Biosorption of heavy metal ions from the aqueous solutions ...

Biosorption of heavy metal ions from the aqueoussolutions using porous Sargassum Wightii (SW)brown algae: batch adsorption, kinetic andthermodynamic studiesV Yogeshwaran  ( [email protected] )

Sri Krishna College of Engineering and TechnologyA.K Priya 

KPR Institute of Engineering and Technology

Research Article

Keywords: Heavy metals, Adsorption, Sargassum Wightii, Thermodynamic studies, Kinetic studies

Posted Date: August 1st, 2022

DOI: https://doi.org/10.21203/rs.3.rs-1802122/v2

License: This work is licensed under a Creative Commons Attribution 4.0 International License.  Read Full License

1

Biosorption of heavy metal ions from the aqueous solutions using 1

porous Sargassum Wightii (SW) brown algae: batch adsorption, 2

kinetic and thermodynamic studies 3

V. Yogeshwaran1*, A.K. Priya2 4

1*Assistant Professor, Department of Civil Engineering, Sri Krishna College of Engineering and 5

Technology, Coimbatore -641008, India. [email protected] 6

2Associate Professor, Department of Civil Engineering, KPR Institute of Engineering and 7

Technology, Coimbatore – 641027, India. [email protected] 8

9

10

11

12

ABSTRACT 13

The removal of heavy metal ions (Cr, Pb and Zn) present in aqueous solutions has been 14

examined utilizing Sargassum Wightii (SW) - brown algae – as an organic adsorbent. The 15

functional groups of SW were determined by FTIR analysis before and after heavy metal ion 16

adsorption. Because of the strong Van der Walls forces, the SEM/EDX picture reveals the 17

presence of heavy metal ions on the surface of the SW. The influence of adsorption was studied 18

in different settings by adjusting the parameters of pH, SW dosage, metal ion concentration, time 19

of contact and temperature. In addition, the thermodynamic and isotherm investigations were 20

carried out in order to determine the adsorption process and its connection. It was found that by 21

adding 0.3 N H2SO4, the maximal desorption rate was achieved. 22

23

Keywords: Heavy metals, Adsorption, Sargassum Wightii, Thermodynamic studies, Kinetic 24

studies. 25

2

1. INTRODUCTION 26

Water contamination is one of the most important concerns that the world has been 27

dealing with since ages. Owing to unrestricted industrial and agricultural activities, coupled with 28

human ignorance in terms of unplanned disposal of wastes, water bodies around the globe have 29

witnessed much increased levels of contamination in recent days. Changes in physical and 30

chemical qualities of water that result from contamination renders the water unfit for drinking. 31

Colours, heavy metals, organic pollutants (suspended/dissolved) and other contaminants often 32

pollute water at exceedingly high quantities (Al – Homaidan et al, 2018). Particularly, heavy 33

metal pollution of water is one of the most significant issues because of the toxicity of metal 34

ions, and this becomes extremely damaging to the environment and humans at high 35

concentration levels of contamination. With the rise of heavy metal pollution, the globe now 36

confronts a slew of health concerns, including cancer, lung disorders and other ailments. As a 37

result, before discharging wastewater into the environment, it is critical to diminish/eliminate the 38

presence of heavy metal ions in the wastewater. To reduce the build-up of heavy metal ions from 39

wastewater, several studies have been performed until date that report different techniques and 40

methodologies. The adsorption method has focussed on eliminating metal ion concentration by 41

utilizing batch and fixed bed processes to build a unique treatment procedure that respond to an 42

urgent demand (Indhumathi et al, 2014). This method offers a few benefits, including minimal 43

capital costs, selective metal removal and desorption without the production of sludge. Using the 44

adsorbate, the pollutants present in the aqueous medium has been removed by adsorption process 45

through batch/column studies. Both natural and industrial by-products (decomposable) were used 46

in many research works for reducing the pollutant concentrations. In order to improve the 47

efficacy of the adsorption process, the adsorbent material is usually transformed to activated 48

carbon (Akbar et al, 2012). 49

Rice husk, leaves, saw dust, coconut shells, rice bran, fly ash, Blast Furnace Slag, etc. 50

have been used as an adsorbent material to remove various types of heavy metal ions from 51

aqueous medium. Apart from the materials, many bacteria, algae, etc. have been used as bio-52

adsorbent for reducing the toxic pollutants from the aqueous solutions. Use of organic material 53

and industrial by-products as an adsorbent material, which results in secondary pollutant 54

generation, and desorption of pollutants from the adsorbent material are challenging tasks. On 55

the other hand, by using biological materials and other organic matters, many toxic metals have 56

3

been removed from the polluted sources without formation of secondary pollutants, and 57

removing the accumulated pollutant from the adsorbent has been done by many easy ways (Yang 58

et al, 2019). Within the domain of micro-organisms, algae – that involve photosynthesis for their 59

growth – are available in marine and fresh waters. Due to their food and fuel production ability, 60

algae are considered as fast-growing beings; and they possess the ability to produce biomass 61

from nutrients using atmospheric CO2 (Molazadeh et al, 2015). In this experimental work, the 62

role of Sargassum wigtii towards removal of toxic metal ions (Cr, Pb & Zn) and its importance 63

have been discussed. In this respect, literature reports on various metal ion removal by micro-64

algae have been discussed in Table 1. Based on the reported results, it can be easily realized that 65

algae can play a vital role in removal of the metal ions from the aqueous solutions. 66

Table – 1: Various metal ion removal by different algae 67

Type of Heavy metal Algal strain and condition Removal efficiency Reference

Selenium Combined algal anaerobic

bacteria – Live algae

94 - 100% Stefanik et al,

2018

Chromium Spirogyra condensate and

Rchizoclonium hieroglyphicum

Dried algae

75% (for low algae

concentrations)

Onyancha et al,

2008

Chromium and

Copper

Sargassum sp. (micro algae) and

Chlorococcum sp. (dried algae)

Sargassum removes 85% of

Cu and 67% of Cr.

