,
maghemite 580-570 cm-1
Fe-O Magnetite,
maghemite 580-570 cm-1
4.2.7 Zero point charge (pHpzc)
Figure 4.15 and 4.16 illustrates the pHpzc of PAMCN and MAMCN. For the
determination of pH (pzc) of PAMCN and MAMCN mass titration method was used. In
this method various amounts of both nanocomposites were added to fresh distilled
water and resulting pH values were measured after 24 h of equilibration. Typical values
of nanocomposites/distilled water by weight were 0.01, 0.05, 0.1, 0.2, 0.3, 0.4, 0.5%,
1.0, 2.0, 3.0, 4.0 and 5.0% used under a nitrogen atmosphere. The containers of
88
nanocomposites/water were sealed and placed on a shaker for 24 h. The pHpzc of
PAMCN and MAMCN were found to be 7.2 and 7.3 (given in Table 4.5) respectively,
which were nearer to those reported for magnetic activated carbon by Mohan et al. 6.80
[205], Mao et al. 7.30 [182], Tu et al. 7.64 [254] and Zhang et al. 8.1 [258].
Figure: 4.15 Mass titration plot of PAMCN sample for pHpzc
Figure: 4.16 Mass titration plot of MAMCN sample for pHpzc
5
5.5
6
6.5
7
7.5
0 1 2 3 4 5 6
Fin
al p
H
Mass (%)
6
6.5
7
7.5
0 2 4 6
Fin
al p
H
Mass (%)
89
4.2.8 pH of nanocomposites slurry
The pH of the PAMCN and MAMCN solutions were determined and are given in Table
4.5. As the removal of FQs from aqueous solutions is mostly dependent on pH of
adsorbents. The pH of both PAMCN and MAMCN (pH = 7) samples were almost same
as reported Mohan et al. [205] and Mao et al. [182].
4.2.9 Ash and moisture content of nanocomposites
The values of ash and moisture content obtained from PAMCN and MAMCN are given
in Table 4.5. The ash content is an inorganic matter in nature and may affect the
adsorptive capacity of the adsorbent in aqueous form. The values of percent ash content
of both nanocomposites are comparable with the one obtained from the physical
parameters of two novel magnetic adsorbents by Tu et al. [254] and Mohan et al. [205].
Moisture is an important factor for adsorbent and counts in adsorption process. The
moisture content usually lies in the capillaries and varies in size and diameter.
Table 4.5 Physical parameters of PAMCN and MAMCN samples
Sample Ash (%) Moisture (%) pH
pHpzc
PAMCN 18.45
3.00 6.8 7.2
MAMCN 17.32 2.65 6.9 7.3
4.3 Drug resistance developed by streptococci and staphylococci against FQs
The effluents were collected from FQs industry. Two types of bacteria streptococci and
staphylococci were detected in them. Through agar well diffusion method the drug
resistance was determined using two other antibiotics CIP and LEV as standards. As
these bacteria were already familiar with ENR and it was expected that ENR will not
exhibit any antimicrobial activity against these bacteria. The zone of inhibition created
90
by the selected antibiotics have been shown in Table 4.6. The data in table clearly
indicates that considerable drug resistance have been developed by the bacteria found
in industrial effluents. It was concluded that the release of antibiotics into water streams
leads to the development of drug resistance in bacteria and therefore they must
efficiently be removed from industrial effluents.
Table. 4.6. Zone of inhibition of selected antibiotics against bacteria found in FQs
industrial effluents.
Bacteria CIP (cm) LEV (cm) ENR (cm)
Streptococci 1.8125 1.7375 0.8375
Staphylococci 1.6750 1.635 0.6375
4.4 Batch adsorption studies
4.4.1 Giles Isotherms
The adsorption of FQs on the surface of PAMCN were studied using Giles isotherm
[258]. The Giles isotherm of the selected FQs antibiotics (CIP, LEV and ENR) on
PAMCN are shown in Figures 4.17, 4.22 and 4.27 respectively, while that of MAMCN
are given in Figures 4.32, 4.37 and 4.42 respectively. The adsorption isotherm data of
FQs for PAMCN and MAMCN are given in Table 4.7 and 4.9 respectively. The
isotherms for these selected antibiotics are C type, previously reported by Mao et al.
[182], Balarak et al. [261], Nazari et al. [262], and Rivera-Utrilla et al. [145]
4.4.2 Langmuir Isotherm
Langmuir adsorption isotherm is based on the assumption that the maximum adsorption
corresponds to a saturated monolayer of solute molecules on the adsorbent surface, with
no interaction from lateral sides adsorbed molecules.
The linear form of the Langmuir isotherm is given by the following equation:
91
𝐶𝑒
𝑞𝑒=
1
𝐾𝐿𝑞𝑚+
𝐶𝑒
𝑞𝑚 ……….. 4.1
In relation (4.1), qe is the amount adsorbed (mgg-1), Ce is the equilibrium concentration
of the adsorbate in mgL-1, qm (mg/g) and KL (L/mg) are Langmuir constants related to
maximum adsorption capacity and energy of adsorption respectively. The Langmuir
plot of specific adsorption (Ce/qe) against equilibrium concentration (Ce) for the
adsorption of CIP, LEV and ENR onto PAMCN are shown in Figures 4.18, 4.23 and
4.28 respectively, while that of MAMCN are shown in Figures 4.33, 4.38 and 4.43
respectively. The Langmuir constants qm and KL were calculated from the slope and
intercept of the plots, and are given in Table 4.8 and 4.10. The lower adsorption
capacity of PAMCN are related to the blockage of micro pores by impregnation of
Fe3O4, as Fe3O4 has low surface area, which decreases the total surface area of the
PAMCN. The regression coefficient (R2) of Langmuir isotherm model for the
adsorption of all antibiotics onto PAMCN and MAMCN is nearly equal to 1.0
suggesting that the Langmuir model is applicable and fitted well for the adsorption of
these antibiotics molecules. The maximum sorption capability (qm) were obtained to
be in the subsequent order of: CIP>ENR>LEV for both nanocomposites. The value of
Langmuir constant KL (Lmg-1) for both PAMCN and MAMCN, for the adsorption of
FQs (CIP, LEV and ENR) Table 4.8 and 4.10 used in this study were less than 1.0,
indicating the favorable nature of adsorption equilibrium and the subsequent order is:
LEV>ENR>CIP for PAMCN and for CIP >LEV>ENR for MAMCN, was previously
reported by Zeng et al. [264], Tang et al. [265] and Khoshnamavand et al. [266].
4.4.3 Freundlich Isotherm
This is an empirical isotherm employed to illustrate the heterogeneous systems [267].
The logarithmic form of the Freundlich model is given by the following equation:
ln 𝑞𝑒 = ln 𝑘 + ln𝐶𝑒
𝑛 ………. 4.2
92
In relation (4.2), Ce is the equilibrium concentration (mgL-1), qe is the amount adsorbed
(mgg-1), k and n are Freundlich constants related to the adsorption capacity and
adsorption intensity respectively. The Freundlich constants K and 1/n can be calculated
from the slope and intercept of the plot obtained from plotting ln Ce vs ln qe. For CIP,
LEV and ENR adsorption on PAMCN, the Freundlich isotherm plots are given in
Figures 4.19, 4.24 and 4.29 respectively, while that of MAMCN are given in Figures
4.34, 4.39 and 4.44 respectively. The values of Freundlich constants and R2 are listed
in Table 4.8 and 4.10. The constant 1/n of Freundlich isotherm gives information about
the surface heterogeneity of PAMCN/MAMCN and its affinity for antibiotics
molecules. Larger value of 1/n (>1) shows the effectiveness of the sorbent materials.
All the values of 1/n were less than 1 previously reported by Zeng et al. [266], except
LEV adsorption onto PACMN, lower values of 1/n suggested strong interaction
between antibiotics molecules and both adsorbents [268]. The values of 1/n decreases
in the following sequence LEV>ENR>CIP, while the values of KF decreases in the
following sequence CIP>ENR >LEV for both nanocomposites.
4.4.4 Jovanovich Isotherm
Jovanovich isotherm is based on the same assumption as of the Langmuir model, but
this isotherm additionally illustrate the mechanical contacts between adsorbent and
adsorbate [269]. The linear form of Jovanovich isotherm is given as follows [270]:
ln 𝑞𝑒 = 𝑙𝑛𝑞𝑚𝑎𝑥 + 𝐾𝑗𝐶𝑒 ……… 4.3
In relation (4.3), qe is the amount adsorbed of adsorbate adsorbed on the surface of
adsorbent in (mgg-1), Ce is the equilibrium concentration of the adsorbate in mgL-1,
qmax (mgg-1) is the maximum uptake of adsorbate obtained from the plotting of ln qe vs
Ce and Kj is Jovanovich isotherm constant. The Jovanovich isotherm plot for the
adsorption of CIP, LEV and ENR onto PAMCN are shown in Figures 4.20, 4.25 and
93
4.30 respectively, while that of MAMCN are given in Figures 4.35, 4.40 and 4.45
respectively. The values of qmax and Kj were calculated from the slope and intercept
of the plots, and are given in Table 4.8 and 4.10. The values of qmax and Kj decreases
in the following order as ENR>CIP>LEV, while that of Kj decreases as
CIP>LEV>ENR for both nanocomposites.
4.4.5 Tempkin Isotherm
The linear form of Tempkin isotherm is applied in the following form.
𝑞𝑒 = 𝛽𝑙𝑛𝛼 + 𝛽𝑙𝑛𝐶𝑒 …… 4.4
Where β=RT/b, T is absolute temperature in kelvin (K), R is a general gas constant and
its value is 8.314 Jmol-1k-1, while b is related to heat of adsorption. A straight line is
obtained by plotting qe against ln Ce with slope β and intercept βlnα. For CIP, LEV and
ENR adsorption onto PAMCN and MAMCN the Tempkin isotherm model is given in
Figures 4.21, 4.26, 4.31, 4.36, 4.41 and 4.46. Different constants of Tempkin isotherm
are calculated from the slope and intercept. The results are listed in Table 4.8 and 4.10.
The Table 4.8 and 4.10 (adsorption isotherm parameters of PAMCN and MAMCN)
shows that the heat of adsorption (b) increases for PAMCN in the order CIP < LEV <
ENR, while that of MAMCN increases in the order ENR < CIP < LEV.
It is clear from different values in these Tables, that Langmuir adsorption isotherm
model best fitted the data than Freundlich and Tempkin isotherm models. The R2 value
for Langmuir model are also higher than the other two models. The same was
previously reported by Peng et al. [271] and Tang et al. [265].
94
Table 4.7. Adsorption Isotherm of CIP, LEV and ENR onto PAMCN
Adsorption Isotherm Temperature = 25oC (298K)
CIP
CIP
Co
mgL-1
Ce
mgL-
1
lnCe
mgL-1 qe
mgg-1 lnqq
mgg-1
Ce/qe
g L-1
LE
V
LE
V
Co
mgL-1 Ce
mgL-1
lnCe
mgL-1 qe
mgg-1 lnqq
mgg-1
Ce/qe
g L-1
20 7 1.95 16 2.80 0.44 10 5 1.61 6.25 1.83 0.8
40 18 2.90 28 3.33 0.64 20 9 2.20 13.6 2.62 0.7
60 28 3.33 40 3.70 0.70 30 18 2.90 15.0 2.70 1.2
80 47 4.10 41.2
5 3.72 1.13 40 26 3.25 17.5 2.86 1.5
100 66 4.20 42 3.74 1.58 50 36 3.58 17.5 2.86 2.0
120 82 4.40 47 3.85 1.74 60 45 3.80 18.8 2.93 2.4
EN
R
Co
mgL-1 Ce
mgL-1
lnCe
mgL-1 qe
mgg-1 lnqq
mgg-1
Ce/qe
g L-1
20 8 2.08 15.00 2.70 0.53
40 24 3.20 20.00 3.00 1.20
60 38 3.64 27.50 3.30 1.40
80 56 4.03 30.00 3.40 1.90
100 74 4.30 32.50 3.50 2.30
120 92 4.52 35.00 3.60 2.60
140 110 4.70 37.50 3.60 2.90
160 128 4.85 40.00 3.70 3.20
180 148 5.00 40.00 3.70 3.70
200 169 5.13 39.00 3.70 4.30
Figure: 4.17 Adsorption isotherm of CIP onto PAMCN
5
15
25
35
45
55
10 20 30 40 50 60 70 80 90 100 110 120 130
qe (m
gg
-1)
C (mg/L)
95
Figure: 4.18 Langmuir adsorption isotherm model of CIP onto PAMCN
Figure: 4.19 Freundlich adsorption isotherm model of CIP onto PAMCN
y = 0.0182x + 0.2827
R² = 0.985
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
2
0 10 20 30 40 50 60 70 80 90
Ce/
qe
Ce (mgL-1)
y = 0.398x + 2.1382
R² = 0.8988
2
2.5
3
3.5
4
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5
ln C
q
ln Ce
96
Figure: 4.20 Jovanovich adsorption isotherm model of CIP onto PAMCN
Figure: 4.21 Tempkin adsorption isotherm model of CIP onto PAMCN
y = 0.0111x + 3.0629R² = 0.6639
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
0 10 20 30 40 50 60 70 80 90
ln q
e
Ce (mgL-1)
y = 28.88x - 66.046
R² = 0.9849
5
10
15
20
25
30
35
40
45
2.5 2.7 2.9 3.1 3.3 3.5 3.7 3.9 4.1
qe
ln qe
97
Figure: 4.22 Adsorption isotherm of LEV onto PAMCN
Figure: 4.23 Langmuir adsorption isotherm model of LEV onto PAMCN
3
6
9
12
15
18
21
5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85
qe
(m
gg
-1)
C (mgL-1)
y = 0.0482x + 0.3307
R² = 0.9841
0
1
2
3
4
5
6
0 10 20 30 40 50 60 70 80
Ce/
qe
Ce (mg/L)
98
Figure: 4.24 Freundlich adsorption isotherm model of LEV onto PAMCN
Figure: 4.25 Jovanovich adsorption isotherm model of LEV onto PAMCN
y = 0.4854x + 1.1053R² = 0.9463
1
1.5
2
2.5
3
3.5
4
1 2 3 4 5
ln C
q
ln Ce
y = 0.0086x + 2.5641R² = 0.8993
1
1.5
2
2.5
3
3.5
0 5 10 15 20 25 30 35 40 45 50
ln q
e
Ce (mgL-1)
99
Figure: 4.26 Tempkin adsorption isotherm model of LEV onto PAMCN
Figure: 4.27 Adsorption isotherm of ENR onto PAMCN
y = 11.163x - 14.557
R² = 0.9818
0
5
10
15
20
25
1.5 1.8 2.1 2.4 2.7 3
qe
(mgg
-1)
ln qe (mgg-1)
5
10
15
20
25
30
35
40
45
10 30 50 70 90 110 130 150 170 190 210 230
qe(
mgg
-1)
C (mgL-1)
100
Figure: 4.28 Langmuir adsorption isotherm model of ENR onto PAMCN
Figure: 4.29 Freundlich adsorption isotherm model of ENR onto PAMCN
y = 0.0216x + 0.5733
R² = 0.9901
0.3
1.55
2.8
4.05
5.3
5 45 85 125 165 205
Ce/
qe
Ce (mgL-1)
y = 0.3662x + 1.9153
R² = 0.9806
2
2.5
3
3.5
4
2 2.5 3 3.5 4 4.5 5
ln q
e
ln Ce
101
Figure: 4.30 Jovanovich adsorption isotherm model of ENR onto PAMCN
Figure: 4.31 Tempkin adsorption isotherm model of ENR onto PAMCN
y = 0.0031x + 3.2446R² = 0.8858
2.5
2.7
2.9
3.1
3.3
3.5
3.7
3.9
0 20 40 60 80 100 120 140 160 180
lnq
e
Ce (mgL-1)
y = 9.1406x - 6.0978
R² = 0.9633
5
15
25
35
45
2 2.5 3 3.5 4 4.5 5
qe
(mgg
-1)
ln Ce
102
Table 4.8. Isotherm parameters of CIP, LEV and ENR onto PAMCN
Langmuir parameter Freundlich parameters Tempkin parameters Jovanovich parameters
An
tib
ioti
c
qmax
(mgg-1
)
kL
(Lmg-1
) R2
Kf
(mgg-1
