with sign Farah Amin Thesis PhD 2018

Ph.D. Thesis

BIOSORPTION OF TOXIC METALS AND ANIONS FROM

AQUEOUS SOLUTIONS BY FUNGAL BIOMASS

THESIS SUBMITTED TOWARDS THE PARTIAL FULFILMENT OF THE

REQUIREMENT OF THE UNIVERSITY OF SINDH, FOR THE AWARD OF

DOCTOR OF PHILOSOPHY DEGREE IN ANALYTICAL CHEMISTRY

FARAH AMIN

National Centre of Excellence in Analytical Chemistry

University of Sindh, Jamshoro Pakistan

2018

I

CERTIFICATE

This is to certify that the work present in this thesis entitled “Biosorption of

Toxic Metals and Anions from Aqueous Solutions by Fungal Biomass” has

been carried out by Ms. Farah Amin D/O Muhammad Yamin under our

supervision. The work is genuine, original and, in our opinion, suitable for

submission to the University of Sindh for the award of degree of Ph.D. in

Analytical Chemistry.

SUPERVISOR

Dr. Farah Naz Talpur

Associate Professor



CO-SUPERVISOR

Dr. Aamna Balouch

Associate Professor



II

DEDICATION

With profound love and deep respect, I dedicate the honor of this Degree to my

beloved Father, Mother, Sister and Brothers; whose affection, love,

encouragement and prays are always with me.

III

ACKNOWLEDGEMENTS

I owe my profound thanks to ALLAH (Subhanahu Wa Ta'ala), Who blessed me

with an opportunity for Ph.D. and gave me the strength, determination and

ability to complete this research project. All of my veneration and devotion goes to

our beloved Prophet Muhammad (Peace Be Upon Him) the source of humanity,

kindness and guidance for the whole creatures and who declared it an obligatory duty

of every Muslim to seek and acquire knowledge.

It seems an obligation upon me to record the word of encouragement for my family

and simple words of thankfulness would not cover the genuine affection, absolute

support, remarkable encouragement and profound prayers of my respectable father

Muhammad Yamin Khan and beloved Mother.

I wish to express my deep sense of gratitude to my supervisors Dr. Farah Naz

Talpur & Dr. Aamna Balouch for their guidance, valuable suggestions and

generous co-operation at every stage of this work, without which this work

would not have been possible.

I would like to extend my gratitude to Dr. Muhammad Aqeel Bhutto (Institute of

Biotechnology and Genetic Engineering, University of Sindh Jamshoro, Pakistan) for

providing fungal biomass to carry out this research successfully and for his advices

during the work. I am thankful to Dr. Zaheer Ahmed Chandio (Dr. M. A. Kazi

Institute of Chemistry, University of Sindh Jamshoro, Pakistan) for his sincere

guidance during AAS analysis. I am also greatly thankful to Prof. Dr. Muhammad

Raza Shah (International Center for Chemical and Biological Sciences, H.E.J.

Research Institute of Chemistry University of Karachi) for AFM analysis and Mr.

Muhammad Kashif Samoon (Centre for Pure and Applied Geology, University of

Sindh, Jamshoro, Pakistan) for SEM-EDX analysis. I am thankful to Director,

NCEAC, Prof. Dr. Shahbuddin Memon, for providing the working facilities and

excellent research environment. All Academic Staff of the Centre is also appreciated

for knowledge exchange and providing their help when needed. My Lab Fellows,

Friends and all Colleagues who provided me good company during the course of my

research work are highly anticipated.

I would not have been able to complete this endeavor without the support,

prayers and love of my family (sister and brothers).

Finally, and most of all I would like to thank my maternal uncle Dr. Shah

Nawab Khan for his everlasting encouragement at every moment of life.

Farah Amin

IV

ABSTRACT

Environmental pollution is becoming a serious and challenging problem all over

the world because of high level of industrial development and growth. Various

industries discharge toxic heavy metals and anions into the environment that

considerably enhanced the humiliation of marine environment and significantly

threats the ecosystem. These unwanted chemicals cause severe health problems,

when they exceed the tolerance limit in water. For this reason, the removal of

toxic pollutants is the greatest challenge. Biosorption method based on

utilization of microorganisms has been given a significant attention due to

efficient, rapid, easier, less expensive and environment friendly properties of

biosorbent material for the removal of toxins from aqu eous solution.

Owing to the significance of biosorption technique, the projected work is based

upon the biological preparation of environmental friendly fungal biomass

Pleurotus eryngii (P. eryngii) and their exploitation for the removal of selected

toxic metal ions (Pb, Cd, Hg) and anions (F-, NO3-) from aqueous system. Before

and after sorption the biomass were characterized by FTIR, AFM, SEM and EDX

techniques to verify surface functionality and morphology, whereas the surface

chemistry charge studies (pHPZC) were carried out to measure the approx. pH at

which biosorbent behave as cationic, anionic and neutral species. After

optimization of experimental variables (concentration, time, temperature),

isotherm (Langmuir, Freundlich, Temkin, D-R models), kinetic (Pseudo first,

Pseudo second, Intra particle diffusion models) and thermodynamic (enthalpy,

entropy, Gibbs free energy) parameters were calculated. The presence of

interfering ions during biosorption and re-usability studies after appropriate

desorption were carried out. Response Surface Methodology (RSM) was also

employed in selected part of the studies to decrease the number of experiments,

improved product yields and reduced treatment time and overall research cost.

For the application of P. eryngii on real water samples; toxic pollutant (metals /

anions) contaminated samples were collected from river, canal, lake and streams

of Sindh, Pakistan. It was evaluated that under optimal conditions (at natural pH

V

values) selected ions were removed effectively underneath the permissible limits

of World Health Organization (WHO) drinking water standards.

Briefly, for 30 mg L-1 Pb(II) ions 100% removal with sorption capacity of 2.971

mg g-1 was successfully achieved within 5 min at optimum pH 6.0 and 0.35 g

sorbent dose. The results following the Langmuir isotherm, pseudo second order

kinetic model and were thermodynamically feasible at temperature 30°C. Overall

elution of Pb ions achieved from the biomass utilizing 0.1 N HCl solution. Field test

results established effectiveness of P. eryngii biomass for the decontamination of

Pb(II) ions from drinking water.

Similarly, for Cd(II) ion removal 99.9% results were achieved at pH 5.0, dosage

0.2 g, concentration 20 mg L-1, time 10 min and temperature 50°C. A favorable

biosorbent capacity of 1.51 mg g−1 was achieved that indicated a good capability

of P. eryngii biomass. The sorption efficiency decreased from 99.99 to 56.89 %

as the biomass was re-cycled up to 5 times. However, the efficiency of Cd(II)

removal from real water samples still lies between 85 to 90%.

Correspondingly, the sorption process was relatively fast and > 98% removal of

Hg(II) was achieved within 5 min at pH 7.0 with 34.01 mg g-1 biosorption

capacity. The Langmuir isotherm and pseudo-second order were the best

applicable models to describe the sorption process. The sorption process was

exothermic and spontaneous by increased randomness at the solid-solution

interface. The adsorbed Hg(II) ions easily desorbed using 5 M HCl solution with

higher effectiveness and can be reused up to five cycles. Different

electronegative functionalities involve in the binding of Hg(II) metal ions on the

surface as evident by various characterization techniques. The study revealed

considerable potential of biosorbent for its exploitation in the treatment of

industrial effluents containing Hg(II) ion contamination.

In further study, toxic anions were selected for the biosorption by white - rot

fungal biosorbent P. eryngii. More than 96% removal of F- was achieved at

optimum conditions (pH: 2.0; biosorbent dose: 0.2 g; initial concentration: 5.0

mg L−1; temperature: 30°C; agitation: 100 rpm). Langmuir model with 66.6 mg

VI

g-1 biosorption capacity fitted the equilibrium data better and followed well

pseudo-second order model; while intra particle diffusion was not by any means

the only rate-controlling step. The biosorbent was multiple times reusable and

showed slight decrease in sorption efficiency in presence of foreign impurities.

The application of fungal biomass on F- removal showed satisfactory

performance on water samples collected from a fluoride-endemic area.

A three level, three factors Central Composite Design (CCD) was used to

evaluate the effects and interactions of the process variables removal of NO3-

ions from aqueous solution onto P. eryngii dried fungal biosorbent. ANOVA, F-

test, Student’s t-test and lack of fit test showed that NO3- ions biosorption is only

slightly concentration dependent, but markedly increases with solution pH and

biosorbent dose. The optimum pH (7.0), biosorbent dose (0.24 g) and initial

concentration (700.0 mg L-1) were found by desirability function. Under these

optimum combinations of process parameter conditions, maximum removal of

88.38% was obtained that assisting its use in larger scale.

In final approach of this bio-analytical study, the fungal biomass packed in a

mini glass column was used to remove one of the selected ion (Pb) from water.

After studying the column performance parameters (initial concentration: 20 mg

L-1, flow rate: 1 ml min-1, bed height: 3 cm) maximum Thomas model entrapping

capacity of 3.30 mg g-1 at pH 7.0 was obtained. A laboratory column evaluation

on real contaminated samples also evident the applicability of sorption column

on commercial scale.

Hence, the results indicated that P. eryngii is a good biosorbent for removal of

heavy metals and anions from polluted water. In addition, the spent fungal

biomass can be easily disposed of and can be used as an alternative raw material

for large scale composting process.

VII

TABLE OF CONTENTS

CERTIFICATE...............................................................................................I

DEDICATION ............................................................................................. II

ACKNOWLEDGEMENTS ........................................................................... III

ABSTRACT ................................................................................................ IV

TABLE OF CONTENTS ............................................................................. VII

LIST OF TABLES .................................................................................... XIII

LIST OF FIGURES ..................................................................................... XV

ABBREVIATIONS ................................................................................... XIX

CHAPTER 1 .................................................................................................. 1

INTRODUCTION ......................................................................................... 1

1.1 MOTIVATION................................................................................................ 1

1.2 CONTRIBUTIONS OF THE THESIS .................................................................... 1

1.3 ENVIRONMENTAL POLLUTION ....................................................................... 2

1.3.1 POLLUTION IN AQUEOUS SOLUTIONS ....................................................... 3

1.3.2 HEAVY METAL POLLUTION ...................................................................... 3

1.3.3 ANIONIC POLLUTION............................................................................... 5

1.4 CONVENTIONAL TECHNIQUES USED FOR THE REMOVAL OF TOXIC METALS AND

ANIONS FROM AQUEOUS SOLUTIONS ....................................................................... 7

1.4.1 CHEMICAL PRECIPITATION ...................................................................... 7

1.4.2 ELECTRO-DIALYSIS ................................................................................ 7

1.4.3 REVERSE OSMOSIS .................................................................................. 7

1.4.4 ION-EXCHANGE ...................................................................................... 8

1.4.5 ULTRA-FILTRATION ................................................................................ 8

1.4.6 ADSORPTION .......................................................................................... 8

1.5 THE REQUIREMENT OF NOVEL INNOVATION FOR THE REMOVAL OF TOXIC

METALS AND ANIONS.............................................................................................. 9

1.5.1 HISTORY OF BIOSORPTION ...................................................................... 9

1.5.2 ADVANTAGES OF BIOSORPTION TECHNIQUE ........................................... 10

1.5.3 BIOSORBENTS / BIOLOGICAL MATERIAL / BIOMASS................................. 10

1.6 EXPECTED MECHANISMS INVOLVE IN BIOSORPTION ..................................... 11

1.6.1 METABOLISM DEPENDENT .................................................................... 11

VIII

1.6.2 NON-METABOLISM DEPENDENT ............................................................. 11

1.6.3 EXTRA CELLULAR ACCUMULATION / PRECIPITATION .............................. 11

1.6.4 CELL SURFACE SORPTION / PRECIPITATION ............................................ 12

1.6.5 INTRACELLULAR ACCUMULATION / COMPLEXATION .............................. 12

1.6.6 ION EXCHANGE ..................................................................................... 12

1.6.7 PHYSICAL ADSORPTION ........................................................................ 12

1.7 FACTORS AFFECTING BIOSORPTION ............................................................. 12

1.7.1 PH ....................................................................................................... 12

1.7.2 BIOMASS CONCENTRATION ................................................................... 13

1.7.3 TEMPERATURE ..................................................................................... 13

1.7.4 INTERFERING IONS ................................................................................ 13

1.8 DESORPTION .............................................................................................. 13

1.9 CHOICE OF TOXIC METAL AND ANION FOR BIOSORPTION PROCESS ................ 13

1.10 EVALUATION OF BIOSORPTION PROCESS ...................................................... 14

1.11 ISOTHERM STUDY (BIOSORPTION ISOTHERMS) ............................................. 14

1.11.1 LANGMUIR SORPTION ISOTHERM ........................................................... 14

1.11.2 FREUNDLICH SORPTION ISOTHERM ........................................................ 15

1.11.3 TEMKIN SORPTION ISOTHERM................................................................ 15

1.11.4 D-R SORPTION ISOTHERM ..................................................................... 16

1.12 KINETIC STUDY (BIOSORPTION KINETIC ISOTHERMS) ................................... 17

1.12.1 LAGERGREN’S PSEUDO FIRST ORDER KINETIC MODEL ............................. 17

1.12.2 HO-MCKAY’S PSEUDO SECOND ORDER KINETIC MODEL ......................... 17

1.12.3 WEBER AND MORRIS INTRA PARTICLE DIFFUSION MODEL ...................... 18

1.13 THERMODYNAMIC STUDY ........................................................................... 18

1.14 STATISTICAL DESIGN OF EXPERIMENT ......................................................... 19

1.15 COLUMN MODELS ....................................................................................... 20

1.15.1 THOMAS MODEL ................................................................................... 20

1.15.2 BDST MODEL ........................................................................................ 20

1.16 AIM AND OBJECTIVES OF PRESENT STUDY ................................................... 21

1.17 STRUCTURE OF THE THESIS ......................................................................... 22

CHAPTER 1 INTRODUCTION .......................................................................... 22

CHAPTER 2 LITERATURE REVIEW .................................................................. 22

CHAPTER 3 RESEARCH METHODOLOGY ......................................................... 22

CHAPTER 4 RESULTS AND DISCUSSION .......................................................... 23

CHAPTER 5 CONCLUSION .............................................................................. 23

CHAPTER 2 ................................................................................................ 24

IX

LITERATURE REVIEW .............................................................................. 24

2.1 SYNTHETIC ADSORBENTS USED FOR THE REMOVAL OF METALS AND ANIONS 24

2.2 NATURAL BIOSORBENTS FOR THE REMOVAL OF METALS AND ANIONS .......... 24

2.3 REMOVAL OF TOXIC METALS BY VARIOUS BIOSORBENTS ............................. 25

2.3.1 BACTERIAL BIOSORBENTS ..................................................................... 25

2.3.2 ALGAL BIOSORBENTS ........................................................................... 27

2.3.3 YEAST BIOSORBENTS ............................................................................ 28

2.4 FUNGAL BIOMASS AS NATURAL BIOSORBENT FOR METAL ION REMOVAL ....... 30

2.5 REMOVAL OF ANIONS BY VARIOUS BIOSORBENT .......................................... 31

2.6 PLEUROTUS ERYNGII – A COMMON EDIBLE MACROFUNGI .............................. 33

2.6.1 PHYSICAL DESCRIPTION ........................................................................ 33

2.6.2 GROWTH HABIT .................................................................................... 33

2.6.3 SCIENTIFIC CLASSIFICATION OF P. ERYNGII ............................................ 34

2.6.4 EFFECTIVENESS OF P. ERYNGII AS BIOSORBENT ...................................... 34

2.7 SUMMARY .................................................................................................. 34

CHAPTER 3 ................................................................................................ 36

RESEARCH METHODOLOGY ................................................................... 36

3.1 CHEMICALS AND REAGENTS ....................................................................... 36

3.2 FUNGAL STRAIN ......................................................................................... 36

3.2.1 INOCULUM PREPARATION ..................................................................... 36

3.2.2 DRIED BIOSORBENT PREPARATION ........................................................ 37

3.2.3 PREPARATION OF BIOSORBENT IN DIFFERENT FORMS ............................. 38

3.3 PREPARATION OF STANDARD SOLUTIONS .................................................... 38

3.4 ANALYTICAL INSTRUMENTATION ................................................................ 39

3.5 POINT OF ZERO CHARGE (PHPZC) .................................................................. 41

3.6 BATCH BIOSORPTION EXPERIMENT .............................................................. 41

3.7 CONTINUOUS (PACKED COLUMN) BIOSORPTION EXPERIMENT ....................... 42

3.8 INTERFERENCE STUDIES ............................................................................. 43

3.9 DESORPTION STUDIES ................................................................................. 43

3.10 STATISTICAL METHODOLOGY FOR NO3- IONS ............................................... 43

3.11 CALCULATION OF DATA .............................................................................. 44

3.12 ANALYSIS OF COLUMN DATA ...................................................................... 45

3.13 STATISTICAL ANALYSIS .............................................................................. 45

3.14 REAL WATER SAMPLE FOR ANALYTICAL APPLICATION ................................. 46

CHAPTER 4 ................................................................................................ 48

X

RESULTS AND DISCUSSION .................................................................... 48

4.1 ECO-EFFICIENT FUNGAL BIOMASS FOR THE REMOVAL OF PB(II) IONS FROM

WATER SYSTEM: A SORPTION PROCESS AND MECHANISM ....................................... 48

4.1.1 CHARACTERIZATION OF THE BIOSORBENT ............................................. 48

4.1.2 OPTIMIZATION OF EXPERIMENTAL PARAMETERS .................................... 50

4.1.3 INVESTIGATION OF INTERFERING IONS ................................................... 60

4.1.4 DESORPTION OF PB(II) IONS AND RE-USABILITY OF SPENT BIOMASS ....... 61

4.1.5 ANALYTICAL APPLICATION ................................................................... 62

4.1.6 SUMMARY ............................................................................................ 62

4.2 UTILIZATION OF P. ERYNGII BIOSORBENT AS AN ENVIRONMENTAL BIOREMEDY

FOR THE DECONTAMINATION OF TRACE CD(II) IONS FROM WATER SYSTEM ............ 64


4.2.2 OPTIMIZATION OF BIOSORPTION EXPERIMENTAL PARAMETERS ............... 67

4.2.3 BIOSORPTION ISOTHERM STUDIES ......................................................... 71

4.2.4 THERMODYNAMIC PARAMETERS ........................................................... 73

4.2.5 BIOSORPTION KINETIC STUDIES ............................................................. 74

4.2.6 ELUTION OF CD(II) ION AND RE-USABILITY OF BIOSORBENT ................... 77

4.2.7 INFLUENCE OF INTERFERING IONS ......................................................... 78


4.2.9 SUMMARY ............................................................................................ 79

4.3 BIOSORPTION OF HG(II) FROM AQUEOUS SOLUTION BY FUNGAL BIOMASS P.

ERYNGII: ISOTHERM, KINETIC AND THERMODYNAMIC STUDIES ............................... 81


4.3.2 EFFECT OF INITIAL PH .......................................................................... 83

4.3.3 EFFECT OF INITIAL BIOMASS CONCENTRATION ....................................... 84

4.3.4 EFFECT OF INITIAL HG(II) CONCENTRATION .......................................... 85

4.3.5 EFFECT OF CONTACT TIME AND TEMPERATURE ...................................... 86

4.3.6 BIOSORPTION ISOTHERMS ..................................................................... 87

4.3.7 BIOSORPTION KINETICS ........................................................................ 89

4.3.8 BIOSORPTION THERMODYNAMICS ......................................................... 91

4.3.9 EFFECT OF CO-EXISTING IONS ............................................................... 92

4.3.10 DESORPTION EFFICIENCY AND REUSABILITY .......................................... 92


4.3.12 SUMMARY ............................................................................................ 94

4.4 BIOSORPTION OF F- FROM AQUEOUS SOLUTION BY WHITE - ROT FUNGUS P.

ERYNGII ATCC 90888 ........................................................................................... 96

XI


4.4.2 CALIBRATION OF IC FOR F- ANALYSIS ................................................... 98

4.4.3 INFLUENCE OF PH ................................................................................. 99

4.4.4 INFLUENCE OF INITIAL F- CONCENTRATION ...........................................100

4.4.5 INFLUENCE OF BIOSORBENT DOSE ........................................................101

4.4.6 BIOSORPTION ISOTHERM MODELS .........................................................101

4.4.7 THERMODYNAMIC STUDIES ..................................................................104

4.4.8 KINETIC STUDIES .................................................................................105

4.4.9 EFFECT OF CO-EXISTING ANIONS ON F- BIOSORPTION ............................107

4.4.10 DESORPTION AND REGENERATION OF BIOSORBENT ...............................108

4.4.11 APPLICATION TO REAL WATER SAMPLES ...............................................109

4.4.12 PROPOSED MECHANISM........................................................................111

4.4.13 SUMMARY ...........................................................................................111

4.5 STATISTICAL METHODOLOGY FOR BIOSORPTION OF NO3- IONS FROM AQUEOUS

SOLUTION BY P. ERYNGII FUNGAL BIOMASS ..........................................................113

4.5.1 CHARACTERIZATION OF THE BIOSORBENT ............................................113

4.5.2 CALIBRATION OF UV-VIS SPECTROPHOTOMETER FOR NO3- ANALYSIS ...116

4.5.3 MODEL FITTING AND STATISTICAL ANALYSIS .......................................117

4.5.4 SELECTION OF A MODEL.......................................................................119

4.5.5 NORMAL PROBABILITY PLOT OF RESIDUALS ..........................................122

4.5.6 EFFECT OF INTERACTIVE VARIABLES ....................................................122

4.5.7 VALIDATION OF THE MODEL ................................................................124

4.5.8 SUMMARY ...........................................................................................125

4.6 EFFICIENT ENTRAPPING OF TOXIC LEAD (PB) IONS FROM AQUEOUS SYSTEM ON

FIXED - BED COLUMN OF FUNGAL BIOSORBENT .....................................................126

4.6.1 COLUMN STUDY ..................................................................................126

4.6.2 COMPARISON OF PB(II) IONS SORPTION CAPACITY DURING BATCH AND

COLUMN MODE ...............................................................................................130

4.6.3 APPLICATION OF COLUMN ON REAL CONTAMINATED WATER SAMPLES...131

4.6.4 SUMMARY ...........................................................................................131

CHAPTER 5 .............................................................................................. 132

CONCLUSION AND FUTURE DIRECTIONS ............................................ 132

5.1 CONCLUSION ............................................................................................132

5.2 SIGNIFICANCE OF THIS RESEARCH ..............................................................134

5.3 RECOMMENDATIONS AND FUTURE DIRECTIONS OF THIS RESEARCH WORK ...134

XII

REFERENCES .......................................................................................... 136

LIST OF PUBLICATIONS ......................................................................... 150

XIII

LIST OF TABLES

TABLE 1.1 COMMON SOURCES, HEALTH PROBLEMS AND MAXIMUM ACCEPTABLE CONCENTRATION

LEVEL BY THE WHO OF SOME TOXIC HEAVY METALS ........................................................ 4

TABLE 1.2 COMMON SOURCES, HEALTH PROBLEMS AND MAXIMUM ACCEPTABLE CONCENTRATION

LEVEL BY THE WHO OF SOME TOXIC ANIONS. .................................................................. 6

TABLE 2.1 OVERVIEW OF BIOSORBENTS AND THEIR SORPTION CAPACITIES FOR SELECTED METALS.

................................................................................................................................... 30

TABLE 2.2 MORPHOLOGY OF P. ERYNGII. ................................................................................ 33

TABLE 2.3 SCIENTIFIC CLASSIFICATION OF P. ERYNGII. ............................................................ 34

TABLE 3.1 METHODS FOR THE PREPARATION OF FUNGAL CELL MASS. ....................................... 38

TABLE 3.2 CONDITIONS OF F-AAS FOR PB(II), CD(II) AND HG-AAS FOR HG(II) ...................... 39

TABLE 3.3 CONDITIONS OF IC FOR F- IONS DETERMINATION. .................................................... 40

TABLE 3.4 EXPERIMENTAL CONDITIONS AND THEIR RANGES USED TO OPTIMIZE THE SORPTION

EFFICIENCY OF METALS AND ANIONS. ............................................................................ 41

TABLE 3.5 EXPERIMENTAL RANGES AND LEVEL OF THE INDEPENDENT VARIABLES..................... 44

TABLE 3.6 DETAIL OF WATER COLLECTION SITES AND GPS CO-ORDINATES MONITORED FOR EACH

ZONE. .......................................................................................................................... 47

TABLE 4.1 THERMODYNAMIC PARAMETERS FOR PB(II) IONS REMOVAL BY P. ERYNGII AT VARIOUS

TEMPERATURES. ........................................................................................................... 53

TABLE 4.2 ISOTHERMS MODEL CONSTANTS AND THEIR RESPECTIVE COEFFICIENTS FOR PB(II) IONS

SORPTION ONTO FUNGAL BIOMASS. ................................................................................ 56

TABLE 4.3 COMPARISON OF SORPTION CAPACITIES OF DIFFERENT ADSORBENTS IN THE

LITERATURE WITH THE CURRENT BIOSORBENT. ............................................................... 57

TABLE 4.4 KINETIC PARAMETERS FOR PB(II) BIOSORPTION ON P. ERYNGII. ............................... 59

TABLE 4.5 INVESTIGATION OF INTERFERING IONS EFFECT ON REMOVAL OF PB(II) IONS (INITIAL

CONCENTRATION = 5 MG L-1) BY P. ERYNGII. .................................................................. 60

TABLE 4.6 REMOVAL OF PB(II) IONS FROM NATURAL WATER SAMPLES. .................................... 62

TABLE 4.7 COMPARISON OF MAXIMUM BIOSORPTION CAPACITY OF P. ERYNGII FOR CD(II) WITH

OTHER REPORTED BIOSORBENTS. ................................................................................... 73

TABLE 4.8 THERMODYNAMIC PARAMETERS FOR CD(II) BIOSORPTION ON P. ERYNGII AT VARIOUS

TEMPERATURES. ........................................................................................................... 74

TABLE 4.9 INFLUENCE OF SOME INTERFERING IONS ON BIOSORPTION OF CD(II). ........................ 78

TABLE 4.10 FIELD TRIAL RESULTS OF BIOSORPTION STUDIES USING REAL WATER SAMPLES. ....... 79

TABLE 4.11 SURFACE FUNCTIONALITIES OBSERVED ON FUNGAL BIOSORBENT BY FTIR

SPECTROSCOPY. ........................................................................................................... 83

TABLE 4.12 HG(II) BIOSORPTION: LANGMUIR AND FREUNDLICH ISOTHERM CONSTANTS. ........... 88

XV

TABLE 4.13 COMPARISON OF BIOSORPTION CAPACITY OF P. ERYNGII FUNGAL BIOMASS FOR HG(II)

IONS WITH OTHER REPORTED BIOSORBENTS. ................................................................... 88

TABLE 4.14 KINETIC MODEL PARAMETERS FOR THE BIOSORPTION OF HG(II) IONS BY ................ 90

TABLE 4.15 EFFECT OF SOME INTERFERING IONS ON THE REMOVAL PROCESS OF HG(II) IONS BY P.