Chlorococcum removes 75%

of Cu and 65% of Cr. The

optimum concentration is 2

mg/L.

Silva et al, 2010

Cadmium, Copper,

Lead and Zinc

Haslea ostrearia, Phaeodactylum

tricornutum, Skeletonema

costatum and Tetraselmis suecica

– Live algae

Results show reduction in Cu

and Cd

Sindy et al, 2006

Cadmium, Mercury,

Lead, Arsenic and

Cobalt

Spirogyra hyaline – Dried algae The order of metal uptake for

the dried biomass was found

to be Hg>Pb>Cd>As>Co

Pham et al, 2021

Nickel Odeogonium hatei – Untreated

and acid treated dried algae

78% of removal was attained Gupta et al, 2010

Copper, Zinc,

Cadmium and

Mercury

Cladophora fracta – Live algae Cu -99%, Zn – 85%, Cd –

97% and Hg – 98% was

attained

Li Ji et al, 2012

4

2. MATERIALS AND METHODS 68

2.1 Preparation of adsorbent & Stock solution – The brown algae adsorbent, SW, was 69

collected from Nagapattinam district, Tamil Nadu, India, and was washed several times to 70

remove the impurities by using double distilled water. Then the collected SW was dried in 71

sunlight for 10 days, cut into small pieces, and crushed several times with a domestic mixer (1 72

HP Micro active, India) to obtain a range of particle size between 150 and 175 µm for porous 73

material preparation. The crushed SW was then kept in an oven at 60C for 24 hours to further 74

remove impurities. For the stock solution preparation, 50 mg of K2Cr2O7, ZnCl2 & PbSO4 were 75

taken and mixed with 500 mL of double distilled water, and the solution was kept in room 76

temperature. The double distilled water dilution was done to obtain the designed concentrations 77

at various levels. The pH of the solution was adjusted by adding 0.1 M of H2SO4. 78

2.2 Pore distribution & BET surface area – The adsorption-desorption isotherm process 79

was used to obtain the diameter of the pore and its size distribution, BET surface area and other 80

micro and meso pore of SW using nitrogen at -196C for this porous material. The rate of 81

adsorption and desorption with nitrogen has been shown in Figure 1, and the observed 82

characteristics have been represented in Table 1. It was realized that the SW possessed micro and 83

meso pores (Type – II) and a BET surface area of around 654 m2/g, which is more than the pore 84

volume (0.412 cm3/g) of other commercial activated carbons (Suresh Jeyakumar et al, 2014). 85

86

87

88

89

90

91

92

93

94

95

96

97

Figure 1 – Adsorption – Desorption Isotherm (Nitrogen). 98

0.0 0.2 0.4 0.6 0.8 1.0

0.0

0.5

1.0

1.5

2.0

Vol

. of N

2 ad

sorb

ed (

cm3/

gm)

Relative Pressure (P/Po)

5

Table 2 - Pore characteristics of SW adsorbent 99

S.No. Parameter Units Value

1. BET surface area m2/g 654

2. Pore volume cm3/g 0.412

3. Micro pore volume cm3/g 0.189

4. Meso pore volume cm3/g 0.082

5. Micro pore area m2/g 392

6. Average pore diameter Nm 0.6 – 2.4

100

2.3 Batch Adsorption Studies – By varying the parameters of metal ion contact time with 101

SW, amount of SW used, initial concentration of metal ions, and potential of hydrogen (pH) and 102

temperature, the batch adsorption experiments were performed. Within the equilibrium period 103

(60 min), the impact of varying adsorption parameters, such as concentration of Cr, Pb and Zn 104

metal ions (50 mg/L with 100 mL of aqueous solution), and pH (2.0 to 7.0), SW’s dosage (0.5 – 105

2.5 g/L) was determined at the constant temperature of 30C. To attain the equilibrium, the 106

samples with the SW were kept in a rotary shaker and shaken for 60 min, and the particles were 107

allowed to settle for up to 15 minutes. The contact time between the heavy metal ions and SW 108

was adjusted from 10 min to 2 hrs. The amount of metal ions adsorbed by the SW adsorbent was 109

obtained by using the Equation 1, at different time intervals, 110 qt = (Co− Ct) Vm mg/g (1) 111

qt – Total amount of adsorbed metal ions by SW (mg/g) 112

Ct – Batch adsorption process and its concentration 113

The residuals were then collected from the conical flask and analyzed by Atomic Adsorption 114

Spectroscopy (AAS) to find out the percentage of metal ions (Cr, Pb & Zn) adsorbed by SW. To 115

obtain the concurrent value, each analysis was repeated for two times and the average value was 116

taken. The Equation 2 provides the percentage of adsorbed metal ions by SW. 117 % Removal = [Co− CeCo ] X100 (2) 118