)
1
𝑛 R2 β α b R2
qmax
(mgg-1
) KJ R2
CIP 55.00 0.065 0.99 137.4 0.34 0.9 25.9 5x 10 -3 84.4 0.98 21.40 0.0111 0.66
LEV 20.75 0.146 0.984 12.75 1.1053 0.94 11.20 0.76 221.94 0.98 13.00 0.0086 0.90
ENR 46.30 0.038 0.9901 82.30 0.37 0.98 9.2 1.80 271.1 0.97 25.70 0.0031 0.89
Table 4.9. Adsorption Isotherm of CIP, LEV and ENR onto MAMCN
Adsorption Isotherm Temperature = 25oC (298K)
CIP
CIP
Co
mgL-1 Ce
mgL-1
lnCe
mgL-1 qe
mgg-1 lnqq
mgg-1
Ce/qe
g L-1
LE
V
LE
V
Co
mgL-1 Ce
mgL-1
lnCe
mgL-1 qe
mgg-1 lnqq
mgg-1
Ce/qe
g L-1
20 5 1.60 18 2.90 0.27 10 3 1.10 7 1.95 0.43
40 14 2.60 33 3.50 0.42 20 6 1.80 18 2.90 0.34
60 24 3.20 45 3.80 0.53 30 15 2.70 19 2.94 0.79
80 42 3.40 48 3.90 0.88 40 23 3.10 21 3.04 1.10
100 61 4.10 49 3.90 1.25 50 31 3.40 24 3.20 1.30
120 79 4.40 51 3.93 1.55 60 40 3.70 25 3.22 1.60
EN
R
Co
mgL-1 Ce
mgL-1
lnCe
mgL-1 qe
mgg-1 lnqq
mgg-1
Ce/qe
g L-1
20 4 1.40 20 3.00 0.20
40 18 2.90 27.50 3.30 0.65
60 34 3.50 32.50 3.50 1.05
80 48 3.90 40.00 3.70 1.20
100 61 4.10 48.75 3.90 1.24
120 78 4.40 51.25 3.90 1.52
140 96 4.60 55.00 4.00 1.75
160 114 4.70 57.50 4.10 2.00
180 132 4.90 60.00 4.10 2.20
200 151 5.00 61.25 4.11 2.50
103
Figure: 4.32 Adsorption isotherm of CIP onto MAMCN
Figure: 4.33 Langmuir adsorption isotherm model of CIP onto MAMCN
5
15
25
35
45
55
65
10 30 50 70 90 110 130
qe
(mgg
-1)
C (mgL-1)
y = 0.0176x + 0.1571
R² = 0.9969
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
0 10 20 30 40 50 60 70 80 90
Ce/q
e (g
L-1)
Ce (mgL-1)
104
Figure: 4.34 Freundlich adsorption isotherm model of CIP onto MAMCN
Figure: 4.35 Jovanovich adsorption isotherm model of CIP onto MAMCN
y = 0.3649x + 2.4813
R² = 0.8554
2
2.5
3
3.5
4
4.5
1 1.5 2 2.5 3 3.5 4 4.5 5
ln q
e
ln Ce
y = 0.047x + 2.7256R² = 0.9522
2
2.2
2.4
2.6
2.8
3
3.2
3.4
3.6
3.8
4
0 5 10 15 20 25 30
ln q
e
Ce (mgL-1)
105
Figure: 4.36 Tempkin adsorption isotherm model of CIP onto MAMCN
Figure: 4.37 Adsorption isotherm of LEV onto MAMCN
y = 11.949x + 2.2314R² = 0.9054
5
15
25
35
45
55
65
1 1.5 2 2.5 3 3.5 4 4.5 5
qe
(mgg
-1)
ln Ce
0
5
10
15
20
25
30
5 15 25 35 45 55 65
q (
mgg
-1)
C (mgL-1)
106
Figure: 4.38 Langmuir adsorption isotherm model of LEV onto MAMCN
Figure: 4.39 Freundlich adsorption isotherm model of LEV onto MAMCN
y = 0.0317x + 0.3347R² = 0.9975
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
2
0 5 10 15 20 25 30 35 40 45
Ce/
qe (g
L-1
)
Ce (mgL-1)
y = 0.4198x + 1.7696R² = 0.791
1.5
1.7
1.9
2.1
2.3
2.5
2.7
2.9
3.1
3.3
3.5
0.5 1 1.5 2 2.5 3 3.5 4
ln q
e
ln Ce
107
Figure: 4.40 Jovanovich adsorption isotherm model of LEV onto MAMCN
Figure: 4.41 Tempkin adsorption isotherm model of LEV onto MAMCN
y = 0.0465x + 1.8458R² = 0.9736
1
1.5
2
2.5
3
3.5
4
0 5 10 15 20 25 30 35 40 45
ln q
e
Ce (mgL-1)
y = 6.0881x + 2.968R² = 0.8813
0
5
10
15
20
25
30
0 0.5 1 1.5 2 2.5 3 3.5 4
qe
(mgg
-1)
ln Ce
108
Figure: 4.42 Adsorption isotherm of ENR onto MAMCN
Figure: 4.43 Langmuir adsorption isotherm model of ENR onto MAMCN
5
15
25
35
45
55
65
15 35 55 75 95 115 135 155 175 195 215
qe
(mgg
-1)
C (mgL-1)
y = 0.0149x + 0.2901R² = 0.99
0
0.5
1
1.5
2
2.5
3
0 20 40 60 80 100 120 140 160
Ce/
qe
(gL
-1)
Ce (mgL-1)
109
Figure: 4.44 Freundlich adsorption isotherm model of ENR onto MAMCN
Figure: 4.45 Jovanovich adsorption isotherm model of ENR onto MAMCN
y = 0.338x + 2.4291R² = 0.961
2.5
2.7
2.9
3.1
3.3
3.5
3.7
3.9
4.1
4.3
1 1.5 2 2.5 3 3.5 4 4.5 5 5.5
ln q
e
ln Ce
y = 0.0082x + 3.1849R² = 0.9922
2.5
2.7
2.9
3.1
3.3
3.5
3.7
3.9
4.1
4.3
0 20 40 60 80 100 120
ln q
e
Ce (mgL-1)
110
Figure: 4.46 Tempkin adsorption isotherm model of ENR onto MAMCN
Table 4.10. Isotherm parameters of CIP, LEV and ENR onto MAMCN
Langmuir parameter Freundlich parameters Tempkin parameters Jovanovich parameters
An
tib
ioti
c
qmax
(mgg-1
)
kL
(Lmg-1
) R2
Kf
(mgg-1
)
1
𝑛 R2 β α b R2
qmax
(mgg-1
) KJ R2
CIP 56.82 0.112 0.997 12 0.37 0.86 11.95 1.2 207 0.91 15.33 0.047 0.95
LEV 31.5 0.095 0.998 5.9 0.42 0.79 6.09 1.63 407 0.882 6.333 0.047 0.97
ENR 67.11 0.0513 0.99 11.35 0.34 0.96 12.6 1.4 198 0.91 24.2 0.0082 0.99
y = 12.573x - 4.1609R² = 0.9126
5
15
25
35
45
55
65
1 1.5 2 2.5 3 3.5 4 4.5 5 5.5
qe
(mgg
-1)
ln Ce
111
4.5. Adsorption Kinetics
4.5.1 Effect of contact time
Contact time is an important parameter in adsorption process for an adsorbent to reach
equilibrium. For FQs under study (CIP, LEV and ENR) the contact time to reach
equilibrium are given in Figures 4.47, 4.52 and 4.57 respectively on the surface of
PAMCN, while for MAMCN, they are given in Figures 4.62, 4.67 and 4.72
respectively. The change in concentration with the passage of time for all FQs under
study at both PAMCN and MAMCN are given in Figures (4.48, 4.53 and 4.58) and
Figures (4.63, 4.68 and 4.73) respectively. It is clearer from these figures that in first
few minutes of adsorption the uptake of all FQs was very fast as at initial stage more
sites are available for adsorption of FQs from aqueous solutions on the surface of both
adsorbents. As time passes maximum adsorption sites are occupied by FQs molecules
and the rate of adsorption slows down. At the end the equilibrium time of adsorption
takes place due to saturation of PAMCN and MAMCN.
4.5.2. Adsorption kinetic models
The knowledge about adsorption kinetics plays a major role in the decontamination of
aqueous media. Therefore to evaluate various kinetic parameters, different kinetic
models were applied to the adsorption kinetic data.
4.5.2.1 Pseudo 1st and 2nd order kinetic models
The Lagergren first-order and pseudo-second-order models were used [162].
The pseudo 1st order was applied to express the sorption characteristics based on the
following relations;
ln(𝑞𝑒 − 𝑞𝑡) = ln 𝑞𝑒 − 𝐾1𝑡 …. 4.5
112
In relation (4.5), where, qt and qe (both are in mgg-1) are the amount of adsorbed
adsorbate at time 𝑡 and equilibrium, respectively, K1 (min-1) is the rate constant of
pseudo 1st order kinetic. The parameter K1 is useful to obtain the optimum operating
conditions for industrial-scale batch processes and provides valuable information about
the mechanism of adsorption and subsequently investigation of the controlling
mechanism of the biosorption process as either mass transfer or chemical reaction. The
value of K1 (min-1) can be calculated from the slope and qe calculated from the intercept
of the linear plot ln (qe-qt) vs t. The values of qe calculated (mgg-1), K1 (min-1) and R2
are given in Table 4.14 for PAMCN and Table 4.18 for MAMCN. The pseudo 1st order
kinetic plot for selected FQs antibiotics (CIP, LEV and ENR) onto the surface of
PAMCN are shown in Figures 4.49, 4.54 and 4.59 respectively, while for MAMCN in
Figures 4.64, 4.69 and 4.74 respectively.
The linear form of pseudo 2nd order kinetic models is given as;
t
qt=
1
k2qe2
+t
qe… … . . 4.6
In relation (4.6), K2 (gmg-1min-1) is the rate constant of adsorption of pseudo 2nd order
kinetic model, qt and qe are the amount of adsorbate (mgg-1) adsorbed at the surface of
adsorbent at time t and equilibrium time respectively. The values of qe and K2 were
calculated from the slopes and intercepts obtained of plotting t/qt vs t of the straight
line respectively, for the selected FQs antibiotics (CIP, LEV and ENR) onto PAMCN
in Figures 4.50, 4.55 and 4.60, while for MAMCN in Figures 4.65, 4.70 and 4.75
respectively. The kinetic parameters calculated from both the linear plots are listed in
Table 4.14 and 4.18 for PAMCN and MAMCN, respectively. From these Figures, it is
clear that pseudo 2nd order kinetic model fits better than pseudo 1st order kinetic model
113
to most of the adsorption data, since R2 is higher in the case of pseudo 2nd order kinetic
model than pseudo 1st order kinetic model for both adsorbents (Table 4.14 and 4.18).
The K1 (min-1) values for the initial concentrations of all selected antibiotics (CIP, LEV
and ENR) is less than unity on the surface of both PAMCN and MAMCN proved that
adsorption process show mixed mechanism (physiosorption and complexation). The
predicted equilibrium capacities (qe) calculated of CIP on the surface of PAMCN and
MAMCN at initial concentration of 40 and 80 mgL-1 are found to be (qe: 39.37 and
93.83 mgg-1 on PAMCN) and (qe: 39.4 and 93 mgg-1 on MAMCN) were different from
the experimental qe (26 mgg-1 and 43.75 mgg-1 for PAMCN). Similarly the predicted
equilibrium capacities of LEV (initial concentration of 20 and 40 mgL-1) and ENR
(initial concentration of 50 and 100 mgL-1) on the surface of PAMCN and MAMCN
are fond to be (LEV= 9.95 and 12.53 mgg-1 on PAMCN, ENR= 17 and 32 mgg-1 on
MAMCN) and (ENR= 27.10 and 50 mgg-1 on PAMCN, ENR= 27.10 and 50 mgg-1 on
MAMCN ) were similar in some cases and different in other cases to the experimental
qe (LEV= 13.75 and 18.75 mgg-1 on PAMCN, LEV= 19 and 32.50 mgg-1 on MAMCN)
and (ENR= 27.50 and 33.75 mgg-1 on PAMCN, ENR= 30 and 52.5 mgg-1 on MAMCN
). These results prove that adsorption process show a mixed mechanism. Furthermore,
from the comparisons of qexp with qcalculated for pseudo 1st and 2nd order kinetic models
suggest that the pseudo 2nd order is the best fitted model to the adsorption kinetic data
(qexperimental = equal to qcalculated). This implies that chemisorption controlled the
rate of reaction. The K2 values from pseudo 2nd order kinetics determine the adsorption
process occur in two steps. The first one is fast and reaches equilibrium quickly and the
second is a slower reaction that can continue for long time periods.
114
4.5.2.2 Intarparticle diffusion model
For the determination of rate controlling step of kinetic data the Weber and Morris
intraparticle diffusion model was employed [272, 273] and are given as;
𝑞𝑡 = 𝐾𝑑𝑖𝑓𝑓𝑡1
2⁄ + 𝐶 ……… 4.7
In relation (4.7), qt (mg g-1) is the quantity of sorbate molecules adsorbed at t time, Kdiff
is a rate constant of intraparticle diffusion model (mg g-1 min1/2) and C (mg g-1) is the
intercept, related to the thickness of the boundary layer. The intraparticle diffusion
model plot is obtained by plotting qt vs t1/2. If the regression qt vs t1/2 is linear and passes
through the origin of the plot, the only rate controlling step is intaparticle diffusion. To
the kinetic mechanism of FQs selected antibiotics (CIP LEV and ENR) adsorption from
aqueous solution onto PAMCN and MAMCN, qt was plotted vs t1/2 (Figures 4.51, 4.56
and 4.61 for PAMCN and Figures 4.66, 4.71 and 4.76 for MAMCN respectively).
These figures showed an initial curve followed by the linear relationship. The initial
curve of the plot for all FQs selected antibiotics can be explained by the boundary layer
effect while linear relationship of the plot corresponds to the intraparticle diffusion. The
deviation of linear plots from the origin clearly suggests that adsorption process of CIP,
LEV and ENR onto both adsorbents may have more than one controlling step [274-
276]. The kinetic parameters of intraparticle diffusion model for PAMCN and
MAMCN are listed in Table 4.14 and 4.18. The lower R2 values of intraparticle
diffusion models suggested that apart from intraparticle diffusion of FQs molecules into
the pores of both adsorbents some other factors are also responsible for the process also
adsorption.
115
Table 4.11. Adsorption kinetics of CIP 40 and 80 mgL-1 onto PAMCN
Temperature = 25oC (298K)
Shaking
time
(minutes)
CIP 40 mgL-1
CIP 80 mgL-1
Ce
(mg/L
qe
(mg/g)
ln (qe-
qt)
t/qt
(gmg-1min-1) t1/2
Ce
(mg/L
qe
(mg/g)
ln (qe-qt)
t/qt
(gmg-1min-1)
20 30 12.5 2.603 1.60 4.47 67 16.25 3.314 1.230
40 26 17.5 2.140 2.29 6.35 59 26.25 2.86 1.523
60 22 22.5 1.253 2.66 7.75 48 40 1.32 1.500
80 20 25 …… 3.20 8.90 46 42.25 0.405 1.893
100 21 24 0.693 4.16 10 45 43.75 …… 2.285
120 20 25 …… 4.80 10.6 45 43.75 …… 2.742
140 19 26 …… 5.40 … 45 43.75 …… 3.200
180 19 26 …… 6.92 … 45 43.75 …… 4.114
220 19 26 …… …… … 45 43.75 …… 5.030
240 19 26 …… …… … 45 43.75 …… 5.485
Figure: 4.47 Adsorption kinetics plot of CIP onto PAMCN
0
10
20
30
40
50
60
0 50 100 150 200 250 300
Am
ount
adso
rbed
(m
gg
-1)
Time (minutes)
■ 80 mgL-1
● 40 mgL-1
116
Figure: 4.48 Ct vs t plot of CIP onto PAMCN
Figure: 4.49 Pseudo 1st order kinetic plot of CIP onto PAMCN
0
10
20
30
40
50
60
70
80
90
0 50 100 150 200 250 300
Ct(m
gL
-1)
Time (minutes)
■ 80 mg/L
● 40 mg/L
40 mgL-1 = -0.0435x + 3.673
R² = 0.9603
80 mgL-1 = -0.0513x + 4.5415
R² = 0.9635
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
0 10 20 30 40 50 60 70 80 90
ln (
qe-
qt)
Time (minutes)
117
Figure: 4.50 Pseudo 2nd order kinetic plot of CIP onto PAMCN
Figure: 4.51 Intraparticle diffusion plot of CIP onto PAMCN
80 mg/L = 0.0202x + 0.4817
R² = 0.9821
40 mg/L = 0.0332x + 0.8069
R² = 0.9931
0
1
2
3
4
5
6
7
8
9
10
0 50 100 150 200 250 300
t/q
t
Time (minutes)
■ 40 mgL-1
● 80 mgL-1
10
15
20
25
30
35
40
45
50
4 5 6 7 8 9 10 11
qt (m
gg
-1)
t1/2 (minutes)
■ 80 mg/L
● 40 mg/L
118
Table 4.12. Adsorption kinetics of LEV 20 and 40 mgL-1 onto PAMCN
Temperature = 25oC (298K)
Shaking
time
(minutes)
LEV 40 mgL-1
LEV 40 mgL-1
Ce
(mg/L
qe
(mg/g)
ln (qe-
qt)
t/qt
(gmg-1min-1) t1/2
Ce
(mg/L
qe
(mg/g)
ln (qe-qt)
t/qt
(gmg-1min-1)
5 18 2.50 2.42 1.33 2.24 35 6.25 2.53 0.80
10 14 7.50 1.83 4.00 3.16 32 10.00 2.17 2.00
20 12 10.00 1.32 4.80 4.47 30 12.50 1.83 1.60
40 10 12.50 0.223 5.80 6.32 27 16.25 0.92 2.50
80 9 13.75 …… 7.27 8.94 25 18.75 …… 4.27