ERYNGII. ...................................................................................................................... 92

TABLE 4.16 DESORPTION OF HG(II) IONS BY P. ERYNGII. ......................................................... 93

TABLE 4.17 ADSORPTION-DESORPTION OF HG(II) IONS BY P. ERYNGII USING 5 M HCL .............. 93

TABLE 4.18 ANALYTICAL RESULTS FOR THE BIOSORPTION OF HG(II) IONS IN NATURAL WATER

SAMPLES. .................................................................................................................... 94

TABLE 4.19 LANGMUIR, FREUNDLICH AND D–R ISOTHERM CONSTANTS ..................................103

TABLE 4.20 COMPARISON OF BIOSORPTION CAPACITY OF P. ERYNGII FUNGAL BIOMASS FOR F- ION

WITH OTHER REPORTED BIOSORBENTS...........................................................................103

TABLE 4.21 THEMODYNAMIC PARAMETERS FOR F- BIOSORPTION ON P. ERYNGII AT VARIOUS

TEMPERATURES. ..........................................................................................................105

TABLE 4.22 KINETIC PARAMETERS FOR F- BIOSORPTION ON P. ERYNGII. ...................................106

TABLE 4.23 THE PHYSICO-CHEMICAL PARAMETERS OF REAL WATER SAMPLES. ........................110

TABLE 4.24 FIELD TRIAL RESULTS OF BIOSORPTION STUDIES USING REAL FIELD WATER. ...........110

TABLE 4.25 EXPERIMENTAL DESIGN AND RESULTS FOR BIOSORPTION EFFICIENCY (%) OF NO3- BY

P. ERYNGII. .................................................................................................................118

TABLE 4.26 SELECTION OF A SATISFACTORY MODEL FOR NO3- BIOSORPTION. ..........................119

TABLE 4.27 ANOVA FOR THE RESPONSE SURFACE REDUCED QUADRATIC MODEL. ...................121

TABLE 4.28 CONDITIONS FOR VALIDATION OF THE DESIGN. ....................................................124

TABLE 4.29 THE THOMAS AND BDST MODEL PARAMETERS FOR THE BIOSORPTION OF PB(II) ON

P. ERYNGII FUNGAL BIOMASS. .......................................................................................128

TABLE 4.30 COMPARISON OF PB(II) IONS SORPTION CAPACITY................................................130

TABLE 4.31 REMOVAL OF PB(II) IONS FROM REAL WATER SAMPLES VIA COLUMN METHOD. ......131

XV

LIST OF FIGURES

FIGURE 3.1 (A) P. ERYNGII MAINTAINED ON PDA PLATE. ......................................................... 36

FIGURE 3.2 (B) WET COLONY SUB-CULTURED ON GPB. ........................................................... 37

FIGURE 3.3 (C) DRIED BIOMASS OF P. ERYNGII. ....................................................................... 37

FIGURE 3.4 BIOSORPTION STUDY BY BATCH EXPERIMENTAL PROCEDURE. ................................. 42

FIGURE 3.5 BIOSORPTION STUDY BY COLUMN EXPERIMENTAL PROCEDURE. .............................. 42

FIGURE 3.6 THE MAP OF SINDH SHOWING SAMPLING ZONE IN RED ARROWS. [IMAGE COURTESY:

GOOGLE MAP]. ............................................................................................................. 46

FIGURE 4.1 FTIR SPECTROMETRY OF FUNGAL BIOMASS BEFORE (A) AND AFTER (B) PB(II) IONS

SORPTION. ................................................................................................................... 49

FIGURE 4.2 AFM MICROSCOPIC IMAGES OF FUNGAL BIOMASS: BEFORE PB(II) EXPOSURE (A:

HEIGHT IMAGE; B: THREE-DIMENSIONAL IMAGE) AND AFTER PB(II) EXPOSURE (C: HEIGHT

IMAGE; D: THREE-DIMENSIONAL IMAGE). ....................................................................... 50

FIGURE 4.3 PERCENTAGE REMOVAL OF PB(II) IONS AS A FUNCTION OF PH (VOLUME: 20 ML;

SORBENT DOSE: 0.2 G; INITIAL CONCENTRATION: 50 MG L−1; CONTACT TIME: 30 MIN;

TEMPERATURE: 27°C). .................................................................................................. 51

FIGURE 4.4 PERCENTAGE REMOVAL OF PB(II) IONS CONCENTRATION AS A FUNCTION OF

BIOSORBENT DOSE (VOLUME: 20 ML; PH: 6.0; INITIAL CONCENTRATION: 50 MG L−1;

CONTACT TIME: 30 MIN; TEMPERATURE: 27°C). .............................................................. 52

FIGURE 4.5 PERCENTAGE REMOVAL OF PB(II) IONS CONCENTRATION AS A FUNCTION OF

TEMPERATURE (VOLUME: 20 ML; PH: 6.0; SORBENT DOSE: 0.35 G; INITIAL CONCENTRATION:

50 MG L−1; CONTACT TIME: 30 MIN). .............................................................................. 52

FIGURE 4.6 VAN’T HOFF PLOT, LOG KC VERSUS 1/T. ............................................................... 53

FIGURE 4.7 EFFECT OF CONCENTRATION OF PB(II) IONS ON THEIR PERCENT REMOVAL OVER P.

ERYNGII (VOLUME: 20 ML; PH: 6.0; SORBENT DOSE: 0.35 G; TEMPERATURE: 30°C; CONTACT

TIME: 30 MIN). ............................................................................................................. 54

FIGURE 4.8 ADSORPTION ISOTHERMS PLOT (A) LANGMUIR, (B) FREUNDLICH, (C) TEMKIN, AND (D)

D-R. ........................................................................................................................... 55

FIGURE 4.9 EFFECT OF CONCENTRATION OF PB(II) IONS ON THEIR PERCENT REMOVAL OVER P.

ERYNGII AS A FUNCTION OF CONTACT TIME (VOLUME: 20 ML; PH: 6.0; SORBENT DOSE: 0.35

G; TEMPERATURE: 30°C; INITIAL CONCENTRATION: 30 MG L−1). ...................................... 58

FIGURE 4.10 PSEUDO FIRST ORDER (A), PSEUDO SECOND ORDER (B), AND INTRA PARTICLE

DIFFUSION KINETIC MODELS PLOTS FOR THE SORPTION OF PB(II) IONS ONTO FUNGAL

BIOMASS. ..................................................................................................................... 58

XV

FIGURE 4.11 A) OPTIMIZATION OF VARIOUS ELUENTS TO CHECK THEIR DESORPTION EFFICIENCY

TOWARD PB(II) IONS. B) DESORPTION – REUSE CYCLES FOR THE REMOVAL OF PB(II) IONS

USING P. ERYNGII BIOMASS. ........................................................................................... 61

FIGURE 4.12 FTIR SPECTRA OF P. ERYNGII FUNGAL BIOMASS (A) BEFORE AND (B) AFTER

BIOSORPTION OF CD(II). ............................................................................................... 65

FIGURE 4.13 SEM MICROGRAPHS OF (A) UNLOADED AND (B) CD(II) LOADED P. ERYNGII FUNGAL

BIOMASS; EDS SPECTRA OF (C) UNLOADED AND (D) CD(II) LOADED P. ERYNGII FUNGAL

BIOMASS. ..................................................................................................................... 66

FIGURE 4.14 AFM IMAGES OF P. ERYNGII FUNGAL BIOSORBENT BEFORE (A) AND AFTER CD(II)

SORPTION (C), THREE-DIMENSIONAL IMAGES OF P. ERYNGII FUNGAL BIOSORBENT BEFORE

AND AFTER CD(II) SORPTION (B AND D). ........................................................................ 67

FIGURE 4.15 INFLUENCE OF P. ERYNGII FUNGAL CELL MASS STATE ON BIOSORPTION OF CD(II). .. 68

FIGURE 4.16 (A) PERCENTAGE REMOVAL OF CD(II) IONS CONCENTRATION AS A FUNCTION OF PH

(BIOSORBENT DOSE: 0.1G; INITIAL CONCENTRATION: 5.0 MG L−1; TEMPERATURE: 30°C;

CONTACT TIME: 20 MIN; AGITATION: 100 RPM). (B) PERCENTAGE REMOVAL OF CD(II)

CONCENTRATION AS A FUNCTION OF BIOSORBENT DOSE (PH: 5.0; INITIAL CONCENTRATION:

5.0 MG L−1; TEMPERATURE: 30°C; CONTACT TIME: 20 MIN; AGITATION: 100 RPM). (C)

EFFECT OF CONCENTRATION OF CD(II) ON THEIR PERCENT REMOVAL OVER P. ERYNGII (PH:

5.0; BIOSORBENT DOSE: 0.2 G; TEMPERATURE: 30°C; CONTACT TIME: 20 MIN; AGITATION:

100 RPM). (D) PERCENTAGE REMOVAL OF CD(II) CONCENTRATION AS A FUNCTION OF

TEMPERATURE (PH: 5.0; BIOSORBENT DOSE: 0.2 G; INITIAL CONCENTRATION: 20 MG L−1;

CONTACT TIME: 20 MIN; AGITATION: 100 RPM). .............................................................. 70

FIGURE 4.17 PERCENTAGE REMOVAL OF CD(II) CONCENTRATION AS A FUNCTION OF CONTACT

TIME (PH: 5.0; BIOSORBENT DOSE: 0.2 G; INITIAL CONCENTRATION: 20 MG L−1;

TEMPERATURE: 50°C; AGITATION: 100 RPM). ................................................................. 71

FIGURE 4.18 (A) LANGMUIR AND (B) FREUNDLICH ISOTHERMS FOR THE BIOSORPTION OF CD(II)

IONS ON P. ERYNGII FUNGAL BIOMASS. ........................................................................... 72

FIGURE 4.19 VAN’T HOFF PLOT, LOG KC VERSUS 1/T. ............................................................. 73

FIGURE 4.20 THE KINETIC FITTING PLOTS (A) PSEUDO FIRST ORDER AND (B) PSEUDO SECOND

ORDER FOR THE BIOSORPTION OF CD(II) IONS ON P. ERYNGII FUNGAL BIOMASS. ................ 75

FIGURE 4.21 INTRA PARTICLE DIFFUSION FOR THE BIOSORPTION OF CD(II) IONS ON P. ERYNGII

FUNGAL BIOMASS. ........................................................................................................ 76

FIGURE 4.22 (A) INFLUENCE OF VARIOUS ELUENTS ON PERCENTAGE RECOVERY OF CD(II) IONS BY

P. ERYNGII FUNGAL BIOMASS. (B) DESORPTION EFFICIENCY OF P. ERYNGII WITH CYCLE

NUMBER. ..................................................................................................................... 77

FIGURE 4.23 SEM IMAGES OF P. ERYNGII BEFORE AND AFTER HG(II) BIOSORPTION (A & B); EDX

ANALYSIS OF P. ERYNGII BEFORE AND AFTER HG(II) BIOSORPTION (C & D). ...................... 81

FIGURE 4.24 FTIR SPECTRA OF P. ERYNGII BEFORE (A) AND AFTER (B) HG(II) IONS BIOSORPTION.

................................................................................................................................... 82

XV

FIGURE 4.25 (A) PERCENTAGE REMOVAL OF HG(II) IONS AS A FUNCTION OF PH (TEMPERATURE:

30°C; AGITATION:100 RPM; BIOSORBENT DOSE: 0.1 G; INITIAL CONCENTRATION: 1.0 MG L−1;

CONTACT TIME: 30 MIN). (B) PLOT OF PHI VS. ΔPH TO OBTAIN POINT OF ZERO CHARGE

(PHPZC) VALUE FOR THE PROPOSED BIOSORBENT P. ERYNGII FUNGAL BIOMASS. .................. 84

FIGURE 4.26 PERCENTAGE REMOVAL OF HG(II) ION AS A FUNCTION OF BIOSORBENT DOSE (PH:

7.0; TEMPERATURE: 30°C; AGITATION: 100 RPM; INITIAL CONCENTRATION: 1.0 MG L−1;

CONTACT TIME: 30 MIN)................................................................................................ 85

FIGURE 4.27 PERCENTAGE REMOVAL OF HG(II) ION AS A FUNCTION OF BIOSORBENT DOSE (PH:

7.0; TEMPERATURE: 30°C; AGITATION: 100 RPM; BIOSORBENT DOSE: 0.25 G; CONTACT TIME:

30 MIN). ...................................................................................................................... 85

FIGURE 4.28 PERCENTAGE REMOVAL OF HG(II) AS A FUNCTION OF CONTACT TIME (PH: 7.0;

TEMPERATURE: 30°C; AGITATION: 100 RPM; BIOSORBENT DOSE: 0.25 G; INITIAL

CONCENTRATION: 7.5 MG L−1). ...................................................................................... 86

FIGURE 4.29 PERCENTAGE REMOVAL OF HG(II) AS A FUNCTION OF CONTACT TIME (PH: 7.0;

AGITATION: 100 RPM; BIOSORBENT DOSE: 0.25 G; CONTACT TIME: 5 MIN; INITIAL

CONCENTRATION: 7.5 MG L−1). ...................................................................................... 87

FIGURE 4.30 LANGMUIR PLOT FOR HG(II) BIOSORPTION ON P. ERYNGII BIOMASS. ...................... 88

FIGURE 4.31 FREUNDLICH PLOT FOR HG(II) BIOSORPTION ON P. ERYNGII BIOMASS. ................... 89

FIGURE 4.32 LAGERGREN / PSEUDO FIRST ORDER PLOTS FOR HG(II) BIOSORPTION ON P. ERYNGII

BIOMASS AT 30°C......................................................................................................... 89

FIGURE 4.33 HO-MCKAY / PSEUDO SECOND ORDER PLOTS FOR HG(II) BIOSORPTION ON ............ 90

FIGURE 4.34 VAN’T HOFF PLOT, LOG KC VERSUS 1/T. ............................................................. 91

FIGURE 4.35 SEM/EDX IMAGES OF P. ERYNGII BIOMASS: (A) AND (C) ARE UNLOADED; WHILE (B)

AND (D) ARE F- LOADED PATTERN OF FUNGAL BIOSORBENT. ............................................ 96

FIGURE 4.36 FTIR SPECTRA OF P. ERYNGII (A) BEFORE AND (B) AFTER F- SORPTION. .................. 98

FIGURE 4.37 IC-CHROMATOGRAM OF F- STANDARDS. ............................................................. 98

FIGURE 4.38 LINEAR CALIBRATION PLOT OF F- AT DIFFERENT CONCENTRATIONS. ...................... 99

FIGURE 4.39 (A) PERCENTAGE REMOVAL OF F- CONCENTRATION AS A FUNCTION OF PH

(BIOSORBENT DOSE: 0.1G; INITIAL CONCENTRATION: 5.0 MG L−1; TEMPERATURE: 30°C;

CONTACT TIME: 240 MIN; AGITATION: 100 RPM). (B) EFFECT OF CONCENTRATION OF F- ON

THEIR PERCENT REMOVAL OVER P. ERYNGII (PH: 2.0; BIOSORBENT DOSE: 0.1 G;

TEMPERATURE: 30°C; CONTACT TIME: 240 MIN; AGITATION: 100 RPM). (C) PERCENTAGE

REMOVAL OF F- CONCENTRATION AS A FUNCTION OF BIOSORBENT DOSE (PH: 2.0; INITIAL

CONCENTRATION: 5.0 MG L−1; TEMPERATURE: 30°C; CONTACT TIME: 240 MIN; AGITATION:

100 RPM). (D) PERCENTAGE REMOVAL OF F- CONCENTRATION AS A FUNCTION OF CONTACT

TIME (PH: 2.0; BIOSORBENT DOSE: 0.2 G; INITIAL CONCENTRATION: 5.0 MG L−1;

TEMPERATURE: 30°C; AGITATION: 100 RPM). ................................................................100

FIGURE 4.40 ADSORPTION ISOTHERMS PLOT (A) LANGMUIR, (B) FREUNDLICH, AND (C) D-R. ....102

FIGURE 4.41 VAN’T HOFF PLOT, LOG KC VERSUS 1/T. ............................................................104

XV

FIGURE 4.42 PSEUDO FIRST ORDER (A), PSEUDO SECOND ORDER (B), AND INTRA PARTICLE

DIFFUSION KINETIC MODELS (C) PLOTS FOR THE SORPTION OF F- IONS ONTO FUNGAL

BIOMASS. ....................................................................................................................106

FIGURE 4.43 EFFECT OF CO-EXISTING ANIONS ON F- REMOVAL (PH: 2.0; BIOSORBENT DOSE: 0.2 G;

INITIAL F- CONCENTRATION: 2.0 MG L−1; CONTACT TIME: 240 MIN; AND TEMPERATURE:

30°C). ........................................................................................................................108

FIGURE 4.44 (A) DESORPTION OF F- BY DIFFERENT DESORBING AGENTS (INITIAL F-

CONCENTRATION 2.0 MG L−1; BIOSORBENT DOSE: 0.2 G; CONTACT TIME 30 MIN; AND

TEMPERATURE 30°C). (B) DESORPTION EFFICIENCY OF P. ERYNGII WITH CYCLE NUMBER. .109

FIGURE 4.45 POSSIBLE MECHANISM ON SURFACE OF BIOMASS. ................................................111

FIGURE 4.46 SEM MICROGRAPHS OF (A) UNLOADED AND (B) NO3- LOADED P. ERYNGII FUNGAL

BIOMASS. ....................................................................................................................114

FIGURE 4.47 EDX SPECTRA OF (A) UNLOADED AND (B) NO3- LOADED P. ERYNGII FUNGAL BIOMASS.

..................................................................................................................................115

FIGURE 4.48 AFM IMAGES OF P. ERYNGII FUNGAL BIOSORBENT BEFORE (A) AND AFTER NO3-

SORPTION (C); THREE-DIMENSIONAL IMAGES OF P. ERYNGII FUNGAL BIOSORBENT BEFORE

AND AFTER NO3- SORPTION (B AND D). ..........................................................................116

FIGURE 4.49 UV-VIS SPECTRA OF NO3- AT DIFFERENT CONCENTRATIONS. ...............................117

FIGURE 4.50 LINEAR CALIBRATION PLOT FOR DIFFERENT NO3- CONCENTRATIONS. ...................117

FIGURE 4.51 PREDICTED RESPONSE VERSUS ACTUAL RESPONSE. .............................................121

FIGURE 4.52 NORMAL % PROBABILITY VERSUS RESIDUAL ERROR. ...........................................122

FIGURE 4.53 3D RESPONSE SURFACE PLOTS OF NO3- BIOSORPTION BY P. ERYNGII FUNGAL BIOMASS

SHOWING VARIABLE INTERACTIONS BETWEEN (A) PH AND BIOSORBENT DOSE; (B) PH AND

CONCENTRATION OF NO3-; AND (C) BIOSORBENT DOSE AND CONCENTRATION OF NO3

-. ....123

FIGURE 4.54 BREAKTHROUGH CURVES FOR DIFFERENT FLOW RATES (INITIAL PB(II) ION

CONCENTRATION: 10 MG L-1; BED HEIGHT: 2 CM). .........................................................127

FIGURE 4.55 BREAKTHROUGH CURVES FOR DIFFERENT PB(II) ION CONCENTRATION (FLOW RATE: 1

ML MIN-1; BED HEIGHT: 2 CM). .....................................................................................128

FIGURE 4.56 (A) BREAKTHROUGH CURVES FOR DIFFERENT BED HEIGHT (FLOW RATE: 1 ML MIN-1;

INITIAL PB(II) ION CONCENTRATION: 20 MG L-1) AND (B) BED DEPTH SERVICE TIME PLOT FOR

THE ADSORPTION OF PB(II) IONS BY FUNGAL BIOMASS IN COLUMN. .................................130

XV

ABBREVIATIONS

Pleurotus eryngii P. eryngii

PDA Potato Dextrose Agar

GPB Glucose Peptone Broth

Pb(NO3)2 Lead Nitrate

3CdSO4·8H2O Cadmium Sulphate

NaF Sodium Fluoride

KNO3 Potassium Nitrate

HgCl2 Mercuric Chloride

WHO World Health Organization

EPA Environmental Protection Agency

ppm Part Per Million

ppb Part Per Billion

F-AAS Flame Atomic Absorption Spectroscopy

HG-AAS Hydride Generation-Atomic Absorption Spectroscopy

IC Ion Chromatograph

UV-Vis Ultraviolet-Visible Spectrophotometry

FTIR Fourier Transform Infrared Spectroscopy

SEM-EDX Scanning Electron Microscope-Energy Dispersive X-ray

EDS Energy Dispersive Spectroscopy

AFM Atomic Force Microscope

D-R Dubinin-Radushkevich

RSM Response Surface Methodology

XV

CCD Central Composite Design

ANOVA Analysis of Variance

BDST Bed Depth Service Time

HCl Hydrochloric Acid

NaOH Sodium Hydroxide

H2SO4 Sulfuric Acid

HNO3 Nitric Acid

NaCl Sodium Chloride

EDTA Ethylenediaminetetraacetic acid

KBr Potassium Bromide

Na2BO4 Sodium Borate (Borax)

1

CHAPTER 1

INTRODUCTION

This chapter contains motivation, contributions of this thesis and general

introduction of environmental pollution. It specifically covers the effect of heavy

metals and anionic contamination of aqueous environment along with their

hazardous impact on human health. Previously reported methods for the removal

of toxic contaminants and their disadvantages were described along with

extensive description of biosorption technique as main objectives in this chapter.

At the end of the chapter, structure of rest of the thesis were present.

1.1 MOTIVATION

The discharge of toxic heavy metals and anions in water system is an emerging

community health related issue existed all over the world but in Pakistan as an under-

developed country and its region like Tharparkar and adjoining areas, the problem

identified as a massive public health issue, which requires the serious response from

the concern authorities. The people getting indulged in severe diseases just

because they have no direct method to decrease the level of toxins in water they

use to drinking purpose. Although extensive work has been done in the developed

world, additionally these studies were provide an awareness and cost-effective

remediation techniques to the community. Hence, the aim of present study was to

provide an efficient, cost effective, and environmental friendly biosorption

method with its potential in removing selected metals and anions from aqueous

system followed by application in real water samples of affected and adjoining

areas.

1.2 CONTRIBUTIONS OF THE THESIS

As water contamination cause severe environmental harm in the earth so new

methodologies with economic viability and easy processing in ecological

2

samples are emerging need. The detailed work in this thesis provides an

importance of fungus as a biosorbent and benefits of using biosorption

technique. It contributes to the removal of toxic metals and anions entered in to

the water system through natural or anthropogenic sources. P. eryngii potential is

explored first time extensively for the removal of toxic pollutant (metals /

anions), after an appropriate optimization of experimental variables and studying

isotherms, thermodynamics and kinetics of the sorption process.

1.3 ENVIRONMENTAL POLLUTION

Environmental pollution has turned into a key concentration of worry for every

one of the countries around the world, as the developing countries as well as

developed nations too are influenced by and experience the ill effects of it.

Pollution has many structures, the air we inhale, the water we drink, the ground

where we cultivate food crops and even the expanding noise we hear ordinary all

add to medical issues and lower personal satisfaction [1]. Among all the

ecological contaminations, contamination of water assets involves incredible

concern. Developing nations are at high hazard because of absence of waste

water treatment advances. The water of aquatic systems gets polluted by

household exercises, mining exercises, municipal wastes, present day rural

practices, marine dumping, radioactive squanders, oil spillage, underground

stockpiling spillages and enterprises. Regardless, the significant offenders

bringing on the contamination of water assets are diverse modern units [2].

Unpredictable release of poisonous chemicals through effluents from an

extensive variety of ventures (i.e. material, steel, oil, tanneries, canneries,

refineries, mines, manures generation units, cleanser creation units,

electroplating units and sugar factories) into water bodies pollutes these assets

and causes hazardous effects on environmental bodies. For these reasons, the

presence of toxic ions in the environment at concentrations above critical values

is unacceptable and their removal from the environment is of primary importance

[3].

3

1.3.1 POLLUTION IN AQUEOUS SOLUTIONS

Contamination of aqueous resources by excessive presence (high concentrations)

of metal ions and anions has become a serious concern worldwide over the past

few decades. These ions enter the water assets through both regular and

anthropogenic sources. Their release into the environment represents a real

concern for human health and environmental toxicology [1-3].

1.3.2 HEAVY METAL POLLUTION

The heavy metals are characteristic part of the earth’s crust. Continuous leaching

of these metals causes the contamination of air, water, and food; due to which a

minor extent of these metals indirectly enter into the human bodies. In

comparison to all, a few heavy metals (e.g. copper, selenium, zinc) played a key

role in up keeping human body digestion. Heavy metal spoiling may possibly

come about because of drinking water desecration; high encompassing air

fixations in close discharge sources, or by means of the natural way of life [5, 6].

The word heavy metal states to any metallic element with relatively high density

(> 5.0 g cm-3). They classified in to three categories: precious metals (i.e.

platinum (Pt), gold (Au), silver (Ag), palladium (Pd), ruthenium (Ru), etc); toxic

metals (i.e. arsenic (As), cadmium (Cd), lead (Pb), mercury (Hg), copper (Cu),

etc); and radio nuclides (uranium (U), thorium (Th), radium (Ra), etc) [7].

Unlike most of the organic toxins, the heavy metals are non-biodegradable type

of test material for remediation process. Owing to its bio-accumulative nature,

their excessive level (concentration) are toxic for living being. The disposal of

waste matter by most of the industries is the major cause of heavy metal

contamination in water system i.e. lakes, streams, groundwater and waterways

[8]. As opposed to other potential toxicants, heavy metals can't be readily

eliminated from a water body. They have strong bonding property to hold on in

silt from where they gradually discharged into the water.

4

Table 1.1 Common sources, health problems and maximum acceptable

concentration level by the WHO of some toxic heavy metals [9].

Pollutant Source of exposure Health aspects Acceptable

concentration level

Toxic metal

Iron (Fe)

Indiscriminate discharge

of toxic chemicals

through effluents from a

wide range of industries.

Poor growth, heart

failure and diabetes. 0.1 mg L−1

Copper (Cu)

Energy and fuel

production, manufacture

of electrical appliances,

aerospace and atomic

energy installation.

Anemia, liver and

kidney diseases,

polyneuritis, and

brain damage.

1.0 mg L−1

Lead (Pb)

Paint and dyes production

industries, mining,

smelting and metal

plating, battery

manufacturing,

ammunition production,

and paper and pulp

processing.

Detrimental effects

on the central

nervous system,

blood circulation

system, basic

cellular processes

and brain functions,

kidneys and

reproductive

system.

0.05 mg L−1

(50 ppb)

Zinc (Zn)

Municipal wastewater

treatment & galvanizing

plants, natural ores, acid -

mine drainage.

Liver, kidney and

pancreas damage. 5.0 mg L−1

Cadmium (Cd)

Incineration of fossil

fuels, manufacturing of

batteries, metal

production plants,

fertilizers, refining

processes, electroplating,

smelting, alloy industries,

mining, pigment and

screens.

Teratogen and

carcinogen with

severe effect on

liver, lungs,

kidneys, and

reproductive organs

when enters in

human body via

food, water,

breathing or

smoking.

0.003 mg L−1

(3 ppb)

Mercury (Hg)

Generated by

pharmaceuticals, textile

industries, pulp and paper

chloralkali, oil refining,

paint, rubber processing,

electrical and fertilizer.

Bio-accumulative

nature affect the

central nervous

systems and

endocrine glands.

Extensive exposure

cause brain damage

and in extreme

circumstances,

death.

0.001 mg L−1

(1 ppb)

5

Being non-biodegradable, these metals collect at tropic levels through natural

pecking order and can bring about human health problems. In people, these

metals gather in living tissues and in this way, replicate the risk. Some health

impacts and wellbeing dangers of some heavy metals to individuals are given in

Table 1.1. The wellbeing dangers of heavy metals ingestion accordingly are of

wide range. A few metal cause physical distresses while others may bring life-

threatening illness, harm to indispensable body framework, or cause different

harms [9-12]. Thus, it is extremely important to control emanation of heavy

metals into the environment.

1.3.3 ANIONIC POLLUTION

Anions are radicals (gatherings of particles) that have a negative charge and can

gain electrons. Various anionic species, (such as fluoride, nitrate, nitrite,

chloride, sulfide, and cyanide) might be considered as toxins when present in

water supplies over specific levels. Additionally, their bioaccumulation turns

into an ecological concern when their focuses in the earth start to influence

human wellbeing and environments [4]. Many of these species occurs naturally

in the atmosphere, water, and soil.

Besides their natural occurrence in the ecosystem, they have extensive

application in several horticultural and industrial sectors which gives

unavoidably ascend to their discharge and scattering into the earth [5].

Contamination of aqueous solutions by these toxic contaminants may represent a

public health problem given their harmful effects on living organisms.

Consequently, many countries and environmental protection agencies have been

forced to implement limiting standards for drinking water and discharges of

industrial wastewaters [6]. As a result, removal of such compounds from

wastewaters becomes crucial toward the conservation of human's wellbeing and

condition. Some normal sources, wellbeing effects to people and restricting

benchmarks of anions are given in Table 1.2.

According to the latest estimation; about 200 million people from 25 nations

across the world are passing through the alarming fate of fluorosis [22].

Meanwhile in Pakistan a few of dry zones are severely under the influence of

fluoride contamination. Predominantly the locality of district Tharparkar, Sindh

6

(Mithi, Diplo, Chachro and Nagarparkar) is severely affected by fluoride

contamination. People in these areas rely heavily on underground water sources

due to unavailability of rivers. Some reports [7, 8] have shown high fluoride

contamination in the water of aforementioned areas of Pakistan and proven to be

the major source of illness.