Co & Ce – Initial and Equilibrium concentration of the solution 119

V – Solution’s volume 120

m – Adsorbent mass 121

6

2.4 Kinetic Studies – By varying the heavy metal ions and their concentrations (25 – 150 122

mg/L), the equilibrium studies were carried out at the pH level of 2.0 and 2 g/L of SW in 100 mL 123

solution. The solution was subjected to a rotary shaker for a period of 60 minutes at 120 rpm 124

speed by adopting 30C of temperature, followed by filtration using a Whattman filter paper. The 125

amount of metal ions adsorbed by SW in the equilibrium condition were calculated by using the 126

Equation 3. 127 qe = (Co− Ce) Vm mg/g (3) 128

C0 & Ce – Initial & equilibrium metal ion concentrations respectively (mg/L) 129

V – Volume of the metal ion solution 130

m – Mass of the adsorbent used 131

The following adsorption active models were utilized to examine the obtained data with 132

respect to the adsorption proficiency and the achievability of the scale up tasks. 133

2.4.1 Pseudo – First order kinetic model - Based on solid adsorption capacity, this 134

model, also known as the Lagergren kinetic rate model, was developed for the adsorption of 135

solid and liquid systems (Hammud et al, 2014). This represents the researchers' sole kinetic 136

model for solute adsorption from a liquid solution. According to the author's conclusion, the 137

driving force is exactly proportional to the total adsorption rate, i.e., the difference between the 138

initial and equilibrium adsorbate concentrations (qe − q). Equation 4 was used to express the 139

pseudo first order kinetic model: 140 𝑑𝑞𝑒𝑑𝑞𝑡 = 𝑘 (𝑞𝑒 − 𝑞𝑡) (4) 141

At the equilibrium, the total amount of metal ions adsorbed at time (t) was obtained by 142

calculating qe & qt, where K is the rate constant. Using the boundary layer conditions, the 143

Equation 4 can be rearranged as Equation 5. 144

log(𝑞𝑒 − 𝑞) = 𝑙𝑜𝑔𝑞𝑒 − 𝑘2.303 𝑡 (5) 145

2.4.2 Pseudo – Second order kinetic model - This kinetic analysis uses the second order 146

chemical adsorption process, with the assumption that the rate of adsorption is proportional to 147

the square of the number of empty sites (Prasanna Kumar et al, 2007). Equation 6 expresses the 148

pseudo second order kinetic equation. 149

7

𝑑𝑞𝑑𝑡 = 𝑘(𝑞𝑒 − 𝑞)2 (6) 150

By applying boundary conditions (t = 0 to t > 0, and q = 0 to q > 0), the Equation 6 can be 151

rearranged as Equation 7. 152

𝑡𝑞 = 1ℎ + 1𝑞𝑒 𝑡 (7) 153

where, h = kqe2 – Initial adsorption rate, and k – rate constant. A plot of t/qt vs. time at various 154

adsorption parameters provides a linear relationship, allowing the determination of 'qe', 'k' and 'h'. 155

2.4.3 Boyd kinetic model – The information found in the Boyd kinetic plot was utilized 156

to analyze the slowest step of adsorption process by the adsorbent (Sheika et al, 2007). The Boyd 157

kinetic equation is presented as Equation 8. 158

𝑞𝑡𝑞𝑒 = 1 − 6𝛱2 exp(−𝐵𝑡) = 𝐹 (8) 159

qt & qe – Total quantity of heavy metal ions adsorbed at time ‘t’ in the equilibrium (mg/g) 160

F – Fraction of metals adsorbed at any time ‘t’ 161

B – Mathematical function 162

Taking natural logarithm in Equation 8, it can be rearranged as Equation 9. 163 𝐵𝑡 = −0.4977 − ln(1 − 𝐹) (9) 164

To access the linearity of experimental data, the plot (Bt vs. t) was used. The Bt values were 165

used to calculate the effective diffusion coefficient, Di (m2/s), using the Equation 10. 166

𝐵 = 𝛱2 𝐷𝑖𝑟2 (10) 167

The effective diffusion coefficient (Di) & the radius of the adsorbent (r) were found using the 168

Equation 10. Moreover, based on the assumptions in sieve analysis, the radius of the adsorbent 169

particles was calculated. 170

2.5 Isotherm Studies - Adsorption isotherms provide a better knowledge of the connection 171

between the adsorbate and the adsorbent, which is vital for optimal adsorbent use. To optimize 172

the adsorption mechanism, accurate inferences must be drawn from the equilibrium plot (Olal et 173

al, 2016). The adsorption isotherm created as a result gives critical data for assessing production 174

in a large-scale industrial system. 175

8

2.5.1 Temkin isotherm study - According to this adsorption isotherm, the adsorption 176

strength of all molecules in the layer decreases linearly with distance due to indirect adsorbate / 177

adsorbent contact (Lucai et al, 2020). 178

The Equation 11 expresses the isotherm equation derived from Temkin studies. 179

𝑞𝑒𝑞 = 𝑅𝑇𝑏 ln 𝐾𝑇 + 𝑅𝑇𝑏 ln 𝐶𝑒 (11) 180

The binding constant at the equilibrium (KT), temperature (T), universal gas constant (R) and 181

adsorption heat constant (b) were used to find out the adsorbate equilibrium concentration (Ceq) 182

by Temkin isotherm studies. 183

2.5.2 D-R isotherm study – The homogeneity or potential sorption of the adsorption 184

process is not assumed, and the D-R (Dubinin – Radushkevich) equation is more analogous 185

compared to other isotherm studies. Equation 12 expresses the D-R character of the adsorption 186

process equation. 187 ln qe = ln xm − β €2 (12) 188

qe – Quantity of metal ions adsorbed in the equilibrium time 189

xm – Capacity of the adsorption in mg/g 190

2.5.3 Sips isotherm study - The Langmuir & Freundlich isotherm models were 191

combined to predict the process of adsorption in the heterogeneous sips isotherm system. The 192

sips model forecasts monolayer adsorption when the concentration of the solution is very high. 193