120 9 13.75 …… 8.72 10.9 25 18.75 …… 6.40
160 9 13.75 …… 10.18 12.6 25 18.75 …… 8.53
200 9 13.75 …… 13.09 14.1 25 18.75 …… 10.67
240 9 13.75 …… 16.00 15.5 25 18.75 …… 12.80
280 9 13.75 …… 17.45 16.7 25 18.75 …… 14.93
Figure: 4.52 Adsorption kinetics plot of LEV onto PAMCN
0
5
10
15
20
25
30
0 50 100 150 200 250 300
Am
ount
adso
rbed
(m
gg
-1)
Time (minutes)
119
Figure: 4.53 Ct vs t plot of LEV onto PAMCN
Figure: 4.54 Pseudo 1st order kinetic plot of LEV onto PAMCN
5
15
25
35
45
0 50 100 150 200 250 300
Ct(m
gL
-1)
Time (minutes)
20 mgL-1 = -0.0597x + 2.5673
R² = 0.9819
40 mgL-1 = -0.0444x + 2.6957
R² = 0.9928
0
0.5
1
1.5
2
2.5
3
3 8 13 18 23 28 33 38 43
ln (
qe-
qt)
Time (minutes)
120
Figure: 4.55 Pseudo 2nd order kinetic plot of LEV onto PAMCN
Figure: 4.56 Intraparticle diffusion plot of LEV onto PAMCN
20 mg/L = 0.052x + 2.8591
R² = 0.9731
40 mg/L = 0.0501x + 0.6612
R² = 0.9953
0
5
10
15
20
25
30
3 53 103 153 203 253 303
t/q
t (m
gg
-1m
in-1
)
Time (minutes)
▲ 20 mgL-1
● 40 mgL-1
0
5
10
15
20
25
0 1 2 3 4 5 6 7 8 9 10
qt(m
gg
-1)
t1/2
121
Table 4.13. Adsorption kinetics of ENR 50 and 100 mgL-1 onto PAMCN
Temperature = 25oC (298K)
Shaking
time
(minutes)
ENR 50 mgL-1
ENR 100 mgL-1
Ce
(mg/L
qe
(mg/g)
ln (qe-
qt)
t/qt
(gmg-1min-1) t1/2
Ce
(mg/L
qe
(mg/g)
ln (qe-qt)
t/qt
(gmg-1min-1)
5 45 6.25 3.05 0.80 2.24 86 17.50 2.80 0.30
10 38 15.00 2.50 0.66 3.16 82 22.50 2.42 0.44
20 34 20.00 2.00 1.00 4.47 77 28.75 1.60 0.70
40 30 25.00 0.92 1.60 6.32 75 31.25 0.92 1.30
60 28 27.50 …… 2.20 7.75 73 33.75 …… 1.80
80 28 27.50 …… 2.90 8.95 73 33.75 …… 2.40
120 28 27.50 …… 4.40 10.1 73 33.75 …… 3.55
140 28 27.50 …… 5.10 11.8 73 33.75 …… 4.15
160 28 27.50 …… 5.80 12.7 73 33.75 …… 4.74
180 28 27.50 …… 6.50 13.4 73 33.75 …… 5.33
200 28 27.50 …… 7.30 14.1 73 33.75 …… 5.92
Figure: 4.57 Adsorption kinetics plot of ENR onto PAMCN
0
10
20
30
40
0 40 80 120 160 200 240
qt(m
g/g
)
Time (minutes)
▲ 50 mgL-1
♦ 100 mgL-1
122
Figure: 4.58 Ct vs t plot of ENR onto PAMCN
Figure: 4.59 Pseudo 1st order kinetic plot of ENR onto PAMCN
20
30
40
50
60
70
80
90
100
0 20 40 60 80 100 120 140 160 180 200
Ct
(mgL
-1)
Time (minutes)
♦ 100 mgL-1
▲ 50 mgL-1
50 mg/L = -0.0671x + 3.3
R² = 0.9534
100 mg/L = -0.0803x + 3.21
R² = 0.9997
0.5
2
3.5
0 5 10 15 20 25
ln (
qe-
qt)
Time (minutes)
123
Figure: 4.60 Pseudo 2nd order kinetic plot of ENR onto PAMCN
Figure: 4.61 Intraparticle diffusion plot of ENR onto PAMCN
50 mg/L= 0.0342x + 0.3184
R² = 0.997
100 mg/L = 0.0288x + 0.1254
R² = 0.9998
0
2
4
6
8
0 50 100 150 200
t/q
t (g
mg
-1m
in-1
)
Time (minutes)
0
10
20
30
40
0 2.5 5 7.5 10
qt(m
g/g
)
t 1/2 (minutes)
♦ 100 mg/L▲ 50 mg/L
124
Table. 4.14. Adsorption kinetics parameters of CIP, LEV and ENR onto PAMCN
Table 4.15. Adsorption kinetics of CIP 40 and 80 mgL-1 onto MAMCN
Temperature = 25oC (298K)
Shaking
time
(minutes)
CIP 40 mgL-1
CIP 80 mgL-1
Ce
(mg/L
qe
(mg/g)
ln (qe-
qt)
t/qt
(gmg-1min-1) t1/2
Ce
(mg/
L
qe
(mg/g)
ln (qe-
qt)
t/qt
(gmg-1min-1)
5 26 17.5 2.53 0.29 2.24 64 20.0 3.40 0.250
10 24 20.0 2.30 0.50 3.20 56 30.0 3.00 0.333
20 22 22.5 2.01 0.88 4.50 48 40.0 2.30 0.500
30 20 25 1.60 1.20 5.50 44 45.0 1.60 0.666
40 18 27.5 0.92 1.45 6.30 41 49.0 …… 0.820
60 17 29.0 …… 2.05 7.80 40 50.0 …… 1.200
80 16 30.0 …… 4.00 …… 40 50.0 …… …… 100 16 30.0 …… 6.92 …… 40 50.0 …… …… 120 16 30.0 …… …… …… 40 50.0 …… …… 150 16 30.0 …… …… …… 40 50.0 …… ……
Adsorbent
(PAMCN)
Pseudo 1st order
kinetics Pseudo 2nd order kinetics
Intra particle diffusion
model
Antibiotic concentration
(mgL-1
)
qe
(mgg-1
)
K1
(min-1
) R2
qe
(mgg-1
)
K2
(gmg-
1min-1)
R2 Kdiff
(mg/gmin-1/2)
C R2
CIP
40
39.37 0.0513 0.96 30 0.0167
0.993
2.3
3.05
0.91
80 93.83 0.0435 0.96 49.50 0.0101 0.982 5.3 6.25
0.91
LEV
20
9.95 0.056 0.982 18.11 0.026 0.973 1.80 3.70 0.943
40
12.53 0.044 0.993 16.25 0.025 0.995 1.522 1.60 0.943
ENR
50
27.10 0.067 0.95 29.20 0.0037 0.997 2.35 15 0.88
100
….. 0.080 0.997 34.70 0.0066 0.999 2.97 3.92 0.88
125
Figure.4.62 Adsorption kinetics plot of CIP 40 and 80 mgL-1 onto MAMCN
Figure.4.63 Ct vs time plot of CIP 40 and 80 mgL-1 onto MAMCN
5
15
25
35
45
55
0 30 60 90 120 150 180
q (
mgg
-1)
Time (Minutes)
CIP40 CIP80 Log. (CIP40) Log. (CIP80)
0
10
20
30
40
50
60
70
80
0 20 40 60 80 100 120 140 160 180
Ce
(mgL
-1)
Time (minutes)
CIP40 CIP80
126
Figure.4.64 Pseudo 1st order kinetic plot of CIP 40 and 80 mgL-1 onto MAMCN
Figure.4.65 Pseudo 2nd order kinetic plot of CIP 40 and 80 mgL-1 onto MAMCN
40mgL-1 = -0.0361x + 2.6961R² = 0.994
80mgL-1 = -0.0715x + 3.7373R² = 0.9995
0.8
1.3
1.8
2.3
2.8
3.3
3.8
4.3
0 5 10 15 20 25 30 35 40 45
ln (
qe-
qt)
Time (minutes)
CIP40 CIP80
40mgL-1= 0.0316x + 0.1939R² = 0.9943
80mgL-1= 0.0171x + 0.1577R² = 0.9987
0
0.5
1
1.5
2
2.5
4 14 24 34 44 54 64 74
t/q
t (g
mg
-1m
in-1
)
Time (Minutes)
CIP40 CIP80
127
Figure.4.66 Intra particle diffusion plot of CIP 40 and CIP 80 mgL-1 onto MAMCN
Table 4.16. Adsorption kinetics of LEV 20 and 40 mgL-1 onto MAMCN
Temperature = 25oC (298K)
Shaking
time
(minutes)
LEV 20 mgL-1
LEV 40 mgL-1
Ce
(mg/L
qe
(mg/g)
ln (qe-
qt)
t/qt
(gmg-1min-1) t1/2
Ce
(mg/
L
qe
(mg/g)
ln (qe-qt)
t/qt
(gmg-1min-1)
5 14 7.50 2.44 0.66 2.24 31 11.25 3.06 0.440
10 12 10.00 2.12 1.00 3.16 27 16.25 2.80 0.615
15 10 12.50 2.01 1.20 3.90 24 20.00 2.53 0.750
20 8 15.00 1.40 1.33 4.50 22 22.50 2.35 0.888
25 6 17.50 1.10 1.43 5.00 18 27.50 1.60 0.900
40 5 19.00 …… 2.10 6.32 16 30.00 …… 1.333
60 5 19.00 …… 3.15 7.75 14 32.50 …… 1.850
80 5 19.00 …… …… 8.94 14 32.50 …… …… 100 5 19.00 …… …… 10.00 14 32.50 …… …… 120 5 19.00 …… …… 10.95 14 32.50 …… ……
0
10
20
30
40
50
60
2 3 4 5 6 7 8 9
qt
(mgg
-1)
t1/2
CIP40 CIP80
128
Figure.4.67 adsorption kinetics plot of LEV 20 and 40 mgL-1 onto MAMCN
Figure.4.68 Ct vs t plot of LEV 20 and 40 mgL-1 onto MAMCN
0
5
10
15
20
25
30
35
40
0 20 40 60 80 100 120 140
qe
(mgg
-1)
Time (Minutes)
LEV20 LEV40
0
5
10
15
20
25
30
35
40
45
50
0 20 40 60 80 100 120 140
Ce
(mgL
-1)
Time (Minutes)
LEV20 LEV40
129
Figure.4.69 Pseudo 1st order kinetic plot of LEV 20 and 40 mgL-1 onto MAMCN
Figure.4.70 Pseudo 2nd order kinetic plot of LEV 20 and 40 mgL-1 onto MAMCN
20mgL-1= -0.068x + 2.834R² = 0.9592
40mgL-1 = -0.0674x + 3.479R² = 0.9219
1
1.5
2
2.5
3
3.5
3 8 13 18 23 28
ln (
qe-
qt)
Time (Minutes)
LEV20 LEV40
20mgL-1 = 0.0431x + 0.4744R² = 0.9882
40mgL-1 = 0.0249x + 0.3455R² = 0.9934
0
0.5
1
1.5
2
2.5
3
0 10 20 30 40 50 60 70
t/q
t (g
mg
-1m
in-1
)
Time (Minutes)
LEV20 LEV40
130
Figure.4.71 Intra particle diffusion plot of LEV 20 and 40 mgL-1 onto MAMCN
Table 4.17. Adsorption kinetics of ENR 50 and 100 mgL-1 onto MAMCN
Temperature = 25oC (298K)
Shaking
time
(minutes)
ENR 50 mgL-1
ENR 100 mgL-1
Ce
(mg/L
qe
(mg/g)
ln (qe-
qt)
t/qt
(gmg-1min-1) t1/2
Ce
(mg/L
qe
(mg/g)
ln (qe-qt)
t/qt
(gmg-1min-1)
5 42 10.00 3.00 0.50 2.24 80 25.00 3.30 0.20
10 36 17.50 2.53 0.60 3.16 74 32.50 3.00 0.31
20 32 22.50 2.00 0.90 4.47 67 41.25 2.42 0.48
40 28 27.50 0.92 1.50 6.32 63 46.25 1.80 0.86
60 26 30.00 …… 2.00 7.75 60 50.00 …… 1.20
80 24 30.00 …… 2.70 8.95 58 52.50 …… 1.50
120 24 30.00 …… …… 10.1 58 52.50 …… …… 140 24 30.00 …… …… 11.8 58 52.50 …… …… 160 24 30.00 …… …… 12.7 58 52.50 …… …… 180 24 30.00 …… …… 13.4 58 52.50 …… …… 200 24 30.00 …… …… 14.1 58 52.50 …… ……
0
5
10
15
20
25
30
35
40
0 1 2 3 4 5 6 7 8 9 10
q (
mgg
-1)
t1/2
LEV20 LEV40
131
Figure: 4.72 Adsorption kinetics plot of ENR 50 and 100 mgL-1 onto MAMCN
Figure: 4.73 Ct vs t plot of ENR 50 and 100 mgL-1 onto MAMCN
0
10
20
30
40
50
60
0 50 100 150 200 250
qe
(mgg
-1)
Time (Minutes)
ENR50 ENR100
10
20
30
40
50
60
70
80
90
0 50 100 150 200
Ce
(mgL
-1)
Time (Minutes)
ENR50 ENR100
132
Figure: 4.74 Pseudo 1st order kinetics plot of ENR 50 and 100 mgL-1 onto MAMCN
Figure: 4.75 Pseudo 2nd order kinetics plot of ENR 50 and 100 mgL-1 onto MAMCN
50mgL-1= -0.0575x + 3.1909R² = 0.992
100mgL-1 = -0.0422x + 3.4217R² = 0.9718
0
0.5
1
1.5
2
2.5
3
3.5
4
0 5 10 15 20 25 30 35 40 45
ln (
qe-q
t)
Time (Minutes)
ENR50 ENR100
50mgL-1 = 0.0279x + 0.3471R² = 0.9983
100mgL-1 = 0.0174x + 0.1337R² = 0.9981
0
0.5
1
1.5
2
2.5
3
0 10 20 30 40 50 60 70 80 90
t/q
t (g
mg
-1m
in-1
)
Time (Minutes)
ENR50 ENR100
133
Figure: 4.76 Intra particle diffusion plot of ENR 50 and 100 mgL-1 onto MAMCN
Table. 4.18. Adsorption kinetics parameters of CIP, LEV and ENR onto MAMCN
0
10
20
30
40
50
60
70
2 4 6 8 10 12 14
qe
(mgg
-1)
t1/2
ENR50 ENR100
Adsorbent
(PAMCN)
Pseudo 1st order
kinetics
Pseudo 2nd order
kinetics
Intra particle diffusion
model
Antibiotic concentration
(mgL-1
)
qe
(mgg-1
)
K1
(min-1
) R2
qe
(mgg-1
)
K2
(gmg-
1min-1)
R2 Kdiff
(mg/gmin-1/2)
C R2
CIP
40
39.4 0.044 0.96 30.1 0.0410
0.993
2.3
3.10
0.91
80 93 0.051 0.96 50 0.0480 0.980 5.3 6.30
0.93
LEV
20
17.00 0.068 0.96 23.2 0.090 0.990 1.80 5.80 0.80
40
32.50 0.067 0.92 40.2 0.075 0.993 3.24 7.20 0.89
ENR
50
35.80 0.080 0.998 23.10 0.058 0.992 1.94 11.40 0.78
100
57.50 0.0130 0.998 34.70 0.042 0.970 2.82 24.80 0.85
134
4.6 Adsorption thermodynamics
The adsorption experiments for the determination of thermodynamics parameters were
carried out at 25, 40, and 60˚C with initial concentration of selected FQs antibiotics,
PAMCN mass of 0.05g and pH 7.
The Van’t Hoff equation is used to determine ΔH˚ and ΔS˚ of the adsorption process
[277].
ln k =∆S°
R−
∆H°
RT ……… 4.8
In equation 4.8, k is the distribution constant, ΔSo is entropy, ΔHo is enthalpy, T is the
temperature in Kelvin and R is a general gas constant. The value of k is determined
from the amount adsorbed and equilibrium concentration ( 𝑘 =𝑞𝑒
𝐶𝑒 ) [278], here qe is the
amount adsorbed and Ce is the FQs concentration at a different temperature. The Van’t
Hoff plots (Figures 4.77, 4.78 and 4.79 for PAMCN and Figures 4.80, 4.81 and 4.82
for MAMCN) were obtained by plotting ln 𝑘 vs 1
𝑇 (slope −
∆𝐻°
𝑅 and intercept
∆𝑆°
𝑅).
The values of standard free energy ΔG˚ were calculated using the equation:
∆G° = ∆H° − T∆S° ……… 4.9
The values of different thermodynamic parameters calculated from the above equations
for the selected FQs antibiotics are listed in Table 4.19. It is clear from the figures that
value of k increases with rise in temperature indicating an exothermic nature of FQs
adsorption [147], previously reported by Ahmad et al. [148], Otker et al. [250] . The
negative values of ΔG˚ at various temperatures specify the spontaneous nature of the
adsorption process and a high affinity of FQs molecules for both nanocomposites.
Similar observations was reported by Zhang et al. [279], Pavlovic et al. [280], Tang et
135
al. [265], Li et al. [274] and El-Shafey et al. [147]. The positive values of ΔSo shows
an increase in randomness at the solid-solution interface during the adsorption of FQs
onto the surface of nanocomposites.
The values of ∆𝐻° decreases in the following order LEV>ENR>>CIP for PAMCN,
while decreases in the sequence as ENR>LEV>CIP for MAMCN. The values of ΔSo
decreases in the following sequence CIP>LEV=ENR for PAMCN and in the order
ENR>LEV>CIP for MAMCN.
Figure: 4.77 Vant Hoff plot of CIP onto PAMCN
3.0 3.1 3.2 3.3
1.8
2.1
2.4
2.7
ln K
1/T x 10-3 (K)
136
Figure: 4.78 Van’t Hoff plot of LEV onto PAMCN
Figure: 4.79 Van’t Hoff plot of ENR onto PAMCN
0
0.3
0.6
0.9
1.2
1.5
0.0029 0.00295 0.003 0.00305 0.0031 0.00315 0.0032 0.00325 0.0033 0.00335 0.0034
ln K
1/T (K-1)
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
0.0028 0.0029 0.003 0.0031 0.0032 0.0033 0.0034
ln K
1/T (K-1)
137
Figure: 4.80 Van’t Hoff plot of CIP onto MAMCN
Figure: 4.81 Van’t Hoff plot of LEV onto MAMCN
0.05
0.25
0.45
0.65
0.85
1.05
1.25
1.45
0.00295 0.003 0.00305 0.0031 0.00315 0.0032 0.00325 0.0033 0.00335 0.0034 0.00345
ln k
1/T (K-1)
0
0.2
0.4
0.6
0.8
1
1.2
1.4
0.00295 0.003 0.00305 0.0031 0.00315 0.0032 0.00325 0.0033 0.00335 0.0034 0.00345
ln K
1/T (K-1)
138
Figure: 4.82 Van’t Hoff plot of ENR onto MAMCN
y = -3375x + 12.23R² = 0.9439
0
0.5
1
1.5
2
2.5
0.00295 0.003 0.00305 0.0031 0.00315 0.0032 0.00325 0.0033 0.00335 0.0034 0.00345
ln k
1/T (K-1)
139
Table. 4.19. Thermodynamic parameters of CIP, LEV and ENR adsorption onto PAMCN and MAMCN
PA
MC
N
CIP
Thermodynamic
Parameter
Temperature (°C)
LE
V
Temperature (°C)
EN
R
Temperature (°C)
25 40 60 25 40 60 25 40 60
ΔHo (kJmol-1) -20 ….. ….. -28.3 ….. ….. -23.60 ….. …..
ΔSo (Jmol-1.K-1) 82 ….. ….. 80 ….. ….. 80 ….. …..
ΔGo (kJmol-1) - 2.40 - 2.60 - 2.70 -2.50 -2.60 -3.00 - 2.40 -3.0 -3.30
MA
MC
N
CIP
Thermodynamic
Parameter
Temperature (°C)
LE
V
Temperature (°C)
EN
R
Temperature (°C)
25 40 60 25 40 60 25 40 60
ΔHo (kJmol-1) -21.6 ….. ….. -23.6 ….. ….. -28.1 ….. …..
ΔSo (Jmol-1.K-1) 75 ….. ….. 80 ….. ….. 101.7 ….. …..
ΔGo (kJmol-1) - 2.40 - 2.60 - 2.73 - 0.3 - 1.50 - 3.10 - 2.30 -3.8 -5.8
140
4.7 Effect of adsorbent dosage and pH on adsorption of FQs
Effect of PAMCN dose i.e. from 0.01g – 0.06g for the selected FQs antibiotics were
determined at pH 7 and 298K. The results of and MAMCN dose are given in Figures
(4.83, 4.84 and 4.85 for PAMCN and 4.86, 4.87 and 4.88 for MAMCN). It is clearer
from these figures that FQs removal increases rapidly with increase in sorbent dosage
(from 0.01g to 0.04g). The onward increase is very slow. The initial fast increase in
removal of FQs may be due to greater number of adsorption sites on the surface of both
nanocomposites. So, 0.04g dose of the both nanocomposites were selected and used in
sorption experiments.