Table 1.2 Common sources, health problems and maximum acceptable

concentration level by the WHO of some toxic anions [9, 11].

Pollutant Source of exposure Health aspects

Acceptable

concentration

level

Toxic anion

Fluoride (F-)

Natural and

anthropogenic sources

are the major cause of

surplus fluoride levels

in drinking and ground

water.

Increase the prevalence

of fluorosis (dental and

skeletal) in children

and adults.

1.5 mg L−1

Nitrate (NO3-)

Exploitation of

nitrogen based

fertilizers and the

uncontrolled

discharges of raw from

industrial processes,

degradation of nitrogen

containing compounds

from natural sources as

soil, bedrock.

Induction of blue -

baby syndrome i.e.,

methemoglobinemia in

infants, formation of

carcinogenic

nitrosamines in adults,

dyspepsia, abdominal

pain, diarrhea, blood

in stool and urine,

weakness, nausea,

depression, head -

ache.

50 mg L−1

Sulphate (SO42-)

Ion exchange,

biological degradation,

membrane filtration,

adsorption and /or ion

exchange and chemical

precipitation.

Altered taste of water,

digestion troubles in

animals and humans. 500 mg L−1

7

1.4 CONVENTIONAL TECHNIQUES USED FOR THE REMOVAL OF

TOXIC METALS AND ANIONS FROM AQUEOUS SOLUTIONS

A few physico-chemical techniques like chemical precipitation, electro-dialysis,

reverse osmosis, ion-exchange, ultra-filtration, adsorption and so forth are usually

utilized for stripping poisonous heavy metals and anions from waste waters. Brief

description of each method is introduced underneath:

1.4.1 CHEMICAL PRECIPITATION

Chemical precipitation is one of the substantial treatment method for the

extraction of metal ions from aqueous solutions [9]. This technique is

accomplished by the expansion of coagulants, for example, lime, alum, press

salts and other natural polymers. The renowned precipitation techniques that’s

utilized by enterprises are sulfide precipitation, carbonate precipitation and

sodium hydroxide precipitation. The disadvantage related to chemical

precipitation technique is the production of large amount of toxic sludge during

the process.

1.4.2 ELECTRO-DIALYSIS

In this process, the ionic constituents of heavy metal were isolated by semi-

permeable ion-selective membranes [10]. Consumption of an electric potential

between the two cathodes causes the movement of cation and anions towards

respective terminals. Because of the alternate spacing of ions in permeable

membranes, cells of concentrated and dilute salts are formed. The disadvantage

of this technique is the arrangement of metal hydroxides, which stop up the layer

and in this way cost included is high.

1.4.3 REVERSE OSMOSIS

The technique of reverse osmosis were generally exploits for the desalination of

drinking water [11]. In earlier decades, a specific exertion has been made in this

technique for the recovery of concentrated metal salt solution and to clean up

aqueous solutions. Normally, the process of metal ion (dissolved solids)

separation via semi-permeable membrane were occur due to the development of

8

pressure more than osmotic pressure between the ions and waste water. The

major disadvantage that limit the application of this process is the cost of

membrane.

1.4.4 ION-EXCHANGE

From quite a few years, the ion exchange technologies have been effectively used for

the interchange of metal ions from dilute solutions on the ion-exchange resin via

electrostatic force of attraction [12]. Typically, the hindrances incorporate excessive

budget and fractional expulsion of specific particles. The process also have limitations

for bulky quantities of opposing monovalent (Na+1) and divalent (Ca+2) ions [13].

1.4.5 ULTRA-FILTRATION

The ultra-filtration process is based upon the utilization of pressure driven

permeable membrane for the discharge of toxic heavy metals [14]. The

generation of extensive sludge is the primary deficit of this process.

1.4.6 ADSORPTION

In the process of adsorption, various adsorbents were used for the removal of

toxic ions from contaminated water phase [15]. Usually amorphous form of

adsorbents were used to increase the surface zone or volume extent.

The above expressed strategies are effective for removal of metals and anions from

aqueous solutions with high concentration of metals while for low concentrations

(ppb, ppm level) of contaminants these methods are not exceptionally

productive. These techniques additionally have other a few inconveniences, such

as incomplete removal, limited tolerance to pH change, expensive equipment and

monitoring system requirements, high reagent or energy requirements and

generation of toxic sludge or other waste products that require disposal [27].

9

1.5 THE REQUIREMENT OF NOVEL INNOVATION FOR THE REMOVAL

OF TOXIC METALS AND ANIONS

To overcome the limitations of physicochemical treatments, an effective and

environmental friendly technique is the fundamental requirement for the removal

of toxic ions.

For this purpose, a green and a cost-effective solution biological treatment i.e.,

biosorption has attained more attention for heavy metals / anions removal [16].

Biosorption is the physicochemical process of toxic pollutant uptake by naturally

available biomass onto its cellular structure [17].

In this process two phases were involved:

• A solid phase of biomass material and

• A liquid phase (normally water) with dissolved quantity of sorbate (metal /

anions).

By means of several complex mechanisms, the sorbate species attract and bound

toward the higher affinity of the sorbent surface. The procedure of sorption

continues till an appropriate equilibrium is achieved among the specific quantity

of sorbent bounded sorbate and its residual portion in contaminated solution.

Typically, the biosorption of heavy metals occurs rapidly (20-60 min), because it

is independent from metabolism. After this period, the uptake of cationic metal

ion becomes slower [18].

1.5.1 HISTORY OF BIOSORPTION

In early 18th and 19th eras, the ionic (metal / anion) uptake capacity of many

important living micro-organisms from contaminated aqueous solution were

examined [19]. A few decades ago, the application of biosorption technique on

aqueous samples was very limited. The process were significantly used by the

industrialists to resolve sewage concerns and to renovate the wastewater that is

produced by the chemical industries [20].

10

1.5.2 ADVANTAGES OF BIOSORPTION TECHNIQUE

The studies of life sciences experts mainly focused on the accumulation effects

of toxic pollutants in microorganisms, whereas an environmental researcher used

this ability of microorganisms (algae, fungi, bacteria) for removal / recovery of

heavy metals or anion from contaminated waters [21].

The significant features of biosorption technique are [22]:

• Offers short capital investment,

• Special selectivity for targeted ions,

• Effective on removal of toxic ions (metals and anions) from effluent,

• The processing is fast, and

• Multiple-time reuse of ion loaded biomass after suitable desorption.

1.5.3 BIOSORBENTS / BIOLOGICAL MATERIAL / BIOMASS

Biosorbents are different sorts of biomaterials (waste or naturally abundant

biomass) that have been utilized in chemical and microbiology research

laboratories for metal and anion adsorption such as; pine barks, wheat bran, tea

leaves, plant tissues, banana pith, tree sawdust, seaweeds, shea butter seed husks,

date stones, brown algae, sugar-beet pulp nut shells, sugarcane bagasse, maize

and rice husks, sunflower stalk, coconut fiber, activated sludge, almond hulls,

and so forth [16, 23, 24]. The majority of these biosorbents are of plant origin

and predominantly agricultural by products. All these biomaterials have been

inspected for their biosorption properties. Diverse level of metal / anion uptakes

has been obtained that are high enough yet low-cost, which added to the pool of

non-tested biomaterial in the world, justifying further research on biosorption

[37].

Recently, numerous biomass of algae, and other microscopic organisms [101-

114] have been utilized as biosorbents. Researches are being made on exploiting

cellulosic nature nonpathogenic biological material as a dynamic asset for

efficient removal of poisonous metals and anions from water system.

11

1.6 EXPECTED MECHANISMS INVOLVE IN BIOSORPTION

Due to the complex cellular structure of microbes (algae, fungi, bacteria), it is

assumed that various pathways may possibly involve in the ionic up take.

The binding mechanism of dead cell (non-living) / inactivated biosorbent depend

upon:

• Physico-chemical nature of contaminant (i.e., size, species type, ionic

charge),

• Nature of the biomass with its definite surface properties, and

• Controlled environmental parameters (i.e., temperature, ionic strength, pH,

existence of competing ions in the solution) [3].

On the basis of cell metabolism, the mechanism of biosorption process were

divided into:

1.6.1 METABOLISM DEPENDENT

Active uptake (slower uptake) is metabolism dependent, causing the transport of

ions across the cell membrane into the cytoplasm for intracellular accumulation

[38]. This biosorption is valid only for viable cells.

1.6.2 NON-METABOLISM DEPENDENT

It is the passive uptake (rapid uptake) of ions on microbial surface within a short

span of time through physico-chemical (ion exchange, complexation,

coordination and chelation) interaction [25]. The basis of uptake is the presence

of functional groups on the cellular surface.

On the basis of ionic removal from contaminated aqueous solution and their

attachment at specific sites of biomass, the biosorption mechanism divided into:

1.6.3 EXTRA CELLULAR ACCUMULATION / PRECIPITATION

This biosorption mechanism may possibly dependent or independent of biomass

cellular metabolism [40].

12

1.6.4 CELL SURFACE SORPTION / PRECIPITATION

In this mechanism [38], the removal of toxic pollutant (either metal or anion)

occurs both in the aqueous phase as well as on the surface of microbe cell wall.

It should also keep in view that, the precipitation process may not be reliant on

cell’s metabolism. But in few circumstances, the presence of toxic metals

enhance the microorganism’s cell metabolism which in turn help releasing the

compounds that favors the precipitation.

1.6.5 INTRACELLULAR ACCUMULATION / COMPLEXATION

The intracellular accumulation [39] involves complexation of ions and reduction

in their toxicity by several species specific processes like phyto-chelatin

reactions, hypertrophying and multiplication of the polyphosphate bodies.

1.6.6 ION EXCHANGE

The cell wall of micro and macro-organisms comprises of polysaccharides which

are responsible for various ionic functionalities on the surface [40]. Usually,

these charged functional groups cause an ion exchange mechanism during

biosorption.

1.6.7 PHYSICAL ADSORPTION

The primary reason of physical adsorption is the presence of Van der Waal’s

forces [25]. In non-living microbial biomass, the process of biosorption in

aqueous system takes place through the electrostatic force of attractions between

the pollutant and the microbe cell surface.

1.7 FACTORS AFFECTING BIOSORPTION

The factors affecting biosorption of a specific metal or anion by a certain

biomass are:

1.7.1 PH

The parameter of solution pH played a significant role in the biosorption process

due to its direct effect on metal - solution chemistry [25]. By means of pH, the

13

expected surface mechanism between the sorption active functionalities of

biomass and that of metallic ions were anticipated.

1.7.2 BIOMASS CONCENTRATION

The specific quantity of biomass (concentration) also had a visible effect on the

biosorption efficiency [26]. Usually in contaminated solution, the lower

concentration of biomass increases the ion uptake while further increment cause

to hinder the particular binding sites.

1.7.3 TEMPERATURE

The temperature had an intermittent effect on the biosorption performance since

most of the reactions are exothermic in nature [27]. However, in some exceptions

metal ions and biomass-metal complex stability and ionization of cell wall

chemical parts can be influenced by temperature.

1.7.4 INTERFERING IONS

The process of biosorption is mainly exploit for the treatment of contaminated

drinking water with more than one type of ion [24]. Therefore, the occurrence of

interfering ions would also had an influence on sorption efficiency of specific

metal of interest.

1.8 DESORPTION

This process is remarkably important together with biosorption. It is use to

recover the biosorbed ion after sorption and to keep the cost of process down

[34]. An ultimate desorption efficiency based upon desorption of sorbed ion from

biosorbent and their regeneration with no physical changes or damage for

another cycle of application.

1.9 CHOICE OF TOXIC METAL AND ANION FOR BIOSORPTION

PROCESS

The process of biosorption is used for the treatment of harmful pollutants (metal

cation and anions) from contaminated drinking water. Generally for biosorption

14

study, the selection of toxic heavy metals and anions ion is highly depend upon

their environmental impact.

For this research, specific metals i.e. Pb, Cd, Hg and anions i.e. F-, NO3- were

chose on the basis of their toxicity level and high degree of anthropogenic

discharge into the environment (Table 1.1, 1.2).

1.10 EVALUATION OF BIOSORPTION PROCESS

Biosorption isotherm, models of column data, kinetic models and

thermodynamic parameters are used to evaluate the sorption phenomenon

between the surface of biosorbent and sorbate during sorption reaction.

1.11 ISOTHERM STUDY (BIOSORPTION ISOTHERMS)

Biosorption isotherms are the way of presentations of amount of solute sorbed per

unit of sorbent. Langmuir, Freundlich, Temkin and D-R sorption isotherm models

were applied to evaluate the sorption phenomenon between surface of sorbent

(biological material) and sorbate (pollutant in solution) during sorption reaction.

These isotherms [43] gives:

• The qualitative statistics of the biosorption progress, and

• The degree of biomass surface coverage by sorbate.

1.11.1 LANGMUIR SORPTION ISOTHERM

This theory assumes a monolayer coverage of sorbate (metal / anion) over a

uniform sorbent surface [28]. The linear form of Langmuir isotherm model is

represented as equation 1:

Cq

= 1Qb + C

Q− − − −(1)

where qe is the amount of metal ion / anion sorbed per unit mass of sorbent (mg

g−1), Ce is the amount of metal ion / anion in liquid phase at equilibrium (mg L-

1), Q0 is the monolayer sorption capacity (mg g−1) and b is the Langmuir constant

related to the free energy of sorption (L mg-1).

15

The essential characteristics of Langmuir isotherm model can be expressed in

terms of dimensionless constant separation factor RL which has four

probabilities:

(1) 0 < RL <1, favorable adsorption; (2) RL > 1, unfavorable adsorption;

(3) RL = 1, linear adsorption; and (4) RL = 0, irreversible adsorption.

The separation factor RL is calculated using equation 2:

R = 1(1 + bC) − − − −(2)

1.11.2 FREUNDLICH SORPTION ISOTHERM

The Freundlich model assumes that stronger binding sites on the biosorbent

surface are occupied first and that the binding strength decreases with increasing

degree of site occupation by sorbate [29]. For fitting the model to experimental

data, the model generally gives a better fit for higher equilibrium concentration

of sorbate in solution.

The linear form of this isotherm describes the formation of multi layers of the

adsorbate on the heterogeneous sorbent surface is represented as equation 3:

lnq = lnK + 1nlnC

− − − −(3)

where KF and n are the constants incorporating all factors affecting the

adsorption process (adsorption capacity and intensity). These constants were

determined from a plot of qe vs. Ce. The n-values (sorption intensity indicator)

are between 1 and 10 represent beneficial adsorption.

1.11.3 TEMKIN SORPTION ISOTHERM

The Temkin isotherm theory assumed that the heat of adsorption (due to sorbent

- sorbate interactions) decrease linearly for all the molecular layer. According to

this model the sorption process is characterized by a uniform distribution of the

maximum bonding energy [30].

16

Here equation 4 represent the linear form of Temkin adsorption isotherm:

q = RTb

lnA + RTb

lnC − − − −(4)

Moreover, the amount of B is usually calculated with equation 5:

B = RTb

− − − −(5)

where R is universal gas constant (8.314J mol-1K-1); T is Temperature in K; bT is

Temkin isotherm constant (KJ mol-1) and is related to the temperature of

adsorption; A is Temkin isotherm equilibrium binding constant (L g-1) and B is

Constant related to heat of sorption.

The A value gives an idea about nature of adsorption, if A value is in between 0

and 8, then the adsorption is physical nature, otherwise it is chemical in nature.

1.11.4 D-R SORPTION ISOTHERM

To evaluate the type of adsorption process [30], the experimental equilibrium

data were applied to D-R sorption isotherm using equation 6:

lnq = lnq ! − K"#Ɛ$ − − − −(6)

where qe is the amount of metal ion / anion sorbed in mg g−1, qmax is the D-R

monolayer sorption capacity (mg g-1), KDR is a constant related to free energy

(mol2 J-2) and ε is Polanyi potential which is related as shown in equation 7:

Ɛ = RTln 1 + 1C

− − − −(7)

where T is temperature (K), R the gas constant (8.314 J mol-1 K-1) and Ce is the

equilibrium concentration of Pb(II) ions in (mg L-1). The sorption energy E (kJ

mol-1) can be obtained by equation 8:

E = 1(−2)*+

− − − −(8)

17

1.12 KINETIC STUDY (BIOSORPTION KINETIC ISOTHERMS)

In order to analyze the sorption kinetics and to calculate adsorbate uptake rate of

metal ion / anion by P. eryngii, two kinetic models i.e. Lagergren’s pseudo-first

order (PFO) and Ho-McKay’s pseudo-second order (PSO) [31] were applied.

These kinetic models give:

• Rate of adsorption process,

• Practical applicability,

• Information about the mechanism of the diffusion.

1.12.1 LAGERGREN’S PSEUDO FIRST ORDER KINETIC MODEL

The first order Lagergren’s rate equation is commonly used for the sorption

process and is calculated using equation 9:

ln(q − q-) = lnq − k/t2.303 − − − −(9)

where qt and qe represents the amounts of metal ion / anion (mg g-1) sorbed at

time t and equilibrium respectively, k1 is the Lagergren rate constant of the

pseudo first order sorption process (min-1).

1.12.2 HO-MCKAY’S PSEUDO SECOND ORDER KINETIC MODEL

The pseudo second-order kinetics of adsorption was applied to check the kinetic

mechanisms between sorbent and sorbate. The parameters k2 and qe was

calculated by using following the equation 10:

tq-

= 1k$q$

+ tq

− − − −(10)

where k2 represents the rate constant of pseudo second order sorption process (g

mg-1 min-1).

18

1.12.3 WEBER AND MORRIS INTRA PARTICLE DIFFUSION MODEL

For further confirmation about the exact mechanism Weber and Morris intra

particle diffusion (IPD) model [32] were applied which define that the intra

particle diffusion varies with the square root of time as equation 11:

q- = k45√t + C − − − −(11)

where kipd is the intra particle diffusion rate constant (mg g-1 min1/2) and C is

constant related to thickness of the boundary layer.

1.13 THERMODYNAMIC STUDY

The biosorption process is associated with several thermodynamic parameters

such as; change in Gibbs free energy (ΔGº), enthalpy (ΔHº), and entropy (ΔSº)

[33]. These parameters were calculated from the Van’t Hoff plot of lnKc versus

1/T according to the equation 12 and 13 respectively:

∆G° = −RTlnKc − − − −(12)

lnKc = − ∆H°

RT + ∆S°

R − − − −(13)

where R is the universal gas constant (0.00831 kJ mol-1 K-1), T is the absolute

temperature (K) and Kc is an equilibrium constant.

If the thermodynamic parameter of sorption process shows the negative value for

ΔGº and ΔHº at the studied temperature range, it confirms the spontaneous and

exothermic nature of biosorption and also indicate the feasibility of reaction at

elevated temperatures. It is reported [47] that enthalpy change data is useful for

distinguishing physio and chemosorption mechanism. Physisorption is typically

associated with heat of adsorption in the range of 2.1-20.9 kJ mol-1, while

chemisorptions are typically associated with much larger ΔHº values (20.9-418.4

kJ mol-1).

The negative value of ΔSº reflects the decreased randomness at the solid-liquid

interface during sorption; while the positive value of ΔS° indicate increased

randomness at the solid / liquid interface, it also illustrate the strong affinity of

19

biosorbent toward sorbate. Similarly, the value of entropy (> 0) demonstrates the

existence of a definite order for the toxic ion on sorbent surface.

1.14 STATISTICAL DESIGN OF EXPERIMENT

Response Surface Methodology (RSM) is an approach that assembles

mathematical and statistical tools for improving the optimization process for

maximum biosorption [34]. It could evaluate the relative significance of several

affecting factors in the presence of complex interactions and offers reduction in

number of experiments when there are several factors integrated in the study.

Central Composite Design (CCD) is one of the most powerful and efficient

experimental design among other response surface designs because of its ability

to find the best set of values for a set of factors giving an optimal response [35].

Since there are only three levels, the quadratic model is suitable.

Coding of the variables was done according to the following equation 14:

x = (X − X)ΔX

− − − −(14)

where Xi is the dimensionless value of an independent variable, Xi is the real

value of an independent variable, X0 is the real value of an independent variable

at the center point, and ΔXi is the step change of the real value of the variable i

corresponding to a variation of a unit for the dimensionless value of the variable

i.

For better accuracy, second-order polynomial response equation 15 was proposed

to correlate the dependent and independent variables:

Y = β + βA + βB + βC + βA$ + βB$ + βC$ + βBAB + βBAC + βBBC − (15)

where Y is the predicted response (biosorption efficiency of sorbate associated

with each factor level combination, β0 is the intercept, bi is the linear coefficient

of the input factor A, B, C; bii is the ith quadratic coefficient of the input factor

A, B, C; and bij is the different interaction coefficient between the input factor

AB, AC, BC.

The data were subjected to Analysis of Variance (ANOVA) and the coefficient

of regression (R2) was calculated to find out the quality of polynomial equation

(i = A, B, C)

20

and goodness of fit of the model. Moreover, investigations over different tests

such as desirability function, sequential model sum of squares, lack of fit tests,

model summary statistics helps in selecting the best model for describing the

relationship between the response and other influencing independent variable.

1.15 COLUMN MODELS

In process applications, a packed bed column is an effective process for cyclic

sorption / desorption, as it makes the best use of the concentration difference

known to be a driving force for pollutant sorption and results in a better quality

of the effluent. Two frequently used models i.e. Thomas and Bed Depth Service

Time (BDST) were used to analyze the compatibility of experimental data of the

tested metals.

1.15.1 THOMAS MODEL

The design of an adsorption packed column requires the determination of column

parameters such as adsorption capacity and the kinetic parameters [36]. The

Thomas model can be implemented to analyze the breakthrough curves and

adsorption capacity for each sorbent. The linearized form of Thomas model

expressed by equation 16:

ln CC − 1 = kCqm

Q − kCCEt − − − −(16)

where C0 and C are the inlet and the effluent solute concentrations at any time t

(m); kTh is the Thomas model constant (mL m-1 mg-1); q0 is the maximum solid-

phase concentration of solute (mg g-1); and M is the total mass of the adsorbent

(g). The model constants kTh and q0 can be determined from slope and intercept

of a plot of ln[(C0/C)-1] against t respectively.

1.15.2 BDST MODEL

The BDST model used to predict the column performance for any bed length, if

data for some depths are known. It relates the service time of a fixed bed with

the height of adsorbent in the bed, hence with its quantity. The measurement of

21

sorbent quantity is more precise than the determination of the respective volume

[37]. Therefore, sorbent quantity is being preferably used, instead of the bed

height.

The linear form of BDST model expressed as equation 17:

t = N ZCϑ − 1

K Cln C

CI− 1 − − − −(17)

where t is the service time (h), N0 is the adsorption capacity (mg cm-3), Z is the

height of column (cm), Cb is the breakthrough sorbate concentration (mg L-1), ϑ

is the linear velocity (cm h-1) and Ka is the rate constant (L mg-1 h-1) at time t. A

plot of t versus bed depth (Z) should yield a straight line and use to evaluate N0

and Ka, respectively. Application of the BDST model requires specification of

the breakthrough time, which was selected arbitrarily.

1.16 AIM AND OBJECTIVES OF PRESENT STUDY

The aim of the present study is to prepare a novel and cost effective fungal

biomass for the removal of toxic metals and anions from aqueous solutions with

following specific objectives:

Characterization of prepared fungal biomass (FTIR, SEM-EDX, AFM) before

and after sorption.

Optimization of a range of factors affecting biosorption (i.e.; pH, initial

concentration, biosorbent dose, temperature, and contact time) for favorable

biosorption of metals and anions under study.

To study the equilibrium, kinetics and thermodynamics of toxic metals i.e.

Pb(II), Hg(II), Cd(II) and anions (F-) removal by dried P. eryngii fungal

biomass in batch system.

Desorption study of sorbed ions from biomass surface and its reusability

studies along with determination of interfering ions during sorption of

targeted ion.

22

To optimize the biosorption capacity of anion (NO3-) removal by fungal

biomass in batch system using statistical Design of Experiments (DoE).

Application of proposed study on real water samples of affected areas along

with column study.

1.17 STRUCTURE OF THE THESIS

There are five chapters in this thesis and each chapter describes the structure of

this research.

CHAPTER 1 INTRODUCTION

This chapter highlights the alarming situation of aqueous environment arising

due to the developing industrialization and technology. It describes the

conventional processes used for the removal of toxic ions and their limitations.

In addition, an eco-friendly and economical treatment technology i.e. biosorption

with its significance and application were described. This chapter also presents

the problem statement, research objectives, scope of research and thesis

organization.

CHAPTER 2 LITERATURE REVIEW

A brief review of the synthetic and natural biosorbents history were covered in

this chapter along with detailed study of different microbial biomass utilized

previously for the removal of toxic heavy metals and anions. The morphology,

growth habitat and effectiveness of newly reported fungal biomass P. eryngii

were also discussed in this chapter of literature review.

CHAPTER 3 RESEARCH METHODOLOGY

All the chemicals, reagents and instruments used throughout the current study

are mentioned in this chapter along with experimental techniques followed in the

research for batch and packed bed column system. In addition, it covers the

investigation methodologies used for characterization of before and after

biosorption

23

CHAPTER 4 RESULTS AND DISCUSSION

The results and discussion chapter covering the experimental data with particular

facts for biosorption studies of toxic metals (Pb, Cd, Hg) and anions (F-, NO3-)

by P. eryngii fungal biomass in batch and packed bed column. The

characterization of the biosorbent and optimization of biosorption process as

well as isotherm, kinetics and thermodynamics were studied. The regeneration of

biosorbent and application to real samples for removal of targeted toxic metals /

anions were also investigated.

CHAPTER 5 CONCLUSION

This chapter states the entire inferences that are based on the outcomes acquired

in “Chapter 4” (Results & discussion). Recommendations for current scenario of

work along with future research directions were also mentioned in this section.

24

CHAPTER 2

LITERATURE REVIEW

In this chapter of literature review, previous reported investigations on synthetic

and naturally available biosorbents for the effective removal of toxic pollutants

from aqueous solutions were present.

2.1 SYNTHETIC ADSORBENTS USED FOR THE REMOVAL OF METALS

AND ANIONS

A broad research has been made on the removal of toxic metals and anions

utilizing synthetic adsorbent materials such as silica materials [38, 39], activated

red mud [40], Amberlite IRA 458 [41], Mg-Al layered double hydroxide [42],

activated alumina [43], fly ash [44], alum sludge [45], chitosan beads [46], red

mud [40, 47], zeolite [48], calcite [49], attapulgite [50], alumina and aluminium

[51, 52], modified activated alumina [53], iron-based adsorbents [54], metal

oxides / hydroxides / oxy hydroxides [52, 55, 56], mixed metal oxides [57],

metal-impregnated oxides [58] and acid treated spent bleaching earth [59], etc.

Yet, high cost, water soluble component nature, hard preparation and generation

of adsorbent waste is a serious environmental problem that cause limit in their

usage [60, 61].

2.2 NATURAL BIOSORBENTS FOR THE REMOVAL OF METALS AND

ANIONS

The biosorption is one of the accessible, reliable, and more affordable technique

to accumulate toxins from aqueous environment and sequester them for large

scale removal [16]. Particularly microbial biomass i.e. bacteria, algae, yeast and

fungi (live, dead or pre-treated) are low cost and efficient natural biosorbents. In

recent years, the screening of cellulosic origin sorbents and their sorption

performance has been studied by many researchers. Their investigations played a

25

key role in the formal application of biosorption technology and to comprehend

the sorption mechanism [33-40].

2.3 REMOVAL OF TOXIC METALS BY VARIOUS BIOSORBENTS

The removal of persistent and non-biodegradable toxic heavy metal ions by

varied micobial origin biomass (bacteria, algae, yeast, and fungi) is becoming an

important integrated approach and have extensively been reported in literature

[101-114].

2.3.1 BACTERIAL BIOSORBENTS

The biosorbents of bacteria were considered as the most abundant biomass

because of their smaller size, ability to grow in bulk (under controlled

conditions) and ubiquity. According to an investigation, most of the bacterial

colonies have versatile capability to constitute a major portion of terrestrial

biomass. During sorption studies of bacteria [101, 102], their resistance against

wide range of environmental conditions were also considered.