Also, the solution’s attention is completely avoided and follows the Langmuir model. The 194

expression for the sips isotherm model can be expressed in equation 13. 195

1𝑞𝑒 = 1𝑄𝑚𝑎𝑥𝐾𝑠 ( 1𝐶𝑒)1𝑛 + 1𝑄𝑚𝑎𝑥 (13) 196

Qmax & Ks – Adsorption capacity and equilibrium constant obtained from the slope and intercept 197

in linear plots & n - factor of heterogeneity lies between 0 to 1 198

3. RESULTS AND DISCUSSION 199

3.1 SEM/EDX Analysis 200

The surface of SW, before and after the adsorption of heavy metal ions (Cr, Pb and Zn), is shown 201

in Figure 2. Figure 2 (a) & (b) shows the presence of uneven holes on the surface of adsorbent, 202

and this was due to the sulfuric acid treatment that saturated the porous material surfaces on the 203

adsorbent. Figure 2 further shows that the chromium, lead and zinc ions are preferentially 204

9

adsorbed by SW, and the adsorption occurred on the inner walls of the adsorbent. The EDX 205

image shows the presence of Cr, Pb and Zn metal ions after the adsorption process, along with 206

additional metal elements/components such as chlorine, nicotine and sulphur. During the acid 207

treatment, the SW powder reacts with sulfuric acid, and the esters were produced by hydroxyl 208

group as a non-ionic functional group that may complex with cations (Dulla et al, 2020). Hence, 209

the charged sites get protonated during the acid treatment, and the functional groups of the 210

adsorbent were not destroyed by the acid. 211

212

213

214

215

216

217

218

219

220

221

222

223

224

Figure 2 – SEM & EDX images of raw and metal ions adsorbed SW. 225

3.2 FTIR – Studies 226

Figure 3 shows the various functional groups of raw SW and metal ions-loaded SW separately. 227

The O-H stretching vibrations were noticed as the band at 3392 cm-1, which can be attributed to 228

the presence of amide and water groups. The peak at 2922 cm-1 belongs to the -CH3 group. The 229

production of N-H was realized from to the stretching vibration of C=O at 1693 cm-1. The 230

bending vibrations of the -CH3 groups are represented by the band at about 1098 cm-1. The -OH 231

stretching frequencies was observed to get shifted from 3352 cm-1 to lower frequencies, which is 232

demonstrated by metal ion-loaded spectrum. Similarly, the –CH3 group's stretch and twisting 233

10

vibrations got moved to a lower frequency. This demonstrates metal ion binding onto the binding 234

sites of SW (Lahari et al, 2011). 235

236

237

238

239

240

241

242

243

244

245

Figure 3 – FT-IR image of (a) Raw and (b), (c) & (d) metal ions (Cr, Pb & Zn) loaded SW. 246

3.3 Effect of pH on metals adsorption - Adsorption tests were carried out at various pH levels 247

(2.0 to 7.0). Figure 4 shows that when the pH of the solution increased from 2.0 to 7.0, the 248

quantity of metal ion adsorption dropped from 99.6 to 63.4 % for Cr, 94.43 to 75.21 % for Pb, 249

and 91.2 to 82.63% for Zn. Due to the properties of protonation, the metal ion adsorption was 250

increased in the lower pH values. When the hydrogen ion concentration is high (at lower pH), the 251

negative charge of the internal pore surface was neutralized, and there arose the possibility of 252

development of new adsorption sites with positive charges that adsorbed the anionic complexes 253

(Cr, Pb and Zn) on the surface (Ghoneim et al, 2014). Furthermore, the starting pH of the 254

solution was always lower than the final pH. This supports the neutralization of negatively 255

charged ions that get drawn to the surface by the H+ ions, and the production of additional H+ 256

ions in the positively charged surface. As a result, the pH of the solution got increased, while and 257

the concentration of H+ ions in the solution got reduced. 258

11

3.4 Effect of SW concentration on metals adsorption - Figure 5 depicts the effect of SW’s 259

dosage on the adsorption of Cr, Pb and Zn metal ions. At an SW dosage of 1 g/L, the maximum 260

percentage removal of metal ions was determined to be 90.12 % for Cr, 96.01 % for Pb, and 261

81.53 % for Zn, and it was found to stay practically constant after thereafter. This occurring may 262

be attributed to a decrease in the aqueous solution's concentration gradient. The rise in 263

percentage adsorption with increasing adsorbent dosage may be attributed to an increase in free 264

surface accessibility, which produced an increase in the number of adsorbate molecules (Kumar 265

et al, 2019). The optimal SWs dosage was determined to be 1 g/L and was used in the subsequent 266

experiments. 267

2 3 4 5 6 7

60

65

70

75

80

85

90

95

100

% A

dso

rptio

n

pH

Cr (VI)