Table 4.20. Effect of PAMCN dosage of on the removal of CIP, LEV and ENR
Adsorption temperature= 25oC ( 298K)
CIP
CIP
Co
mgL-1
Ce
mgL-1
Dose
g
% R
LE
V
LE
V
Co
mgL-1
Ce
mgL-1
Dose
g
% R
EN
R
EN
R
Co
mgL-1
Ce
mgL-1
Dose
g
% R
30 25 0.01 17 20 18 0.01 20 40 34 0.01 15
30 22 0.02 26 20 17 0.02 30 40 30 0.02 25
30 18 0.03 40 20 16 0.03 40 40 23 0.03 42
30 11 0.04 63 20 14 0.04 55 40 21 0.04 47
30 9 0.05 70 20 13 0.05 60 40 20 0.05 50
30 8 0.06 73 20 13 0.06 65 40 19 0.06 52
Table 4.21. Effect of MAMCN dosage of on the removal of CIP, LEV and ENR
Adsorption temperature= 25oC ( 298K)
CIP
CIP
Co
mgL-1
Ce
mgL-1
Dose
g
% R
LE
V
LE
V
Co
mgL-1
Ce
mgL-1
Dose
g
% R
EN
R
EN
R
Co
mgL-1
Ce
mgL-1
Dose
g
% R
30 22 0.01 27 20 15 0.01 25 40 29 0.01 28
30 18 0.02 40 20 12 0.02 40 40 26 0.02 35
30 14 0.03 53 20 10 0.03 50 40 20 0.03 50
30 10 0.04 67 20 7 0.04 65 40 17 0.04 58
30 7 0.05 76 20 6 0.05 70 40 14 0.05 65
30 6 0.06 80 20 5 0.06 75 40 12 0.06 70
141
Figure: 4.83 Effect of PAMCN dosage on CIP removal
Figure: 4.84 Effect of PAMCN dosage on LEV removal
17
26
40
63
7073
0
10
20
30
40
50
60
70
80
0.01 0.02 0.03 0.04 0.05 0.06
% R
emo
val
of
CIP
Mass of PAMCN (g)
20
30
40
55
60
65
0
10
20
30
40
50
60
70
0.01 0.02 0.03 0.04 0.05 0.06
% R
emo
val
of
LE
V
Mass of PAMCN (g)
142
Figure: 4.85 Effect of PAMCN dosage on ENR removal
Figure: 4.86 Effect of MAMCN dosage on CIP removal
15
25
42
4750
52
0
10
20
30
40
50
60
0.01 0.02 0.03 0.04 0.05 0.06
% R
emo
val
of
EN
R
Mass of PAMCN (g)
20
30
40
50
60
70
80
0.01 0.02 0.03 0.04 0.05 0.06
27
40
53
67
7680
% R
emo
val
MAMCN dose (g)
143
Figure: 4.87 Effect of MAMCN dosage on LEV removal
Figure: 4.88 Effect of MAMCN dosage on ENR removal
10
20
30
40
50
60
70
80
0.01 0.02 0.03 0.04 0.05 0.06
25
40
50
6570
75
% R
emo
val
of
LE
V
MAMCN dose (g)
10
20
30
40
50
60
70
0.01 0.02 0.03 0.04 0.05 0.06
28
35
50
58
6570
% R
emo
val
of
EN
R
MAMCN dose (g)
144
The influence of pH on the adsorption of FQs selected antibiotics (CIP, LEV and ENR)
onto PAMCN and MAMCN was investigated in the pH range of 3-11. It is clear from
all these Figures 4.89a, 4.90, 4.91 for PAMCN and Figures 4.92, 4.93, 4.94 onto
MACN an increase in the FQs adsorption were observed as pH increased from 3-7.
Between pH 3-7 FQs exists as cation FQs+ due to protonation of amine group (-NH-),
as pH increases the cationic form of FQ decreases and FQ are converted to FQs+-
(zwitter ion) in solution. When the pH of solution becomes alkaline a steady decrease
in FQs removal occurs, as anionic form (FQs-) dominates due to deprotonation of
carboxyl group (-COOH). This is mainly because the pH value of the solution affects
the surface charge of both nanocomposites and the form of FQs in the solution [182].
At low pH, the surface of both nancomposites is positively charged due to the
protonation reaction of N-atom on the surface of both nanocomposites. With increasing
pH, the surface of nanocomposites becomes negatively charged due to the
deprotonation reaction of –COOH group. In addition, the pH value affects the
ionization degree of the FQs molecules. At pH range from 6-7 the FQs molecules and
surface of nanocomposites are oppositely charged, due to which electrostatic forces of
attractions are formed, which is responsible for higher removal of FQs molecules. The
other reason for the higher removal of FQs molecules is π-π interaction between FQs
molecules and nanocomposites as the surfaces of both are planar. It is clear from
molecular structure of FQs molecules (CIP, LEV and ENR) that FQs molecules have a
benzene ring and two heterocyclic substituents. The presence of F atom on the benzene
ring is a strong electron withdrawing group and behave as π- electron accepter, the
presence of electron donating group on the surface of nanocomposites results in π-π
electron donor-accepter (EDA) interaction may also describe the sorption of FQs
molecules onto the surface of both adsorbents. Another reason for the removal of FQs
145
molecules may be the formation of H- bond between N-containing groups of FQs
molecules with –OH group of nanocomposites (Figure 4.89). The factor for highest
removal of FQs at acidic pH or at neutral pH may be due to cationic exchange [186].
Nanocomposites Fluoroquinolne molecule
Fluoroquinolne molecule Nanocomposites Fluoroquinolne molecule
Figure: 4.89 Mechanism of FQs molecule removal on the surface of nanocomposite
Table 4.22. Effect of pH on the removal of CIP, LEV and ENR onto PAMCN
Adsorption temperature= 25oC ( 298K)
CIP
C
IP
Co
mgL-1
Ce
mgL-1
pH
qe
mgg-1
LE
V
L
EV
Co
mgL-1
Ce
mgL-1
pH
qe
mgg-1
EN
R
E
NR
Co
mgL-1
Ce
mgL-1
Ph
qe
mgg-1
40 34 3 8 30 27 3 4 20 16 3 5
40 32 4 10 30 26 4 5 20 13 4 8.6
40 28 5 15 30 24 5 8 20 10 5 13
40 24 6 20 30 23 6 9 20 08 6 15
40 20 7 25 30 20 7 13 20 09 7 14
40 20 8 25 30 21 8 12 20 11 8 11
40 25 9 18 30 22 9 10 20 12 9 10
40 30 10 13 30 24 10 8 20 12 10 10
40 34 11 7.5 30 24 11 8 20 13 11 9
146
Figure: 4.89a Effect of pH on CIP removal onto PAMCN
Figure: 4.90 Effect of pH on LEV removal onto PAMCN
8
10
15
20
25 25
18
13
7.5
0
5
10
15
20
25
30
3 4 5 6 7 8 9 10 11
Am
ount
adso
rbed
(mgg
-1)
pH
3.75
5
7.5
8.75
12.5
11.25
10
7.5 7.5
2
4
6
8
10
12
14
3 4 5 6 7 8 9 10 11
Am
ount
adso
rbed
(m
gg
-1)
pH
147
Figure: 4.91 Effect of pH on ENR removal onto PAMCN
Table 4.23. Effect of pH on the removal of CIP, LEV and ENR onto MAMCN
Adsorption temperature= 25oC ( 298K)
CIP
C
IP
Co
mgL-1
Ce
mgL-1
pH
qe
mgg-1
LE
V
L
EV
Co
mgL-1
Ce
mgL-1
pH
qe
mgg-1
EN
R
E
NR
Co
mgL-1
Ce
mgL-1
pH
qe
mgg-1
40 30 3 12.5 30 24 3 7.5 20 14 3 7.5
40 28 4 15 30 22 4 10 20 11 4 11
40 23 5 21 30 19 5 14 20 7 5 16
40 20 6 25 30 17 6 15 20 6 6 17.5
40 16 7 30 30 15 7 19 20 8 7 15
40 19 8 26 30 16 8 17.5 20 10 8 12.5
40 22 9 22.5 30 19 9 14 20 11 9 11
40 28 10 15 30 20 10 12.5 20 13 10 9
40 31 11 11 30 23 11 9 20 13 11 9
5
8.6
13
15
14
11
10 10
9
0
2
4
6
8
10
12
14
16
3 4 5 6 7 8 9 10 11
Am
ount
adso
rbed
(m
gg
-1)
pH
148
Figure: 4.92 Effect of pH on CIP removal onto MAMCN
Figure: 4.93 Effect of pH on LEV removal onto MAMCN
12.5
15
21
25
30
26
22.5
15
11
5
10
15
20
25
30
35
40
45
3 4 5 6 7 8 9 10 11
q (
mgg
-1)
pH
7.5
10
14
15
19
17.5
14
12.5
9
5
7
9
11
13
15
17
19
21
23
25
3 4 5 6 7 8 9 10 11
q (
mgg
-1)
pH
149
Figure: 4.94 Effect of pH on ENR removal onto MAMCN
7.5
11
16
17.5
15
12.5
11
9 9
5
7
9
11
13
15
17
19
3 4 5 6 7 8 9 10 11
q (
mgg
-1)
pH
150
4.8 Effect of humic acid (HA) on FQs removal
Humic acid (HA) is common component of aqueous environment and often coexists
with antibiotics in wastewater reservoirs. Humic acid (HA) molecules consist of –
COOH, phenolic – OH and many other functional groups, which can interfere with the
interactions between FQs molecules and nanocomposites. Therefore, it is of great
significance to study the effect of HA on the adsorption process of FQs. The effect of
different concentrations of HA (0 - 80 mgL-1) on the adsorption of FQs from aqueous
solution on nanocomposites were studied and are given in Figures 4.95, 4.96 and 4.97
for PAMCN and in Figures 4.98, 4.99 and 4.100 for MAMCN. It is clearer from these
figures, that lower concentration of HA have a minor effect on the % removal of FQs.
While the adsorption capacity decreases with increasing HA concentration. This mainly
occurs because at low concentration, HA is adsorbed on the surface of nanocomposites
by hydrogen bonding, electrostatic attraction and π–π conjugation, and the groups on
the HA molecules can integrate with the FQs molecules. This is the same as increasing
the number of adsorption sites on the nanocomposites surface. When the HA
concentration exceeds a certain limit, the amount of free-moving HA molecules in the
solution increases [182, 281], the HA molecules form a soluble complex with FQs
molecules which blocks the pores on the surface of both PAMCN and MAMCN leading
to a decrease in the adsorption capacity of nanocomposites.
151
Table 4.24. Effect of Humic Acid (HA) on the removal of CIP, LEV and ENR onto PAMCN
Adsorption temperature= 25oC ( 298K)
CIP
C
IP
Co
mgL-1
Ce
mgL-1
Mass of HA
(mgL-1)
Percent
removal
LE
V
L
EV
Co
mgL-1
Ce
mgL-1
Mass of HA
(mgL-1)
Percent
removal
EN
R
E
NR
Co
mgL-1
Ce
mgL-1
Mass of HA
(mgL-1)
Percent
removal
30 13 0 57 30 11 0 63.33 30 10 0 66.66
30 16 20 47 30 13 20 57 30 13 20 56.66
30 16.5 30 45 30 14 30 53 30 14 30 53.33
30 18 40 40 30 15 40 50 30 16 40 46.66
30 18.5 50 38 30 15 50 50 30 17 50 43.33
30 19 60 37 30 16 60 47 30 18 60 40.00
30 16 70 47 30 17 70 43 30 18 70 40.00
30 18 80 40 30 17 80 43 30 18 80 40.00
152
Figure: 4.95 Effect of HA on CIP removal onto PAMCN
Figure: 4.96 Effect of HA on LEV removal onto PAMCN
46.6645
4038.33
36.66
46.66
40
0
10
20
30
40
50
60
20 30 40 50 60 70 80
% R
emo
val
of
CIP
Concentration of HA (mgL-1)
63.33
57
5350 50
47
43 43
0
10
20
30
40
50
60
70
0 20 30 40 50 60 70 80
% R
emo
val
of
LE
V
Mass of HA (mgL-1)
153
Figure: 4.97 Effect of HA on ENR removal onto PAMCN
66.66
56.66
53.33
46.66
43.33
40 40 40
20
30
40
50
60
70
80
0 20 30 40 50 60 70 80
% R
emo
val
of
EN
R
Mass of HA (mgL-1)
154
Table 4.25. Effect of Humic Acid (HA) on the removal of CIP, LEV and ENR onto MAMCN
Adsorption temperature= 25oC ( 298K)
CIP
C
IP
Co
mgL-1
Ce
mgL-1
Mass of HA
(mgL-1)
Percent
removal
LE
V
L
EV
Co
mgL-1
Ce
mgL-1
Mass of HA
(mgL-1)
Percent
removal
EN
R
E
NR
Co
mgL-1
Ce
mgL-1
Mass of HA
(mgL-1)
Percent
removal
30 9 0 70 30 10 0 67 30 8 0 73
30 11 20 63 30 11 20 63 30 14 20 53
30 12 30 60 30 13 30 57 30 15 30 50
30 14 40 53 30 13 40 57 30 15 40 50
30 15 50 50 30 13 50 57 30 15 50 50
30 15 60 50 30 13 60 57 30 16 60 47
30 15 70 50 30 14 70 53 30 16 70 47
30 15 80 50 30 14 80 53 30 16 80 47
155
Figure: 4.98 Effect of HA on CIP removal onto MAMCN
Figure: 4.99 Effect of HA on LEV removal onto MAMCN
0
10
20
30
40
50
60
70
0 20 30 40 50 60 70 80
7063
6053
50 50 50 50
% R
emo
val
of
CIP
Mass of HA (mgL-1)
0
10
20
30
40
50
60
70
0 20 30 40 50 60 70 80
6763
57 57 57 5753 53
% R
emo
val
of
LE
V
Mass of HA (mgL-1)
156
Figure: 4.100 Effect of HA on ENR removal onto MAMCN
4.9 Effect of ionic strength (Sodium Chloride) on FQs removal
For the determination of ionic strength, NaCl was used. The results of effect of ionic
strength are given in Figures 4.101, 4.102 and 4.103 for PAMCN and in Figures 4.104,
4.105 and 4.106 for MAMCN. The results obtained showed that ionic strength have
little effect on FQs removal. As the concentration of NaCl increases both FQs and NaCl
competes for the surface of nanocomposites, an increase in concentration of NaCl
weakens the interaction of FQs particles with nanocomposites due to the compression
of electrical double layer [182, 281] by Na+ and Cl-. Overall, it is concluded that NaCl
solution have a little effect on the removal of FQs from aqueous solution on the surface
of nanocomposites.
0
10
20
30
40
50
60
70
80
0 20 30 40 50 60 70 80
73
53 50 50 50 47 47 47
% R
emo
val
of
EN
R
Mass of HA (mgL-1)
157
Table 4.26. Effect of ionic strength (NaCl) on the removal of CIP, LEV and ENR onto PAMCN
Adsorption temperature= 25oC ( 298K)
CIP
C
IP
Co
mgL-1
Ce
mgL-1
Moles of
NaCl used
(molL-1)
Percent
removal
LE
V
L
EV
Co
mgL-1
Ce
mgL-1
Moles of
NaCl used
(molL-1)
Percent
removal
EN
R
E
NR
Co
mgL-1
Ce
mgL-1
Moles of
NaCl used
(molL-1)
Percent
removal
30 14 0 53 30 16 0 47 30 10 0 67
30 15 0.025 50 30 15 0.025 50 30 12 0.025 60
30 16 0.05 47 30 15 0.05 50 30 14 0.05 53
30 16.5 0.10 45 30 15 0.10 50 30 14 0.10 53
30 16.5 0.15 45 30 15 0.15 50 30 14 0.15 53
30 16 0.20 47 30 15 0.20 50 30 14 0.20 53
158
Figure: 4.101 Effect of NaCl on CIP removal onto PAMCN
Figure: 4.102 Effect of NaCl on LEV removal onto PAMCN
5047 46 45 47
0
10
20
30
40
50
60
70
80
90
100
0.025 0.05 0.1 0.15 0.2
% R
emo
val
of
CIP
Moles of NaCl (molL-1)
47
50 50 50 50 50
30
35
40
45
50
55
60
0 0.025 0.05 0.1 0.15 0.2
% R
emo
val
of
LE
V
Moles of NaCl (molL-1)
159
Figure: 4.103 Effect of NaCl on ENR removal onto PAMCN
67
60
53 53 53 53
0
10
20
30
40
50
60
70
80
0 0.025 0.05 0.1 0.15 0.2
% R
emo
val
Moles of NaCl (molL-1)
160
Table 4.27. Effect of ionic strength (NaCl) on the removal of CIP, LEV and ENR onto MAMCN
Adsorption temperature= 25oC ( 298K)
CIP
C
IP
Co
mgL-1
Ce
mgL-1
Moles of
NaCl used
(molL-1)
Percent
removal
LE
V
L
EV
Co
mgL-1
Ce
mgL-1
Moles of
NaCl used
(molL-1)
Percent
removal
EN
R
E
NR
Co
mgL-1
Ce
mgL-1
Moles of
NaCl used
(molL-1)
Percent
removal
30 10 0 67 30 11 0 63 30 9 0 70
30 12 0.025 50 30 12 0.025 60 30 11 0.025 63
30 12 0.05 47 30 13 0.05 57 30 11 0.05 63
30 12 0.10 45 30 13 0.10 57 30 11 0.10 63
30 12 0.15 45 30 13 0.15 57 30 11 0.15 63
30 12 0.20 47 30 13 0.20 57 30 11 0.20 63
161
Figure: 4.104 Effect of NaCl on CIP removal onto MAMCN
Figure: 4.105 Effect of NaCl on LEV removal onto MAMCN
0
10
20
30
40
50
60
70
0 0.025 0.05 0.1 0.15 0.2
67
5047 45 45 47
% R
emo
val
of
CIP
Moles of NaCl (molL-1)
30
35
40
45
50
55
60
65
0 0.025 0.05 0.1 0.15 0.2
6360
57 57 57 57
% R
emo
val
of
LE
V
Moles of NaCl (molL-1)
162
Figure: 4.106 Effect of NaCl on ENR removal onto MAMCN
4.10 Membranes and adsorption/membrane hybrid processes
4.10.1 Effect of selected FQs antibiotics (CIP, LEV and ENR) on permeate flux of
UF, NF and RO membranes
The concentration polarization and fouling by organic materials affect the efficiency of
membrane systems. The effects of concentration polarization are usually observed for
a very short period of time at the initial stages of the membrane systems, and after this,
passage of time flux remains persistent while a gradual curtailment in permeate flux is
observed in long-term applications due to fouling. Fouling of membrane systems may
be due to pore blocking, adsorption and cake formation [245, 282, 283]. In order to
check the effects of MCN on fouling, the pilot plant Figure 3.4 was connected with a
specially designed container equipped with electromagnet in series where MCN was
30
35
40
45
50
55
60
65
70
0 0.025 0.05 0.1 0.15 0.2
70
63 63 63 63 63
% R
emo
val
of
EN
R
Moles of NaCl (molL-1)
163
mixed with antibiotic solution and stirred for approximately one hour time. Membrane
parameters such as permeate flux, percent retention of the selected FQs antibiotics (CIP,
LEV and ENR) under study, and their effect on backwash time were determined.