Though, the process of bacterial isolation, their appropriate harvesting

and screening for effective sorption is complicated on commercial scale; but still

this microbe has its broad usage as remediating species. It is estimated that the

metal removal capacities of the bacteria were came across in range between 0.70

- 568 mg g-1 [77].

El Bestawy et al. [62] in his studies of metallic bisorption isolate various species

of bacteria like Enterobacter, Stenotrophomonas, Comamonas,

and Ochrobactrum from acclimatized activated sludge. The author reported that

respective species can resist for selected metals Cu (275 mg L-1), Cd (320 mg L-

1), Co (140 mg L-1) and Cr (29 mg L-1) with good sorption capacity. The

proposed activated sludge system augmented with the acclimatized strains also

ensures excessive performance under the metal stress of industrial effluents.

Oves et al. [63] states the metallic biosorption capacity of Bacillus thuringiensis

biomass that were recovered from rhizosphere of cauliflower grown in frequently

industrial effluents irrigated soil. Authors reported that the biosorption ability

of B. thuringiensis were pH and metal concentration dependent. The highest

26

biosorption efficiency were recorded for Ni (94%) followed by Cu (91.8%),

whereas the lowermost sorption for Cd (87%) at 25 mg L-1 initial metal ion

concentration.

Leung et al. [64] isolate and identified twelve aerobic bacteria from activated

sludge i.e. Gram-positive (e.g., Bacillus) and Gram-negative (e.g., Pseudomonas)

bacteria. One of the selected bacterial species P. pseudoalcaligenes were used

for the biosorption of Pb and Cu metallic ions. The result of the study shows that

reaction followed Langmuir isotherm model with biosorption capacity (qmax) of

271.7 mg g-1 (Pb) and 46.8 mg g-1 (Cu) at pH 5.0. However, a slight effect in

sorption capacity were detected possibly due to mutual inhibitory influence of Pb

- Cu system.

Hussein et al. [65] under aseptic conditions prepare dead (non-living) biomass of

various Pseudomonas species for biosorption of Cr, Cu, Cd and Ni ions. The

study revealed maximum adsorption capacity for Ni followed by Cd, Cu and Cr.

Kumar et al. [17] isolate different microorganisms (Bacillus sp., Pseudomonas

sp., Staphylococcus sp., and Aspergillus niger) from soil and sludge through

enrichment process. As a batch culture, the isolated species were grown in

synthetic broth media amended with toxic metal solution. The biosorption

process evaluated that Pseudomonas and Bacillus sp. reduced Cu 4.165 mg L-1

and 3.332 mg L-1 (68% and 56%) and Ni 5.015 mg L-1 and 3.8 mg L-1 (65% and

48%) respectively. Aspergillus niger reduced Cd 0.267 mg L-1 (50%) and Zn

5.988 mg L-1 (58%) whereas Staphylococcus sp. reduced Cr 4.108 mg L-1 (45%),

Cu 2.615 mg L-1 (42%) and Pb 0.813 mg L-1 (93%). The results showed that

Pseudomonas sp. reduced heavy metals more than other microbes but

Staphylococcus sp. reduced 93% Pb which was comparatively higher uptake than

other studied metals.

Parungao et al. [66] investigate Stenotrophomonas maltophilia bacteria for Cu,

Cd, and Pb ions biosorptive removal from single and mixed metal aqueous

environment. Approximately 22% of Cu, 24% of Cd, and 42.75% of Pb were

removed from single metal solutions while 16% of Cu, 8% of Cd, and 35% of

Pb, were removed from three / mixed metal solutions.

Gelagutashvili [67] deliberate the biosorption capacity of cyanobacteria

Spirulina platensis for Cd, Ag and Au; Streptomyces sp. for Au and Arthrobacter

27

sp. for Cr. According to this study, the pH had a significant role in the removal

of Cd, Ag, Au and Cr metals.

2.3.2 ALGAL BIOSORBENTS

Algae were considered as a promising biosorbent because of their definite sorption

properties and copious availability in aqueous environment (e.g., oceans and seas). It

has been reported that the algae uptake efficiencies toward heavy metals are

comparatively higher (~15.3 - 84.6%) than other microbial biosorbents [68].

Unfortunately, the use of algae as a biosorbent material were rarely reported as

compare to fungi and bacteria. Of all species, brown algae have gained an exceptional

distinction as biosorbent because of its maximum adsorption capacity for metals (Cd,

Ni, Pb) due to specific chemical functionalities on their surface such as sulfonate,

carboxyl, and amino group [11].

Hamdy [69] investigate the biosorption capacity of brown and red algae species to

biosorb Cr, Co, Ni, Cu, and Cd heavy metal ions. In this study, author obtained a

significant increase in biosorption rate with the increase of time and biomass

concentration.

Kayalvizhi et al. [70] studied the biosorption of Pb ions onto Rhizoclonium hookeri.

The equilibrium of this study were attained within 30 min reaction time with a

subsequent fit for Freundlich isotherm and Pseudo second order kinetic model.

Thermodynamics verifies that the adsorption process is endothermic and spontaneous.

Prasher et al. [71] used an inexpensive and copious quantity of dried red

algae Palmaria palmata biomass for the removal of heavy metal ions (i.e., Pb, Cu, Ni,

Cd and Zn). The maximum sorption capacity acquired from Langmuir model were

15.17 mg g-1 for Pb and 6.65 mg g-1 for Cu at a pH range of 5.5-6.0. In this study, a

rapid uptake of heavy metals were achieved within first 10 minutes for Cu (70%) and

Pb (100%).

Ching [72] studied the biosorption of Cu, Zn, Cd and Pb metals using nonliving

marine algae (Sargassum sp.) biosorbent via batch and column techniques.

Adsorption of all the metals were rapid within 30 min, however equilibrium attained

after 120 min. The column experiments showed that the efficiency of heavy metal

removal were reduced with the rise of flow rate but improved with the increase of

column bed height.

28

Wilke et al. [73] examined that the cyanophyceae Lyngbya taylorii exhibited higher

uptake capacities for the selected metals from aqueous solutions. They attain

subsequent order of selective sorption: Pb >> Ni > Cd > Zn. It was observed that the

electrolytic metal ions (Na, Ca, K, and Mg) have a small interfering effect on the

sorption abilities of immobilized L. taylorii.

Sulaymon et al. [74] used a mixture of green and blue-green algae for the biosorption

of Pb, Cd, Cu and As in fluidized bed reactor. A higher affinity of the biomass

towards Pb was observed due to high electronegativity of this metal as compared with

others.

Kushwah and Srivastav [75] investigate the biosorption of Cu ions onto the dead

biomass of Spirogyra (green algae) in a batch mode. It was observed that the removal

process of Cu ions from aqueous solution were pH dependent and maximum removal

rate were achieved at pH 8.5.

Apiratikul et al. [24] used dried Caulerpa lentillifera for screening the adsorption

potential of Cu, Cd, Pb and Zn. The adsorption equilibrium follow the Freundlich

isotherm type. The total adsorption capacity of the algae in most of cases decrease by

30-50% when there were more than one heavy metal in the solution. However, the

adsorption of mixtures i.e. Cd and Cu, and of Pb and Cu did not show a reduction in

the total adsorption capacity.

Utomo et al. [76] investigated the capability of marine and freshwater algae biomass

for adsorbing heavy metals Cu, Pb, Zn and Cd from water medium using synthetic

water and industrial water. According to the findings, presence of several

functionalities on marine and freshwater algae surface (i.e., hydroxyl, carboxylic and

amine groups) enabled it to adsorb heavy metals.

2.3.3 YEAST BIOSORBENTS

Yeasts have a wide application in industries for fermentation processes. They

also used as biomass adsorption of toxic metal ions from contaminated water. As

a biosorbent, yeast species display excellent abilities for the metal uptake and

establish a strong complex resistance mechanism to counterbalance metal

toxicity [77].

29

Farhan and Khadom [78] evaluate the performance of Saccharomyces

cerevisiae yeast for the removal of Pb, Zn, Cr, Co, Cd, and Cu heavy metals

from aqueous system. Results of this study revealed rapid metal uptake at pH

range 5.0-6.0. The functionalities on the surface of yeast biomass (i.e. carboxyl,

amine, and phosphate groups) were supposed to the specific sites for metal ion

biosorption.

Infante et al. [79] studied the sorption properties of yeast S. cerevisiae for the

removal of dissolved Pb, Hg, Ni ions from drinking water. It was observed that

the biomass of S. cerevisiae removed a higher percentage of Pb (86.4%) as

compared to Hg and Ni (69.7 and 47.8% respectively) when the pH were set at

5.0.

Mata et al. [80] describe the biosorptive capacity of selected yeast species toward Zn,

Cu, Mn, and Fe ions. The yeast were isolated from continuous system of San Pedro

River. In this study, after 40-days of experimental period a noticeable reduction were

obtained in biosorption of heavy metals (i.e. Zn 81.5%, Cu 76.5%, Mn 95.5%, and Fe

99.8%).

Tálos et al. [81] investigate the biosorption of Cd from synthetically contaminated

aqueous solution by native baker’s yeast. The highest metal uptake value was 110 mg

g-1 in a suspension of 0.3 g L-1 yeast at pH 6.0. The adsorption equilibrium were

reached within 60 minutes and the sorption process followed pseudo second order

kinetics.

Breierova´et al. [82] studied the accumulation of Cd metal in different forms of yeasts

(Hansenul aomala, S. cerevisiae). Result shows, the highest concentration of Cd in

the growth medium were tolerated by H. aomala strain, while the lowest tolerance

were recorded for S. cerevisiae. It is assume that the composition of saccharide

moiety in the extracellular glycoproteins may responsible for the difference in

adsorption tolerance.

30

2.4 FUNGAL BIOMASS AS NATURAL BIOSORBENT FOR METAL ION

REMOVAL

Table 2.1 Overview of biosorbents and their sorption capacities for selected

metals.

Microbial

Group

Microbial

biosorbent Metal pH

Dose

(g)

Temp.

(°C)

Time

(min)

Initial

metal ion

concentration

(mg L-1)

Capacity

(mg g-1) Ref.

Bacteria

Arthrobacter sp. Pb(II) 5.75 9.9 - - 108.79 9.6 [85]

Streptococcus pyogenes

Hg(II) 8 - - - - 4.8 [86]

Algae

Sargassum fusiforme

(a)Hg(II)

(b)Cd(II) 8-10 2.0 - 60 10

(a)30.86

(b)7.69 [87]

Spirulina platensis

Pb(II) 3 2.0 26 60 100 - [88]

Spirulina platensis

Pb(II) 7 2 25 60 50 40 [19]

Chlamydomonas reinhardtii

(a)Hg(II)

(b)Cd(II) (c)Pb(II)

6 5-35

60 -

(a)72.2

(b)42.6 (c)96.3

[89]

Oedogonium urceolatum

Hg(II) 4 0.3 - 90 300 375 [90]

(a) Sargassum glaucescens and

(b)Gracilaria corticated

Hg(II) (a)5

(b)7 - -

(a)90

(b)30

(a)200

(b)1000

(a)147.05

(b)4.71 [91]

Yeast Saccharomyces

cerevisiae Hg(II) 5 - 35 60 200 114.6 [92]

Fungi

Trichoderma harzianum

Cr(II) 2 0.1 - 180 25 50 [93]

Phanerochaete chrysosporium

(a)Cd(II)

(b)Pb(II)

(c)Cu(II)

6 0.2 25 360 100

(a)23.04

(b)69.77

(c)20.23

[94]

Streptomyces fradiae

Pb(II) 5 1 - 120 10-200 138.88 [95]

Rhizopus oligosporus

Hg(II) 6 1 30 360 20-100 33.33 [96]

Penicillium purpurogenum

(a)As(III) (b)Hg(II)

(c)Cd(II)

(d)Pb(II)

5 - 20 240 100

(a)35.6 (b)70.4

(c)110.4

(d)252.8

[94]

Lycoperdon perlatum

Hg(II) 6 4 - 60 10 107.4 [97]

Aspergillus terreus

(a)Hg(II)

(b)Pb(II) (c)Cd(II)

5 - 30 90

(a)800

(b)6000 (c)300

(a)41.26

(b)253.16 (c)25.72

[98]

Aspergillus niger

Hg(II) 3 0.8 40 120 250 405.3 [99]

31

Of all the toxic metal ion adsorbing micro / macro organisms, fungal biomass

were considered as an exceptional biosorbent because of its excessive growth

and informal cultivation [83]. It’s highly filamentous morphology and bulk cell

wall material makes it a proficient adsorbent that can exploit over a wide - range

of pH, temperature and concentration [84]. To get productive outcomes,

numerous fungal species can be used for the biosorption process [100] that:

• Acquired by high fermentation rate,

• Extensively use in food production,

• Require easy cultivation in reasonable broth media,

• Being by-product or industrial fermentation waste in large quantities, and

• Have environment friendly properties.

All these attributes exhibited that the fungal cells have enormous capacity to bind /

aggregate heavy metals and anions. Hence, fungi can actively exploit for the

removal of toxic metal from polluted drinking water and industrial effluents.

In a study by Júnior et al. [101], the effectiveness of a fungal isolate, Aspergillus

niger for concurrent removal of heavy metals from industrial effluent were

examined. Their study inferred that biosorption process with A. niger could be

successfully used for heavy metal removal at a pH of 4.75 from oil field water in

the oil industry.

The biosorption capacity of previously reported biosorbents (bacteria, algae,

yeast, fungi) as presented in Table 2.1, shows that most of the species are able to

absorb appreciable amount of Pb(II), Hg(II), and Cd(II) ions metal ions from the

aqueous solution under optimum conditions.

2.5 REMOVAL OF ANIONS BY VARIOUS BIOSORBENT

The research on biosorptive removal of anions has adopt a less attention since

past two decades. As compare to heavy metals biosorption, only a few studies

were reported on anionic removal. In this section, only available anionic removal

reports were discussed. The removal of F- and NO3- anion as sorbate is part of

this thesis study.

32

Bacteria belongs to Bacillus, Geobacillus, Arthrobacter, Micrococcus,

Pseudomonas genus and fungi like Aspergillus, Rhizopus, Trichoderma,

Neurospora species have revealed a substantial sorption capability for various

ions.

Dwivedi et al. [102] used Shewanella putrefaciens for the sorption of F-ions

from aqueous solutions. In this study, the simultaneous adsorption reduced the

initial concentration of F- from 20 to >1.5 mg L-1 at pH 7.0.

Mohan et al. [103] studied the adsorption performance of non-viable algal

Spirogyra as biosorbent toward F- removal from aqueous phase at lower pH

range. In addition, Hiremath and Theodore [104] used a fixed bed / packed

column to determine the potential of immobilized Chlorella vulgaris in calcium

alginate beads to remove F- from synthetic and real water.

Taziki et al. [105] studied the NO2- and NO3

- removal from contaminated water

using micro-algae Chlorella vulgaris, Neochloris oleoabundans and Dunaliella

tertiolecta. In this study, alternative culture methods, immobilization and biofilm

formation for NO3- remediation were introduced that decrease the costs of

harvesting process.

Merugu et al. [106] investigate Ca and alkali treated Aspergillus nidulans fungal

biomass for the removal of F- from aqueous environment. The defluoridation of

water were strongly pH dependent, it decrease with increase of solution pH.

Prajapat et al. [107] identified saw dust, Aspergillus penicilloides and Mucor

racemosus (Division-Mycota) as a potential biomaterial for removal of Ca and F-

ions. The study revealed that the presence of specific cations on biomass surface

enhance the adsorption of anions. Typically, this increase in sorption is not

possible due to the presence of large number of negative charge on cell-surface.

Chen et al. [108] studied the equilibrium and kinetics of PO43- removal from

aqueous solution on hydro-thermally modified oyster shell material. The optimal

pH 11.0 were used for the maximum phosphate adsorption.

Hrenovic et al. [109] used an immobilized bio-solids to enhance the PO43-

removal from contaminated water in an aerated biological system. They acquired

179.0 meq/100 g of dry bentonite cation exchange capacity (CEC) for the

constructed system.

33

Hence it can be inferred from this detailed survey that there is a potential need of

novel natural material especially micro and macro organisms for the removal of

toxic pollutant from water system.

2.6 PLEUROTUS ERYNGII – A COMMON EDIBLE MACROFUNGI

The fruiting stage of mushroom Pleurotus species occupies 5th position in the

world of all the edible basidiomycetes fungi. Usually they grown in nature as

saprophytic fungi on wood trunks. Pleurotus fungi in fruit form termed as

“oyster mushroom” because of the opening of its eccentric stalk like an oyster

shell during morphogenesis. According to latest reports, in recent years the

production of Pleurotus booming in Taiwan and Japan [110]. Its high cultivation

and yields also made it extra popular in several renowned countries of the world

like - Australia, Canada China Europe, United States, and many Asian parts.

2.6.1 PHYSICAL DESCRIPTION

The main characteristics of Pleurotus eryngii mycelial morphology [111] are

presented in Table 2.2.

Table 2.2 Morphology of P. eryngii.

Characteristics Visual observation

Surface state Cotton fibrous

Compactness Semi-solid

Pigmentation Off-white or whitish

Growth form Regular, plentiful and bulk

2.6.2 GROWTH HABIT

In China, the crop of P. eryngii – mushroom were extensively cultured due to its

rapid environmental adaptations in specific climatic conditions. The strain of

Pleurotus species have capability to colonize a range of higher plants with an

extensive natural ligno-cellulosic wastes [111]. Consequently, its fruit can grow

over a wide range of temperature (usually 15 to 31°C).

34

2.6.3 SCIENTIFIC CLASSIFICATION OF P. ERYNGII

The scientific classification of P. eryngii presented [112] in Table 2.3.

Table 2.3 Scientific classification of P. eryngii.

2.6.4 EFFECTIVENESS OF P. ERYNGII AS BIOSORBENT

Unlike other microorganisms, P. eryngii were applicable as a good biosorbent

because of its semi-solid consistency, bulk structure and some specific physical

features which makes it a favorable biomass for ionic removal without any

modification / immobilization of surface [127-130]. Therefore, the present study

were designed to estimate the maximum adsorption performance of the

infrequently yielding mushroom P. eryngii mycelia as a biosorbent for the

removal of toxic metals and anions from aqueous solutions.

2.7 SUMMARY

Several studies have been reported for the efficient removal of toxic chemical

pollutants from water system using variety adsorbents (natural and synthetic),

but only a few research work has been reported on the removal of toxic ions by

P. eryngii fungal biomass. In previous investigations, P. eryngii were used as

whole mushroom (fresh fruit body of macro fungus), in immobilized form, and

as lyophilized (freeze dried) cells. However, the potential of mycelial form

toward toxic pollutants remains unknown.

Rank Taxonomy

Phylum Basidiomycota

Class Agaricomycetes

Order Agaricales

Family Pleurotaceae

Genus Pleurotus

Species Pleurotus eryngii

Kingdom Fungi

35

Thus, there is a need to study the biosorption performance of Pleurotus fungal

strain to obtain sufficient data for practical application. This research were

developed to study the potential use of P. eryngii for the removal of toxic metal

ions Pb(II), Hg(II), Cd(II) and anions (F-, NO3-) from aqueous solutions.

36

CHAPTER 3

RESEARCH METHODOLOGY

This chapter covers the material and methods which were employed during the

biosorption experiment for batch and packed bed column system. It also consists

of characterization methodologies for fungal biomass by simple and rapid

techniques (FTIR, AFM, SEM-EDX).

3.1 CHEMICALS AND REAGENTS

Concentrated H2SO4, HNO3, HCl and NaOH, Na2BO4 were of analytical grade

acquired from Sigma-Aldrich (Steinheim, Germany) and Merck (Darmstadt,

Germany). Stock standards of Pb, Hg, Cd, F- and NO3- were prepared for

calibration from standard solutions of Fluka Chemika (Bushs, Switzerland). All

plastic and glass wares were thoroughly washed then rinsed with distilled /

deionized water. After washing, the apparatus were dried up in an electric oven.

Potato dextrose agar (PDA), glucose, peptone used were of analytical grade

(Scharlau, Spain & Daejung, Korea).

3.2 FUNGAL STRAIN

For biosorption study, the fungal strain of P. eryngii ATCC® 90888 TM were

procured from Edible Fungi Institute, Shanghai Academy of Agricultural

Sciences, Shanghai, China.

3.2.1 INOCULUM PREPARATION

Figure 3.1 (a) P. eryngii maintained on PDA plate.

37

Fungal culture were routinely maintained on PDA slants / petries (Figure 3.1a).

To yield the bulk quantity of mycelial biomass for biosorption experiments, the

seed culture were prepared by loop inoculation in GPB (glucose peptone broth)

(Figure 3.2b). The formulation of liquid medium (broth) prepared in laboratory

composed of g L−1; glucose (50), peptone (5), KH2PO4 (5) and NaCl (5), adjusted

to pH 6.0 ± 0.2 and incubated for 27 days at 27 ± 2ºC [113].

Figure 3.2 (b) Wet colony sub-cultured on GPB.

3.2.2 DRIED BIOSORBENT PREPARATION

Figure 3.3 (c) Dried biomass of P. eryngii.

After 27 days’ cultivation, the fungal mycelium were harvested by filtration of

liquid medium and washed persistently with ultra-pure water. The process of

cell washing were carried out till the dark brown color of washing fluid (i.e.

water) turns to transparent. The resultant fungal biomass afterward evaporated to

dryness at 60 °C for 24 hours.

38

After suitable drying, the biomass were finely divided (particle size of 0.18 mm)

into powder form and stored in a screw capped plastic bottle for subsequent

usage in biosorption experiment (Figure 3.3c). Before using fungal biosorbent,

no any immobilization / impregnation or activation were performed on biomass

surface.

3.2.3 PREPARATION OF BIOSORBENT IN DIFFERENT FORMS

To estimate the optimum operating state of cell mass, five different techniques

were also applied for the preparation of biosorbent shown in Table 3.1.

Table 3.1 Methods for the preparation of fungal cell mass.

Parts of fungal

cell State of cell mass Preparation method

Dead cell (non-living)

P-1 Oven dried Dehydrated (dried) in hot-air oven at

60ºC for 24 h

P-2 Air dried Dried in direct open-air atmosphere

P-3 Autoclaved Autoclave at 15 lb pressure for 15 min

Living cell (non-growing)

P-4 Living Water was soaked by blotting paper

P-5 Freeze dried Lyophilized for 75 min

3.3 PREPARATION OF STANDARD SOLUTIONS

The stock solutions (1000 mg L-1) of Pb, Cd, F- and NO3- were prepared by

dissolving 4.58, 2.29, 2.21 and 1.63 g of Pb(NO3)2, 3CdSO4·8H2O, NaF and

KNO3 respectively in 1000 mL deionized water (conductivity 0.050 μS cm−1);

however 100 mg L-1 Hg stock solution were prepared by dissolving 0.135 g of

HgCl2 in 1000 mL deionized water. The standard solutions of metal ions were

prepared regularly by dilution of stock solutions. The ionic-Hg were reduced to

metallic-Hg by NaBH4 in an HCl matrix. The reductant solution (reducing agent)

were prepared by NaBH4 (0.2%) (w/v) in NaOH (0.5%) (w/v), while the acid

solution was 10% w/w HCl.

39

The pH of the test solutions were adjusted according to subsequent experimental

design with 0.1 M NaOH or 0.1 M HCl solutions.

3.4 ANALYTICAL INSTRUMENTATION

Innova 4230 Incubator (New Brunswick Scientific Co; Huntingdon, UK) was

used for the batch experiments. The pH meter (InoLab-WTW GmbH; Weilheim,

Germany) with glass electrode and an internal reference electrode was used for

pH measurements.

The quantification of Pb(II) and Cd(II) ions before and after the sorption

equilibrium were carried out by Varian AA 20 spectra atomic absorption

spectrometer (Mulgrave, Victoria, Australia) equipped with cathode lamp of

respective elements.

A system equipped with MHS-15 Mercury / Hydride System were used in this

study for the analysis of Hg(II) ions. The Varian vapor generation accessory

(VGA-77, Australia) uses a peristaltic pump to intermingle sample with a supply

of nitrogen gas. The N2 and Hg volatiles were released from the gas-liquid

separator. The separated gas flows into a flow-through cell arranged on path of

the light from AAS. The optimum conditions used throughout these studies are

given in Table 3.2.

Table 3.2 Conditions of F-AAS for Pb(II), Cd(II) and HG-AAS for Hg(II)

ions determination.

Parameter Pb Cd Hg

Wavelength (nm) 217.0 228.8 253.7

Hollow cathode lamp current (mA) 5 4 4

Type of flame Air-C2H2 Air-C2H2 -

Background correction ON ON ON

Slit width (nm) 1.0 0.5 0.5

Acetylene flow rate (L min-1) 1.5 1.5 -

Air flow rate (L min-1) 3 3 -

Flame condition Oxidizing Oxidizing -

Expansion factor 1 1 -

Reading time (s) - - 60

Nitrogen flow rate (mL min-1) - - 50

40

During column studies, the flow rates of Pb(II) solution were optimized by

peristaltic pump (Eyela MP3, Tokyo Rikakikai Co., Ltd. Japan). The flow system

were made of PTFE 0.5 mm i.d.

For F- analysis, the Ion-Chromatograph (Ω Metrohm; Herisau, Switzerland)

instrument 861 Advance Compact with 833 IC liquid handling unit equipped

with self-regenerating suppressor consists of a double gradient peristaltic pump

along with conductivity detector were used. The anion column (4.0mm×250mm)

METROSEP A SUPP 4-250 with carbonate and bicarbonate buffer mobile phase

were used. The IC conditions for the analysis of F- ions are given in Table 3.3.

Table 3.3 Conditions of IC for F- ions determination.

Perkin Elmer (Shelton, CT 06484, USA) Lambda 35-UV–Vis spectrophotometer

were used to record NO3- ion UV–Vis spectra at an absorbance of 410 nm

following reagent blank. The NO3- ions in the filtrates were measured through

directions of Environmental Protection Agency (EPA) approved Brucine method

[114].

The chemical and morphological characterization of P. eryngii before and after

metal and anions sorption was studied by SEM equipped with EDX analyzer

(JEOL; Tokyo, Japan). FTIR spectra were recorded on a Nicolet 5700 FTIR

spectrometer (Thermo Electron; USA) as KBr pellets; whereas, elemental

IC anion column METROSEP A SUPP 4

Particle size 9.0 µm

Eluent 1.8 mmol Carbonate;

1.7 mmol Bicarbonate.

Eluent flow rate 0.5 mL min-1

Temperature 20°C

Pressure 4-5 MPa

Injection volume 20 µL

Detector Conductivity detector

41

analysis were performed with elemental analyzer (Flash EA 1112; Rodano-

Milan, Italy) and AFM (5500 Agilent; USA) respectively.

3.5 POINT OF ZERO CHARGE (PHPZC)

For pHPZC of the biomass, 50 mL KNO3 (0.1 M) solution were added in a series

of 11 conical flask (100 mL). The initial pH of flasks were adjusted from pH 2.0

to 12.0 by HCl and NaOH (0.1 N) solutions. Subsequently, 0.1 g P. eryngii

biomass were added to all flask. Tightly stoppered flasks were then kept for

agitation at room temperature (for about 48 hours). After completion of 48 hours,

the final pH of the supernatant liquid were record [113].

3.6 BATCH BIOSORPTION EXPERIMENT

The biosorption study were initiated by batch experimental process. Table 3.4

shows different experimental conditions to optimize the sorption efficiency of

metals and anions.

Table 3.4 Experimental conditions and their ranges used to optimize the

sorption efficiency of metals and anions.

In typical procedure, a known quantity of biomass (0.1 g) in each 100 mL

conical flask and 5 mg L-1 Pb(II), 5 mg L-1 Cd(II), 1 mg L-1 Hg(II), 2 mg L-1 F-

solution with suitable volume were agitated at 100 rpm for 20, 15, 30 and 10 min

respectively at pH 7.0 keeping ambient temperature of 27 ± 2ºC. Figure 3.4

showing a batch biosorption study that was conducted in laboratory.