Pb (II)

Zn (II)

268

Figure 4 – Changes in metal ion adsorption by varying the pH. 269

0.5 1.0 1.5 2.0 2.5 3.0

40

50

60

70

80

90

100

% A

dso

rptio

n

Adsorbent Dose (mg/L)

Cr (VI)

Pb (II)

Zn (II)

270

Figure 5 - Changes in metal ion adsorption by varying the SW’s dose. 271

12

3.5 Effect of solution concentration on metal ions adsorption – Initially, the adsorption tests 272

were conducted by fixing the metal ion concentration at 25 mg/L, followed by an increase up to 273

150 mg/L. Figure 6 shows the gradual decrement in the efficiency of adsorption when the 274

concentration of metal ions was increased. The amount of metal ion adsorption was increased 275

from 64.26 to 98.63 % for Cr, 68.92 to 89.27 % for Pb, and 68.82 to 82.39 % for Zn, with a 276

decrease in the primary concentrations of the heavy metal ions. The percentage removal 277

efficiency was found to rise consistently when the adsorbate concentration was decreased, 278

showing that the adsorbent material did not achieve saturation (Bhagyalakshmi et al, 2016). 279

20 40 60 80 100 120 140 160

60

65

70

75

80

85

90

95

100

% A

dso

rptio

n

Adsorbate Concentration (mg/L)

Cr (VI)

Pb (II)

Zn (II)

280

Figure 6 - Changes in metal ion adsorption by varying the metal ion concentrations. 281

3.6 Effect of contact time on metals adsorption – The contact time in between the SW 282

adsorbent and heavy metal ions was adjusted from 10 min to 2 hrs., and the effects were studied 283

and represented in Figure 7. During the initial stages, the metal ion elimination was highly rapid, 284

while at later stages there were no significant changes. After 60 minutes, the metal ion uptake 285

reached the constant rate and there was no improvement in Cr, Pb and Zn metal adsorption. This 286

was because the adsorbate molecules faced saturation of their solid surfaces, leading to decrease 287

in the metal ion uptake after 60 min due to repulsive forces. Also, the passage of time resulted in 288

decrease in mass transfer between the solid and liquid phases, as the heavy metal ions need to 289

travel very long distances through the pores with very high concentration (Alguacil et al, 2020). 290

3.7 Effect of temperature on metals adsorption – Taking the concentration of heavy metal 291

ions as 50 mg/L, with 2.5 g/L of SW’s concentration, the impact of temperature was analyzed up 292

13

to 60 minutes. Initially, the percentage of adsorption rose up to 30C before gradually 293

decreasing. As a result, the optimal adsorption occurred at 30°C. The drop in percentage 294

adsorption at 45°C might be attributed to a rise in the desorption rate (Esameili et al, 2012). 295

Figure 8 shows the adsorption effectiveness of the adsorbents at various temperatures ranging 296

from 15 to 60 C. 297

3.8 Kinetic studies 298

3.8.1 Pseudo – First order kinetic study – The kinetic plot of log (qe – q) vs. time (t) for 299

heavy metal ions (Cr, Pb and Zn) adsorption is shown in Figure 9, obtained using the Equation 5. 300

Based on the linearity of the plots, the rate constant and the correlation coefficient (k & R2, 301

respectively) were calculated and presented in Table 2. The R2 values were found to be low (< 302

0.95) and this model does not fit with the pseudo first order kinetics, which indicates that the 303

adsorption process has not reached the equilibrium status (Ghayedi et al, 2019). 304

3.8.2 Pseudo – Second order kinetic study – Varying the concentrations of metal ions 305

(25 – 150 mg/L), the second order kinetic plots (t/q vs. t) was obtained and shown in Figure 10. 306

Based on the plots and its linearity, the coefficients of correlation (h & k) values were calculated 307

and presented in Table 3. From the table, it can be readily realized that both the calculated and 308

the experimental values of qe are nearly correlated, and the R2 values were > 0.95, which 309

confirms the suitability of this kinetic model as the adsorption process has reached its 310

equilibrium conditions. 311

3.8.3 Boyd kinetic study – To find out the rate determining step of the adsorption 312

process, the Boyd kinetic plots were used. The 'Bt vs. t' plot was used to determine if the 313

experimental variables are linear. Referring to the Boyd’s kinetic plots (Figure 11) for 314

chromium, lead and zinc ions adsorptions by SW, the lines were found to be in linear; however, 315

they did not pass through the origin point. This is because of external film diffusion of 316

adsorption of metal ions by SW indicates the external of film diffusion of metal ion adsorption 317

by SW (Rico et al, 2018). Using Figure 11, the Boyd kinetic parameters (Di & B) were 318

calculated and presented in Table 4, which demonstrated very high regression values (R2 > 0.95). 319

320

14

321 322

Figure 7 - Changes in metal ion adsorption by varying the contact time. 323

324

10 20 30 40 50 60

70

75

80

85

90

% A

dso

rptio

n

Temperature

Cr (VI)

Pb (II)

Zn (II)

325

Figure 8 - Changes in metal ion adsorption by varying the temperature. 326

15

327

Figure 9 - Pseudo first order kinetic plot for heavy metal (Cr, Pb and Zn) removal using 328

SW. 329

Table 2 Pseudo First order kinetic parameters for heavy metals (Cr, Pb and Zn) adsorption 330

using SW. 331

S.No Name of the metal

ion

Concentration

of the ion

solution (mg/l)

k

(min-1)

qe,

cal (mg/g) R2

1.