The effect of selected FQs antibiotics (CIP, LEV and ENR) on permeate flux of
membranes (UF, NF and RO) are presented in Figures 4.107, 4.108, 4.109, 4.110,
4.111, 4.112, 4.113, 4.114, 4.115 and 4.116 for PAMCN, while, Figures 4.117, 4.118,
4.119, 4.120, 4.121, 4.122, 4.123, 4.124 and 4.125 are presenting the same parameters
for the second adsorbent, MAMCN. These figures clearly show a decline in permeate
flux in the initial stages for double distilled water through all the three selected
membranes, which is due to the interaction of the ions present in double distilled water
and may also be due to the intrinsic membrane resistance. In double distilled water
usually H+1 and OH-1 ions are present, which is clear from the conductance values of
distilled water (6.3 x 10-5 S. m-1) [161, 245, 246]. The permeate flux of all membranes
then reaches to a steady state after 20-30 minutes and are no longer affected with in
experimental cycle and condition. The molecular weight of selected FQs (CIP
=331.346gmol-1, LEV = 370.38gmol-1 and ENR = 359.401gmol-1) are smaller than
molecular weight cutoff (MWCO) of UF membrane. FQs molecules are expected to
pass freely from UF membrane and the permeate concentration (Cp) should be equal to
that of the bulk concentration (Cb) without addition of PMCN and MAMCN in hybrid
manner. However there were differences in the concentrations of antibiotics in the Cp
and Cb which was due to the fact that these antibiotics get adsorbed over the surface of
membrane resulting in blockage of the membrane pores thus effecting the permeate flux
across the membrane.
The molecules of selected antibiotics were larger enough to be stopped by the other two
membranes NF and RO. Thus in these cases high percent retention were expected and
164
consequently greater reduction in permeate flux. High percent retention were observed
and effect of selected antibiotics on permeate flux was also pronounced. RO membrane
system was more efficient in removal of selected antibiotics.
Table 4.28. Permeate flux with distilled water
UF
S.No Time
(minute)
Volume
(Liter)
J
(Lh-1m-2)
NF
Time
(minute) Volume
(Liter) J
(Lh-1m-2)
RO
Time
(minute) Volume
(Liter) J
(Lh-1m-2) 1 2.3 0.25 0.130 2.40 0.25 1.95 05.00 0.25 0.94
2 5.3 0.50 0.111 4.90 0.50 1.91 10.50 0.50 0.90
3 8.3 0.75 0.108 7.90 0.75 1.79 16.00 0.75 0.88
4 11.3 1.0 0.106 10.90 1.00 1.73 21.50 1.0 0.87
5 14.3 1.25 0.104 13.90 1.25 1.70 27.00 1.25 0.87
6 17.3 1.50 0.103 16.90 1.50 1.67 32.50 1.50 0.87
7 20.3 1.75 0.103 19.90 1.75 1.65 38.00 1.75 0.86
8 23.3 2.0 0.102 22.90 2.00 1.64 43.50 2.0 0.86
9 26.3 2.25 0.102 25.90 2.25 1.63 49.00 2.25 0.86
10 29.3 2.5 0.102 28.90 2.50 1.62 54.50 2.5 0.86
11 32.3 2.75 0.100 31.90 2.75 1.61 60.00 2.75 0.86
12 35.3 3.0 0.100 34.90 3.00 1.61 65.50 3.0 0.86
13 38.3 3.25 0.100 37.90 3.25 1.61 71.00 3.25 0.86
14 41.3 3.50 0.100 40.90 3.50 1.61 76.50 3.50 0.86
15 44.3 3.75 0.100 43.90 3.75 1.61 82.00 3.75 0.86
16 47.3 4.0 0.100 46.90 4.00 1.61 87.50 4.0 0.86
Table 4.29. Permeate flux of membranes with CIP 40mgL-1
UF
S.No Time
(minute) Volume (Liter)
J (Lh-1m-2)
NF
Time (minute)
Volume (Liter)
J (Lh-1m-2)
RO
Time (minute)
Volume (Liter)
J (Lh-1m-2)
1 3.0 0.25 0.111 2.40 0.25 1.56 05.30 0.25 0.88
2 6.5 0.50 0.092 4.90 0.50 1.45 11.00 0.50 0.86
3 9.5 0.75 0.089 7.90 0.75 1.34 17.00 0.75 0.83
4 12.5 1.0 0.088 10.90 1.00 1.30 23.00 1.0 0.82
5 15.5 1.25 0.088 13.90 1.25 1.27 29.00 1.25 0.81
6 18.5 1.50 0.087 16.90 1.50 1.25 35.00 1.50 0.80
7 21.5 1.75 0.087 19.90 1.75 1.24 41.00 1.75 0.80
8 24.5 2.0 0.087 22.90 2.00 1.23 47.00 2.0 0.79
9 27.5 2.25 0.087 25.90 2.25 1.22 53.00 2.25 0.79
10 30.5 2.5 0.086 28.90 2.50 1.21 59.00 2.5 0.79
11 33.5 2.75 0.086 31.90 2.75 1.21 65.00 2.75 0.79
12 36.5 3.0 0.086 34.90 3.00 1.21 71.00 3.0 0.79
13 39.5 3.25 0.086 37.90 3.25 1.21 77.00 3.25 0.79
14 42.5 3.50 0.086 40.90 3.50 1.21 83.00 3.50 0.79
15 45.5 3.75 0.086 43.90 3.75 1.21 89.00 3.75 0.79
16 48.5 4.0 0.086 46.90 4.00 1.21 95.00 4.0 0.79
165
Figure: 4.107 Permeate flux of UF with CIP 40 mgL-1
Figure: 4.108 Permeate flux of NF with CIP 40 mgL-1
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
J (L
m-2
h-1
)
Time (Hour)
♦ Distill water
▲UF CIP 40
0
0.5
1
1.5
2
2.5
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
J (L
m-2
h-1
)
Time (Hour)
Water CIP 40
166
Figure: 4.109 Permeate flux of RO with CIP 40 mgL-1
Table 4.30 Permeate flux of membranes with LEV 40mgL-1
UF
S.No Time
(minute)
Volume
(Liter)
J
(Lh-1m-2)
NF
Time
(minute)
Volume
(Liter)
J
(Lh-1m-2)
RO
Time
(minute)
Volume
(Liter)
J
(Lh-1m-2)
1 3.1 0.25 0.098 2.50 0.25 1.87 5.30 0.25 0.88
2 6.5 0.50 0.092 5.50 0.50 1.70 10.70 0.50 0.88
3 9.9 0.75 0.090 8.80 0.75 1.60 16.70 0.75 0.84
4 13.3 1.0 0.090 12.10 1.0 1.55 22.70 1.0 0.83
5 16.7 1.25 0.089 15.40 1.25 1.52 28.70 1.25 0.82
6 20.1 1.50 0.089 18.70 1.50 1.50 34.70 1.50 0.81
7 23.5 1.75 0.089 22.00 1.75 1.49 40.70 1.75 0.81
8 26.9 2.0 0.089 25.30 2.0 1.48 46.70 2.0 0.80
9 30.3 2.25 0.089 28.60 2.25 1.47 52.70 2.25 0.80
10 33.7 2.5 0.089 31.90 2.5 1.47 58.70 2.5 0.80
11 37.1 2.75 0.089 35.20 2.75 1.46 64.70 2.75 0.80
12 40.5 3.0 0.089 38.50 3.0 1.46 70.70 3.0 0.80
13 44.3 3.25 0.088 41.80 3.25 1.45 76.70 3.25 0.80
14 47.7 3.50 0.088 45.10 3.50 1.45 82.70 3.50 0.80
15 51.1 3.75 0.088 48.40 3.75 1.45 88.70 3.75 0.80
16 54.5 4.0 0.088 51.70 4.0 1.45 94.70 4.0 0.80
0.765
0.81
0.855
0.9
0.945
0.99
0.05 0.3 0.55 0.8 1.05 1.3 1.55
J (L
m-2
h-1
)
Time (Hour)
▲Water
● CIP
167
Figure: 4.110 Permeate flux of UF membrane with water and LEV 40 mgL-1
Figure: 4.111 Permeate flux of UF membrane with LEV 40mgL-1
0.03
0.05
0.07
0.09
0.11
0.13
0.15
0.01 0.11 0.21 0.31 0.41 0.51 0.61 0.71 0.81 0.91 1.01
J (L
h-1
m-2
)
Time (Hour)
■ Water
▲UF
0.05
0.06
0.07
0.08
0.09
0.1
0.11
0.12
0.13
0.14
0.15
0.03 0.13 0.23 0.33 0.43 0.53 0.63 0.73 0.83 0.93
J (L
h-1
m-2
)
Time (Hour)
168
Figure: 4.112 Permeate flux of NF membrane with LEV 40mgL-1
Figure: 4.113 Permeate flux of RO membrane with water and LEV 40 mgL-1
1
1.125
1.25
1.375
1.5
1.625
1.75
1.875
2
2.125
2.25
2.375
2.5
0.01 0.135 0.26 0.385 0.51 0.635 0.76 0.885
J (L
h-im
-2)
Time (Hour)
0.5
0.625
0.75
0.875
1
0.05 0.1755 0.301 0.4265 0.552 0.6775 0.803 0.9285 1.054 1.1795
J (L
h-1
m-2
)
Time (Hour)
169
Table 4.31. Permeate flux of membranes with ENR 40mgL-1
UF
S.No Time
(minute)
Volume
(Liter)
J
(Lh-1m-2)
NF
Time
(minute)
Volume
(Liter)
J
(Lh-1m-2)
RO
Time
(minute)
Volume
(Liter)
J
(Lh-1m-2)
1 2.5 0.25 0.120 2.45 0.25 1.95 05.50 0.25 0.85
2 6.00 0.50 0.0903 5.50 0.50 1.71 11.00 0.50 0.85
3 10.00 0.75 0.0860 8.50 0.75 1.63 17.00 0.75 0.83
4 14.00 1.0 0.0830 11.50 1.00 1.62 23.00 1.0 0.82
5 18.00 1.25 0.0820 14.50 1.25 1.61 29.00 1.25 0.81
6 22.00 1.50 0.0810 17.50 1.50 1.60 35.00 1.50 0.80
7 26.00 1.75 0.0800 20.50 1.75 1.60 41.00 1.75 0.80
8 30.00 2.0 0.0800 23.50 2.00 1.60 47.00 2.0 0.79
9 34.00 2.25 0.0790 26.50 2.25 1.59 53.00 2.25 0.79
10 38.00 2.5 0.0780 29.50 2.50 1.59 59.00 2.5 0.79
11 42.00 2.75 0.0780 32.50 2.75 1.59 65.00 2.75 0.79
12 46.00 3.0 0.0780 35.50 3.00 1.59 71.00 3.0 0.79
13 50.00 3.25 0.0780 38.50 3.25 1.59 77.00 3.25 0.79
14 54.00 3.50 0.0780 41.50 3.50 1.59 83.00 3.50 0.79
15 58.00 3.75 0.0780 44.50 3.75 1.59 89.00 3.75 0.79
16 62.00 4.0 0.0780 47.50 4.00 1.59 95.00 4.0 0.79
Figure: 4.114 Permeate flux of UF membrane with water and ENR 40 mgL-1
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
J (L
m-2
h-1
)
Time (Hour)
UF D. Water UF ENR 40
170
Figure: 4.115 Permeate flux of NF membrane with water and ENR 40 mgL-1
Figure: 4.116 Permeate flux of RO membrane with water and ENR 40 mgL-1
0.9
1.1
1.3
1.5
1.7
1.9
2.1
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
J (L
m-2
h-1
)
Time (Hour)
Water ENR40
0.78
0.8
0.82
0.84
0.86
0.88
0.9
0.92
0.94
0.96
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6
J (L
m-2
h-1
)
Time (Hour)
Water ENR 40
171
Table 4.32. Permeate flux with distilled water
UF
S.No Time
(minute) Volume (Liter)
J (Lh-1m-2)
NF
Time (minute)
Volum
e
(Liter)
J (Lh-1m-2)
RO
Time (minute)
Volume (Liter)
J (Lh-1m-2)
1 2.3 0.25 0.130 2.00 0.25 2.35 5.00 0.25 0.94
2 5.3 0.50 0.111 4.05 0.50 2.30 10.50 0.50 0.90
3 8.3 0.75 0.108 6.10 0.75 2.28 16.00 0.75 0.88
4 11.3 1.0 0.106 8.15 1.0 2.27 21.50 1.0 0.87
5 14.3 1.25 0.104 10.20 1.25 2.26 27.00 1.25 0.87
6 17.3 1.50 0.103 12.25 1.50 2.26 32.50 1.50 0.87
7 20.3 1.75 0.103 14.30 1.75 2.26 38.00 1.75 0.86
8 23.3 2.0 0.102 16.35 2.0 2.26 43.50 2.0 0.86
9 26.3 2.25 0.102 18.40 2.25 2.26 49.00 2.25 0.86
10 29.3 2.5 0.102 20.45 2.5 2.26 54.50 2.5 0.86
11 32.3 2.75 0.100 22.50 2.75 2.26 60.00 2.75 0.86
12 35.3 3.0 0.100 24.55 3.0 2.26 65.50 3.0 0.86
13 38.3 3.25 0.100 27.00 3.25 2.26 71.00 3.25 0.86
14 41.3 3.50 0.100 29.05 3.50 2.26 76.50 3.50 0.86
15 44.3 3.75 0.100 31.10 3.75 2.26 81.50 3.75 0.86
16 47.3 4.0 0.100 33.15 4.0 2.26 87.00 4.0 0.86
Table 4.33. Permeate flux of membranes with CIP 40mgL-1
UF
S.No Time
(minute)
Volume
(Liter)
J
(Lh-1m-2)
NF
Time
(minute)
Volume
(Liter)
J
(Lh-1m-2)
RO
Time
(minute)
Volume
(Liter)
J
(Lh-1m-2)
1 3.0 0.25 0.100 2.30 0.25 2.00 5.50 0.25 0.85
2 7.0 0.50 0.086 5.60 0.50 1.70 11.00 0.50 0.85
3 11.0 0.75 0.082 10.00 0.75 1.40 17.00 0.75 0.83
4 15.0 1.0 0.080 14.00 1.0 1.30 23.00 1.0 0.82
5 19.0 1.25 0.079 18.00 1.25 1.30 29.00 1.25 0.81
6 23.0 1.50 0.078 22.00 1.50 1.30 35.00 1.50 0.81
7 27.0 1.75 0.077 26.00 1.75 1.30 41.00 1.75 0.80 8 31.0 2.0 0.077 30.00 2.0 1.30 47.00 2.0 0.80 9 35.0 2.25 0.077 34.00 2.25 1.30 53.00 2.25 0.80 10 39.0 2.5 0.077 38.00 2.5 1.20 59.00 2.5 0.80 11 43.0 2.75 0.077 42.00 2.75 1.20 65.00 2.75 0.80 12 47.0 3.0 0.077 46.00 3.0 1.20 71.00 3.0 0.80 13 51.0 3.25 0.076 50.00 3.25 1.20 77.00 3.25 0.80 14 55.0 3.50 0.076 54.00 3.50 1.20 83.00 3.50 0.80 15 59.0 3.75 0.076 58.00 3.75 1.20 89.00 3.75 0.80 16 63.0 4.0 0.076 62.00 4.0 1.20 95.00 4.0 0.80
172
Figure: 4.117 Permeate flux of UF membrane with water and CIP 40 mgL-1
Figure: 4.118 Permeate flux of NF membrane with water and CIP 40 mgL-1
0.05
0.06
0.07
0.08
0.09
0.1
0.11
0.12
0.13
0.14
0 0.2 0.4 0.6 0.8 1 1.2
J (L
m-2h
-1)
Time (Hour)
Water UF CIP40
0
0.5
1
1.5
2
2.5
0 0.2 0.4 0.6 0.8 1 1.2
J (L
m-2
h-1
)
Time (Hour)
Water NF CIP40
173
Figure: 4.119 Permeate flux of RO membrane with water and CIP 40 mgL-1
Table 4.34. Permeate flux of membranes with LEV 40mgL-1
UF
S.No Time
(minute)
Volume
(Liter)
J
(Lh-1m-2)
NF
Time
(minute)
Volume
(Liter)
J
(Lh-1m-2)
RO
Time
(minute)
Volume
(Liter)
J
(Lh-1m-2)
1 3.0 0.25 0.10 2.50 0.25 1.87 5.30 0.25 0.88
2 6.0 0.50 0.10 5.50 0.50 1.70 10.70 0.50 0.88
3 9.5 0.75 0.095 8.80 0.75 1.60 16.70 0.75 0.84
4 13.0 1.0 0.092 12.10 1.0 1.55 22.70 1.0 0.83
5 17.0 1.25 0.090 15.40 1.25 1.52 28.70 1.25 0.82
6 21.0 1.50 0.090 18.70 1.50 1.50 34.70 1.50 0.81
7 25.0 1.75 0.090 22.00 1.75 1.49 40.70 1.75 0.81
8 29.0 2.0 0.080 25.30 2.0 1.48 46.70 2.0 0.80
9 33.0 2.25 0.080 28.60 2.25 1.47 52.70 2.25 0.80
10 37.0 2.5 0.080 31.90 2.5 1.47 58.70 2.5 0.80
11 41.0 2.75 0.080 35.20 2.75 1.46 64.70 2.75 0.80
12 45.0 3.0 0.080 38.50 3.0 1.46 70.70 3.0 0.80
13 49.0 3.25 0.080 41.80 3.25 1.45 76.70 3.25 0.80
14 53.0 3.50 0.080 45.10 3.50 1.45 82.70 3.50 0.80
15 57.0 3.75 0.080 48.40 3.75 1.45 88.70 3.75 0.80
16 61.0 4.0 0.080 51.70 4.0 1.45 94.70 4.0 0.80
0
0.2
0.4
0.6
0.8
1
1.2
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8
J (L
m-2
h-1
)
Time (Hour)
Water RO CIP40
174
Figure: 4.120 Permeate flux of UF membrane with LEV 40 mgL-1
Figure: 4.121 Permeate flux NF membrane with LEV 40 mgL-1
0.04
0.05
0.06
0.07
0.08
0.09
0.1
0.11
0.12
0.13
0.14
0 0.2 0.4 0.6 0.8 1 1.2
J (L
m-2
h-1
)
Time (Hour)
Water UF LEV40
0.5
1
1.5
2
2.5
3
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
J (L
m-2
h-1
)
Time (Hour)
Water NF LEV40
175
Figure: 4.122 Permeate flux of RO membrane with LEV 40 mgL-1
Table 4.35. Permeate flux of membranes with ENR 40mgL-1
UF
S.No Time
(minute)
Volume
(Liter)
J
(Lh-1m-2)
NF
Time
(minute)
Volume
(Liter)
J
(Lh-1m-2)
RO
Time
(minute)
Volume
(Liter)
J
(Lh-1m-2)
1 2.5 0.25 0.120 2.50 0.25 1.90 05.50 0.25 0.85
2 6.00 0.50 0.0903 6.50 0.50 1.50 11.00 0.50 0.85
3 10.00 0.75 0.0860 9.50 0.75 1.50 17.00 0.75 0.83
4 14.00 1.0 0.0830 12.50 1.00 1.50 23.00 1.0 0.82
5 18.00 1.25 0.0820 15.50 1.25 1.50 29.00 1.25 0.81
6 22.00 1.50 0.0810 18.50 1.50 1.50 35.00 1.50 0.80
7 26.00 1.75 0.0800 21.50 1.75 1.50 41.00 1.75 0.80
8 30.00 2.0 0.0800 24.50 2.00 1.50 47.00 2.0 0.79
9 34.00 2.25 0.0790 27.50 2.25 1.50 53.00 2.25 0.79
10 38.00 2.5 0.0780 30.50 2.50 1.50 59.00 2.5 0.79
11 42.00 2.75 0.0780 33.50 2.75 1.50 65.00 2.75 0.79
12 46.00 3.0 0.0780 38.50 3.00 1.50 71.00 3.0 0.79
13 50.00 3.25 0.0780 41.50 3.25 1.50 77.00 3.25 0.79
14 54.00 3.50 0.0780 44.50 3.50 1.50 83.00 3.50 0.79
15 58.00 3.75 0.0780 47.50 3.75 1.50 89.00 3.75 0.79
16 62.00 4.0 0.0780 50.50 4.00 1.50 95.00 4.0 0.79
0.5
0.55
0.6
0.65
0.7
0.75
0.8
0.85
0.9
0.95
1
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8
J (L
m-2
h-1
)
Time (Hour)
Water RO LEV40
176
Figure: 4.123 Permeate flux of UF membrane with ENR 40 mgL-1
Figure: 4.124 Permeate flux of NF membrane with ENR 40 mgL-1
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8
J (L
m-2
h-1
)
Time (Hour)
Water UF ENR40
0.5
1
1.5
2
2.5
3
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
J (L
m-2
h-1
)
Time (Hour)
Water NF ENR40
177
Figure: 4.125 Permeate flux of RO membrane with ENR 40 mgL-1
4.10.2 Improved permeate flux of UF, NF and RO membranes with PAMCN and
MAMCN in hybrid manner
Apart from low retention, flux reduction were observed with both PAMCN and
MAMCN. For PAMCN/UF and MAMCN/UF operations (Figures, 4.126, 4.129, 4.132
and 4.135, 4.138, 4.141 respectively), improved permeate flux were observed for the
selected FQs antibiotics molecules under study than UF membrane alone. In case of NF
and RO membranes the molecular weight of selected FQs antibiotics are larger than
MWCO of the membranes, therefore the molecules of FQs were almost 100% retained
which consequently effects the permeate flux. The effect of selected FQs antibiotics on
permeate fluxes of NF and RO membranes were more pronounced. When these
membranes were used in hybrid manner with PMCN and MAMCN reactors, quite
improved fluxes were observed for both PAMCN/NF and MAMCN/NF operations
(Figures, 4.127, 4.130, 4.133 and 4.136, 4.139, 4.142 respectively), and RO/PAMCN
0.6
0.65
0.7
0.75
0.8
0.85
0.9
0.95
1
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8
J (L
m-2
h-1
)
Time (Hour)
Water RO ENR40
178
and RO/MAMCN operations (Figures, 4.128, 4.131, 4.134 and 4.137, 4.140, 4.143
respectively). The differences in permeate fluxes were due to different sorption
capacities of the PAMCN and MAMCN for the rejection of foulants (CIP, LEV and
ENR) from aqueous media.