Metal /

anion

Range of parameters

pH Biosorbent

dose (g)

Initial

concentration

(mg L-1)

Time

(min)

Temperature

( C)

Pb(II) 2-9 0.2-0.45 1-10 5-40 30-60

Cd(II) 3-8 0.1-0.5 4-20 1-15 30-70

Hg(II) 3-9 0.15-0.35 0.5-10 1-6 30-60

F- 2-7 0.1-0.5 5-25 60-300 15-30

42

After completion of the sorption process, the mixture were filtered under

Whatman’s filter paper No. 42 and also by 0.45 µm syringe filter. Later on,

metal ion / anions were quantified in the filtrate solution.

Figure 3.4 Biosorption study by batch experimental procedure.

3.7 CONTINUOUS (PACKED COLUMN) BIOSORPTION EXPERIMENT

For continuous biosorption investigation, a mini glass column of 5 mm x 120

mm dimension were filled with the glass wool followed by a layer of glass beads

(~2 cm) at the base. Then a calculated amount of sorbent material were packed in

column to carry on process parameters.

Figure 3.5 Biosorption study by column experimental procedure.

43

From column inlet, the Pb ion solution (influent) of 20, 30 mg L-1 concentrations

were pumped through the packed column of different bad heights (1, 2 and 3

cm), at optimal flow rates (1, 3 and 5 mL min-1). The samples were collected

from outlet portion and examined for remaining Pb concentration. Figure 3.5

showing a column biosorption study that were conducted in laboratory at room

temperature.

3.8 INTERFERENCE STUDIES

In addition to targeted metal ion and anions, an aqueous solution also contain

several other ions. Therefore, to check the selectivity / efficiency of P. eryngii

biomass toward specific ion; sorption experiments of Pb(II), Cd(II), Hg(II), F-

were performed in the existence of supplementary ions respectively, keeping

different combination of folds.

3.9 DESORPTION STUDIES

Desorption and reuse experiments were performed at room temperature to check

the reusability of the spent sorbent for the consecutive cycles. For this study, the

metal ion and anion loaded biomass (washed with ultra-pure water) were shaken

in 0.1 N each HNO3, H2SO4, HCl, and NaOH, EDTA, NaCl desorbing agents /

eluents for 30 min at 100 rpm to desorb loaded Pb(II), Cd(II), and F- ion

respectively from fungal biomass at predetermined temperature, then the

resultant filtrate were analyzed for the residual content. Besides, the Hg(II) ions

were desorbed with 10 mL of HCl with different concentrations (0.1–5.0 M),

followed by deionized water.

The reusability studies of the biosorbent were conducted by introducing desorbed

biomass again in the fresh ionic solution. The procedure can repeat for

consecutive adsorption-desorption cycles.

3.10 STATISTICAL METHODOLOGY FOR NO3- IONS

To determine the factors and interaction effects of various parameters that

influence the biosorption of NO3- ions, a three level-three factors CCD with 17

44

runs to locate the true optimum values of pH (A), biosorbent dose (B), and initial

NO3- concentration (C) combining factorial points as low (-1), medium (0), and

high (+1) of experiment was applied, as shown in Table 3.5.

Table 3.5 Experimental ranges and level of the independent variables.

For each run, weighed amount of sorbent were added to flasks containing 10 mL

of NO3- ion solution and pH was adjusted to the desired value by NaOH or HCl

solutions. The flasks were agitated at a preset temperature (30 ± 3°C) in an

incubated rotary shaker at 100 rpm. The suspension were then filtered and the

NO3- content in the filtrates were determined through UV-Vis spectrophotometer

@ 410 nm absorbance (EPA approved Brucine method) after an appropriate

calibration of the instrument.

3.11 CALCULATION OF DATA

The biosorption capacity i.e., amount of metal ions and anions biosorbed on P.

eryngii were calculated by the following equation (18):

Q = (C − CJ)M V − − − − − (18)

where Q is the metal ions / anion uptake (mg g−1), V is the solution volume (L),

Ci and Cf are the initial and final ionic concentrations in the solution (mg L−1)

respectively, and M is the mass of biosorbent (g).

Biosorption efficiency of metal ions and anions calculated by the following

equation (19):

Biosorption efficiency (%) = C − CJC

x 100 − − − − − (19)

Factor Units Coded

symbols Range and level

1 0 +1

pH - A 2 7 12

Biosorbent dose g B 0.1 0.24 0.4

Initial NO3- concentration mg L-1 C 60 700 1340

45

Desorption efficiency were calculated from the following formula (20):

%Desorption Amountofsorbatedesorbedpereffluent

AmountofsorbateloadedonbiosorbentZ 100 20

3.12 ANALYSIS OF COLUMN DATA

The overall amount of sorbate adsorbed in column (mad) were calculate from the

area above the breakthrough curve multiplied by the flow rate.

Dividing the amount of sorbate (mad) by the amount of biosorbent (M) clues to

the uptake capacity (Q) of biomass.

The whole quantity of sorbate sent to the column were calculate from the

following equation (21):

m-E- [ CFte

1000 21

where C0 is the inlet sorbate concentration (mg L-1); F is the volumetric flow rate

(mL h-1); and te locate the exhaustion time (h).

Total sorbate removal (%) with respect to flow volume were calculate from the

ratio of sorbate mass adsorbed (mad) to the total amount of sorbate sent to the

column (mtotal) as follows (22):

Totalsorbateremoval% m 5

m-E- [

x100 22

3.13 STATISTICAL ANALYSIS

The Design-Expert® software (Version 9.0.6.2, Stat-Ease, Inc., Minneapolis,

USA) were used for designing experiments as well as for regression coefficients

and graphical analysis of the experimental data.

46

3.14 REAL WATER SAMPLE FOR ANALYTICAL APPLICATION

To explore the adsorption performance of P. eryngii at natural conditions, the

sorption experiments were carried out using real water samples collected from

different regions of Sindh Province, Pakistan (Figure 3.6). The details of the

sample collection sites along with geographical coordinates (GPS-Global

Positioning System) are presented in Table 3.6.

Figure 3.6 The map of Sindh showing sampling zone in red arrows. [Image courtesy:

Google map].

47

Table 3.6 Detail of water collection sites and GPS co-ordinates monitored for

each zone.

S.

No.

Water-sample

collection site* GPS co-ordinates

Latitude Longitude

1. Karachi 24.8607° N 67.0011° E

2. Dadu 26.7341° N 67.7795° E

3. Tharparkar 24.8777° N 70.2408° E

4. Kotri 25.3494° N 68.2743° E

5. Jamshoro 25.4304° N 68.2809° E

6. Hyderabad 25.3960° N 68.3578° E

7. Nawabshah 26.2447° N 68.3935° E *Regions of Sindh Province, Pakistan.

48

CHAPTER 4

RESULTS AND DISCUSSION

PART 1

Remarks: All work of this part has been published in J. Int. J. Environ. Res.

3(11):315-325.

4.1 ECO-EFFICIENT FUNGAL BIOMASS FOR THE REMOVAL OF PB(II)

IONS FROM WATER SYSTEM: A SORPTION PROCESS AND MECHANISM

Part 1 describes the Pb(II) ion sorption potential of a newly cultured fungal

biomass P. eryngii from aqueous media. The fungal biomass was prepared by

loop inoculation and incubating the fungus in GPB. The fungal biomass was

characterized by using FTIR and AFM.

4.1.1 CHARACTERIZATION OF THE BIOSORBENT

FTIR ANALYSIS

The FTIR spectra of unloaded and Pb(II) loaded biomass forms was used to

identify the functional groups involved in the adsorbing process, which is

important for elucidation of the surface-bonding mechanism.

The FTIR spectrum of pure fungal biomass (Figure 4.1a) showed several distinct

and sharp absorptions at 3380 cm−1 (−OH or −NH2 groups), 2923-2852 cm−1 (C–

H groups), 1724 cm−1 (C=O of protein bonds), 1654 cm−1 (N–H and C-N of

amide groups), 1558.25 cm-1 (types I and II vibrating amid), 1380 cm−1 (C = O

of amide I) and at 1043 cm−1 (C-O-C and C-O of polysaccharide) [115]. The

FTIR spectra of Pb(II) ions loaded fungal biomass (Figure 4.1b) suggested no

shifts or change in any of the characteristic absorbance bands except for a peak

shift at 3399 cm−1, 1644 cm−1 1547 cm−1, and 1085 cm−1 after loading of Pb(II).

The significant changes in the wave number of these peaks after loading of

Pb(II) indicate that the functional groups i.e.; amido, hydroxyl, and carboxyl

49

were involved in the sorption of Pb(II) on the surface of P. eryngii fungal

biomass. The presence of these functional groups and their chemical substances

content originate electron cloud with negative bar that was of an immense

importance in adsorbing Pb(II) positive ion.

Figure 4.1 FTIR spectrometry of fungal biomass before (a) and after (b) Pb(II) ions

sorption.

AFM ANALYSIS

AFM study was carried out to visualize the surface topography, columnar

structures or troughs on the surface of biomass before and after metal ion

exposure. The micrograph (Figure 4.2 a, b) indicate that fungal biomass exhibits

irregular and rough (less - smooth) surface before sorption of Pb(II) while

induced substantial modification on surface after sorption (Figure 4.2 c, d). This

modification is likely ascribed to the fact that the interaction of Pb(II) with

surface functional groups leads to a change in surface architecture as reflected by

an increase in surface roughness or irregularity.

50

Figure 4.2 AFM microscopic images of fungal biomass: before Pb(II) exposure (a:

height image; b: three-dimensional image) and after Pb(II) exposure (c: height image; d:

three-dimensional image).

4.1.2 OPTIMIZATION OF EXPERIMENTAL PARAMETERS

EFFECT OF PH

The effect of the pH of a solution is a major factor that can significantly affect

the sorption of heavy metals. It is related to the capability of the hydrogen ion

competition with the active site on the sorbent surface. From the results of Pb(II)

ions uptake with respect to varied pH (Figure 4.3) it was inferred that, except at

pH 2 and 3, where there was low level of Pb(II) ion sorption (39.5 and 45%), in

all other pH levels (4, 5, 6, 7) there was more than 50% sorption achieved. The

possible reasons for the lower removal at pH < 4 is that, sorbent are protonated

and restrict the entry of metallic ions; and at pH > 4, the groups responsible for

the retention of metals are negatively charged facilitating the binding of the

metals ions [116]. Therefore, pH 6 (86%) was considered as the optimum pH in

51

which competition of hydrogen ions reaches to minimum and consequently metal

sorption increases.

Figure 4.3 Percentage removal of Pb(II) ions as a function of pH (volume: 20 mL;

sorbent dose: 0.2 g; initial concentration: 50 mg L−1; contact time: 30 min; temperature:

27°C).

EFFECT OF DOSE

The sorption efficiency is highly dependent on the biomass dosage. Figure 4.4

shows that the rate of Pb(II) ion removal increased by 80% with increase of

sorbent concentration from 0.2 to 0.35 g and then decrease after this dosage

level. With sorbent concentration of 0.2 g, the rate of sorption was slightly low

and equilibrium was obtained faster. In lower doses, sorption level is lower due

to less adsorption sites. Moreover, it was observed that maximum sorption of

about 90% Pb(II) ions was attained using 0.35 g biomass compared to other

dosages. This is probably due to increase in number of available adsorption ionic

sites as the sorbent dose increased, since the concentration of metal ions in

solution is fixed, initially more ions get exchanged with the metal ions but after

the saturation is reached adsorption decreases. After this dosage, there was a

decrease in adsorption levels could be attributed to the consequence of partial

aggregation of biomass at higher concentrations.

52

Figure 4.4 Percentage removal of Pb(II) ions concentration as a function of biosorbent

dose (volume: 20 mL; pH: 6.0; initial concentration: 50 mg L−1; contact time: 30 min;

temperature: 27°C).

EFFECT OF TEMPERATURE AND ADSORPTION THERMODYNAMIC STUDIES

The effect of temperature on sorption was carried out from 30-45°C (303-318

K). The Pb(II) removal efficiency changed insignificantly from 90.0% to 75.0%

when the temperature increased above 30°C as shown in Figure 4.5. It is because

elevated temperatures tend to decrease the boundary layer thickness; metal ions

therefore had increased tendency to escape from the biomass surface to the

solution phase.

Figure 4.5 Percentage removal of Pb(II) ions concentration as a function of temperature

(volume: 20 mL; pH: 6.0; sorbent dose: 0.35 g; initial concentration: 50 mg L−1; contact

time: 30 min).

53

The decreased adsorption with increasing temperature also suggests weak adsorption

interaction between biomass surface and the metal ion, which supports physio sorption.

This result indicated that Pb(II) adsorption by the fungal biomass was temperature -

dependent.

To understand the adsorption mechanism of the Pb(II) ions onto fungal biomass,

thermodynamic parameters of the adsorption system were analyzed as given in

Table 4.1. The parameter like Gibbs free energy (ΔGº) was calculated according

to the equation 14, whereas, enthalpy (ΔHº), and entropy (ΔSº) were calculated

from the Van’t Hoff plot of lnKc versus 1/T (Figure 4.6) according to the

equation 15.

Table 4.1 Thermodynamic parameters for Pb(II) ions removal by P. eryngii at

various temperatures.

Figure 4.6 Van’t Hoff plot, log Kc versus 1/T.

T (K) ∆Gº (kJ mol-1) ∆Hº (kJ mol-1) ∆Sº (kJ mol-1 K-1)

303 -5.532

-55.058 -0.164

308 -3.881

313 -3.605

318 -2.903

54

The negative ΔGº values for all temperatures revealed that the adsorption of

Pb(II) onto biomass could occur spontaneously. The negative value of ΔHº

showed that the Pb(II) adsorption is an exothermic process, while the negative

ΔSº value implied that the orderliness at the solid-liquid interface increased

during the adsorption process and this adsorption process was reversible.

EFFECT OF CONCENTRATION AND ADSORPTION ISOTHERM STUDIES

The effect of Pb(II) ion concentration on the sorption efficiency of P. eryngii

fungal biomass was done under optimum conditions as shown in Figure 4.7. The

percentage of Pb(II) ions adsorption decreased with increasing initial

concentration from 30-70 mg L-1 (96% to 69.2%).

Figure 4.7 Effect of concentration of Pb(II) ions on their percent removal over P.

eryngii (volume: 20 mL; pH: 6.0; sorbent dose: 0.35 g; temperature: 30°C; contact time:

30 min).

This is because at lower concentration there are sufficient active sites that Pb(II)

ions can easily occupy. However, at higher concentrations, active sorption sites

are not sufficiently available for the adsorbate to occupy. Hence, Pb(II) ions

were not completely adsorbed from solutions due to the saturation of binding

sites.

Langmuir, Freundlich, Temkin and D-R adsorption isotherm models were

applied to evaluate the sorption phenomenon between surface of P. eryngii and

Pb(II) ions during sorption reaction.

55

The linear form of Langmuir adsorption isotherm is represented as equation 1.

The straight line of plot (Figure 4.8a) indicated that all adsorption processes

could be well described by Langmuir model. Parameters and correlation

coefficients calculated from corresponding models were given in Table 4.2,

suggesting that the adsorption is complex, containing physical and chemical

processes. The adsorption process of Pb(II) ions onto fungal biomass could be

considered as monolayer adsorption.

Figure 4.8 Adsorption isotherms plot (a) Langmuir, (b) Freundlich, (c) Temkin, and (d)

D-R.

The essential characteristics of Langmuir isotherm model can be expressed in

terms of dimensionless constant separation factor RL which has four

probabilities: (1) 0 < RL <1, favorable adsorption; (2) RL > 1, unfavorable

adsorption; (3) RL = 1, linear adsorption; and (4) RL = 0, irreversible adsorption.

The separation factor RL is calculated using equation 2. Because values of RL

obtained under the conditions of 30 °C were between 0 and 1, indicating that the

uptake of Pb(II) by fungal biomass was favorable.

56

The linear form of Freundlich adsorption isotherm describes the formation of

multilayers of the adsorbate on the heterogeneous sorbent surface is represented

as equation 3. These constants were determined from a plot of qevs. Ce (Figure

4.8b) given in Table 4.2.

Table 4.2 Isotherms model constants and their respective coefficients for Pb(II)

ions sorption onto fungal biomass.

The linear form of Temkin adsorption isotherm is represented as equation 4 and

5. The Temkin parameter obtained from plot (Figure 4.8c) are given in Table 4.2.

The A value gives an idea about nature of adsorption, in present study A value is

> 8 which indicate the adsorption is chemical in nature.

To evaluate the adsorption type, equilibrium data were further applied to D-R

isotherm with following equation 6. The calculated parameters of D-R model

(Figure 4.8d) are presented in Table 4.2. The value of E was greater than 8 kJ

mol-1, indicates that the interaction of fungal biomass with Pb(II) ions is

chemisorption in nature.

Langmuir

Qo mg g−1 2.971

B L mg−1 0.574

RL - 0.055-0.024

R2 - 0.99

Freundlich

Kf mg g−1 1.546

N - 5.136

R2 - 0.932

Temkin

bT kJ mol-1 6.018

KT L g-1 34.902

R2 - 0.904

D-R

q max mg g-1 5.959

KDR mol2 J-2 0.0014

E kJ mol-1 18.9

R2 - 0.925

57

Qo is a critical parameter for describing the adsorption performance of

adsorbents. The Pb(II) ion adsorption capacity of P. eryngii fungal biomass and

other adsorbents were compared and shown in Table 4.3. Qe for Pb(II) adsorption

on P. eryngii were better than more of these reports. Nevertheless, the sorption

capacity of fungal biomass can further be increased by modifying the sorbent

surface.

Table 4.3 Comparison of sorption capacities of different adsorbents in the

literature with the current biosorbent.

EFFECT OF TIME AND ADSORPTION KINETIC STUDIES

The plotted results in Figure 4.9 shows that with the increase in contact time

from 0.5-25 min, the rate of Pb(II) ions uptake was fast and maximum removal

of 100% was obtained within 5 min of reaction time. From observation, it is also

exposed that the Pb(II) ions sorption efficiency increases in the initial stage but

progressively decreased and become constant when equilibrium reached. The

trend in Pb(II) ions adsorption gives an indication that the binding may have

occurred due to conjugation with functional groups located on the surface of the

fungal biomass and a few minutes later, unavailable surface sites are hard to be

filled due to repulsive forces between the Pb(II) on the solid and the aqueous

phases.

Biosorbent Sorption capacity (mg g-1) References

Phanerochaete chrysosporium 2.0 [117]

Bagasse fly ash 2.50 [118]

Agave sisalana 1.34 [119]

Yerba mate waste 1.78 [120]

Treated corn (Z. mays) leaves 0.31 [121]

Blighia sapida (Akee apple) 0.38 [122]

Spent coffee grounds 2.46 [2]

P. eryngii 2.97 Present study

58

Figure 4.9 Effect of concentration of Pb(II) ions on their percent removal over P.

eryngii as a function of contact time (volume: 20 mL; pH: 6.0; sorbent dose: 0.35 g;

temperature: 30°C; initial concentration: 30 mg L−1).

To analyze the sorption kinetics and to calculate adsorbate uptake rate of Pb(II)

ions by P. eryngii, two kinetic models i.e. Lagergren’s pseudo first order (PFO)

and Ho McKay’s pseudo-second order (PSO) were applied.

Figure 4.10 Pseudo first order (a), pseudo second order (b), and Intra particle diffusion

kinetic models plots for the sorption of Pb(II) ions onto fungal biomass.

59

The first order rate equation of Lagergren is represented as equation 9. Straight

line plot of t against ln(qe–qt) (Figure 4.10a) was used to determine the PFO

kinetics parameters as given in Table 4.4.

Table 4.4 Kinetic parameters for Pb(II) biosorption on P. eryngii.

The pseudo second-order kinetics of adsorption was applied to check the kinetic

mechanisms between sorbent and sorbate. The parameters were calculated by

using following the equation 10. The straight-line plot (Figure 4.10b) of t versus

t/qt indicate the relevancy of the above equation to Pb(II) sorption on the

biomass. The second-order rate constant and other parameters are given in Table

4.4.

Calculated correlations are closer to unity for pseudo second-order kinetic model

and the predicted value of qe is comparable to the experimental one; therefore,

the sorption kinetics could well be approximated more favorably by second-order

kinetics model rather than pseudo first order kinetics for Pb(II) ions uptake.

For further confirmation about the mechanism, Weber and Morris Intra particle

diffusion (IPD) model were applied as equation 11. The values of IPD model

obtained from the slope of t1/2qt versus plot (Figure 4.10c) are given in Table 4.4.

Model Parameter Values

qe,exp.(mg g-1) 1.71

Pseudo first order

k1 (min-1) 0.64

qe,cal. (mg g-1) 0.068

R2 0.978

Pseudo second order

k2 (g mg-1 min-1) 42.82

q,cal.(mg g-1) 1.687

h (mg g-1 min-1) 121.9

R2 1.0

Intra particle diffusion

kipd(mg g-1 min-0.5) 0.031

C (mg g-1) 1.627

R2 0.977

60

From the plot, it is observed that the intercept does not pass through the origin,

which indicates that the pore diffusion is not only the rate-limiting step for

sorption of Pb(II) on P. eryngii.

However, by comparing constants of all kinetic models, the pseudo second order

kinetic model seems to be best fitted for the experiment.

4.1.3 INVESTIGATION OF INTERFERING IONS

The presence of interfering ions can affect the removal efficiency of the target ion in

any sorption process. In this study, the effect of Pb ions were evaluated separately

under the optimized conditions against different cations. From prior studies it was

proved that if the interfering ions affect the elimination signal less than ±5%, the

interference effects were negligible and would not be considered [123].

The results of these experiments are illustrated in Table 4.5. The ions Fe6+, Co4+, Ni2+,

Cu2+ and Zn2+, considered as interfering ions because they have a detrimental effect

on the uptake of Pb(II) by fungal biomass. While, the presence of electrolytes (Na+,

K+, Ca2+ and Mg2+) have no considerable influence. The hindrance in sorption may

occur due to the competition among the metal ions for the sorption sites.

Table 4.5 Investigation of interfering ions effect on removal of Pb(II) ions

(initial concentration = 5 mg L-1) by P. eryngii.

Interfering

ions Pb(II) ions

removal (%)

Na+ 98.9

K+ 97.8

Ca2+ 97.9

Mg2+ 98.4

Fe6+ 94.0

Co4+ 94.4

Ni2+ 93.8

Cu2+ 93.9

Zn2+ 93.0

61

4.1.4 DESORPTION OF PB(II) IONS AND RE-USABILITY OF SPENT BIOMASS

To reuse the spent fungal biomass, various eluents viz. HCl, HNO3, H2SO4,

NaOH of 0.1 N were used respectively. The results are presented in Figure 4.11a.

As per observation, the order of elution performance is as follows HCl > HNO3 >

H2SO4 > NaOH. Maximum recovery of 95% was obtained with the use of HCl as

eluent, whereas lower desorption was observed in the case of NaOH (77.8%).

This is evident that chemical ion exchange is involved in the sorption mechanism

[124]. Figure 4.11b shows that as the biomass was re-cycled up to 5 times there

are perceptible decrease in sorption efficiency from 97.4 to 85.3%. It is because

the continuous acid treatments alter the surface sites of the biomass and may

affect their binding capacity.

Figure 4.11 a) Optimization of various eluents to check their desorption efficiency

toward Pb(II) ions. b) Desorption – reuse cycles for the removal of Pb(II) ions using P.

eryngii biomass.

62

4.1.5 ANALYTICAL APPLICATION

The sorption capacity of the tested biomass could be significantly lower if real

field water were used instead of synthetic solutions, as Pb ions may compete for

the sorption sites with other ions present in the water samples. The experimental

results on the field trail analysis are given in Table 4.6. From results, it was

evaluated that under optimal conditions (at natural pH values) made in the

aqueous system and batch mode Pb(II) ions were removed successfully below the

permissible limits (0.05 mg L-1) of WHO drinking water standards.

Thus, it is accomplished that this proposed sorption technique and biomass is

feasible, reliable and suitable for the removal of Pb(II) ions at commercial and

household level.

Table 4.6 Removal of Pb(II) ions from natural water samples.

*S-1= Malir River, Karachi; S-2= Korangi Industrial Area, Karachi; S-3= Kotri Industrial Area, Kotri; S-4= Phuleli

Canal, Hyderabad.

4.1.6 SUMMARY

In this bio-analytical study, a fungal biomass P. eryngii was biologically

produce, characterized and exploit to specifically adsorb Pb(II) ions from the

water system. Characterization techniques such as FTIR and AFM were

employed to characterize the pure and Pb(II) ions loaded biomass. Impact of

different equilibrium parameters for the sorption of Pb(II) ions on P. eryngii was

examined. The sorption process followed the Langmuir isotherm model with the

calculated monolayer sorption capacity of 2.971 mg g−1 at temperature 303 K.

The kinetic data illustrate well by the pseudo second order model. With the

dynamic gathering of functionalities (–NH2, –NH–, –OH, and carboxyl) the

sorption reaction occurred both inside and on the upper surface of biomass. This

Sample

I.D.*

Pb(II) concentration (mg L-1) in sample

water

Pb(II) biosorption

(%)

Amount of Pb(II) after biosorption

(mg L-1) S-1 0.189 86.9 0.024 S-2 0.167 84.2 0.026 S-3 0.151 86.7 0.020 S-4 0.072 91.9 0.005

63

study revealed the potential of P. eryngii sorbent for the exclusion of Pb(II) ions

from the water system.

64

PART 2

Remarks: All work of this part has been published in Water Sci. Technol. 78 (5):

1148-1158.

4.2 UTILIZATION OF P. ERYNGII BIOSORBENT AS AN

ENVIRONMENTAL BIOREMEDY FOR THE DECONTAMINATION OF

TRACE CD(II) IONS FROM WATER SYSTEM

In this study, various experimental parameters were conducted and evaluated to

enhance sorption efficiency of P. eryngii for Cd(II). It has been observed that

fungal biomass has high sensitivity as well as specificity for Cd(II) ions in

aqueous system. Besides this, equilibrium isotherm, thermodynamic parameters

and kinetic models were also plotted to elaborate sorption chemistry between

biosorbent and sorbate during soption process. Additionally, reusability,

interference and application to real water samples were also tested using flame

atomic absorption spectroscopic technique. The interference study reveals

pronounced selectivity of fungal biomass toward Cd(II) even in the presence of

different ions.


FTIR ANALYSIS

To investigate the changes in functional group regions of fungal biomass (before

and after Cd(II) ions sorption) FT-IR studies were carried out. As shown in

Figure 4.12 (a & b) broad, strong and superimposed bands around 3500–3200

cm-1, indicates overlap of O–H and N–H stretching vibrations. A change in the

peak position of O–H and N–H in the spectrum could be attributed to the binding

of Cd ions with amino and hydroxyl group. The strong absorption peak at 2923

and 2852 cm-1 assigned to –CH stretching vibration, which shows the presence of

–CH3 and –CH2 functional groups respectively. In addition, the strong adsorption

band at 1654 cm-1 represents a C=O stretching vibration and NH deformation

(amide I) was also observed. The peak at 1558 cm-1 was assigned to a motion

combining both−NH bending (amide II) and−CN stretching vibration of the

65

protein. A typical amide III band appeared at 1380 cm-1, and C–N stretching

band at 1229 cm-1. Some absorption bands i.e. P–O stretching at 1153 cm-1; P–

O–C stretching at 1043 cm-1 were indicative of a phosphonate group [133]. After

adsorption, a significant peak at 1724 cm-1, corresponds to C=O was disappeared.

The significant changes in the wave number of above mentioned specific peaks

suggested that amido, hydroxy, C=O and C–O groups could be involved in the

biosorption of Cd(II) ions on P. eryngii biomass.

Figure 4.12 FTIR spectra of P. eryngii fungal biomass (a) before and (b) after

biosorption of Cd(II).

SEM-EDS ANALYSIS

After FTIR the topographical characteristics of P. eryngii were studied by SEM

before and after Cd(II) sorption, as presented in Figure 4.13. It is observed in

Figure 4.13a that the surface of biomass is irregular, porous, rough and

heterogeneous in nature. Figure 4.13b represents the micrographs of Cd(II)

loaded fungal biomass. The slight dotted structure was observed on the surface

66

of sorbent which may due to the sorption of Cd(II) ions. However, the rest of

surface morphology seems similar as before sorption.

Figure 4.13 SEM micrographs of (a) unloaded and (b) Cd(II) loaded P. eryngii fungal

biomass; EDS spectra of (c) unloaded and (d) Cd(II) loaded P. eryngii fungal biomass.

