Zinc

Zinc is a micronutrient and found in different effluents (Wang, Yuan, et al. 2013). The element causes muscular stiffness, irritation, and nausea above acceptable concentrations (Meitei and Prasad 2014). Zinc finds its way into the environment from pharmaceutical wastewater, paints, insecticides, and cosmetics (Afroze et al. 2016). An overview of the experimental parameters and optimized conditions from batch adsorption experiments for zinc is presented in Table 4.4.

Effect of pH

The adsorption of zinc increases with pH (Zhang, Li, et al. 2010; Lu and Chiu 2006; Afroze et al. 2016; Feng et al. 2010; Bogusz et al. 2015). The dependence of metal adsorption on pH is based on two things, i.e. chemical behavior of the metal and chemical behavior of the functional groups at the surface of the adsorbent (Afroze et al. 2016). Zinc undergoes hydrolysis at higher pH, i.e. greater than 6 (Zhang, Li, et al. 2010; Adeli et al. 2017) or predominant form of zinc as Zn(OH)+ above pH 5.1 (Afroze et al. 2016). So, Zn(II) undergoes less adsorption at higher pH. At higher pH, conversion of Zn(II) to Zn(OH)+ leads to the decrease in charge of the metallic ion. The decrease in charge led to less adsorption of Zn(II). However, the total removal of zinc increased on raising the pH up to 8 (Zhang, Li, et al. 2010). The another reason for increase of percentage removal is also attributed to the adsorbent (Lu and Chiu 2006). The adsorbent surface becomes more negative with increase of pH, leading to increase of electrostatic attraction.

The precipitation pH reported for zinc was pH 8 (Feng et al. 2010). The predominant species of zinc between 8 and 12 were Zn(OH)+, Zn(OH)°2, and Zn(OH)~3. The zinc removal between pH 8 and 12 was attributed to the precipitation of Zn(OH), and adsorption of Zn(OH)+ and Zn(OH)~3 (Lu and Chiu 2006; Sen and Gomez 2011). However, at pH 12, predominant species were OH . Zn(OH)3", and Zn(OH)42-. The competition between them and decrease of electrostatic attraction were responsible for decline in removal at pH 12 (Lu and Chiu 2006).

TABLE 4.4

Summary of Parameters and Optimized Conditions for Batch Adsorption of Zinc

Surface Area

Adsorbent

Adsorbate

(m2/g), Pore

Volume

(cm3/g), Pore

Size (nm)

pHzpc

Experimental

Conditions

Adsorption

Capacity (mg/g)

Thermodynamic Parameters

Kinetic

Model and

Curve Fitting

Isotherm

Model and

Curve Fitting

Maximum

Adsorption

Conditions

Eucalyptus

Zn

Surface area

5

pH = 2-5.5

128.21

ДН°

Pseudo

Freundlich

pH = 5.1

sheathiana bark

= 6.55

Dose

= -32.43 kJ/mol

second-order

model Linear

Dose

Pore volume

=0.2-0.6 g/l

ÁS°

model linear

= 0.2-0.6 g/l

= 0.003

Agitation speed

= —90J/mol К

Contact time

= 120rpm

ÁG°

= lOOmin

Concentration

= negative

Temperature

= 20-70 mg/1

= 30°C

(isotherm)

Contact time

= lOOmin

Temperature

=30°C, 45°C and

60°C

Eucalyptus

Zn

Surface area

Do

250

ДН°

Pseudo

Freundlich

Do

sheathiana bark

= 20.33

= -6.19 kJ/mol

second-order

model Linear

modified with

Pore volume

ÁS°

model

NaOH

= 0.011

= -20J/mol К

Linear

ÁG°

= negative

Oxidized CNT

Zn

3.9

pH =7

58

Pseudo-

both Langmuir

Contact time

sheets

Dose = 2 g/l

second-order

and Freundlich

= 48h

Concentration

model at low

model Linear

= 100-1200 mg/1

concentration

Contact time

and pseudo

= up to 72 h

first order

Temperature

model at high

= 25°C

initial

concentration

linear

References

Afroze et al. (2016)

Afroze et al. (2016)

Tofighy and

Mohammadi

  • (2011)
  • 156 Batch Adsorption Process of Metals and Anions

TABLE 4.4 (Continued)

Summary of Parameters and Optimized Conditions for Batch Adsorption of Zinc

Surface Area

(m2/g), Pore

Volume

Adsorption

Kinetic

Isotherm

Maximum

(cm3/g), Pore

Experimental

Capacity

Thermodynamic

Model and

Model and

Adsorption

Adsorbent

Adsorbate

Size (nm) pHzpc

Conditions

(mg/g)

Parameters

Curve Fitting

Curve Fitting

Conditions

References

Bentonite

Zn

pH = 3.81-7.69

68.49

Kl=q(/Ce

Overall

Langmuir model

pH = 6.76

Sen and Gomez

Dose = 0.25-0.75 g/1

AH°

pseudo

Linear

Dose

(2011)

Agitation speed

= -12.31 kJ/mol

second-order

= 0.25 g/1 (in

=80rpm

AH0

model with

terms of

Concentration

= negative

linear curve

adsorption

= 10-90 m g/1

AS0

fitting and

capacity)