Table 4.36. Improved permeate flux with PAMCN/membrane
UF
S.No Time
(minute) Volume (Liter)
J (Lh-1m-2)
NF
Time (minute)
Volume (Liter)
J (Lh-1m-2)
RO
Time (minute)
Volume (Liter)
J (Lh-1m-2)
1 2.0 0.25 0.15 02.80 0.25 1.70 05.10 0.25 0.92
2 5.0 0.50 0.12 06.00 0.50 1.56 10.70 0.50 0.88
3 8.0 0.75 0.112 09.50 0.75 1.51 16.50 0.75 0.85
4 11.0 1.0 0.109 13.00 1.0 1.45 22.30 1.0 0.84
5 14.0 1.25 0.107 16.50 1.25 1.42 28.10 1.25 0.83
6 17.0 1.50 0.105 20.00 1.50 1.41 33.90 1.50 0.82
7 20.0 1.75 0.105 23.50 1.75 1.40 39.70 1.75 0.82
8 23.0 2.0 0.104 27.00 2.0 1.39 45.50 2.0 0.82
9 26.0 2.25 0.103 30.50 2.25 1.38 51.30 2.25 0.82
10 29.0 2.5 0.103 34.00 2.5 1.38 57.10 2.5 0.82
11 32.0 2.75 0.103 37.50 2.75 1.37 62.90 2.75 0.82
12 35.0 3.0 0.102 41.00 3.0 1.37 68.70 3.0 0.81
13 38.0 3.25 0.102 44.50 3.25 1.37 74.50 3.25 0.81
14 41.0 3.50 0.102 48.00 3.50 1.37 80.30 3.50 0.81
15 44.0 3.75 0.102 51.50 3.75 1.37 86.10 3.75 0.81
16 47.0 4.0 0.102 55.00 4.0 1.37 91.90 4.0 0.81
Figure: 4.126 Improved permeate flux of UF/PAMCN with CIP 40 mgL-1
0.08
0.09
0.1
0.11
0.12
0.13
0.14
0.15
0.16
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
J (L
h-1
m-2
)
Time (hour)
▲Water
● PAMCN/UF CIP 40
■ UF CIP 40
179
Figure: 4.127 Improved permeate flux of NF/PAMCN with CIP 40 mgL-1
Figure: 4.128 Improved permeate flux of RO/PAMCN with CIP 40 mgL-1
1
1.2
1.4
1.6
1.8
2
2.2
2.4
2.6
0 0.1 0.2 0.3 0.4 0.5 0.6
J (L
m-2
h-1
)
Time (Hour)
▲Distill water
♦ PAMCN/NF CIP 40
■ NF CIP 40
0.6
0.7
0.8
0.9
1
1.1
1.2
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6
J (L
m-2
h-1
)
Time (Hour)
■ Distill. water
▲RO CIP 40
♦ PAMCN/RO 40
180
Table 4.37. Improved permeate flux of membranes with PAMCN/membrane
UF
S.No Time
(minute) Volume (Liter)
J (Lh-1m-2)
NF
Time (minute)
Volume (Liter)
J (Lh-1m-2)
RO
Time (minute)
Volume (Liter)
J (Lh-1m-2)
1 2.3 0.25 0.13 2.30 0.25 2.03 5.10 0.25 0.92
2 5.3 0.50 0.11 4.70 0.50 2.00 10.60 0.50 0.89
3 8.3 0.75 0.10 7.10 0.75 1.98 16.30 0.75 0.87
4 11.3 1.0 0.10 9.90 1.0 1.89 22.00 1.0 0.85
5 14.3 1.25 0.10 12.70 1.25 1.85 27.80 1.25 0.84
6 17.3 1.50 0.10 15.50 1.50 1.81 33.60 1.50 0.84
7 20.3 1.75 0.10 18.30 1.75 1.79 39. 40 1.75 0.83
8 23.3 2.0 0.10 21.10 2.0 1.78 45. 20 2.0 0.83
9 26.3 2.25 0.10 23.90 2.25 1.76 51. 00 2.25 0.83
10 29.3 2.5 0.10 26.70 2.5 1.75 56. 80 2.5 0.83
11 32.3 2.75 0.10 29.50 2.75 1.75 62. 60 2.75 0.83
12 35.3 3.0 0.10 32.30 3.0 1.74 68. 40 3.0 0.82
13 38.3 3.25 0.10 35.10 3.25 1.74 74. 20 3.25 0.82
14 41.3 3.50 0.10 37.90 3.50 1.74 80. 00 3.50 0.82
15 44.3 3.75 0.10 40.70 3.75 1.74 85. 80 3.75 0.82
16 47.3 4.0 0.10 43.50 4.0 1.74 91. 60 4.0 0.82
Figure: 4.129 Improved permeate flux of PAMCN /UF membrane with LEV 40mgL-
1
0.04
0.065
0.09
0.115
0.14
0.01 0.26 0.51 0.76 1.01
J (L
h-1
m-2
)
Time (Hour)
181
Figure: 4.130 Improved permeate flux of NF/PAMCN hybrid membrane with LEV
40mgL-1
Figure: 4.131 Improved permeate flux of RO/PAMCN with LEV 40 mgL-1
1
1.25
1.5
1.75
2
2.25
2.5
0.02 0.27 0.52 0.77
J (L
h-1
m-2
)
Time (Hour)
0.7
0.75
0.8
0.85
0.9
0.95
1
0.07 0.32 0.57 0.82 1.07 1.32 1.57
J (L
h-1
m-2
)
Time (Hour)
182
Table 4.38 Improved permeate flux of PAMCN/membrane with ENR 40mgL-1
UF
S.No Time
(minute)
Volume
(Liter)
J
(Lh-1m-2)
NF
Time
(minute)
Volume
(Liter)
J
(Lh-1m-2)
RO
Time
(minute)
Volume
(Liter)
J
(Lh-1m-2)
1 2.3 0.25 0.130 2.30 0.25 2.04 05.30 0.25 0.885
2 5.00 0.50 0.120 5.30 0.50 1.80 10.60 0.50 0.884
3 8.00 0.75 0.110 8.30 0.75 1.70 16.60 0.75 0.85
4 11.00 1.0 0.110 11.30 1.00 1.65 22.60 1.0 0.84
5 14.00 1.25 0.110 14.30 1.25 1.63 28.60 1.25 0.82
6 17.00 1.50 0.110 17.30 1.50 1.62 34.60 1.50 0.81
7 20.00 1.75 0.110 20.30 1.75 1.61 40.60 1.75 0.81
8 23.00 2.0 0.100 23.30 2.00 1.61 46.60 2.0 0.81
9 26.00 2.25 0.100 26.30 2.25 1.60 52.60 2.25 0.80
10 29.00 2.5 0.100 29.30 2.50 1.60 58.60 2.5 0.80
11 32.00 2.75 0.100 32.30 2.75 1.60 64.60 2.75 0.80
12 35.00 3.0 0.100 35.30 3.00 1.60 70.60 3.0 0.80
13 38.00 3.25 0.100 38.30 3.25 1.60 76.60 3.25 0.80 14 41.00 3.50 0.100 41.30 3.50 1.60 82.60 3.50 0.80 15 44.00 3.75 0.100 44.30 3.75 1.60 88.60 3.75 0.80 16 47.00 4.0 0.100 47.30 4.00 1.60 94.60 4.0 0.80
Figure: 4.132 Improved permeate flux of PAMCN/UF membrane with water and
ENR 40 mgL-1
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0 0.2 0.4 0.6 0.8 1
J (L
m-2
h-1
)
Time (Hour)
UF D. Water UF ENR 40 PAMCN/UF ENR 40
183
Figure: 4.133 Improved permeate flux of PAMCN/NF membrane with water and
ENR40 mgL-1
Figure: 4.134 Improved permeate flux of PAMCN/RO membrane with water and
ENR 40 mgL-1
0.9
1.1
1.3
1.5
1.7
1.9
2.1
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
J (L
m-2
h-1
)
Time (Hour)
Water ENR40 PAMCN/NF ENR40
0.78
0.8
0.82
0.84
0.86
0.88
0.9
0.92
0.94
0.96
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6
J (L
m-2
h-1
)
Time (Hour)
Water ENR 40 PAMCN/RO ENR40
184
Table 4.39. Improved permeate flux with MAMCN/membranes CIP 40 mgL-1
UF
S.No Time
(minute) Volume (Liter)
J (Lh-1m-2)
NF
Time (minute)
Volume (Liter)
J (Lh-1m-2)
RO
Time (minute)
Volume (Liter)
J (Lh-1m-2)
1 2.4 0.25 0.125 2.30 0.25 1.90 05.00 0.25 0.92
2 5.0 0.50 0.120 5.20 0.50 1.80 10.50 0.50 0.89
3 8.0 0.75 0.110 8.00 0.75 1.80 16.50 0.75 0.87
4 11.0 1.0 0.110 11.00 1.0 1.70 21.50 1.0 0.85
5 14.0 1.25 0.110 14.00 1.25 1.70 26.50 1.25 0.84
6 17.0 1.50 0.110 17.00 1.50 1.60 31.50 1.50 0.84
7 20.0 1.75 0.100 20.00 1.75 1.60 36. 50 1.75 0.83
8 23.0 2.0 0.100 23.00 2.0 1.60 41. 50 2.0 0.83
9 26.0 2.25 0.100 26.00 2.25 1.60 46. 50 2.25 0.83
10 29.0 2.5 0.100 29.00 2.5 1.60 51. 50 2.5 0.83
11 32.0 2.75 0.100 32.00 2.75 1.60 56. 50 2.75 0.83
12 35.0 3.0 0.100 35.00 3.0 1.60 62. 00 3.0 0.82
13 38.0 3.25 0.100 38.00 3.25 1.60 68. 00 3.25 0.82
14 41.0 3.50 0.100 41.00 3.50 1.60 74. 00 3.50 0.82
15 44.0 3.75 0.100 44.00 3.75 1.60 80. 00 3.75 0.82
16 47.0 4.0 0.100 47.00 4.0 1.60 86. 00 4.0 0.82
Figure: 4.135 Improved permeate flux of MAMCN/UF membrane with CIP 40 mgL-
1
0.05
0.06
0.07
0.08
0.09
0.1
0.11
0.12
0.13
0.14
0 0.2 0.4 0.6 0.8 1 1.2
J (L
m-2
h-1
)
Time (Hour)
Water UF CIP40 MAMCN/UF CIP40
185
Figure: 4.136 Improved permeate flux of MAMCN/NF membrane with CIP 40 mgL-
1
Figure: 4.137 Improved permeate flux of MAMCN/RO membrane with CIP 40
mgL-1
0.1
0.6
1.1
1.6
2.1
2.6
0 0.2 0.4 0.6 0.8 1 1.2
J (L
m-2
h-1
)
Time (Hour)
Water NF CIP40 MAMCN/NF CIP40
0.03
0.23
0.43
0.63
0.83
1.03
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8
J (L
m-2
h-1
)
Time (Hour)
Water RO CIP40 MAMCN/RO CIP40
186
Table 4.40. Improved permeate flux of membranes with MAMCN/membrane
UF
S.No Time
(minute)
Volume
(Liter)
J
(Lh-1m-2)
NF
Time
(minute)
Volume
(Liter)
J
(Lh-1m-2)
RO
Time
(minute)
Volume
(Liter)
J
(Lh-1m-2)
1 2.5 0.25 0.12 2.40 0.25 1.95 5.00 0.25 0.94
2 5.0 0.50 0.12 4.80 0.50 1.95 10.40 0.50 0.90
3 8.0 0.75 0.11 7.40 0.75 1.90 16.40 0.75 0.86
4 11.0 1.0 0.11 10.00 1.0 1.87 22.30 1.0 0.84
5 14.0 1.25 0.11 13.00 1.25 1.80 28.30 1.25 0.83 6 18.0 1.50 0.10 16.00 1.50 1.76 34.30 1.50 0.82 7 22.0 1.75 0.10 19.00 1.75 1.73 40.30 1.75 0.81
8 26.0 2.0 0.09 22.00 2.0 1.70 46. 30 2.0 0.80
9 30.0 2.25 0.09 25.00 2.25 1.63 52. 30 2.25 0.80
10 34.0 2.5 0.09 28.00 2.5 1.63 58. 00 2.5 0.80
11 38.0 2.75 0.09 31.00 2.75 1.63 64. 00 2.75 0.80
12 42.0 3.0 0.09 34.00 3.0 1.63 70. 00 3.0 0.80
13 46.0 3.25 0.09 37.00 3.25 1.63 76. 00 3.25 0.80
14 50.0 3.50 0.09 40.00 3.50 1.63 82. 00 3.50 0.80
15 54.0 3.75 0.09 43.00 3.75 1.63 88. 00 3.75 0.80
16 58.0 4.0 0.09 47.00 4.0 1.63 94. 00 4.0 0.80
Figure: 4.138 Improved permeate flux of MAMCN/UF membrane with LEV 40
mgL-1
0.04
0.05
0.06
0.07
0.08
0.09
0.1
0.11
0.12
0.13
0.14
0 0.2 0.4 0.6 0.8 1 1.2
J (L
m-2
h-1
)
Time (Hour)
Water UF LEV40 MAMCN/UF LEV40
187
Figure: 4.139 Improved permeate flux of MAMCN/NF membrane with LEV 40
mgL-1
Figure: 4.140 Improved permeate flux of MAMCN/RO membrane with LEV 40
mgL-1
0.5
1
1.5
2
2.5
3
0.03 0.13 0.23 0.33 0.43 0.53 0.63 0.73 0.83
J (L
m-2
h-1
)
Time (Hour)
Water NF LEV40 MAMCN/NF LEVO40
0.5
0.6
0.7
0.8
0.9
1
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8
J (L
m-2
h-1
)
Time (Hour)
Water RO LEV40 MAMCN/RO LEV40
188
Table 4.41. Improved permeate flux of MAMCN/membrane with ENR 40mgL-1
UF
S.No Time
(minute)
Volume
(Liter)
J
(Lh-1m-2)
NF
Time
(minute)
Volume
(Liter)
J
(Lh-1m-2)
RO
Time
(minute)
Volume
(Liter)
J
(Lh-1m-2)
1 2.2 0.25 0.14 2.35 0.25 2.00 05.00 0.25 0.92
2 4.8 0.50 0.13 6.00 0.50 1.60 10.50 0.50 0.89
3 7.40 0.75 0.12 9.00 0.75 1.60 16.50 0.75 0.87
4 10.0 1.0 0.12 12.00 1.00 1.60 21.50 1.0 0.85
5 12.6 1.25 0.12 15.00 1.25 1.60 26.50 1.25 0.84
6 15.2 1.50 0.12 18.00 1.50 1.60 31.50 1.50 0.84
7 17.8 1.75 0.12 21.00 1.75 1.60 36. 50 1.75 0.83
8 20.4 2.0 0.12 24.00 2.00 1.60 41. 50 2.0 0.83
9 23.0 2.25 0.12 27.00 2.25 1.60 46. 50 2.25 0.83
10 25.6 2.5 0.12 30.00 2.50 1.60 51. 50 2.5 0.83
11 28.2 2.75 0.12 33.00 2.75 1.60 56. 50 2.75 0.83
12 30.8 3.0 0.11 36.00 3.00 1.60 62. 00 3.0 0.82
13 33.4 3.25 0.11 39.00 3.25 1.60 68. 00 3.25 0.82
14 36.4 3.50 0.11 42.00 3.50 1.60 74. 00 3.50 0.82
15 39.4 3.75 0.11 45.00 3.75 1.60 80. 00 3.75 0.82
16 42.4 4.0 0.11 48.00 4.00 1.60 86. 00 4.0 0.82
Figure: 4.141 Improved permeate flux of MAMCN/UF membrane with ENR 40
mgL-1
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
0.18
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8
J (L
m-2
h-1
)
Time (Hour)
Water UF ENR40 MAMCN/UF ENR40
189
Figure: 4.142 Improved permeate flux of MAMCN/NF membrane with ENR 40
mgL-1
Figure: 4.143 Improved permeate flux of MAMCN/RO membrane with ENR 40
mgL-1
0.5
1
1.5
2
2.5
3
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
J (L
m-2
h-1
)
Time (Hour)
Water NF ENR40 MAMCN/NF ENR40
0.6
0.65
0.7
0.75
0.8
0.85
0.9
0.95
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8
J (L
m-2
h-1
)
Time (Hour)
Water RO ENR40 MAMCN/RO ENR40
190
4.10.3 Percent retention/rejection of selected FQs antibiotics by membranes and
adsorption/membrane hybrid processes
First the selected FQs (CIP, LEV and ENR) antibiotics solutions of 40 mgL-1 were
passed through all the three selected membrane systems. The percent retention of
selected FQs antibiotics for each membrane was calculated individually. The MWCO
(molecular weight cut off) of the UF membrane was larger as compared to molecular
weight of selected FQs antibiotics (CIP =331.346gmol-1, LEV = 370.38gmol-1 and ENR
= 359.401gmol-1) [161, 244-246]. Therefore lower percent retention of CIP, LEV and
ENR were observed with naked UF membrane as well as PAMCN/UF and
MAMCN/UF processes (Figures, 4.144, 4.147, 4.150, 4.153, 4.156 and 4.159
respectively).