EDS elemental composition of the unloaded (Figure 4.13c) biosorbent,

illustrated the presence of C, O, Na, P, Cl, K and S elements as natural species

on fungal biomass. The presence of these elements may influence the sorption

mechanism through ion-exchange interactions. Furthermore, Figure 4.13d

revealed the sorption of Cd(II) ions on biomass by indicating a strong signal of

Cd at ~3.1 KeV. In addition, the disappearance of Cl, K and Na peaks after

sorption signifies the involvement of an ion exchange mechanism during

biosorption of Cd(II) on fungal biomass.

67

AFM ANALYSIS

To further confirm the surface morphology of fungal biomass, AFM study was

carried out. It is an ideal tool for determining the changes in cellular morphology

before and after interaction of sorbate (Cd). The micrograph as shown in Figure

4.14a exhibits relatively smooth surface of the fungus. The fungal image is found

to be clearly resolved into three-dimensional height image (Figure 4.14b). The

surface of the biomass undergoes a significant change due to the sorption of

Cd(II) ions (Figure 4.14c). In general, results of AFM study showed that the

uppermost layer of fungal biomass become rougher or irregular due to the

formation of metal ion bumps impact on the surface (Figure 4.14d).

Figure 4.14 AFM images of P. eryngii fungal biosorbent before (a) and after Cd(II)

sorption (c), three-dimensional images of P. eryngii fungal biosorbent before and after

Cd(II) sorption (b and d).

4.2.2 OPTIMIZATION OF BIOSORPTION EXPERIMENTAL PARAMETERS

To increase the Cd(II) ions uptake by fungal biosorbent; the influence of various

experimental parameters, i.e.; fungal cell mass state, pH, biosorbent dose, initial

68

Cd(II) ion concentration, temperature and time were optimized.

The state of the cell mass is a basic monitoring parameter in the biosorption process.

Therefore, Cd(II) ions biosorption capacity was checked toward different forms of

fungal cell mass (P-1 to P-5). As shown in Figure 4.15, that the maximum biosorption

efficiency was obtained from the oven-dried cell mass (P-1) as compared to other cell

states. Arica et al. [143] explained that during oven-dried biomass preparation, larger

surface area were developed as a result of cell membrane destruction.

Figure 4.15 Influence of P. eryngii fungal cell mass state on biosorption of Cd(II).

Secondly, the biosorption efficiency is considerably influenced by the pH of an

experimental solution. Figure 4.16a illustrates, the effect of pH on the sorption

capacity of P. eryngii biomass for Cd(II) ions. It is demonstrated from Figure

4.16a that the sorption efficiency of P. eryngii was 48% at initial pH 3.0, but

substantial increase in efficiency was observed from 55 to 70% as the pH of the

solution changed from 4.0 to 5.0 respectively. Owing to the high density of

proton (H+) on sorption sites of biomass surface, positively charged metal ions

were restricted as a result of electrostatic repulsion [144]. As the pH increases,

the negatively charged (OH-) group becomes available, which promote the

sorption of the positively charged metal ion.

Later, a drastic decline in the graph was observed as the pH was further

increased from 6.0 to 7.0 which indicate the low efficiency of P. eryngii at

higher pH. This effect attributed to the saturation of negative charge at higher

pH, due to the formation of anionic hydroxide complexes [Cd(OH)2]. These

69

complexes appeared as precipitates in solution and begin their competition with

the active sites [145].

Afterward, the subsequent experiments were continued at pH 5.0 ± 0.2 as

optimum pH. Akhtar et al. [146] demonstrated that carboxylic groups of the

fungal cell wall are major sites for metal ion absorption, as these functionalities

significantly deprotonated and readily bound to Cd(II) ions.

After pH optimization, the results were illustrated in Figure 4.16b showed lower

Cd(II) removal efficiency ~85% at small dose 0.1g of sorbent which significantly

enhanced up to 95% at the use of 0.2 g of P. eryngii fungal biomass. Further

increase in biomass resulted in decreased Cd(II) ions removal. Results of metal-

free control experiments after removal of fungal biomass, indicated that no

Cd(II) ions were present initially, hence cells were free from any Cd(II) ions

contamination.

At a given equilibrium concentration, the biomass takes up more metal ions at

lower cell densities than at higher cell densities [147]. It has been suggested that

electrostatic interaction between cells can be a significant factor in the

relationship between biomass concentration and metal sorption [103]. In this

regard, at a given metal concentration, the lower the biomass concentration in

suspension, the higher will be the metal / biosorbent ratio and the metal retained

by a sorbent unit, unless the biomass reaches saturation, suggesting that high

biomass concentrations can exert a shell effect protecting the active sites from

being occupied by the metal. Thus, a smaller amount of metal uptake per

biomass unit is enabled. In the present study, it was noted that the amount of

adsorbent significantly influenced the extent of Cd (II) biosorption.

Moreover, the effect of Cd(II) ion concentration on the adsorption efficiency of

P. eryngii fungal biomass was also done under optimum conditions as shown in

Figure 4.16c. The sorption efficiency increased from 37.5 to 98.1% for Cd(II)

ions with increasing initial concentration from 4.0 to 20 mg L-1. Tewari et al.

[148] explained that at lower initial concentration adsorption of the metal ions

occurred slowly, but the higher concentration enhanced the driving force

70

between the aqueous and solid phases, thus increase the number of collisions

between metal ions and adsorbents.

Temperature played a vital role in sorption process that is why the effect of

temperature in the range of 25 to 70°C for removal of Cd(II) ions were also

checked. By examining the sorption trend in Figure 4.16d, a significant increase

in percent removal (90 to 96%) was achieved when temperature increased from

25 to 50°C. However, further increase in temperature (>50°C) shows a decline in

the sorption efficiency due to deterioration of biomass boundary layer thickness.

This deterioration alters the active functionalities and attractive forces between

biomass surface and metal ion [149, 150]. Maximum sorption of Cd(II) ions were

achieved at 50 °C, which is similar as reported in the literature of various metal

ions sorption [151-153].

Figure 4.16 (a) Percentage removal of Cd(II) ions concentration as a function of pH

(biosorbent dose: 0.1g; initial concentration: 5.0 mg L−1; temperature: 30°C; contact

time: 20 min; agitation: 100 rpm). (b) Percentage removal of Cd(II) concentration as a

function of biosorbent dose (pH: 5.0; initial concentration: 5.0 mg L−1; temperature:

30°C; contact time: 20 min; agitation: 100 rpm). (c) Effect of concentration of Cd(II) on

their percent removal over P. eryngii (pH: 5.0; biosorbent dose: 0.2 g; temperature:

71

30°C; contact time: 20 min; agitation: 100 rpm). (d) Percentage removal of Cd(II)

concentration as a function of temperature (pH: 5.0; biosorbent dose: 0.2 g; initial

concentration: 20 mg L−1; contact time: 20 min; agitation: 100 rpm).

Contact time for sorbent and sorbate effects the percent removal efficiency of

targeted analyte and simultaneously used to elucidate the kinetics of reaction.

Figure 4.17 shows that the sorption process was slow at 1 to 2 minutes but later

the sorption efficiency was increased gradually with respect to time. The

maximum removal of Cd(II) ions ~99.9% was obtained within 10 min of reaction

time. This apparent change occurs because numerous sites are available for

sorption at the initial stage which provides the space for adsorption. After a few

minutes later, the remaining vacant surface sites were hard to occupy because of

the repulsive forces between Cd(II) ions and the aqueous phases [154-156]. From

the observed sorption trend, it was concluded that agitation time of 10 min is

suitable for complete removal of Cd(II) ions from aqueous system. Further

increase in contact time did not show any change which symbolizes the

attainment of equilibrium condition.

Figure 4.17 Percentage removal of Cd(II) concentration as a function of contact time

(pH: 5.0; biosorbent dose: 0.2 g; initial concentration: 20 mg L−1; temperature: 50°C;

agitation: 100 rpm).

4.2.3 BIOSORPTION ISOTHERM STUDIES

For Langmuir isotherm model, the straight-line graph Ce versus Ce/Cads (g L-1)

were extrapolated according to equation 1 which showed 0.928 regression

72

coefficient along with 1.515 mg g−1 of Q and 2.268 L mg-1 of b. Further

calculations provided RL between 0.002 – 0.099, which confirms the favorable

uptake of Cd(II) ions at all working Cd(II) ion concentrations (Figure 4.18a).

Later, Freundlich model was elaborated for the non-ideal sorption on

heterogeneous surfaces involving multilayer sorption. The graph Log Ce (mg L-1)

versus Log Cads (mg g-1) were plotted (Figure 4.18b) that shows a low value of

R2 0.855 then Langmuir isotherm model with Kf 15.595 mg g-1 and n 1.22.

It is concluded from the obtained data that the biosorption reaction follows

Langmuir isotherm which indicates the monolayer sorption phenomenon and

chemical type of interaction between sorbent surface and sorbate.

Figure 4.18 (a) Langmuir and (b) Freundlich isotherms for the biosorption of

Cd(II) ions on P. eryngii fungal biomass.

73

Moreover, biosorption capacity of P. eryngii was compared with previously

reported work and it is evident from the data that, sorption capacity of P. eryngii

is higher than other reported biosorbents (Table 4.7).

Table 4.7 Comparison of maximum biosorption capacity of P. eryngii for Cd(II)

with other reported biosorbents.

4.2.4 THERMODYNAMIC PARAMETERS

The thermodynamic parameters (ΔGº, ΔHº and ΔSº) were calculated from

Van’t Hoff plot of lnKc versus 1/T (Figure 4.19) according to the equation 12

and 13 respectively:


Biosorbents Biosorption capacity

(mg g-1) References

Wheat bran 0.67 [125]

Grafted rice husk 0.89 [126]

Saw dust 0.29 [126]

Wheat straw (Triticum aestivum) 1.48 [127]

P. eryngii 1.52 This work

74

The thermodynamic parameters for the sorption of Cd(II) ions on fungal biomass

are given in Table 4.8. The negative values of ΔGº and ΔHº at the studied

temperature range confirmed the spontaneous and exothermic nature of

biosorption process, respectively and indicates the feasibility of reaction against

elevated temperatures [18]. Moreover, Deng et al. [159] reported that enthalpy

change data is useful for distinguishing the physical and chemosorption

mechanism. Physisorption is typically associated with the heat of adsorption in

the range of 2.1-20.9 kJ mol-1, while chemisorption with ΔHº values 20.9-418.4

kJ mol-1. From the enthalpy value represented in tabulated data, it is concluded

that the biosorption of Cd(II) ions on P. eryngii is chemisorptive in nature.

The negative value of ΔSº reflects the decreased randomness at the solid-liquid

interface during sorption. According to Dos Santos et al. [137] the entropy value

less than zero demonstrate the occurrence of a certain order for the metal ions on

the biosorbent surface. This allowed that the biosorption were governed by

enthalpy factors as opposed to entropic factors.

Table 4.8 Thermodynamic parameters for Cd(II) biosorption on P. eryngii at

various temperatures.

4.2.5 BIOSORPTION KINETIC STUDIES

To analyze the biosorption kinetics and to calculate the adsorbate uptake

rate of Cd(II) ions on P. eryngii, two kinetic models i.e. Lagergren’s

pseudo first [160] and Ho-McKay’s pseudo second order [161] were

applied.

The first order rate equation of Lagergren is widely used for the sorption

of solute from a liquid solution and is represented in equation 9. Straight

line plot of t against ln(qe–qt) (Figure 4.20a) was used to determine the


288 -12.05

-67.75 -0.192 293 -11.63 298 -8.885 303 -3.174

343 -2.469

75

rate constant and biosorption capacity. The values of k1 and R2 along with

the calculated uptake capacity qe, cal are 0.202 min-1, 0.866 and 0.290 mg

g-1 respectively.

Figure 4.20 The kinetic fitting plots (a) pseudo first order and (b) pseudo second

order for the biosorption of Cd(II) ions on P. eryngii fungal biomass.

The pseudo second order kinetics of adsorption was applied to verify the

kinetic mechanisms between sorbate and sorbent. The parameters k2 and qe

were calculated by following the equation 10.

The straight-line plot (Figure 4.20b) of t versus t/qt indicate the relevancy of

the above equation for the biosorption of Cd(II) ions on fungal biomass. The

second order rate constant k2 1.867 g mg-1 min-1, correlation constant R2

0.999 along with calculated uptake capacity (qe) is 0.838 mg g-1.

76

Calculated correlations are closer to unity for the pseudo second-order kinetic

model and the predicted value of qe is comparable to the experimental one (q,

exp. 0.889 mg g-1); therefore, the biosorption kinetics could well be

approximated more favorably by second-order kinetics model than pseudo-

first order kinetics.

The results are also analyzed in terms of Weber and Morris intra particle

diffusion model to investigate whether the intra particle diffusion is the rate

controlling step in biosorption of Cd(II) on P. eryngii biomass. According to

this model intra particle diffusion varies with the square root of time as given

in equation 11:

The values of kid 0.073, C 0.547 and R2 0.99 were obtained from the slope of

t1/2 versus qt plot (Figure 4.21). It is observed from the plot that intercept

does not pass through the origin, thus pore diffusion is not only the rate

determining factor for the biosorption of Cd(II) ions on P. eryngii.

Figure 4.21 Intra particle diffusion for the biosorption of Cd(II) ions on P. eryngii

fungal biomass.

By comparing constants of all kinetic models, it is evaluated that pseudo

second order kinetic model best fitted for the biosorption experiment.

77

4.2.6 ELUTION OF CD(II) ION AND RE-USABILITY OF BIOSORBENT

To reuse the biomass for next sorption reaction Cd(II) ions desorption study was

carried out. The results presented in Figure 4.22a showed maximum recovery of

99.89% Cd(II) ions with the use of HNO3 as eluent. The result illustrate following

order of elution performance: HNO3 > HCl > EDTA > H2SO4 > NaOH > NaCl.

For the complete unloading of Cd(II) ions, the biomass was washed with an

excess amount of HNO3 followed by appropriate washing with ultra-pure water to

a maximum removal of H+ ions from the surface of sorbent to maintain the

removal efficiency of sorbent.

Thereafter, the unloaded fungal biomass was re-used for the next set of

experiment. The data present in Figure 4.22b shows that the sorption efficiency

was decreased from 99.99 to 56.89% as the biomass were re-cycled up to 5 times.

Figure 4.22 (a) Influence of various eluents on percentage recovery of Cd(II) ions

by P. eryngii fungal biomass. (b) Desorption efficiency of P. eryngii with cycle

number.

78

The reduction in efficiency could be attributed to the use of HNO3 solution which

enriches the H+ ions on the biomass surface and results in the electrostatic repulsion

of positively charged Cd(II) ion that eventually causes the decrease in sorption

capacity.

4.2.7 INFLUENCE OF INTERFERING IONS

Table 4.9 shows the effect of different interfering ions during biosorption of

Cd(II) from aqueous system. Selected concentration of co-existence ions was

added to 10 mL test solution of Cd(II) ion (5 mg L-1) and then subjected to

the general procedure.

From the results of an interfering study it was found that the ions naturally

existing in real samples (Na+, K+, Ca2+, Mg2+, SO42-, NO3

-, PO43-, Cl-) have no

significant effect on the removal of Cd(II) ions under experimental conditions.

Exceptionally, PO43- anion may severely interfere in the determination of

Cd(II) probably due to the formation of precipitates in the working pH. These

results confirmed that the proposed pre-concentration method could be applied

to samples that contain a high number of interfering ions at ppm (mg L-1)

[162].

Table 4.9 Influence of some interfering ions on biosorption of Cd(II).

S. No. Interfering ions Interfering conc. % Biosorption

Cd(II) : Cation

1. Na+ 100 97

2. K+ 100 99

3. Ca2+ 50 97

4. Mg2+ 50 98

Cd(II) : Anion

5. SO42- 100 97

6. NO3- 100 99

7. PO43- 100 95

8. Cl- 100 99

79


To set up the validity of proposed method, the batch biosorption study was

performed in real field application. Three water samples having a higher

concentration of Cd(II) ions were collected from river, canal, and lake of

Sindh, Pakistan. In general, the removal efficiency for Cd(II) was higher for

synthetic wastewater (>98%) than for real water samples (~90%) as presented

in Table 4.10. It is because in real water samples, on the contrary to synthetic

wastewater, supplementary cations are competing with Cd(II) for active sites

on the fungal biomass and at the same time many anions are in complexation

reaction with Cd(II). Both affect may cause to reduce the sorption efficiency

in real samples.

Table 4.10 Field trial results of biosorption studies using real water samples.

*S-1 = Phuleli canal, Hyderabad; S-2= River indus, Jamshoro; S-3= Manchar Lake, Distt. Dadu.

Though, the efficiency of Cd(II) removal from real water samples lies between

85 to 90% which accomplished that this proposed technique is feasible, reliable

and suitable for the removal of Cd(II) ions from real water samples.

4.2.9 SUMMARY

The present study provides an efficient, cost-effective and environmental

friendly biosorbent with its high potential in removing Cd(II) ions from aqueous

system. The sorption of Cd(II) ions was found to be pH dependent and maximum

removal was observed at pH 5.0. P. eryngii biomass was successfully utilized for

the removal of Cd(II) ions from aqueous solution with 99.9% sorption efficiency.

The sorption was rapid and equilibrium was achieved within 10 min. Langmuir

isotherm offers the best correlation for the adsorption of Cd(II) ions confirming

monolayer coverage. The sorption process obeyed a pseudo second order kinetic

model. Batch elution process revealed that the complete elution of Cd(II) ions

Sample

I.D.* Cd(II) concentration (mg L-1)

in sample water Cd(II) sorption

(%)

Amount of Cd(II)

after biosorption (mg L-1)

S-1 0.04 90 0.003 S-2 0.03 92 0.002 S-3 0.05 91 0.003

80

was achieved from the biomass using 0.1 N HNO3 solution. The used fungal

biomass can be easily disposed of since it is biodegradable and can also be used

as an alternative raw material for the large-scale composting process. Besides,

people of affected areas can take advantage of this natural safe method for

removal of toxic Cd(II) ions from contaminated water.

81

PART 3

Remarks: All work of this part has been published in J. Environ. Prog. Sustain.

Energy 35(5):1274-1282.

4.3 BIOSORPTION OF HG(II) FROM AQUEOUS SOLUTION BY FUNGAL

BIOMASS P. ERYNGII: ISOTHERM, KINETIC AND THERMODYNAMIC

STUDIES


SEM-EDX ANALYSIS

SEM micrographs and EDX spectra of pure and Hg(II) loaded P. eryngii biomass

are presented in Figure 4.23.

Figure 4.23 SEM images of P. eryngii before and after Hg(II) biosorption (a & b); EDX

analysis of P. eryngii before and after Hg(II) biosorption (c & d).

82

Obvious morphological changes were seen in the cell wall structure after metal

binding, where metal seems to be deposited on the surface of the biomass as a

glossy film like structure.

Biosorption of Hg(II) was also confirmed by EDX analysis, which revealed the

presence of Hg(II) signal on the metal loaded fungal biomass.

FTIR ANALYSIS

FTIR spectroscopy was carried out to identify the functional groups present on

fungal biomass before and after Hg(II) biosorption (Figure 4.24). The broad band

at 3395 cm-1 before Hg(II) uptake indicate the presence of hydrogen bonded –OH

stretching modes from alcohols or phenols and may also dominate by –NH

stretching. The peak 2920 cm-1 represents –CH stretching on the cell surface of

fungal biomass. The band at 2354 cm-1 is mostly due to atmospheric carbon

dioxide (CO2).

Figure 4.24 FTIR spectra of P. eryngii before (a) and after (b) Hg(II) ions biosorption.

The bands appearing at 1639, 1544, 1380, 1230 and 1073 cm-1 are due to C=C

stretching, –NH bending, alkyl group, –CN stretching and –CO stretching

respectively; indicating major changes in their peak positions after sorption of

Hg(II). All these changes indicate the participation of N or O groups present on

biomass for Hg(II) sorption. The change in 1380 to 1373 cm-1 may be due to the

83

presence of oxygen atom attached with alkyl group that may have coordinated

with Hg(II). The band assignments are shown in Table 4.11.

Table 4.11 Surface functionalities observed on fungal biosorbent by FTIR

spectroscopy.

Before biosorption (cm-1)

After biosorption (cm-1)

Band assignment

3395 3420 -OH, -NH stretch 1639 1645 C=C stretch 1544 1555 -NH bending vibrations 1380 1373 CH3, alkyl groups 1230 1219 -CN stretching vibrations 1073 1027 -C-O stretch

4.3.2 EFFECT OF INITIAL PH

The pH is an important variable governing the biosorption of metal ions by

sorbent that influence both cell-surface metal binding sites and metal chemistry

in water. Effect of pH for the removal of Hg(II) ions by P. eryngii biomass was

studied in the pH range 3.0–9.0 as shown in Figure 4.25a. At low pH values (pH

<5), the cell wall ligands (hydroxyl group or other lone pair carrier groups as

carbonyl) would be closely associated with the hydronium ions (H3O+) that limit

access to ligands by metal ions due to repulsive forces; this repulsion is stronger

as pH decreases. Hence, there arises a competition between H3O+ ions and Hg(II)

metal ions in the solution. As the pH increased, further ligands probably

exposed, i.e. carrying negative charges, with the subsequent attraction of

metallic ions with a positive charge and adsorption onto the cell surface. Beyond

optimum pH, an alkaline condition led to decreased Hg(II) removal efficiency; it

is because at high pH, the solution has an excess number of OH− ions, which

enhance the probability of salt or hydroxide formation with metal ions in the

solution. In case of alkali and alkaline earth metal ions, this probability can be

ignored as their hydroxides are soluble but for heavy metal ions like Hg(II) and

so forth, it contributes significantly. Hence, the optimum pH for maximal Hg(II)

sorption was thus determined to be around 7.0.

The point of zero charge (pHpzc) represents the pH where sorbent surface

becomes electrically neutral. Above the pHpzc value, surface of biosorbent

84

acquired negative charge, whereas below the pHpzc point surface acquired

positive charge [113]. Hence, cationic biosorption will be favorable above the

pHpzc point and anionic will be optimum below the pHpzc point. The value of

pHpzc was found to be 5.75 for P. eryngii (Figure 4.25b). The results are in

agreement with the pH values obtained for the same experiment showing

maximum biosorption at pH 7.0 for P. eryngii.

Figure 4.25 (a) Percentage removal of Hg(II) ions as a function of pH (temperature:

30°C; agitation:100 rpm; biosorbent dose: 0.1 g; initial concentration: 1.0 mg L−1;

contact time: 30 min). (b) Plot of pHi vs. ΔpH to obtain point of zero charge (pHpzc)

value for the proposed biosorbent P. eryngii fungal biomass.

4.3.3 EFFECT OF INITIAL BIOMASS CONCENTRATION

The biosorption efficiency for Hg(II) ions was found to be increased

proportionally with the biosorbent concentration from 0.15 to 0.35 g (Figure

4.26). This result can be explained by the fact that with the increase in biomass

concentration, more sites are available for Hg(II) sorption. The maximum

85

biosorption (77.4%) was achieved at 0.25 g biomass concentration. However,

further increase in sorbent concentration did not result in a sufficient increase in

the biosorption yield due to the aggregation of available binding sites [128].

Figure 4.26 Percentage removal of Hg(II) ion as a function of biosorbent dose (pH: 7.0;

temperature: 30°C; agitation: 100 rpm; initial concentration: 1.0 mg L−1; contact time:

30 min).

4.3.4 EFFECT OF INITIAL HG(II) CONCENTRATION

The initial concentration of Hg(II) ions in the solution remarkably influenced the

sorption process. The biosorption of Hg(II) raised (58 to 83.4%) as the initial

concentration increased from 0.5–7.5 mg L-1 (Figure 4.27), after that no increase

was observed because the system reaches to a saturation point after attaining

equilibrium [129].

Figure 4.27 Percentage removal of Hg(II) ion as a function of biosorbent dose (pH: 7.0;

temperature: 30°C; agitation: 100 rpm; biosorbent dose: 0.25 g; contact time: 30 min).

86

4.3.5 EFFECT OF CONTACT TIME AND TEMPERATURE

Contact time is one of the significant factors, which imparts practical application

of the biomass. Figure 4.28 shows the effect of contact time on the removal of

Hg(II) ions by P. eryngii.

The percent removal rapidly increases up to 96.97% with a rise in contact time.

The rapid biosorption rate at the beginning of the sorption process may be

explained by an increase in the number of active metal binding sites on the

sorbent surface. After an increase in contact time, the saturation of active sites

inhibits the further uptake ability of biosorbent [130].

Figure 4.28 Percentage removal of Hg(II) as a function of contact time (pH: 7.0;

temperature: 30°C; agitation: 100 rpm; biosorbent dose: 0.25 g; initial concentration:

7.5 mg L−1).

The biosorption of Hg(II) by P. eryngii fungus appears to be temperature-

dependent over the temperature range tested. The effect of temperature on Hg(II)

biosorption was studied in range from 30–60ºC.

87

Figure 4.29 Percentage removal of Hg(II) as a function of contact time (pH: 7.0;

agitation: 100 rpm; biosorbent dose: 0.25 g; contact time: 5 min; initial concentration:

7.5 mg L−1).

The observed trend with increasing temperature (Figure 4.29) suggests that the

biosorption process of Hg(II) by the fungal biomass is unfavorable in a higher

temperature. It is because elevated temperatures tend to decrease the boundary-

layer thickness; therefore, escaping tendency of Hg(II) metal ions increased from

the biomass surface to the solution phase and thus less time of interaction

available for Hg(II) ions with biosorbent active sites. The decreased biosorption

efficiency with a rise in temperature also suggests weak sorption interaction

between biomass surface and the metal ion, which supports physiosorption [129,

131].

4.3.6 BIOSORPTION ISOTHERMS

In the present work, the equilibrium data were analyzed by the linear regression

of two isotherm models. That is, Langmuir and Freundlich isotherm.

The Langmuir isotherm theory assumes monolayer coverage of sorbate / Hg(II)

over a homogeneous biosorbent surface. It is valid for single-layer biosorption

and based on the assumption that all the biosorption sites have equal affinity for

sorbate molecules and there is no transmigration of sorbate on the surface. The

linear form of Langmuir isotherm is calculated by equation 1.

The Q value was calculated from the slope of a linear plot of Ce/Cads versus Ce.

The related parameters obtained by calculation from the values of the slope and

intercept of the respective linear plot (Figure 4.30) are shown in Table 4.12.

88

Figure 4.30 Langmuir plot for Hg(II) biosorption on P. eryngii biomass.

Table 4.12 Hg(II) biosorption: Langmuir and Freundlich isotherm constants.

All the values of RL were between 0 and 1indicated that biosorption is favorable

to the conditions being applied [132]. The Langmuir biosorption capacities

obtained in the present study were compared with those reported earlier (Table

4.13).

Table 4.13 Comparison of biosorption capacity of P. eryngii fungal biomass for

Hg(II) ions with other reported biosorbents.

Biosorbents Biosorption

capacity (mg g−1) References

Camel bone charcoal 28.2 [36]

Eucalptus bark 33.1 [37] Streptococcus pyogenes 4.8 [38] Garlic (Allium sativum L.) 0.65 [39]

P. eryngii 34.01 Present study

On the other hand, Freundlich biosorption isotherm is an empirical equation that

describes the biosorption in heterogeneous systems and exponential distribution

of sites and energy. The linearised Freundlich isotherm is given in the following

equation 3.

Langmuir Freundlich Q (mg g−1)

B (L mg−1)

RL R2 Kf (mg g−1)

N R2

34.01 0.25 0.28–0.88 0.925 0.15 1.57 0.99

89

Freundlich isotherm constants of the biosorbent (Figure 4.31) were calculated

from the slope and intercept of the linear plot log Cads vs. log Ce.

Figure 4.31 Freundlich plot for Hg(II) biosorption on P. eryngii biomass.

The value of n is < 1, shows that biosorption of Hg(II) ions on fungal biomass is

a chemical type of interaction. Assuming the regression coefficient, the obtained

data fit the Freundlich adsorption isotherm.

4.3.7 BIOSORPTION KINETICS

Kinetics of metal sorption governs the rate that determines the residence time,

and it is one of the important characteristics defining the efficiency of a sorbent.

Figure 4.32 Lagergren / Pseudo first order plots for Hg(II) biosorption on P. eryngii

biomass at 30°C.