Hexavalent

Chromium –

Cr (VI)

25 0.0668 11.492 0.918

50 0.0736 28.504 0.921

75 0.0760 46.559 0.927

100 0.0829 83.716 0.946

125 0.0714 84.139 0.936

150 0.0692 84.725 0.927

16

2. Lead – Pb (II)

25 0.0678 12.445 0.927

50 0.0714 29.040 0.911

75 0.0737 54.935 0.928

100 0.0875 84.121 0.924

125 0.0921 94.189 0.931

150 0.0985 132.573 0.943

3. Zinc – Zn (II)

25 0.0645 11.561 0.916

50 0.0737 30.794 0.922

75 0.0898 69.343 0.935

100 0.0806 74.989 0.930

125 0.0875 92.336 0.935

150 0.0936 115.88 0.942

332

Figure 10 - Pseudo second order kinetic plot for heavy metal (Cr, Pb and Zn) removal 333

using SW. 334

17

Table 3 - Pseudo – Second order kinetic parameters for heavy metals (Cr, Pb and Zn) 335

adsorption using SW. 336

S.No Name of the

metal ion

Concentration

of the ion

solution

(mg/L)

K

(g/mg.min)

X 10-3

qe,

cal

(mg/g)

h

(mg/g.min)

qe, exp

(mg/g)

R2

1.

Hexavalent

Chromium –

Cr (VI)

25 8.980 13.988 1.751 12.983 0.997

50 4.722 26.878 3.607 25.126 0.997

75 2.826 41.766 3.986 38.214 0.996

100 1.969 56.552 4.552 50.873 0.995

125 1.353 66.763 4.793 59.129 0.994

150 1.114 72.361 5.216 68.427 0.994

2. Lead – Pb (II)

25 7.763 13.968 1.522 12.840 0.997

50 3.600 26.513 2.778 24.450 0.997

75 2.870 38.642 3.623 36.892 0.979

100 1.530 51.235 4.617 48.711 0.969

125 0.949 62.458 4.655 59.122 0.994

150 0.782 72.357 4.925 68.458 0.994

3. Zinc – Zn (II)

25 8.186 13.514 1.495 12.631 0.975

50 4.250 25.641 2.466 24.221 0.976

75 2.522 37.307 3.640 35.015 0.964

100 1.478 52.363 4.908 47,234 0.965

125 1.258 66.672 5.392 59.286 0.972

150 1.009 73.314 4.484 67.194 0.964

337

338

339

340

18

Figure 11 - Boyd kinetic plot for heavy metals (Cr, Pb and Zn) adsorption using SW. 341

Table 4 - Boyd Kinetic parameters for heavy metals (Cr, Pb and Zn) adsorption using SW. 342

S.No Name of the

metal ion

Concentration

of the ion

solution (mg/l)

B Di

(x 10-3m2/s) R2

1.

Hexavalent

Chromium –

Cr (VI)

25 0.086 11.942 0.918

50 0.074 12.605 0.912

75 0.076 12.848 0.928

100 0.083 14.207 0.944

125 0.085 14.762 0.938

150 0.072 12.974 0.926

2. Lead – Pb 25 0.068 11.492 0.928

19

(II) 50 0.072 12.373 0.914

75 0.086 14.354 0.925

100 0.088 14.730 0.927

125 0.093 15.177 0.931

150 0.096 15.673 0.918

3. Zinc – Zn

(II)

25 0.066 10.895 0.912

50 0.072 12.605 0.922

75 0.090 15.120 0.936

100 0.083 14.782 0.930

125 0.088 13.520 0.935

150 0.094 12.834 0.918

3.9 Isotherm Studies 343

3.9.1 Temkin Adsorption Isotherm – The bio-adsorbent (SWs) provided very high rate 344

of metal ions adsorption from the aqueous solutions. Parameters, such as size and volume of the 345

pore, specific surface area, etc., were obtained by using the adsorption isotherm studies. The 346

adsorption process by SW was examined using a Temkin isotherm model to determine the 347

adsorbent characteristics (Manjuladevi et al, 2018). The Temkin plots (qe vs. Ce) are shown in 348

Figure 12 for heavy metal ion (Cr, Pb and Zn) adsorption, and the kinetic constants (KT & b) 349

were calculated from the plots. At 30°C, the Temkin isotherm model was found to fit with the 350

process of adsorption by referring to the R2 values from Table 5. 351

3.9.2 D-R Adsorption Isotherm – To access the nature of the adsorbent, the method of 352

adsorption by SW was explored by D-R isotherm study. The plots of D-R isotherm (ln qe vs €2) 353

for chromium, lead and zinc metal ions are shown in Figure 13, and the constants are presented 354

in Table 5. By fixing a constant temperature of 30°C, the regression coefficient (R2) values were 355

calculated and the values were observed to be in agreement (R2 > 0.95) with the adsorption 356

process (Yogeshwaran et al, 2021). Then, the R2 values calculated by Temkin and D – R 357

isotherm plots were compared to each other to find out the best fit of isotherm study. The results, 358