Definitely high percent retention (almost 100%) were expected from NF and RO
membrane systems as the MWCO were very small as compared to molecular weight of
the selected FQs antibiotics. About 96% retention were observed with NF membrane
system Figures 4.145, 4.148, 4.151, 4.154, 4.157 and 4.160. While 100% retention
were observed with RO system for the three FQs antibiotics Figures 4.146, 4.149,
4.152, 4.155, 4.158 and 4.161. When the membranes were used in hybrid manner with
PAMCN and MAMCN reactors, the percent retention RO membrane system in hybrid
manner were again 100% and efficiently removed CIP, LEV and ENR. The NF percent
retention went high up to 100% with PAMCN and MAMCN, while improvement in
UF percent retention were also observed with PAMCN and MAMCN but still was not
100% efficient which was due high MWCO of the UF membrane.
191
Table 4.42. Percent rejection of CIP 40mgL-1 with membrane only
UF
S.No Time
(minute)
C
(mgL-1)
Percent
rejection
NF
Time
(minute) C
(mgL-1) Percent
rejection
RO
Time
(minute) C
(mgL-1) Percent
rejection
1 3.0 32 20 03.00 2 95 05.30 0.00 100
2 6.5 36 10 06.50 3 93 11.00 0.00 100
3 9.5 38 5 10.50 3 93 17.00 0.00 100
4 12.5 38 5 14.50 3 93 23.00 0.00 100
5 15.5 38 5 18.50 3 93 29.00 0.00 100
6 18.5 38 5 22.50 3 93 35.00 0.00 100
7 21.5 38 5 26.50 3 93 41.00 0.00 100
8 24.5 38 5 30.50 3 93 47.00 0.00 100
9 27.5 38 5 34.50 3 93 53.00 0.00 100
10 30.5 38 5 38.50 3 93 59.00 0.00 100
11 33.5 38 5 42.50 3 93 65.00 0.00 100
12 36.5 38 5 46.50 3 93 71.00 0.00 100
13 39.5 38 5 50.50 3 93 77.00 0.00 100
14 42.5 38 5 54.50 3 93 83.00 0.00 100
15 45.5 38 5 58.50 3 93 89.00 0.00 100
16 48.5 38 5 62.50 3 93 95.00 0.00 100
Table 4.43. Percent rejection of CIP 40mgL-1 with PAMCN/membrane
UF
S.No Time
(minute)
C
(mgL-1)
Percent
rejection
NF
Time
(minute) C
(mgL-1) Percent
rejection
RO
Time
(minute) C
(mgL-1) Percent
rejection
1 3.0 20 50 02.80 0.00 100 05.10 0.00 100
2 6.5 21 48 06.00 0.00 100 10.70 0.00 100
3 9.5 22 45 09.50 0.00 100 16.50 0.00 100
4 12.5 25 38 13.00 0.00 100 22.30 0.00 100
5 15.5 26 35 16.50 0.00 100 28.10 0.00 100
6 18.5 27 34 20.00 0.00 100 33.90 0.00 100
7 21.5 28 30 23.50 0.00 100 39.70 0.00 100
8 24.5 28 30 27.00 0.00 100 45.50 0.00 100
9 27.5 28 30 30.50 0.00 100 51.30 0.00 100
10 30.5 28 30 34.00 0.00 100 57.10 0.00 100
11 33.5 28 30 37.50 0.00 100 62.90 0.00 100
12 36.5 28 30 41.00 0.00 100 68.70 0.00 100
13 39.5 28 30 44.50 0.00 100 74.50 0.00 100
14 42.5 28 30 48.00 0.00 100 80.30 0.00 100
15 45.5 28 30 51.50 0.00 100 86.10 0.00 100
16 48.5 28 30 55.00 0.00 100 91.90 0.00 100
192
Figure: 4.144 Percent rejection of CIP onto UF and PAMCN/UF
Figure: 4.145 Percent rejection of CIP onto NF and PAMCN/NF
0
10
20
30
40
50
60
70
80
90
100
0.2 0.7 1.2 1.7 2.2 2.7 3.2 3.7 4.2
% R
ejec
tio
n
Volume (L)
■MCN/UF
●UF
80
85
90
95
100
105
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5
% R
ejec
tio
n
Volume (L)
NF CIP40 PAMCN/NF CIP40
193
Figure: 4.146 Percent rejection of CIP onto RO and PAMCN/RO
Table. 4.44. Percent rejection of LEV 40mgL-1 with membrane only
UF
S.No Time
(minute)
C
(mgL-1)
Percent
rejection
NF
Time
(minute) C
(mgL-1) Percent
rejection
RO
Time
(minute) C
(mgL-1) Percent
rejection
1 3.1 36 10 2.30 1.5 96 5.30 0 100
2 6.5 37 8 4.70 2.0 95 10.70 0 100
3 9.9 39 3 7.10 2.5 94 16.70 0 100
4 13.3 39 3 9.90 3.0 93 22.70 0 100
5 16.7 39 3 12.70 3.0 93 28.70 0 100
6 20.1 39 3 15.50 3.0 93 34.70 0 100
7 23.5 39 3 18.30 3.0 93 40.70 0 100
8 26.9 39 3 21.10 3.0 93 46.70 0 100
9 30.3 39 3 23.90 3.0 93 52.70 0 100
10 33.7 39 3 26.70 3.0 93 58.70 0 100
11 37.1 39 3 29.50 3.0 93 64.70 0 100
12 40.5 39 3 32.30 3.0 93 70.70 0 100
13 44.3 39 3 35.10 3.0 93 76.70 0 100
14 47.7 39 3 37.90 3.0 93 82.70 0 100
15 51.1 39 3 40.70 3.0 93 88.70 0 100
16 54.5 39 3 43.50 3.0 93 94.70 0 100
0
20
40
60
80
100
120
0.25 0.5 0.75 1 1.25 1.5 1.75 2 2.25 2.5 2.75 3 3.25 3.5 3.75 4
% R
ejec
tio
n
Volume (L)
RO CIP 40 RO/PAMCN
194
Table. 4.45. Percent rejection of LEV 40mgL-1 with PAMCN/membrane
UF
S.No Time
(minute)
C
(mgL-1)
Percent
rejection
NF
Time
(minute) C
(mgL-1) Percent
rejection
RO
Time
(minute) C
(mgL-1) Percent
rejection
1 2.3 20 50 2.30 0 100 5.30 0 100
2 5.3 21 48 4.70 0 100 10.70 0 100
3 8.3 22 45 7.10 0 100 16.70 0 100
4 11.3 23 44 9.90 0 100 22.70 0 100
5 14.3 25 38 12.70 0 100 28.70 0 100
6 17.3 27 34 15.50 0 100 34.70 0 100
7 20.3 27 34 18.30 0 100 40.70 0 100
8 23.3 27 34 21.10 0 100 46.70 0 100
9 26.3 27 34 23.90 0 100 52.70 0 100
10 29.3 27 34 26.70 0 100 58.70 0 100
11 32.3 27 34 29.50 0 100 64.70 0 100
12 35.3 27 34 32.30 0 100 70.70 0 100
13 38.3 27 34 35.10 0 100 76.70 0 100
14 41.3 27 34 37.90 0 100 82.70 0 100
15 44.3 27 34 40.70 0 100 88.70 0 100
16 47.3 27 34 43.50 0 100 94.70 0 100
Figure: 4.147 Percent rejection of LEV onto UF and PAMCN/UF
0
20
40
60
80
0.2 0.7 1.2 1.7 2.2 2.7 3.2 3.7 4.2
% R
eten
tion
Volume (L)
195
Figure: 4.148 Percent rejection of LEV onto NF and PAMCN/NF
Figure: 4.149 Percent rejection of LEV onto RO and PAMCN/RO
90
92.5
95
97.5
100
102.5
105
0.2 0.7 1.2 1.7 2.2 2.7 3.2 3.7 4.2
% R
eten
tio
n
Volume (L)
▲ NF/PAMCN
■ NF
0
20
40
60
80
100
120
0.25 0.5 0.75 1 1.25 1.5 1.75 2 2.25 2.5 2.75 3 3.25 3.5 3.75 4
% R
ejec
tio
n
Volume (L)
RO LEV 40 RO/PAMCN
196
Table 4.46. Percent rejection of ENR 40mgL-1 with membrane only
UF
S.No Time
(minute) C
(mgL-1) Percent rejection
NF
Time (minute)
C (mgL-1)
Percent rejection
RO
Time (minute)
C (mgL-1)
Percent rejection
1 2.5 33 18 2.45 2.0 95 05.50 0.00 100
2 6.00 34 15 5.50 2.5 94 11.00 0.00 100
3 10.00 35 13 8.50 3.0 94 17.00 0.00 100
4 14.00 36 10 11.50 3.0 94 23.00 0.00 100
5 18.00 36 10 14.50 3.0 94 29.00 0.00 100
6 22.00 36 10 17.50 3.0 94 35.00 0.00 100
7 26.00 36 10 20.50 3.0 94 41.00 0.00 100
8 30.00 36 10 23.50 3.0 94 47.00 0.00 100
9 34.00 36 10 26.50 3.0 94 53.00 0.00 100
10 38.00 36 10 29.50 3.0 94 59.00 0.00 100
11 42.00 36 10 32.50 3.0 94 65.00 0.00 100
12 46.00 36 10 35.50 3.0 94 71.00 0.00 100
13 50.00 36 10 38.50 3.0 94 77.00 0.00 100
14 54.00 36 10 41.50 3.0 94 83.00 0.00 100
15 58.00 36 10 44.50 3.0 94 89.00 0.00 100
16 62.00 36 10 47.50 3.0 94 95.00 0.00 100
Table 4.47. Percent rejection of ENR 40mgL-1 with PAMCN/membrane
UF
S.No Time
(minute)
C
(mgL-1)
Percent
rejection
NF
Time
(minute) C
(mgL-1) Percent
rejection
RO
Time
(minute) C
(mgL-1) Percent
rejection
1 2.3 18 55 2.30 0.00 100 05.30 0.00 100
2 5.00 19 53 5.30 0.00 100 10.60 0.00 100
3 8.00 20 50 8.30 0.00 100 16.60 0.00 100
4 11.00 22 45 11.30 0.00 100 22.60 0.00 100
5 14.00 24 40 14.30 0.00 100 28.60 0.00 100
6 17.00 25 39 17.30 0.00 100 34.60 0.00 100
7 20.00 25 39 20.30 0.00 100 40.60 0.00 100
8 23.00 25 39 23.30 0.00 100 46.60 0.00 100
9 26.00 25 39 26.30 0.00 100 52.60 0.00 100
10 29.00 25 39 29.30 0.00 100 58.60 0.00 100
11 32.00 25 39 32.30 0.00 100 64.60 0.00 100
12 35.00 25 39 35.30 0.00 100 70.60 0.00 100
13 38.00 25 39 38.30 0.00 100 76.60 0.00 100
14 41.00 25 39 41.30 0.00 100 82.60 0.00 100
15 44.00 25 39 44.30 0.00 100 88.60 0.00 100
16 47.00 25 39 47.30 0.00 100 94.60 0.00 100
197
Figure: 4.150 Percent rejection of ENR 40mgL-1 onto UF and PAMCN/UF
Figure: 4.151 Percent rejection of ENR 40mgL-1 onto NF and PAMCN/NF
5
15
25
35
45
55
65
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5
% R
ejec
tio
n
Volume (L)
UF PAMCN/UF
85
87
89
91
93
95
97
99
101
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5
% R
ejec
tio
n
Volume (L)
NF PAMCN/NF
198
Figure: 4.152 Percent rejection of ENR 40mgL-1 onto RO and PAMCN/RO
Table 4.48. Percent rejection of CIP 40mgL-1 with membrane only
UF
S.No Time
(minute)
C
(mgL-1)
Percent
rejection
NF
Time
(minute) C
(mgL-1) Percent
rejection
RO
Time
(minute) C
(mgL-1) Percent
rejection
1 3.0 36 10 2.30 1.5 96 5.30 0 100
2 7.0 37 8 5.60 2.0 95 10.70 0 100
3 11.0 39 3 10.00 2.5 94 16.70 0 100
4 15.0 39 3 14.00 3.0 93 22.70 0 100
5 19.0 39 3 18.00 3.0 93 28.70 0 100
6 23.0 39 3 22.00 3.0 93 34.70 0 100
7 27.0 39 3 26.00 3.0 93 40.70 0 100
8 31.0 39 3 30.00 3.0 93 46.70 0 100
9 35.0 39 3 34.00 3.0 93 52.70 0 100
10 39.0 39 3 38.00 3.0 93 58.70 0 100
11 43.0 39 3 42.00 3.0 93 64.70 0 100
12 47.0 39 3 46.00 3.0 93 70.70 0 100
13 51.0 39 3 50.00 3.0 93 76.70 0 100
14 55.0 39 3 54.00 3.0 93 82.70 0 100
15 59.0 39 3 58.00 3.0 93 88.70 0 100
16 63.0 39 3 62.00 3.0 93 94.70 0 100
20
30
40
50
60
70
80
90
100
110
120
0.25 0.5 0.75 1 1.25 1.5 1.75 2 2.25 2.5 2.75 3 3.25 3.5 3.75 4
% R
ejec
tio
n
Volume (L)
RO ENR 40 RO/PAMCN
199
Table 4.49. Percent rejection of CIP 40mgL-1 with MAMCN/membrane
UF
S.No Time
(minute)
C
(mgL-1)
Percent
rejection
NF
Time
(minute) C
(mgL-1) Percent
rejection
RO
Time
(minute) C
(mgL-1) Percent
rejection
1 2.4 18 55 2.30 0 100 05.00 0 100
2 5.0 19 53 5.20 0 100 10.50 0 100
3 8.0 20 50 8.00 0 100 16.50 0 100
4 11.0 23 44 11.00 0 100 21.50 0 100
5 14.0 23 44 14.00 0 100 26.50 0 100
6 17.0 23 44 17.00 0 100 31.50 0 100
7 20.0 23 44 20.00 0 100 36. 50 0 100
8 23.0 23 44 23.00 0 100 41. 50 0 100
9 26.0 23 44 26.00 0 100 46. 50 0 100
10 29.0 23 44 29.00 0 100 51. 50 0 100
11 32.0 23 44 32.00 0 100 56. 50 0 100
12 35.0 23 44 35.00 0 100 62. 00 0 100
13 38.0 23 44 38.00 0 100 68. 00 0 100
14 41.0 23 44 41.00 0 100 74. 00 0 100
15 44.0 23 44 44.00 0 100 80. 00 0 100
16 47.0 23 44 47.00 0 100 86. 00 0 100
Figure: 4.153 Percent rejection of CIP 40mgL-1 onto UF and MAMCN/UF
0
10
20
30
40
50
60
70
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5
% R
ejec
tio
n
Volume (L)
UF CIP40 MAMCN/UF CIP40
200
Figure: 4.154 Percent rejection of CIP 40mgL-1 onto NF and MAMCN/NF
Figure: 4.155 Percent rejection of CIP 40mgL-1 onto RO and MAMCN/RO
88
90
92
94
96
98
100
0.25 0.5 0.75 1 1.25 1.5 1.75 2 2.25 2.5 2.75 3 3.25 3.5 3.75 4
% R
ejec
tio
n
Volume (L)
NF CIP40 MAMCN/NF CIP40
20
30
40
50
60
70
80
90
100
110
0.25 0.5 0.75 1 1.25 1.5 1.75 2 2.25 2.5 2.75 3 3.25 3.5 3.75 4
% R
ejec
tio
n
Volume (L)
RO CIP40 MAMCN/RO CIP40
201
Table 4.50. Percent rejection of LEV 40mgL-1 with membrane only
UF
S.No Time
(minute)
C
(mgL-1)
Percent
rejection
NF
Time
(minute) C
(mgL-1) Percent
rejection
RO
Time
(minute) C
(mgL-1) Percent
rejection
1 3.0 36 10 2.50 1.5 96 5.30 0 100
2 6.0 37 8 5.50 2.0 95 10.70 0 100
3 9.5 39 3 8.80 2.5 94 16.70 0 100
4 13.0 39 3 12.10 3.0 93 22.70 0 100
5 17.0 39 3 15.40 3.0 93 28.70 0 100
6 21.0 39 3 18.70 3.0 93 34.70 0 100
7 25.0 39 3 22.00 3.0 93 40.70 0 100
8 29.0 39 3 25.30 3.0 93 46.70 0 100
9 33.0 39 3 28.60 3.0 93 52.70 0 100
10 37.0 39 3 31.90 3.0 93 58.70 0 100
11 41.0 39 3 35.20 3.0 93 64.70 0 100
12 45.0 39 3 38.50 3.0 93 70.70 0 100
13 49.0 39 3 41.80 3.0 93 76.70 0 100
14 53.0 39 3 45.10 3.0 93 82.70 0 100
15 57.0 39 3 48.40 3.0 93 88.70 0 100
16 61.0 39 3 51.70 3.0 93 94.70 0 100
Table 4.51. Percent rejection of LEV 40mgL-1 with MAMCN/membrane
UF
S.No Time
(minute)
C
(mgL-1)
Percent
rejection
NF
Time
(minute) C
(mgL-1) Percent
rejection
RO
Time
(minute) C
(mgL-1) Percent
rejection
1 2.5 18 55 2.40 0 100 5.00 0 100
2 5.0 19 53 4.80 0 100 10.40 0 100
3 8.0 20 50 7.40 0 100 16.40 0 100
4 11.0 21 48 10.00 0 100 22.30 0 100
5 14.0 21 48 13.00 0 100 28.30 0 100
6 18.0 21 48 16.00 0 100 34.30 0 100
7 22.0 21 48 19.00 0 100 40.30 0 100
8 26.0 21 48 22.00 0 100 46. 30 0 100
9 30.0 21 48 25.00 0 100 52. 30 0 100
10 34.0 21 48 28.00 0 100 58. 00 0 100
11 38.0 21 48 31.00 0 100 64. 00 0 100
12 42.0 21 48 34.00 0 100 70. 00 0 100
13 46.0 21 48 37.00 0 100 76. 00 0 100
14 50.0 21 48 40.00 0 100 82. 00 0 100
15 54.0 21 48 43.00 0 100 88. 00 0 100
16 58.0 21 48 47.00 0 100 94. 00 0 100
202
Figure: 4.156 Percent rejection of LEV 40mgL-1 onto UF and MAMCN/UF
Figure: 4.157 Percent rejection of LEV 40mgL-1 onto NF and MAMCN/NF
0
10
20
30
40
50
60
70
80
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5
% R
ejec
tio
n
Volume (L)
UF LEV40 MAMCN/UF LEV40
80
85
90
95
100
105
110
0.25 0.5 0.75 1 1.25 1.5 1.75 2 2.25 2.5 2.75 3 3.25 3.5 3.75 4
% R
ejec
tio
n
Volume (L)
NF LEV40 MAMCN LEV40
203
Figure: 4.158 Percent rejection of LEV 40mgL-1 onto RO and MAMCN/RO
Table 4.52. Percent rejection of ENR 40mgL-1 with membrane only
UF