90

In this study, the biosorption kinetics were investigated by using two kinetic

models, Lagergren’s pseudo first and Ho McKay’s pseudo second order model.

The pseudo first order rate equation is stated as in equation 9. The plot of ln (qe–

qt) against t (Figure 4.32) yields a correlation coefficient of 0.879, which

concluded that biosorption of Hg(II) on fungal biomass do not follow pseudo

first order kinetics (Table 4.14).

Table 4.14 Kinetic model parameters for the biosorption of Hg(II) ions by

P. eryngii.

Pseudo first order Pseudo second order Experimental

value

k1

(min-1)

qe, cal.

(mg g-1) R2

k2

(g mg-1 min-1)

q, cal.

(mg g-1) R2

q, exp.

(mg g-1)

2.677 0.115 0.879 6.077 0.310 0.997 0.291

The plot of t/qt versus t for pseudo second order model following equation 10

yields (Figure 4.33) a good correlation coefficient, where; qe, and k can be

determined from the slope and intercept of the plot, respectively.

Figure 4.33 Ho-McKay / Pseudo second order plots for Hg(II) biosorption on

P. eryngii biomass at 30 °C.

Additionally, experimental value is in a good accordance with the calculated

equilibrium biosorption capacity qe, cal. Therefore, it is possible to suggest that

the biosorption of Hg(II) by fungal biomass followed the pseudo second order

reaction, which relies on the assumption that chemisorption may be the rate-

91

limiting step. In chemisorptions, the Hg(II) ions stick to the biosorbent surface

by forming a chemical bond and tend to find sites that maximize their

coordination number at the surface. The biosorption kinetics constant obtained

from the pseudo second order model is given in Table 4.14.

4.3.8 BIOSORPTION THERMODYNAMICS

The thermodynamic behavior of the biosorption of Hg(II) ions on P. eryngii

biomass was investigated using parameters that include; change in free energy

(ΔG°), enthalpy (ΔH°) and entropy (ΔS°). These parameters were calculated

from following equations 12 and 13.

The values of ΔH° and ΔS° were computed from the slope and intercept of lnKc

vs. 1/T (K−1) by Van’t Hoff plot as shown in Figure 4.34.


Gibbs free energy change (∆Gº) was calculated to be −10.9, −5.83, −4.74, and

−3.92 kJ mol−1 for Hg(II) biosorption. The negative ∆Gº values suggest that

biosorption process is thermodynamically feasible and spontaneous in nature.

The ∆Hº parameter was found to be −78.1 kJ mol−1. The negative ∆Hº shows the

exothermic nature of the biosorption process at 30–60 ºC. The ∆Sº parameter

was found to be −0.226 kJ mol−1 K−1. The negative ∆Sº value intends a decrease

in the randomness at solid/solution interface during the biosorption process of

Hg(II).

92

4.3.9 EFFECT OF CO-EXISTING IONS

The Hg-contaminated water may contain several other ions which may compete

with the sorption process of Hg(II) ions by P. eryngii. The present study assessed

Hg(II) ions sorption behavior in the presence of 2 folds (2 mg L-1) chromium,

lead, copper, cadmium, selenium; 5 folds (5 mg L-1) magnesium, calcium; and 10

folds (10 mg L-1) sodium, potassium, fluoride, chloride, nitrate, sulfate; keeping

initial Hg(II) concentration as 1 fold (1 mg L-1).

As shown in Table 4.15, most of the investigated ions that frequently exist in

natural ground water do not interfere with the sorption of Hg(II) under selected

experimental conditions. The high sorptive selectivity and affinity toward Hg(II)

ions in the present study could be due to relatively high affinity to the binding

groups, that makes P. eryngii fungal biomass a highly suitable sorbent for water

treatment applications.

Table 4.15 Effect of some interfering ions on the removal process of Hg(II) ions

by P. eryngii.

Tolerance ratio Interfering ions % Biosorption

Hg : Cation

1:2

Cr6+ 96

Pb2+ 95

Cu2+ 97

Cd2+ 96

Se4+ 97

1:5 Mg2+ 98

Ca2+ 97

1:10 Na+ 95

K+ 96

Hg : Anion

1:10

F- 98 Cl- 97

NO3- 95

SO42- 95

4.3.10 DESORPTION EFFICIENCY AND REUSABILITY

A batch desorption study was conducted to recover the metal, to regenerate P.

eryngii for repeated use and to recycle the metal-recovered wastewater. After

performing biosorption experiments with 5 mg L-1 of Hg(II) solution and 0.3 g of

93

biomass dose at pH 7.0, the biomass was washed with deionized water for 15

min and left in HCl eluting agent of different concentrations for 5 min agitation

at room temperature. The biomass was separated from the solution by filtration

and washed with deionized water until the pH of the filtrate reached 7.0. Then

the recovered biomass was dried in an oven at 60oC, and the biosorption

efficiency were determined. The results are illustrated in Table 4.16.

Table 4.16 Desorption of Hg(II) ions by P. eryngii.

To show the reusability of the biosorbent, the sorption desorption cycle for

Hg(II) ions was repeated five times using the same fungal biomass (Table 4.17).

In addition, the sorption efficacy of biosorbent reduced up to 14.7% through the

repeated operation. The regeneration of biomass shows that it has good reuse

performance for its possible utilization in continuous systems in industrial

processes. A promising cause of reduction in the biosorption capacity of the

fungal cells could be attributed to the adverse effect of the desorbing agent on

the binding sites of the fungal cell wall components (i.e. HCl hydrolyses most of

the fungal cell macromolecules).

Table 4.17 Adsorption-desorption of Hg(II) ions by P. eryngii using 5 M HCl

as eluent.

Cycle Hg(II) biosorption (%) 1 99.1 2 95.6 3 92.3 4 90.1 5 85.3

Eluent Concentration (M) Desorption (%)

HCl

0.1 54.5 0.5 57.2 1.0 60.5 3.0 77.8 5.0 99.1

94


To validate the performance of newly explored biosorbent, P. eryngii was

applied to natural water samples that were collected from various locations of

Sindh, Pakistan. The amount of Hg(II) in all water samples was found above the

permissible limit (0.001 mg L-1) of WHO drinking water standards.

Table 4.18 Analytical results for the biosorption of Hg(II) ions in natural water

samples.

*S-1= Gajrawah Canal, Nawabshah; S-2= Phuleli Canal, Hyderabad; S-3= Manchar Lake, Distt. Dadu; S-4= Korangi

Creek, Karachi.ꜝN.D. = not detected.

The removal process of water samples was carried out at optimum conditions.

The results are given in Table 4.18 showed that the Hg(II) level in every single

real water sample decreased well below the acceptable limit.

4.3.12 SUMMARY

In the present study, biosorption of Hg(II) ions from aqueous solution on P.

eryngii fungal biomass was investigated. Different experimental parameters such

as the effects of pH, sorbent dose, initial Hg(II) ion concentration, contact time,

and temperature were evaluated systematically. The sorption process was

relatively fast and > 98% removal of Hg(II) was achieved within 5 min at pH

7.0. To analyze the suitability of the process and maximum amount of metal

uptake, Langmuir and Freundlich isotherm models were applied. The biosorption

capacity of P. eryngii fungal biomass was found to be 34.01 mg g-1. Among

kinetic models studied, the pseudo second order was the best applicable model to

describe the sorption process. Thermodynamic parameters of Hg(II) sorption

were evaluated by applying the Van’t Hoff equation which indicates that the

sorption process was exothermic and spontaneous by increased randomness at

the solid-solution interface. The adsorbed Hg(II) ions were easily desorbed from

Sample

I.D.* Hg(II) concentration

(mg L-1) in sample water Hg(II) biosorption

(%)

Amount of Hg(II) after biosorption

(mg L-1) S-1 0.0030 75.0 0.0007 S-3 0.0029 91.3 N.D.ꜝ S-3 0.0019 64.2 0.0006 S-4 0.0020 70.5 0.0005

95

the fungal biomass using 5 M HCl solution with higher effectiveness and can be

reused up to five cycles. The nature of the possible cell-metal ion interactions

was evaluated by FTIR, SEM, EDX and pHpzc analysis. These examinations

indicate that different electronegative functionalities involve in the binding of

Hg(II) metal ions on the surface.

96

PART 4

Remarks: All work of this part has been published in J. Environ. Nanotechnol.

Monit. Manage. 3:30-37.

4.4 BIOSORPTION OF F- FROM AQUEOUS SOLUTION BY WHITE - ROT

FUNGUS P. ERYNGII ATCC 90888


SEM AND EDX STUDIES

SEM images of untreated sample of P. eryngii exhibits non-adhesive and matt

appearance (Figure 4.35a) without well-defined porous structure (only few pores

on the surface). After biosorption, the surface of P. eryngii become adhesive in

appearance as evident from Figure 4.35b.

Figure 4.35 SEM/EDX images of P. eryngii biomass: (a) and (c) are unloaded; while (b)

and (d) are F- loaded pattern of fungal biosorbent.

Elemental composition of pure and F- loaded biomass analyzed by SEM / EDX

are shown in Figure 4.35c and d. The weight percent of F- loaded fungal biomass

gives F- peak (0.32% in weight) apart from C (34.85%) and O (22.18%) peaks.

97

The presence of prominent F- peak indicates that F- is superficially biosorbed on

the surface of P. eryngii.

FTIR STUDIES

To determine the characteristic functional groups responsible for biosorption of

F- ions by P. eryngii, FTIR spectroscopy was utilized as a powerful tool.

Biosorption of F- has resulted in several changes like the disappearance of some

bands, shifts and decrease in the percentage of transmittance in the IR spectra of

the solid surface in the range 4000-500 cm−1. Interpretations of the spectra were

based on the information acquired from literature [133].

The FTIR spectra of the biosorbent before and after F- sorption are shown in

Figure 4.36. Very strong broad band at the region of 3500-3200 cm-1 is the

overlapping peak of –NH2 and –OH stretching vibrations [134]. The peak around

2923.0 and 2852.3 cm−1 is due to presence of aliphatic (–CH2) groups in the

biomass. The strong bands at 1724.6 and 1654.1 cm−1 may be due to involvement

of double bond structures such as C=C or C=O groups. The peaks at 1558.0 and

1457.1 cm−1 attributed to N−H bending in the amine group. The band observed at

1043.8 cm−1 was assigned to the C-O stretching of alcohols and carboxylic acids.

Thus, P. eryngii contain hydroxyl, carboxyl, and amine groups on its surface as

important sorption sites.

The peaks for –NH2 were shifted from 1558.0 and 1457.1 to 1539.4 and 1456.1

cm−1 in F- loaded biomass. This decrease in the wave number of the peaks may

indicate the interaction of –NH2 group of biomass with F- ions. The hydrogen

bonding in amines is weaker than that of hydroxyl groups, so –NH2 stretching

bands are not as broad or intense as –OH stretching bands [115]. A slight

broadening of –NH2 stretching band in the F- sorbed P. eryngii (Figure 4.36a)

may be taken as an indicative of hydrogen bonding between the protonated

amine (–NH3+) and F- [19]. Comparable results were reported by other authors

while studying F- sorption on chelating ion exchange resins [18]. After sorption

of F-, the carboxyl peak that observed in unloaded fungal biomass at 1724.6 cm−1

becomes very sharp and shifts to higher wave number 1747.1 cm−1. This could

be due to the interaction of hydrogen atoms in the carboxylic group and F- ions.

98

Consequently, new bands appear at 1078.0, and 999.7 cm−1 after F- biosorption

(Figure 4.36b), may indicate the presence of –C–F stretching modes.

Figure 4.36 FTIR spectra of P. eryngii (a) before and (b) after F- sorption.

4.4.2 CALIBRATION OF IC FOR F- ANALYSIS

F- ion samples were subjected to IC analysis. For ion chromatography, standards

of F- were run consecutively (5-100 mg L-1) as shown in Figure 4.37. They

showed good separation, as evident from Figure 4.38.

Figure 4.37 IC-Chromatogram of F- standards.

99

Figure 4.38 Linear calibration plot of F- at different concentrations.

4.4.3 INFLUENCE OF PH

The solution pH is one of the main factors which affect the biosorption capacity.

The fungal cell wall contains a high number of polysaccharides and some of

them are associated with proteins and other components [135]. These bio-

macromolecules on the fungal cell surfaces have several functional groups (such

as amino, carboxyl, thiol, and phosphate groups) and biosorption phenomena

depends on the protonation or deprotonation of these functional groups on the

surface of the cell wall [89]. The ionic form of F- in solution and the electrical

charge of the fungal cell wall components (i.e. functional groups carrying

polysaccharides and proteins) depend on the solution pH [135]. To study the

effect of pH on F- sorption (5 mg L−1) by P. eryngii, studies were performed at

various solution pH (i.e., 2–7) as shown in Figure 4.39a. The pHpzc of P. eryngii

was found to be 5.75 which suggest that defluoridation capacity of the fungal

biosorbent is appreciable in acidic range (pH<pHpzc). At pH 2, the maximum

percentage (81.2%) of F- removal was achieved. While increase in pH decrease

the sorption capacity of F-. The same trend has been reported in Moringa indica

based activated carbon [136].

At acidic pH due to the protonated effect of surface functionalities such as

amino, carboxyl, thiol etc, positive charges impart on the surface [89, 136, 137]

and hence increase the biosorption of negatively charged F- ions at lower pH.

100

Figure 4.39 (a) Percentage removal of F- concentration as a function of pH (biosorbent

dose: 0.1g; initial concentration: 5.0 mg L−1; temperature: 30°C; contact time: 240 min;

agitation: 100 rpm). (b) Effect of concentration of F- on their percent removal over P.

eryngii (pH: 2.0; biosorbent dose: 0.1 g; temperature: 30°C; contact time: 240 min;

agitation: 100 rpm). (c) Percentage removal of F- concentration as a function of

biosorbent dose (pH: 2.0; initial concentration: 5.0 mg L−1; temperature: 30°C; contact

time: 240 min; agitation: 100 rpm). (d) Percentage removal of F- concentration as a

function of contact time (pH: 2.0; biosorbent dose: 0.2 g; initial concentration: 5.0 mg

L−1; temperature: 30°C; agitation: 100 rpm).

4.4.4 INFLUENCE OF INITIAL F- CONCENTRATION

The effect of initial F- concentration was studied by varying F- concentration

from 5 to 25 mg L−1 at pH 2. Maximum biosorption (92%) was achieved at 5 mg

L−1, which shows that all F- ions present in the solution would interact with

binding sites (Figure 4.39b). At higher concentration, more F- ions are left

unabsorbed in the solution due to the saturation of binding sites [138].

101

4.4.5 INFLUENCE OF BIOSORBENT DOSE

Biosorbent dose is an important parameter owing to its effect on efficiency and

on the amount of F- removed per unit weight of biomass. Biosorbent dosages was

varied from 0.1 to 0.5 g under optimum conditions (pH: 2.0; concentration: 5 mg

L−1; temperature: 30°C; time: 240 min; agitation: 100 rpm). At 0.2 g of

biosorbent maximum F- removal (97.03%) was obtained and remains constant

with the increase in dosage of biosorbent (Figure 4.39c). Therefore 0.2 g of the

biomass was taken as the optimized dose for F- removal and used for further

experiments. The increase in F- removal with increase in biosorbent dose is due

to the greater availability of exchangeable sites or surface area of the biosorbent.

By further increment in sorbent dose, the removal capacity was not increased

possibly due to the aggregation of available binding sites.

4.4.6 BIOSORPTION ISOTHERM MODELS

The biosorption isotherm expresses the specific relation between the

concentration of F- and its degree to accumulate on biosorbent surface at

constant temperature. The equilibrium data was analyzed by the linear regression

of isotherm models, viz., Langmuir, Freundlich and D-R isotherm.

LANGMUIR BIOSORPTION ISOTHERM

The Langmuir isotherm theory assumes monolayer coverage of sorbate (F-) over

a homogeneous biosorbent surface. The Langmuir isotherm model is given in

Figure 4.40a and its linearised form is given in equation 1.

102

Figure 4.40 Adsorption isotherms plot (a) Langmuir, (b) Freundlich, and (c) D-R.

103

Table 4.19 Langmuir, Freundlich and D–R isotherm constants

(Initial F- concentration range = 5 – 25 mg L−1).

The related parameters obtained by calculation shown in Table 4.19. All the

values of RL were between 0 and 1 suggesting biosorption is favorable at the

conditions being applied [10].

The Langmuir biosorption capacities obtained in the present study were

compared with those reported earlier (Table 4.20). The present study shows that

P. eryngii is an effective low-cost biosorbent for the removal of F- from aqueous

solutions.

Table 4.20 Comparison of biosorption capacity of P. eryngii fungal biomass for

F- ion with other reported biosorbents.

Biosorbent Biosorption capacity (mg g−1) References

Used tea leaves 0.51 [139]

Spirodela polyrrhiza 0.91 [140]

Rice husk 0.82 [141]

Pleurotus ostreatus – 1804 1.27 [135]

Spirogyra IO1 1.27 [103]

Moringa indica based activated carbon 0.23 [136]

Ca-treated Chlorococcum humicola 4.50 [142]

P. eryngii 66.6 Present

study

FREUNDLICH BIOSORPTION ISOTHERM

This is an empirical equation that describes biosorption in heterogeneous system

and exponential distribution of sites and energy. The Freundlich biosorption

Langmuir Freundlich D-R

Q (mg g−1)

B (L mg−1)

RL R2 Kf (mg g−1)

N R2 Xm (mol g−1)

E (kJ

mol−1) R2

66.60 1.5 0.025 –

0.117 0.998 36.72 2.33 0.976 0.004 2.056 0.911

104

isotherm is given in Figure 4.40b and its linearised form is given in equation 3.

The value n > 1 indicate that biosorption of F- is favorable [143].

D-R BIOSORPTION ISOTHERM

To evaluate the adsorption type, equilibrium data was applied to D-R isotherm

with following equation 6. While biosorption energy E (kJ mol-1) is calculated by

equation 7 and 8.

The calculated parameters of D-R model from plot (Figure 4.40c) are presented

in Table 4.19. The value E > 8 kJ mol-1, showed that F- - biomass interaction is

chemisorption in nature.

From results obtained, it was established that experimental data fit the Langmuir

adsorption isotherm.

4.4.7 THERMODYNAMIC STUDIES

The uptake of F- is highly dependent on temperature. The percentage biosorption

of F- increased from 78.38 to 97.0% when the temperature changes in the range

of 288˗303 K (15 to 30°C). This is because biosorption get accelerated at higher

temperature, which in turn indicate endothermic nature of reaction.

The change in standard Gibb’s free energy (ΔG°), enthalpy (ΔH°) and entropy

(ΔS°) were evaluated from the thermodynamic study as given in equation 12 and

13.


105

The values of ΔH° and ΔS° were computed from the slope and intercept of lnKc

vs. 1/T (K−1) by Van’t Hoff plot as shown in Figure 4.41. The negative values of

ΔG° (Table 4.21) indicate the spontaneity of the biosorption reaction,

emphasizing that biosorption is more favorable at higher temperature.

Table 4.21 Themodynamic parameters for F- biosorption on P. eryngii at various

temperatures.

Similarly, the value of ∆H° obtained in present study confirms that biosorption is

endothermic in nature and exhibits chemical mechanism. The positive value of

ΔS° indicates strong affinity of biosorbent toward F- molecule and shows

increasing randomness at the solid / liquid interface during biosorption [144].

4.4.8 KINETIC STUDIES

Figure 4.38d illustrates the removal of F- by fungal biomass as a function of

contact time (60-300 min) at 30 °C. The F- removal efficiency was increased

linearly up to 240 min and thereafter it remains constant indicating the

attainment of biosorption equilibrium. Therefore, 240 min was fixed as optimum

contact time for the defluoridation with maximum F- removal of 97.7%.

To investigate the mechanism of biosorption process, the two main types of

biosorption kinetic models, namely reaction based (pseudo first and pseudo

second order model) and diffusion based (intra particle diffusion) models were

adopted to fit the experimental data.

REACTION BASED MODELS

The pseudo first order rate equation is given in equation 9. Straight line plots of

ln (qe–qt) against t (Figure 4.42a) were used to determine the rate constant k1,


288 -3.083

+107.10 0.379 293 -3.414 298 -5.084 303 -8.752

106

and adsorption capacity. From results (Table 4.22) it was concluded that

biosorption of F- on fungal biomass did not follow pseudo first order kinetics.

The pseudo second order equation is expressed in equation 10.

Table 4.22 Kinetic parameters for F- biosorption on P. eryngii.

(Experimentally obtained qe,exp. value is 0.244 mg g−1 for 5 mg L−1 initial F-

concentration).

Figure 4.42 Pseudo first order (a), pseudo second order (b), and Intra particle diffusion

kinetic models (c) plots for the sorption of F- ions onto fungal biomass.

Pseudo first order model Pseudo second order model

k1

(min-1) qe,cal.

(mg g-1) R2

k2

(g mg-1 min-1)

q,cal.

(mg g-1)

h (mg g-1 min-1)

R2

0.051 0.132 0.843 0.438 0.252 0.028 0.999

107

From Table 4.22, it was found that there is an agreement between experimental

and calculated qe values for the pseudo second order model (Figure 4.42b).

Hence, the pseudo second order model better represents the sorption kinetics.

DIFFUSION BASED MODELS

In a solid-liquid biosorption process, the transfer of solute was characterized by

particle diffusion control. The possible contribution of intra particle diffusion on

F- biosorption is described by Weber-Morris model as equation 11.

The values of kid and C obtained from slope of qt versus t1/2 (Figure 4.42c) are

0.002 mg g-1 min-0.5 and 0.209 respectively. In addition, the straight line did not

pass through its origin which shows that besides intra particle diffusion other

mechanisms are also involved in rate determining step.

4.4.9 EFFECT OF CO-EXISTING ANIONS ON F- BIOSORPTION

Interference experiments were performed to find out the interference of other

species with the binding of target ion on the biomass. The F-contaminated water

may contain several other anions which can compete with the sorption of F-. The

interference studies were carried out in the presence of various co-ions viz., Cl−,

Br−, NO3−, SO4

2−, PO43−, and CO3

2− in 1˗10 folds (binary mixture: fluoride ion 2

mg L−1 with co-ions 2, 4, 10 and 20 mg L−1). Results are presented in Figure

4.43, which shows tolerable effect with 1:1 fold of co-ions, whereas increasing

concentration retarded the F- removal capacity in different extent. The order of

interference in the presence of anions for F- removal is: CO32− > NO3

− > Cl− >

SO42− > PO4

3− > Br−.

The F- sorption amount decreased quickly from 100 to 69.45% in the presence of

10-fold carbonate. The higher concentration of carbonate may decrease F-

removal due to the high columbic repulsive forces, which reduce the probability

of F- interactions with the active sites. In general, presence of competitive anions

may decrease the attraction between F- and biomass surface, because like charges

repel each other and they cause to increase columbic repulsive forces. The

results are in good agreement with Kumar et al.[145].

108

Figure 4.43 Effect of co-existing anions on F- removal (pH: 2.0; biosorbent dose: 0.2 g;

initial F- concentration: 2.0 mg L−1; contact time: 240 min; and temperature: 30°C).

A slight interference was obtained in the presence of nitrate, chloride, sulfate and

phosphate; however, bromide had virtually no impact on F- sorption. The

observed increase in sorption could be due to the increase in ionic strength of the

solution or a weakening of lateral repulsion between adsorbed F- ions.

4.4.10 DESORPTION AND REGENERATION OF BIOSORBENT

Water purification by biosorption technology is economical with the

regeneration of biosorbent. Moreover, reuse of biosorbent helps in reducing

environmental impacts related with biosorbent disposal.

It is found that alkaline solution desorption capacity was higher compared to

acidic ones. For P. eryngii the order of desorption was NaOH > HCl > H2SO4 >

HNO3 > EDTA. Out of the six eluents, NaOH identified as the best eluent as it

desorbed 97.6% F- ions (Figure 4.44a).

109

Figure 4.44 (a) Desorption of F- by different desorbing agents (initial F- concentration

2.0 mg L−1; biosorbent dose: 0.2 g; contact time 30 min; and temperature 30°C). (b)

Desorption efficiency of P. eryngii with cycle number.

The biomass was washed with deionized water, filtered and dried at 60 °C for

next sorption experiment. This sorption-desorption cyclic study was carried out

for four consecutive cycles. In fourth cycle, the F- biosorption capacity was

decreased approx. 30% from 97.6% (Figure 4.43b). Decrease in biosorption

capacity is possibly due to the decomposition of surface active sites as evident

from previous studies [146].

4.4.11 APPLICATION TO REAL WATER SAMPLES

For practical efficacy of the studied biosorbent, three water samples from

fluorosis affected areas of Tharparkar district, Pakistan were collected; the

physico-chemical parameters are reported in Table 4.23.

110

Table 4.23 The physico-chemical parameters of real water samples.

The sorption studies performed at natural pH values shows after biosorption the

F- levels in the ground water samples were decreased well below the permissible

limits (1.5 mg L-1) of WHO drinking water standards as depicted in Table 4.24.

Table 4.24 Field trial results of biosorption studies using real field water.

S. No. Water-quality

parameters S-1 S-2 S-3

1. Fluoride (mg L-1) 2.4 0.69 3.37

2. pH 7.90 7.20 8.10

3. TDS (mg L-1) 1855 550 1214

4. EC (µS cm-1) 3850 1144 2520

5. Hardness (mg L-1) 2.26 1.76 3.38

6. Chloride (mg L-1) 1000 187.5 675

7. Sulphate (mg L-1) 707.7 411.5 625.4

8. Bicarbonate(mg L-1) 462 203 435

Sample

I.D.

Sampling

site*

F− initial

concentration

(mg L-1)

F− final

concentration

(mg L-1)

Removal

efficiency

(%)

S-1 Mithi 2.40 0.83 65.20

S-2 Diplo 0.69 0.23 67.01

S-3 Nagarparkar 3.37 1.20 64.24

*Tharparkar district, Sindh, Pakistan.

111

4.4.12 PROPOSED MECHANISM

The proposed mechanism shows (Figure 4.45) that the cell wall structure of

fungi were responsible for the attachment of anion on biomass surface.

Figure 4.45 Possible mechanism on surface of biomass.

4.4.13 SUMMARY

In present study, the biosorption characteristics of F- anions from aqueous

solution using white rot fungus (P. eryngii) were investigated as a function of

pH, initial F- concentration, biosorbent dose, temperature, and contact time.

Langmuir model fitted the equilibrium data better than the Freundlich isotherm.

The monolayer biosorption capacity of P. eryngii biomass for F- ions was found

to be 66.6 mg g-1. Thermodynamic parameters such as ∆H°, ∆S° and ∆G°

indicate that the removal of F- ions by fungal biomass was endothermic and

spontaneous in nature. The biosorption process of F- ion followed well pseudo

second order model, where, intra particle diffusion was not the only rate-

controlling step. The surface and sorption characteristics were analysed by SEM,

EDX, and FTIR spectrometry. To check the practical utility of the studied

biosorbent, batch studies were carried out with F- contaminated water samples

collected from F- endemic area. Eventually, this fungal biomass recommended to

112

be used as a suitable, environment friendly and low cost biosorbent for removal

of F- ion concentration to standard permissible limit.

113

PART 5

Remarks: All work of this part has been published in Model. Earth Syst. Environ.

3(3):1101–1112.

4.5 STATISTICAL METHODOLOGY FOR BIOSORPTION OF NO3- IONS

FROM AQUEOUS SOLUTION BY P. ERYNGII FUNGAL BIOMASS

To determine the effects of various operating conditions (pH, biosorbent dose and

initial NO3- concentration) and their interactions on the overall sorption of NO3

- ions

by P. eryngii fungal biomass, RSM involving CCD, combined with techniques of

regression was performed. The statistical approach helped in rapidly identifying key

factors, studying the interactions between them and determining their optimum levels.

The second-order polynomial equation model whose validity is agreed upon is

estimated using ANOVA statistical testing, t-test and F test. These tests showed that

solution pH (A), biosorbent dose (B) and initial NO3- concentration (C) and the

interactions of A×B, A×C, B×C, and A×B×C were statistically significant, and the

second-order effect of pH was found to have a significant effect on the biosorption of

NO3-. Following the determination of significant variables through CCD, a

desirability function was employed to achieve the best conditions for NO3- uptake.