Chromium: Temkin > D-R, Lead: Temkin > D-R and Zinc: Temkin > D-R fitted very well with 359

each other. The Temkin isotherm study fitted well along with the adsorption process, compared 360

20

to the D-R model, based on the obtained R2 values that indicated monolayer adsorption on the 361

SW surface. Nevertheless, the R2 values were in agreement with both the isotherms, which 362

followed monolayer & heterogeneous adsorption process (Pholosi et al, 2019). 363

364

Figure 12 - Temkin plot for the adsorption for heavy metals (Cr, Pb and Zn) using SW. 365

366

Figure 13 - D – R plot for the adsorption for heavy metals (Cr, Pb and Zn) using SW. 367

y = 0.3648x - 0.2348

R² = 0.9897

y = 0.4908x - 0.6172

R² = 0.9502

y = 0.4508x - 0.4672

R² = 0.9762

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5

qe

(m

g g

-1)

ln Ce

Cr (VI) Pb (II) Zn (II)

y = 0.001x + 4.8212

R² = 0.9895

y = 0.0016x + 4.1747

R² = 0.9983

y = 0.0033x + 4.5574

R² = 0.993

0

5

10

15

20

25

0 1000 2000 3000 4000 5000 6000

ln q

e(m

g g

-1)

€2 (J2 mol-2)

Cr (VI) Pb (II) Zn (II)

21

3.9.3 Sips isotherm – The constants of the Sips model Qmax & Ks were obtained by taking slope 368

and deflection values from the kinetic linear plots of this model (Figure 14). The values of 369

constants and regression standards are represented in Table 5. The coefficient of regression (R2) 370

value is more than 0.95, which indicates the fitting process of dye adsorption. Based on the 371

heterogeneity factor (n) value, the model describes the nature of fitting, and the value of n lies 372

between 0 to 1. If the n value reaches 1, this equation reduces to the Langmuir equation, and it 373

infers the adsorption process in homogeneous nature. 374

375

Figure 14 - Sips plot for the adsorption for heavy metals (Cr, Pb and Zn) using SW. 376

Table 5 Isotherm constants for metal ion adsorption. 377

Type of

study

Metal ions

Parameters Units Cr Pb Zn

Temkin

KT (L mol-1) L/Mol 1.27 X 107 1.05 X 105 1.88 X 104

b x 10-6 J g mol-2 25.6 12.1 23.8

R2 - 0.989 0.965 0.956

Xm x 10-3 (mol/g) 4.15 4.65 3.76

y = 1.0532x - 3.8503

R² = 0.991

y = 1.3193x - 4.792

R² = 0.9599

y = 1.5729x - 5.114

R² = 0.9182

-8

-6

-4

-2

0

2

4

6

-1 0 1 2 3 4 5 6 7

ln [

qe

/(q

m -

qe

)]

ln Ce

Cr (VI) Pb (II) Zn (II)

22

D-R € KJ/mol 11.75 10.62 10.31

R2 - 0.989 0.950 0.976

Sips

KS bar-1 12.8689 6.13959 3.7113

βS mmol g-1 1.25346 1.54742 1.6536

aS - 0.47347 0.24345 0.1544

R2 - 0.9182 0.9599 0.9991

3.10 Thermodynamic studies on metal ion adsorption by SW 378

The removal efficiency of heavy metal ions by SW adsorbent was investigated under 379

different temperature conditions (15 to 60 °C). Referring to Figure 14, it was observed that the 380

metal ion adsorption and its efficiency were highly dependent on the temperature. The highest 381

metal ion adsorption by the adsorbent was recorded at 20°C, beyond that a sharp decrease in 382

adsorption efficiency was noticed. Due to the reduction of surface activity, the metal ion 383

adsorbent reached the exothermic state (Yang et al, 2018). The thermodynamic plots (log Kc vs. 384

1/T) of metal ion adsorption process are shown in Figure 15, and the slope & intercept values 385

(∆H° & ΔS°) were calculated and presented in Table 6 under different concentrations (25 - 150 386

mg/L) of metal ions. Due to the spontaneous nature of the adsorption process, the negative ΔH° 387

values with negative ΔG° values indicated the exothermic nature of the adsorption process 388

(Feszterová et al, 2021). Also, the ΔS° values suggested the increases in uncertainty during the 389

metal ion adsorption by SW in aqueous solutions. 390

3.11 Batch desorption study 391

The ability of the spent adsorbent (SWs) towards desorption of metal ions is directly 392

proportional to the desorption process (Momina et al, 2019). The batch desorption study was 393

carried out by varying the sulfuric acid concentrations from 0.1 to 0.4 N, and its impact on the 394

recovery of heavy metal ions is represented in Table 7. The maximum amount of recovery of 395

metal ions was determined by increasing the concentration of sulfuric acid. In this work, the total 396

amount of heavy metal ions and its recovery was achieved by adding 0.3 N of H2SO4, and 397

thereafter the metal ion recovery attained a constant rate. Further increase in the concentration of 398

H2SO4 was not found to increase the metal ion recovery from the spent SW. As a result, at 0.3 N 399

23

of H2SO4, the optimal level of desorption of metal ions from waste SW was achieved. 400

Furthermore, the SW was recovered and utilised as an adsorbent in subsequent adsorption tests. 401