S.No Time
(minute)
C
(mgL-1)
Percent
rejection
NF
Time
(minute) C
(mgL-1) Percent
rejection
RO
Time
(minute) C
(mgL-1) Percent
rejection
1 2.5 33 18 2.45 2.0 95 05.50 0.00 100
2 6.00 34 15 6.50 2.5 94 11.00 0.00 100
3 10.00 35 13 9.50 3.0 94 17.00 0.00 100
4 14.00 36 10 12.50 3.0 94 23.00 0.00 100
5 18.00 36 10 15.50 3.0 94 29.00 0.00 100
6 22.00 36 10 18.50 3.0 94 35.00 0.00 100
7 26.00 36 10 21.50 3.0 94 41.00 0.00 100
8 30.00 36 10 24.50 3.0 94 47.00 0.00 100
9 34.00 36 10 27.50 3.0 94 53.00 0.00 100
10 38.00 36 10 30.50 3.0 94 59.00 0.00 100
11 42.00 36 10 33.50 3.0 94 65.00 0.00 100
12 46.00 36 10 38.50 3.0 94 71.00 0.00 100
13 50.00 36 10 41.50 3.0 94 77.00 0.00 100
14 54.00 36 10 44.50 3.0 94 83.00 0.00 100
15 58.00 36 10 47.50 3.0 94 89.00 0.00 100
16 62.00 36 10 50.50 3.0 94 95.00 0.00 100
20
30
40
50
60
70
80
90
100
110
120
0.25 0.5 0.75 1 1.25 1.5 1.75 2 2.25 2.5 2.75 3 3.25 3.5 3.75 4
RO LEV40 MAMCN/RO LEV40
204
Table 4.53. Percent rejection of ENR 40mgL-1 with MAMCN/membrane
UF
S.No Time
(minute)
C
(mgL-1)
Percent
rejection
NF
Time
(minute) C
(mgL-1) Percent
rejection
RO
Time
(minute) C
(mgL-1) Percent
rejection
1 2.2 16 60 2.30 0.00 100 05.30 0.00 100
2 4.8 17 58 5.30 0.00 100 10.60 0.00 100
3 7.40 19 53 8.30 0.00 100 16.60 0.00 100
4 10.0 20 50 11.30 0.00 100 22.60 0.00 100
5 12.6 20 50 14.30 0.00 100 28.60 0.00 100
6 15.2 20 50 17.30 0.00 100 34.60 0.00 100
7 17.8 20 50 20.30 0.00 100 40.60 0.00 100
8 20.4 20 50 23.30 0.00 100 46.60 0.00 100
9 23.0 20 50 26.30 0.00 100 52.60 0.00 100
10 25.6 20 50 29.30 0.00 100 58.60 0.00 100
11 28.2 20 50 32.30 0.00 100 64.60 0.00 100
12 30.8 20 50 35.30 0.00 100 70.60 0.00 100
13 33.4 20 50 38.30 0.00 100 76.60 0.00 100
14 36.4 20 50 41.30 0.00 100 82.60 0.00 100
15 39.4 20 50 44.30 0.00 100 88.60 0.00 100
16 42.4 20 50 47.30 0.00 100 94.60 0.00 100
Figure: 4.159 Percent rejection of ENR 40mgL-1 onto UF and MAMCN/UF
0
10
20
30
40
50
60
70
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5
% R
ejec
tio
n
Volume (L)
UF ENR40 MAMCN/UF ENR40
205
Figure: 4.160 Percent rejection of ENR 40mgL-1 onto NF and MAMCN/NF
Figure: 4.161 Percent rejection of ENR 40 mgL-1 onto RO and MAMCN/RO
91
92
93
94
95
96
97
98
99
100
0.25 0.5 0.75 1 1.25 1.5 1.75 2 2.25 2.5 2.75 3 3.25 3.5 3.75 4
% R
ejec
tio
n
Volume (L)
NF ENR40 MAMCN/NF ENR40
50
60
70
80
90
100
110
0.25 0.5 0.75 1 1.25 1.5 1.75 2 2.25 2.5 2.75 3 3.25 3.5 3.75 4
% R
ejec
tio
n
Volume (L)
RO ENR40 MAMCN/RO ENR40
206
4.10.4 Back wash time of UF, NF and RO membrane systems
After each 50 minutes cycle, backwashing process of membranes were performed with
distilled water. The back washing time taken was much less for PMCN and MAMCN
prepared from biomass precursors of pineapple and mangoe respectively. Because the
particles of PAMCN and MAMCN were completely removed from the slurry by
application of external magnetic field. Blackening of the pipes and flowmeters of the
membrane systems were not observed by application of PAMCN and MAMCN. Thus
PAMCN and MAMCN are useful in membrane systems and inexpensive from an
economical point of view because it reduces the backwash time of membrane systems.
Also they have been prepared from low cost biomass precursors.
4.11 Reusability/Regeneration and recycling of MCN (Desorption experiment)
In chemical treatment to further evaluate the regeneration and reusability of PAMCN
and MAMCN (Figures 4.162, 4.163 and 4.164 for PAMCN and figures 4.165, 4.166
and 4.167 for MAMCN), desorption experiment was carried out. First, 0.150 g of both
nanocomposites i.e. PAMCN and MAMCN was added to 50 mL initial CIP
concentration of 80 mgL-1 and initial concentration of LEV = ENR = 40 mgL-1 at pH
7.0 . The reaction was oscillated at 150 rmin-1 in a 25 °C water bath for six hours. The
remaining concentration of each antibiotic in the filtrate was measured using a
UV/Visible double beam spectrophotometer, and the adsorption capacity was
calculated. The PAMCN/CIP, PAMCN/LEV, PAMCN/ENR and MAMCN/CIP,
MAMCN/ENR loaded complexes were isolated from the reaction mixture with a
magnet, and the solid was washed several times with a 3% NaOH solution, methanol
and double distilled water. At last the washed samples was individually oven dried in
an oven at 70oC for five hours. The collected adsorbent was reintroduced into 50 mL
solution of initial concentration of selected antibiotics at pH 7.0, and the regeneration
207
performance of both samples were investigated under the same conditions. The same
experiment was carried out six times under the same conditions [184, 283].
208
Table 4.54. Regeneration of CIP, LEV and ENR loaded PAMCN
Adsorption temperature= 25oC ( 298K)
(pH=7, PAMCN, dose=0.15g, shaking time=150 minutes)
CIP
Co
mgL-1 State of
adsorbent Ce
mgL-1 % Removal
LE
V
Co
mgL-1 State of
adsorbent
Ce
mgL-1
% Removal
EN
R
Co
mgL-1
State of
adsorbent
Ce
mgL-1
% Removal
80 Fresh 8 90 40 Fresh 12 70 40 Fresh 08 80
80 1st 13 84 40 1st 15 63 40 1st 10 75
80 2nd 16 80 40 2nd 18 55 40 2nd 13 68
80 3rd 18 78 40 3rd 20 50 40 3rd 16 60
80 4th 22 73 40 4th 24 40 40 4th 22 45
80 5th 29 64 40 5th 27 33 40 5th 23 43
80 6th 37 54 40 6th 29 28 40 6th 24 40
209
Figure: 4. 162 Regeneration of CIP loaded PAMCN
Figure: 4.163 Regeneration of LEV loaded PAMCN
40
50
60
70
80
90
100
Fresh 1st 2nd 3rd 4th 5th 6th
90
84
8078
73
64
54
% R
emo
val
State of PAMCN
20
30
40
50
60
70
80
Fresh 1st 2nd 3rd 4th 5th 6th
70
63
55
50
40
33
28
% R
emo
val
State of PAMCN
210
Figure 4. 164 Regeneration of ENR loaded PAMCN
20
30
40
50
60
70
80
90
Fresh 1st 2nd 3rd 4th 5th 6th
80
75
68
60
4543
40
% R
emo
val
State of PAMCN
211
Table 4.55. Regeneration of CIP, LEV and ENR loaded MAMCN
Adsorption temperature= 25oC ( 298K)
(pH=7, PAMCN, dose=0.15g, shaking time=150 minutes)
CIP
Co
mgL-1 State of
adsorbent Ce
mgL-1 % Removal
LE
V
Co
mgL-1 State of
adsorbent
Ce
mgL-1
% Removal
EN
R
Co
mgL-1
State of
adsorbent
Ce
mgL-1
% Removal
80 Fresh 7 91 40 Fresh 11 73 40 Fresh 07 83
80 1st 20 75 40 1st 20 50 40 1st 14 65
80 2nd 26 68 40 2nd 24 40 40 2nd 17 58
80 3rd 30 63 40 3rd 26 35 40 3rd 20 50
80 4th 32 60 40 4th 29 28 40 4th 23 43
80 5th 36 55 40 5th 32 20 40 5th 25 38
80 6th 44 45 40 6th 35 13 40 6th 29 28
212
Figure: 4. 165 Regeneration of CIP loaded MAMCN
Figure: 4. 166 Regeneration of LEV loaded MAMCN
0
10
20
30
40
50
60
70
80
90
Fresh 1st 2nd 3rd 4th 5th 6th
91
7568
63 6055
45
% R
emo
val
State of MAMCN
0
10
20
30
40
50
60
70
80
Fresh 1st 2nd 3rd 4th 5th 6th
73
50
40
35
28
20
13
% R
emo
val
State of MAMCN
213
Figure: 4. 167 Regeneration of ENR loaded MAMCN
4.12 Comparison with other adsorbents
The Table 4.56 shows the adsorption capacities of various sorbents for the removal of
different FQs molecules from wastewater. From all these results it is obvious that
PAMCN and MAMCN made from biomass prcursors of pineapple and mengo have
quite satisfactory sorption capacities and can easily be removed from the solution using
external magnet.
0
10
20
30
40
50
60
70
80
Fresh 1st 2nd 3rd 4th 5th 6th
83
6558
5043
38
28% R
emo
val
State of MAMCN
214
Table 4.56. Comparison with other adsorbents
S. No. Adsorbent Antibiotic qm (mgg-1) Reference
1 Nano-hydroxy appetite CIP 1.49 [160]
2 PAC
(powder activated carbon)
NOR 1.30
[161]
CIP 237.00
NOR 289.00
ENR 275.00
OFL 230.00
SAR 236.00
3 Bamboo biochar ENR 19.90
[162] OFL 19.90
4 Carbon derived from hazelnut CIP 65.00 [163]
5 Magnetic carbon CIP 90.10 [164]
6 Magnetic humic acid CIP 101.00 [165]
7 PAMCN CIP 55.00 This work
8 PAMCN ENR 46.30 This work
9 PAMCN LEV 20.75 This work
10 MAMCN CIP 56.82 This work
11 MAMCN ENR 67.11 This work
12 MAMCN LEV 31.50 This work
Figure: 4. 168 Schematic diagram of the synthesis of MCN
Conclusions
The current research work was primarily focused to develop a low cost magnetic carbon
nanocomposites (MCN) and used it effectively in batch adsorption and membrane
hybrid system for the removal of FQs antibiotics (CIP, LEV and ENR) from aqueous
solution. For the objectives, bio-waste based precursors of pineapple and mango were
215
used. The prepared nanocomposites were then characterized through various
instrumental techniques. The influence of experimental conditions, regeneration and
adsorption– desorption properties of the adsorbent were determined using CIP, LEV
and ENR as model pollutants in aqueous solutions.
Characteristics
Both nanocomposites were composed of particles having microporous to
mesoporous structures with uneven particle sizes.
Different functional groups such as hydroxyl, amines, carboxyl groups and Fe-
O bonding were present in both nanocomposites which were responsible for
higher adsorption.
The MAMCN has high BET surface area as compared to PAMCN.
SEM images show the mean diameter of both MCN were around 50-70 nm with
equal distribution of white patches as depicted in the images of both MCN
showing the crystallization of nano-particles of Fe3O4.
The pHpzc of pineapple and mango based MCN were found to be 7.2 and 7.3
respectively.
Experimental conditions
The adsorption of the FQs on prepared adsorbent were influenced by physico-
chemical parameters like pH, sorbent doses, contact time, temperature, initial
concentration, ionic strength and humic acid.
The Thermodynamics parameters determined showed that the adsorption of
FQs onto prepared adsorbents was spontaneous and exothermic in nature.
Regeneration and reuse
216
The PAMCN/FQs and MAMCN/FQs solid complexes were washed
individually with 3% NaOH solution, methanol and distilled water. The
recycling test was conducted. The adsorbent recovered still showed high
adsorption capacities.
Kinetics of adsorption
The kinetics characteristics of adsorbents were examined and the following results were
obtained:
Maximum adsorption were achieved in 60 minutes.
Maximum adsorption were achieved at pH 6-7.
Adsorption kinetics data from both nanocomposites showed good agreement
with pseudo-2nd order model.
Intraparticle diffusion model posed good fitness with the kinetics data.
Isotherms of adsorption
The equilibrium adsorption of FQs were examined and the following results are found:
The initial FQs concentration had significant influences on the isotherm
parameters. Hence, it is essential to evaluate the isotherm parameters of models
covering wide range of initial FQs concentrations.
The equilibrium data fitted well with Langmuir and Jovanovich models (R2 is
around equivalent to 1.0), which determine that the nanocomposites contain
monolayer and homogeneous cites to adsorb FQs molecules.
The Langmuir isotherm predicted efficiently the maximum adsorption capacity
(qm) for CIP, LEV and ENR molecules adsorption.
217
The maximum adsorption capacities for CIP, LEV and ENR molecules
adsorption were 55.0, 20.75 and 46.30 mgg-1 onto PAMCN respectively.
The maximum adsorption capacities for CIP, LEV and ENR molecules
adsorption were 56.82, 31.50 and 67.11 mgg-1 onto MAMCN respectively.
Among the three FQs, CIP molecules were effectively removed by the PAMCN
than the other two, while in case of MAMCN the ENR molecules were
effectively adsorbed than the other.
Membranes and adsorption/membrane hybrid processes
Improved permeate fluxes were observed with membrane hybrid processes.
The percent retention of antibiotics in NF and RO membrane hybrid processes
were 100%. While, in case of UF increases appreciably from 5 to 50%.
The back washing time was much lesser for PMCN and MAMCN membrane
hybrid processes.
Blackening of the pipes and flowmeters of the membrane systems were not
observed for hybrid processes (as particles of PAMCN and MAMCN were
removed from the slurry before feeding to membrane systems by using a
magent).
The use of PAMCN and MAMCN with membrane systems in a hybrid manner
is an inexpensive material deposited on the surface of low-cost biomass
precusors of pineapple and mango. From an economical point of view the use
of PAMCN and MAMCN with membrane systems decreases the backwash time
of all membranes are a positive sign.
218
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