The maximum NO3- removal efficiency obtained from the optimization procedure was

88.4%, which was reached in 17 experiments at a pH level of 7, sorbent dose of 0.24

g and initial NO3- concentration of 700.0 mg L-1. EDX study shows the involvement

of ion exchange and complexation processes as the mechanisms of biosorption that

occurred in P. eryngii.


The surface characteristics and physical morphologies of P. eryngii fungal

biosorbent were examined by using SEM technique. Figure 4.46 shows the

textural structure investigation of pure and NO3- loaded biosorbent at 550x and

1000x magnification, respectively. SEM images of fungal biosorbent showed

severe differences before and after NO3- biosorption. Pure biosorbent (Figure

4.46a) had a bumpy surface along with an appropriate thick wall structure. A

series of irregular cavitation distributed around the surface of fungal biomass

114

provides large surface area for NO3- sorption. However, no significant changes

occurred in morphology of the biosorbent surface after NO3- biosorption as

shown in Figure 4.46b.

Figure 4.46 SEM micrographs of (a) unloaded and (b) NO3- loaded P. eryngii fungal

biomass.

The EDX analysis was used to analyze the elemental constitution of fungal

biosorbent before and after NO3- sorption as shown in Figure 4.47. Oxygen,

carbon, sulfur, sodium, chlorine, potassium, and phosphorus signals can be

observed as the principal elements of fungal biosorbent (Figure 4.47a) that may

influence the sorption mechanism through ion-exchange interactions.

Furthermore, Figure 4.47b confirms the sorption of NO3- ion on biomass by

indicating strong signal of nitrogen (N) at ~ 0.4 KeV. In addition, Cl and Na

peaks disappeared after NO3- sorption, which signify the involvement of an ion

exchange mechanism during biosorption.

For further characterization, AFM was used to investigate the changes in fungal

cell surface morphology following NO3- sorption. The biosorbent was transferred

on mica surface, air-dried and the images were recorded in tapping mode. The

fungal surface is found to be clearly resolved into two and three-dimensional

height image (Figure 4.48). Imaging of the cells before (Figure 4.48a and b) and

115

after (Figure 4.48c and d) NO3- sorption shown undamaged cell surface with

variation in cell size.

Figure 4.47 EDX spectra of (a) unloaded and (b) NO3- loaded P. eryngii fungal biomass.

116

Figure 4.48 AFM images of P. eryngii fungal biosorbent before (a) and after NO3-

sorption (c); three-dimensional images of P. eryngii fungal biosorbent before and after

NO3- sorption (b and d).

Interaction of NO3- ions with surface proteins and lipo-polysaccharides possibly

leads to a change in surface structural design as reflected by an increase in

surface roughness. Furthermore, possible rupturing of the fungal cell because of

NO3- interaction is also responsible for increase in surface roughness.

4.5.2 CALIBRATION OF UV-VIS SPECTROPHOTOMETER FOR NO3- ANALYSIS

Figure 4.49 shows the standard calibration curve of absorbance vs. NO3-

concentration (covering the range of 1.25-15 mg L-1 NO3-) with good linearity

(Figure 4.50), as evident from excellent regression coefficient (R2=0.983).

117

Figure 4.49 UV-Vis Spectra of NO3- at different concentrations.

Figure 4.50 Linear calibration plot for different NO3- concentrations.

4.5.3 MODEL FITTING AND STATISTICAL ANALYSIS

INTERPRETATION OF REGRESSION MODEL USING CCD

The design matrix of tested variables in 17 experimental runs along with the

experimental responses (using the model equation 14 and 15) is shown in Table

4.25.

118

Table 4.25 Experimental design and results for biosorption efficiency (%) of

NO3- by P. eryngii.

The biosorption efficiency of the fungal biosorbent increased to 88.4% after

running the response surface design using the following conditions: pH 7.0,

biosorbent dose 0.24 g and initial NO3- dye concentration 700 mg L-1.

For comparing and correlating the responses, CCD was applied for the

interpretation of the polynomial regression equations. The model expression was

selected in accordance with sequential model sum of square that is based on the

polynomial's highest order where the model was not aliased and the additional

terms were significant. The correlation between predicted and experimental data

was evident as indicated by the model's R2 values of 0.998 for NO3- which was

also within desirability range. Multiple regression analysis was used to analyze

the data to obtain an empirical model for the best response and thus a second-

order polynomial equation was derived as follows:

Y = + 87.76 + 6.15A + 1.54B + 0.79C + 0.063AB – 0.39AC – 0.79BC – 31.76A2

– 2.31B2 – 2.26C2

Factor 1 Factor 2 Factor 3 Response 1

SD Run A:

pH

B:

Biosorbent

dose (g)

C:

Initial NO3-

concentration (mg L-1)

Biosorption

efficiency

(%)

7 1 2 0.4 1340 48.1

11 2 7 0.1 700 84.3

6 3 12 0.1 1340 58.1

9 4 2 0.24 700 50.2

10 5 12 0.24 700 62.2

12 6 7 0.4 700 87.0

5 7 2 0.1 1340 44.9

8 8 12 0.4 1340 58.1

2 9 12 0.1 60 54.0

14 10 7 0.24 1340 86.0

13 11 7 0.24 60 85.4

15 12 7 0.24 700 88.4

16 13 7 0.24 700 87.2

17 14 7 0.24 700 86.9

3 15 2 0.4 60 45.6

1 16 2 0.1 60 42.2

4 17 12 0.4 60 60.1

119

The synergetic and antagonistic effects of the respective variables were informed

by the positive and negative signs before the terms. The appearance of a single

variable in a term signified a uni-factor effect; two variables imply a double

factor effect and a second order term of variable appearance indicate the

quadratic effect [147].

4.5.4 SELECTION OF A MODEL

To decide about the adequacy of the model for NO3- removal by the biosorbent,

three different tests such as the Sequential Model Sum of Squares, Lack of Fit

Tests and Model Summary Statistics were carried out as shown in Table 4.26. It

is found that the p values for most of the regressions were greater than 0.01.

Table 4.26 Selection of a satisfactory model for NO3- biosorption.

This means that at least one of the terms in the regression equation had an

insignificant correlation with the response variable. As a natural log

transformation was applied to the experimental data, the interaction of two

factors (2FI) and the linear model were suggested to be insignificant using the

response surface methodology. The model summary statistic showed highest

regression coefficient (R2 = 0.9987) for the quadratic model with minimum

Sequential model sum of squares

Source Sum of squares Degree of

freedom Mean square F-value p-value (Prob.> F) Remarks

Mean 74939.04 1 74939.04 - - -

Linear 408.18 3 136.06 0.37 0.7794 -

2FI 6.19 3 2.06 4.266 x 10-3 0.9996 -

Quadratic 4832.36 3 1610.79 1654.56 < 0.0001 suggested

Cubic 5.10 4 1.27 2.23 0.2683 aliased

Residual 1.72 3 0.57 - - -

Total 80192.59 17 4717.21 - - -

Lack of fit tests

Source Sum of squares Degree of

freedom Mean square F-value p-value (Prob.> F) Remarks

Linear 4844.11 11 440.37 699.01 0.0014 -

2FI 4837.91 8 604.74 959.90 0.0010 -

Quadratic 5.55 5 1.11 1.76 0.4002 suggested

Cubic 0.46 1 0.46 0.73 0.4842 aliased

Pure

Error 1.26 2 0.63 - -

-

Model summary statistics

Source Standard

deviation R2 Adj. R2 Pre. R2 PRESS Remarks

Linear 19.31 0.0777 -0.1351 -0.5826 8314.49 -

2FI 22.00 0.0789 -0.4738 -4.5958 29397.96 -

Quadratic 0.99 0.9987 0.9970 0.9785 112.99 suggested

Cubic 0.76 0.9997 0.9983 0.8617 726.55 aliased

120

standard deviation (0.99). ANOVA analysis confirmed that the form of the

model chosen to explain the relationship between the factors and the response is

correct.

ANALYSIS OF VARIANCE (ANOVA)

The test for significance of the regression models, the test for significance on

individual model coefficients and the lack of fit test were performed using the

same statistical package [148]. By selecting the manual regression method,

which eliminated the insignificant model terms automatically, the resulting

ANOVA (Table 4.27) for the reduced quadratic models summarizes the analysis

of variance of each response and shows the significant model terms. In general,

the model terms with value of Prob. > F less than 0.05 are considered as

significant. With respect to NO3- sorption, the model F value is 598.81 and Prob.

> F value of 0.0001 justifying the model's significance. The significant model

terms are A, B, C, A2, B2, and C2, while rest of the terms are considered as

insignificant to the response. Lack of fit test gives idea about fitting of

experimental data. The lack of fit F- value of 1.76 implies that lack of fit is not

significant relative to the pure error and model is capable to optimize the present

removal process significantly. The predicted R2 of 0.978 was in good agreement

with adjusted R2 of 0.997, indicating that the model was significant.

Adequate precision is a measure of signal-to-noise ratio, and ratio of value

greater than 4 is desirable. In this study, the obtained ratio of 60.843 specify an

adequate signal. The coefficient of variance (CV) is the ratio of standard error of

estimate to the mean value and considered as reproducible once it is not greater

than 10%. The CV ratio of 1.49% has found in this study. From the statistical

results obtained, the models were suitable in predicting biosorption of NO3-

within the range of the studied variables.

Additionally, relationship between actual and the predicted values of biosorption

efficiency of NO3- is shown in Figure 4.51. The predicted values versus the

experimental values for NO3- sorption revealed that the developed models

successfully captured the relation between the biosorption process variables to

the responses. The developed model is adequate because the residuals for the

121

prediction for most of the responses are less than 10%, and the residuals tend to

be close to the diagonal line.

Table 4.27 ANOVA for the response surface reduced quadratic model.

R2

= 0.998; adjusted R2

= 0.997; predicted R2

= 0.978; adequate precision = 60.843; CV = 1.49%

Figure 4.51 Predicted response versus actual response.

Source of

variation

Sum of

squares

Degree of

freedom

Mean

square F value Prob. (> F)

Model 5246.73 9 582.97 598.81 < 0.0001

A 378.23 1 378.23 388.50 < 0.0001

B 23.72 1 23.72 24.36 0.0017

C 6.24 1 6.24 6.41 0.0391

AB 0.031 1 0.031 0.032 0.8629

AC 1.20 1 1.20 1.23 0.3033

BC 4.96 1 4.96 5.10 0.0586

A2 2702.28 1 2702.28 2775.72 < 0.0001

B2 14.28 1 14.28 14.67 0.0065

C2 13.67 1 13.67 14.04 0.0072

Residual

error 6.81 7 0.97 - -

Lack of fit 5.55 5 1.11 1.76 0.4002

(not significant)

Pure error 1.26 2 0.63

Correlation

(total) 5253.55 16 - - -

122

4.5.5 NORMAL PROBABILITY PLOT OF RESIDUALS

For the statistical analysis of the experimental data, it is necessary to assume that

the data come from a normal distribution [149].

Figure 4.52 Normal % probability versus residual error.

To determine whether the data set is normally distributed, a normal probability

plot or a dot diagram of these residuals is shown in Figure 4.52. The data set has

normal distribution if the points fall close enough to the straight line. It is

evident from Figure 4.52 that the data points on this plot lie reasonably close to a

straight line suggesting normal distribution of the data.

4.5.6 EFFECT OF INTERACTIVE VARIABLES

To explain the interaction effect of variables and to determine the optimum level

of each variable (biosorbent dose, pH and initial NO3- concentration) for

maximum response in the NO3- biosorption, the three dimensional (3D) graphical

surface plots for the predicted responses were illustrated (Figure 4.53a, b, c).

Here, each response surface plot represented the effect of two independent

variables, holding the other variable at zero level. These surface plots provide a

method to predict the biosorption efficiency for different values of the tested

variables [150].

123

Figure 4.53 3D response surface plots of NO3- biosorption by P. eryngii fungal biomass

showing variable interactions between (a) pH and biosorbent dose; (b) pH and

concentration of NO3-; and (c) biosorbent dose and concentration of NO3

-.

Figure 4.53a clarifies the combined effect of biosorbent dose and pH of solution

at constant initial NO3- concentration. It was observed that at aqueous phase pH

7, increasing biosorbent dose had a slight negative effect on biosorption of NO3-,

but at lower and higher pH values the trend of biosorption was decreased. Thus,

biosorption efficiency was found to be good (> 80%) at biosorbent dose of 0.24 g

and at neutral pH.

124

Figure 4.53b shows the interactive effect of initial NO3- concentration and pH of

the solution. A similar trend as observed for initial NO3- concentration was

obtained. This phenomenon mainly attributed to an increase in the adsorbable

surface area and the accessibility of further sorption sites. The biosorption of

NO3- most likely occurs via surface exchange reaction until the surface efficient

sites are completely occupied. Subsequently, the NO3- molecules diffuse into the

pores of the fungal biomass for promoting reactions. Furthermore, sorption is

found to decrease when moving away from these points, since either increase or

decrease in the pH value results in turn down of the biosorption efficiency. The

three-dimensional response surface of the combined effect of initial NO3-

concentration and biosorbent dose on sorption of NO3- at constant pH (7) is

shown in Figure 4.53c that demonstrate a maximum sorption of NO3- ~ 88% at

optimum values.

4.5.7 VALIDATION OF THE MODEL

An independent run were performed for the validation of RSM based

experimental trials keeping following set of condition (Table 4.28).

Table 4.28 Conditions for validation of the design.

The confirmatory experiment showed a NO3- biosorption efficiency of 88.4%

under optimal conditions compared with the NO3- removal percent obtained by

the model. This indicates the suitability and accuracy of the model.

pH

Biosorbent

Dose

Initial

nitrate concentration

Biosorption

efficiency

- g mg L-1 %

7.0 0.24 700 88.4

125

4.5.8 SUMMARY

In the present study, CCD of RSM was employed to investigate the effects of

different operating conditions on the removal of NO3- ions from aqueous solution

onto P. eryngii dried fungal biosorbent. A three level, three factors CCD was

used to evaluate the effects and interactions of the process variables, i.e.,

solution pH, biosorbent dose and initial NO3- concentration. The second order

mathematical model was developed by regression analysis of the experimental

data of 17 batch runs. ANOVA, F-test, Student’s t-test and lack of fit test

showed that NO3- ions biosorption is only slightly concentration dependent, but

markedly increases with solution pH and biosorbent dose. Under these optimum

combinations of process parameter conditions (pH 7.0, biosorbent dose 0.24 g

and initial concentration 700.0 mg L-1), maximum removal of 88.4% was

obtained that assisting its use in larger scale. Hence, it is suggested that P.

eryngii has potential for biosorption as a low-cost and effective sorbent for NO3-

removal from aqueous solution.

126

PART 6

Remarks: All work of this part has been published in Journal of Geology, Ecology,

and Landscapes 2(1):39–44.

4.6 EFFICIENT ENTRAPPING OF TOXIC LEAD (PB) IONS FROM

AQUEOUS SYSTEM ON FIXED - BED COLUMN OF FUNGAL BIOSORBENT

This study investigate the adsorption capacity of fungal biomass toward Pb(II)

ions in a packed / fixed bed column. In this study, the performance of column

were evaluated by applying various parameters i.e., influence of flow rate, initial

ion concentration and bed height. The experimental (breakthrough) data were

analyzed by means of BDST and Thomas models.

4.6.1 COLUMN STUDY

EFFECT OF FLOW RATE

The adsorption column were operated in 1, 3 and 5 mL min-1 flow rates at a fixed

concentration and bed height till no further Pb(II) ions exclusion were detect.

The breakthrough curve for a column were determined by plotting the ratio of

the Ce/C0 (Ce and C0 are the Pb(II) concentrations of effluent and influent,

respectively) against time, as shown in Figure 4.54. The column performed well

at the lower flow rate (1 mL min-1). Prior breakthrough (Ce/C0=0.05) and

exhaustion time were achieved, when the flow rate increased from 3 to 5 mL

min-1. It is because the decrease in residence time restricted the contact of Pb(II)

solution to the fungal biomass. At higher flow rates the Pb(II) ions did not have

enough time to diffuse into the pores of the fungal biomass and they exited the

column before equilibrium [151].

127

Figure 4.54 Breakthrough curves for different flow rates (Initial Pb(II) ion

concentration: 10 mg L-1; Bed height: 2 cm).

EFFECT OF INITIAL PB(II) IONS CONCENTRATION (THOMAS MODEL)

The adsorption breakthrough curves obtained by changing initial Pb(II)

concentration (20 and 30 mg L-1) at 1 mL min-1 flow rate as given in Figure 4.55.

As estimated, a decrease in Pb(II) concentration gave a later breakthrough curve;

because the treated volume was greatest at the lowest transport due to a

decreased diffusion coefficient or mass transfer coefficient.

Breakthrough time (Ce/C0=0.05) came up after 9.0 min at 20 mg L-1 initial Pb

concentration while the breakthrough time was 3.0 min at 30 mg L-1. The

breakthrough time decreased with increasing Pb concentration as the binding

sites became more quickly saturated in the column [152].

128

Figure 4.55 Breakthrough curves for different Pb(II) ion concentration (Flow rate: 1 mL

min-1; Bed height: 2 cm).

The Thomas model kinetic parameters calculated from equation 16 reveals a

good fit of the experimental data at all concentration examined (Table 4.29). The

correlation coefficient greater than 0.983 showed that the external and internal

diffusions were not the rate limiting step. The rate constant (kTh) decreased with

increasing Pb(II) concentration which indicates that the mass transport resistance

increases due to the driving force between Pb(II) concentration and fungal

biomass.

Table 4.29 The Thomas and BDST model parameters for the biosorption of

Pb(II) on P. eryngii fungal biomass.

Thomas model parameters

Pb(II)

concentration

(mg L-1)

qo

(mg g-1)

kTh

(mL m-1 mg-1) R2

20 2.78 1.42x10-3 0.983

30 3.30 1.39x10-3 0.905

The BDST model parameters

No

(mg cm-3)

Ka

(L mg-1 h-1)x10-3 R2

0.767 5.385 0.964

129

EFFECT OF BED HEIGHT (BDST MODEL)

The accumulation of Pb(II) ions in a fixed-bed column is dependent on the

quantity of biosorbent inside the column. To study the effect of bed height on

Pb(II) retention, fungal biomass of three different bed heights. As depicted by

Figure 4.56a, the breakthrough time varied with bed height. The breakthrough

time decreased with a decreasing bed depth from 3 to 1 cm, as binding sites were

restricted at low bed depths. At low bed depth, the Pb(II) ions do not have

enough time to diffuse into the surface of the biomass, and a reduction in

breakthrough time occurs. Conversely, with an increase in bed depth, the

residence time of Pb(II) solution inside the column was increased, allowing the

Pb(II) ions to diffuse deeper into the fungal biomass.

A plot of service time versus bed depth, at a flow rate of 1 mL min-1 (Figure

4.56b) was linear. The correlation coefficient value (R2=0.964) indicated the

validity of the BDST model for the present system. The values of BDST model

parameters are presented in Table 4.6 calculated from equation 17.

From this model and its obtained constants, feasibility of column structure and

its performance were evaluated using sufficient concentration and flow rate for

sorption of Pb(II) ions onto fungal biomass without further experimental analysis

and data [37].

130

Figure 4.56 (a) Breakthrough curves for different bed height (Flow rate: 1 mL min-1;

Initial Pb(II) ion concentration: 20 mg L-1) and (b) Bed depth service time plot for the

adsorption of Pb(II) ions by fungal biomass in column.

4.6.2 COMPARISON OF PB(II) IONS SORPTION CAPACITY DURING BATCH AND

COLUMN MODE

A relatively high sorption capacity from column has been observed then batch

mode (Table 4.30), which is generally attributed to more time interaction

between the biosorbent and the sorbate surface with column

Table 4.30 Comparison of Pb(II) ions sorption capacity.

Samples* Influent Pb(II)

(mg L-1) Effluent Pb(II)

(mg L-1) Total Pb(II) removal

(%)

Industrial Area, Kotri 0.146±0.005 0.018±0.0026 87.63±1.79

Phuleli Canal,

Hyderabad 0.063±0.0026 0.0049±0.0015 92.28±1.97

131

4.6.3 APPLICATION OF COLUMN ON REAL CONTAMINATED WATER SAMPLES

The removal of toxic ions from real water samples is a link between laboratory

and commercial application of column. In this study, all the laboratory

adsorption column conditions developed (flow rate, bed height) are transferred to

the normal level. Results obtained are given in Table 4.31 suggest that Pb(II)

ions removed successfully below the permissible limits (0.05 mg L-1) of WHO

drinking water standards.

Table 4.31 Removal of Pb(II) ions from real water samples via column method.

(Number of replicates *n=3)

4.6.4 SUMMARY

This study proved that P. eryngii fungal biomass has good potential to be used in

sorption of Pb(II) ions from aqueous solution in fixed bed column. Thomas and

BDST models have been used successfully to evaluate the column performance.

The values of Ka and No indicated that the biosorbent could be used for removal

of Pb(II) metal solutions.

Sorption

capacity Batch mode Column mode

mg g-1 2.97 3.30

132

CHAPTER 5

CONCLUSION AND FUTURE DIRECTIONS

In this chapter conclusion, significance, recommendations and prospects of this

research work were presented.

5.1 CONCLUSION

Present study concluded that the release of hazardous metal ions via industrial

wastewater discharge is the major cause of water pollution. In many parts of the

world, metal and anionic concentration in drinking water is higher than some

international guideline values. To reduce level of toxic ions below the safety

limit from water is a matter of concern because of its extremely high toxicity and

serious threat to human life. For this purpose, a sustainable and environmental

friendly approach is crucial. Work of this thesis introduces an efficient,

environmental friendly, non-pathogenic and a novel fungal biosorbent P. eryngii

for the removal of toxic ions from aqueous system. The study revealed presence

of various functionalities on surface of P. eryngii fungal biomass which were

responsible for attachment of targeted ions toward it.

During sorption process the pH has assumed as an essential part for the removal

of Pb(II) ions. The maximum sorption efficiency monitored in the range of pH 6-

7; thus, optimal pH 7 were selected for further process. From the literature study,

it was accomplished that electrostatic attraction (driving forces) due to ion-

exchange and complexation were responsible for the Pb(II) ions removal. The

equilibrium data for Pb(II) sorption effectively followed the Freundlich isotherm

model for multilayer coverage. P. eryngii biomass was utilized successfully for

the removal of Pb with About 99.9% sorption efficiency from aqueous solution.

The sorption process was rapid and equilibrium was reached after 20 min for

Pb(II) ions. The sorption process obeyed a pseudo second order kinetic model.

All the sorption processes investigated were spontaneous and thermodynamically

feasible. Batch elution tests revealed that complete elution of Pb can be achieved

133

from the biomass using 0.1 N HCl solution. From field trial results it was

concluded that, P. eryngii biomass could be used as an efficient, low cost

biomass for the decontamination of Pb(II) ions from drinking and wastewater at

field level.

Sorption of Cd(II) ions was found to be pH dependent and maximum removal

was observed at pH 5. P. eryngii biomass was utilized successfully for the

removal of Cd with 99.9% sorption efficiency from aqueous solution. The

sorption was rapid and equilibrium was achieved within 10 min. Langmuir

adsorption isotherm was demonstrated to provide the best correlation for the

adsorption of Cd ions confirming monolayer coverage. The sorption process

obeyed a pseudo second order kinetic model. Batch elution tests revealed that

complete elution of Cd can be achieved from the biomass using 0.1 N HNO3

solution. The results are very encouraging for the industrial application of the

technique.

The maximum removal of Hg(II) was achieved at natural water pH. P. eryngii

has rapid and high adsorption-desorption property and reusability in repetitive

cycles. The study revealed that this novel biosorbent exhibit significant potential

for its exploitation in the treatment of industrial effluents containing mercury ion

contamination and can be used for scaling-up existing laboratory-scale

biosorption system to a larger system which are more appropriate for water

purification applications.

Biosorption of F- on fungal biomass was achieved at pH 2. Experimental

equilibrium data best fit to the Langmuir isotherm in contrast with Freundlich

and D-R isotherm models, indicating monolayer biosorption on a homogenous

surface. Thermodynamic parameters revealed that sorption of F- was spontaneous

and endothermic in nature. Modeling of biosorption kinetics showed good

agreement of experimental data with the pseudo second order kinetic model. The

fungal biomass has also shown encouraging results with ground water sample

collected from endemic areas of Tharparkar district, Pakistan.

To determine the effects of various operating conditions (pH, biosorbent dose

and initial NO3- concentration) and their interactions on the overall sorption of

134

NO3- ions by P. eryngii fungal biomass, RSM involving CCD combined with

techniques of regression was performed. The maximum NO3- removal efficiency

obtained from the optimization procedure was 88.4%, which was reached in 17

experiments at a pH level of 7, sorbent dose of 0.24 g and initial NO3-

concentration of 700 mg L-1. Moreover, ion exchange and complexation

processes are the mechanisms of biosorption that occurred in P. eryngii.

Therefore, respective utilization of P. eryngii biomass makes it an effective

sorbent for removal of Pb(II), Cd(II), Hg(II), F- and NO3- ions from aqueous

environment.

5.2 SIGNIFICANCE OF THIS RESEARCH

The present study provides an efficient, cost effective and environmental

friendly biosorbent with its potential in removing metals and anions from

aqueous system.

The used fungal biomass can be easily disposed of since it is biodegradable

or can be used as an alternative raw material for large scale composting

process.

In addition, people of affected areas can take advantage of this natural safe

method for removal of toxic ions from contaminated water.

5.3 RECOMMENDATIONS AND FUTURE DIRECTIONS OF THIS

RESEARCH WORK

•••• The biosorption technique using white-rot fungus Pleurotus eryngii is

reported first time in literature, more novel species of fungal biomasses can

be introduced in future for removal of hazardous ions.

•••• Exploitation of farming waste and other microbial materials may promote the

sustainability of the environment. Particularly in developing countries these

materials will have favorable benefits for commercial persistence.

•••• It is recommended to perform sorption studies on more oxo-anions and

cations using new species of fungal biomass and other natural biosorbents;

subsequently bioremediation seems to be an area which needs broad

135

consideration of scientists and investigators with reference to environmental

pollution.

•••• As present examination have uncovered the alarming level of toxic metals

and anions in aqueous system, that is highly toxic for the health of people

having frequent consumption of it. Henceforth in future a multi-disciplinary

approach by environmentalists and chemists requires for the development of

more state-of-the-art techniques, particularly to detoxify vegetables and food

sources.

136

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LIST OF PUBLICATIONS

1. Amin F, Talpur FN, Balouch A, Surhio MA, Bhutto MA (2015).

Biosorption of fluoride from aqueous solution by white - rot fungus

Pleurotus eryngii ATCC 90888. Environmental Nanotechnology,

Monitoring & Management 3:30–37.

2. Amin F, Talpur FN, Balouch A, Chandio ZA, Surhio MA, Afridi HI

(2016). Biosorption of mercury(II) from aqueous solution by fungal

biomass Pleurotus eryngii: isotherm, kinetic, and thermodynamic studies.

Environmental Progress & Sustainable Energy 3:1274–1282.

3. Amin F, Talpur FN, Balouch A, Samoon MK, Afridi HI, Surhio MA

(2018). Utilization of Pleurotus eryngii biosorbent as an environmental

bioremedy for the decontamination of trace cadmium(II) ions from water

system. Water Science & Technology 78 (5): 1148-1158.

4. Amin F, Talpur FN, Balouch A, Afridi HI (2017). Eco-efficient fungal

biomass for the removal of Pb(II) ions from water system: A sorption

process and mechanism. International Journal of Environmental Research

3(11):315–325.

5. Amin F, Talpur FN, Balouch A, Afridi HI, Khaskheli AA (2018).

Efficient entrapping of toxic Pb(II) ions from aqueous system on fixed-

bed column of fungal biosorbent, Geology, Ecology, and Landscapes

2(1):39–44.

6. Amin F, Talpur FN, Balouch A, Afridi HI, Surhio MA (2017). Statistical

methodology for biosorption of nitrate (NO3-) ions from aqueous solution

by Pleurotus eryngii fungal biomass, Modeling Earth Systems and

Environment 3:1101–1112.

with sign Farah Amin Thesis PhD 2018

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Transcript of with sign Farah Amin Thesis PhD 2018