Figure 14 – Impact of temperature of metal ions (Cr, Pb & Zn) adsorption using 402

SW. 403

404

405

20 30 40 50 60

75

80

85

90

95

% Cr (VI) Removal

Tem

pera

ture

25 mg/L

50 mg/L

75 mg/L

100 mg/L

125 mg/L

150 mg/L

20 30 40 50 60

80

82

84

86

88

90

92

94

96

98

% Pb (II) Removal

Tem

pe

ratu

re

25 mg/L

50 mg/L

75 mg/L

100 mg/L

125 mg/L

150 mg/L

20 30 40 50 60

75

80

85

90

95

% Zn (II) Removal

Tem

pera

ture

25 mg/L

50 mg/L

75 mg/L

100 mg/L

125 mg/L

150 mg/L

24

Figure 15 – Thermodynamic plots for the adsorption of metal ions (Cr, Pb & Zn) 406

using SW. 407

408

409

410

411

0.0029 0.0030 0.0031 0.0032 0.0033 0.0034

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

log Kc1/T

25 mg/L

50 mg/L

75 mg/L

100 mg/L

125 mg/L

150 mg/L

0.0029 0.0030 0.0031 0.0032 0.0033 0.0034

0.0

0.2

0.4

0.6

0.8

1.0

1.2

log Kc

1/T

25 mg/L

50 mg/L

75 mg/L

100 mg/L

125 mg/L

150 mg/L

0.0029 0.0030 0.0031 0.0032 0.0033 0.0034

0.0

0.2

0.4

0.6

0.8

1.0

1.2

log Kc

1/T

25 mg/L

50 mg/L

75 mg/L

100 mg/L

125 mg/L

150 mg/L

25

Table 6 Thermodynamic constants of the metal ion adsorption by SW. 412

Cr ion

(Initial Conc.)

∆H0

(KJ/mol)

∆S0

(J/mol/

∆Go (kJ/mol)

15C 30C 45C 60C

25 -83.38 222.52 -15.90 -10.82 -9.24 -8.24

50 -42.73 96.87 -11.31 -8.98 -7.45 -7.32

75 -26.45 61.28 -8.60 -7.45 -6.58 -6.15

100 -19.64 41.29 -6.69 -6.72 -6.19 -5.93

125 -16.82 32.35 -6.24 -6.12 -5.68 -5.28

150 -13.76 24.28 -5.45 -5.84 -5.12 -4.98

Pb ion

(Initial Conc.)

25 -56.24 143.77 -13.30 -11.15 -8.93 -8.13

50 -31.69 72.86 -9.02 -8.80 -7.47 -6.69

75 -26.44 56.98 -8.12 -6.90 -6.64 -5.51

100 -19.89 39.31 -7.62 -6.09 -5.38 -5.20

125 -15.49 21.83 -6.63 -5.44 -4.92 -4.69

150 -11.27 15.98 -5.57 -4.84 -4.52 -4.09

Zn ion

(Initial Conc.)

25 -40.02 99.09 -11.16 -9.29 -8.54 -7.31

50 -25.45 51.27 -9.01 -7.89 -7.02 -6.02

75 -19.92 40.51 -7.69 -6.32 -5.93 -5.29

100 -15.56 31.48 -6.24 -5.89 -5.05 -4.78

125 -13.29 28.92 -5.92 -5.02 -4.58 -4.22

150 -11.92 25.59 -5.01 -4.32 -4.10 -4.00

413

414

26

Table 7 Desorption of metal ions from the spent SW. 415

416

Initial

concentration

(25 mg/L)

Efficiency

of metal ion

removal

(%)

Concentration of H2SO4

0.10 N 0.20 N 0.30 N 0.40 N

% Desorption of metal ions

Cr 99.60 89.26 93.57 93.82 91.31

Pb 89.27 80.93 83.25 83.94 81.84

Zn 82.37 71.73 74.58 75.23 73.83

4. CONCLUSION 417

The removal efficiency of Chromium, Lead and Zinc metal ions present in aqueous 418

solutions was examined by utilizing Sargassum Wightii as an adsorbent. At a pH of 2.0, the 419

highest removal efficiency of 99.6 % (Cr), 89.27 % (Pb) and 82.39% (Zn) was achieved by using 420

the batch adsorption study. The ideal condition was found to be at an adsorbent dose level of 2.0 421

g/L, a contact period of 60 minutes, an initial adsorbate concentration of 25 mg/L and a 422

temperature of 30°C. The Temkin and D-R isotherm models suited the isotherm investigations 423

well, and the process followed the pseudo-second order and Boyd kinetic models. As a result, the 424

reported research infers Sargassum Wigtii's capacity to eliminate harmful metal ions from an 425

aqueous medium. 426

427

Author Contributions - All authors contributed to the experimental analysis, study conception. 428

Material preparation, analysis of data and content writing were performed by V. Yogeshwaran. 429

Draft preparation, corrections, validation of test results were performed by A.K. Priya. The two 430

authors read and approved the final manuscript. 431

Funding – Not Applicable 432

Data availability - The datasets generated during and/or analyzed during the current study are 433

available from the corresponding author on reasonable request. 434

Conflicts of Interests - The authors have no conflicts of interest to declare that are relevant to 435

the content of this article. 436

Ethics Approval – Not applicable 437

Consent to Participate/Publication – Not applicable 438

27

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