(isotherm study)

= -0.03 285 J/mol

two-step

Agitation speed

Contact time

K

process

= 80rpm

=up to 120min

Contact

Temperature

lime = 80 min

=30°C-65°C

Temperature

= 30°C

Industrial

Zn

Surface area

pH = 1-7.5

40.18

Pseudo

Langmuir model

pH = 7

Boguszet al. (2015)

biochar from

= 26.3

Dose = 4 g/1

second-order

Contact

wheat straw

Agitation speed

model

time = 24 h

= 120rpm

Linear

Concentration

=5-500 mg/1

(isotherm study)

Contact time

=up to 26 h

Temperature

=22°C

Lab-prepared

Zn

Surface area

Do

45.12

Pseudo

Langmuir model

Do

Boguszet al. (2015)

biochar from

= 27.1

second-order

Linear

Sida

model

hermaphrodita

Linear

Remediation of Essential Elements 157

Ul со

TABLE 4.4 (Continued)

Summary of Parameters and Optimized Conditions for Batch Adsorption of Zinc

Adsorbent

Adsorbate

Surface Area

(m2/g), Pore

Volume

(cm’/g), Pore

Size (nm)

pHzpc

Experimental

Conditions

Adsorption

Capacity (mg/g)

Thermodynamic Parameters

Kinetic

Model and

Curve Fitting

References

Isotherm Maximum

Model and Adsorption

Curve Fitting Conditions

Graphene oxide

Zn

Zeta potential measured

pH =2-10

Dose = 0.066-0.33 g/l

Agitation speed = 170rpm

Concentration = 10-100 mg/1 (isotherm)

Contact time =up to 480min

Temperature =20°C-45°C

245.7

AH0

= -2.171 kJ/mol

AS0

= 134-137J/K mol

AG°

= negative

Pseudo

second-order

model

Linear

Langmuir model pH = 7

Linear Dose =0.066 g/1

Contact lime

= 120 min

Temperature =20°C

Wang. Yuan, et al.

(2013)

Nanozinc oxide

Zn

pH =4-8

Dose = 0.025 g/1

Agitation speed = 200rpm

Concentration

= 100-600 mg/1 (isotherm)

Contact time

= up to 2h Temperature

=3O°C-7O°C

357

AH0

= -22.23 kJ/mol

AS0

= -70.64J/K mol

AG°

= negative

Pseudo

second-order

model

Linear

Langmuir model pH = 5.5

Linear Temperature

= 30°C

Sheela et al. (2012)

(continued)

Batch Adsorption Process of Metals and Anions

TABLE 4.4 (Continued)

Summary of Parameters and Optimized Conditions for Batch Adsorption of Zinc

Surface Area

(m2/g), Pore

Adsorbent

Adsorbate

Volume

(cm’/g), Pore

Size (nm)

pHzpc

Experimental

Conditions

Adsorption

Capacity (mg/g)

PVA/EDTA chelating agent

Zn

pH = 1-8

Dose = 0.05 -0.8 g/l

Agitation speed

= lOOrpm

Concentration

= 10-100 mg/1

(isotherm)

Contact time

=5-90 min

Temperature

=25°C-35°C

  • 39.92
  • (calculated from maximum conditions)

Activated carbon from watermelon .shell

Zn

Surface area

= 710

Pore volume

= 0.263

3.05

pH =4.5

Dosc = 10 g/l

Concentration

= 10-500 mg/1

(isotherm)

Contact time

= 2 weeks

Temperature

= room temperature

11.31

Activated carbon from walnut shell (GACN)

Zn

Surface area

= 789

Pore volume

4.5

Do

6.0

= 0.304

Kinetic

Isotherm

Maximum

Thermodynamic Parameters

Model and

Curve Fitting

Model and

Curve Fitting

Adsorption

Conditions

References

AH°

= 35.89 kJ/mol

AS°

= 188.35 J/K mol

AG°

= negative

Pseudo

second-order

model

Linear

No clear distinction suggested by the author Based on R2 it was Dubinin-Radushkevich

pH = 6

Ek> sc

= 0.6 g/l

Contact time

= 25 min

Zhang. Li. et al.

(2010)

Langmuir model

Concentration = 50 mg/1

Moreno-Barbosa et al. (2013)

Langmuir model

Concentration = 10 mg/1

Moreno-Barbosa ct al. (2013)

Remediation of Essential Elements 159

TABLE 4.4 (Continued) °

Summary of Parameters and Optimized Conditions for Batch Adsorption of Zinc

Surface Area

Adsorbent

Adsorbate

(m2/g), Pore Volume (cm’/g), Pore Size (nm)

pHzpc

Experimental

Conditions

Adsorption Capacity (mg/g)

Thermodynamic Parameters

Kinetic

Model and

Curve Fitting

Isotherm

Model and Curve Fitting

Maximum

Adsorption

Conditions

References

Sulfurized

Zn

Surface area

4.3

pH =2-10

147

Pseudo

Langmuir model pH = 6.5

Anoop Krishnan

activated

= 500

Dose = up to 8 g/l

second-order

Linear

Ek> sc

et al. (2016)

carbon

(calculation

Agitation speed

model

= 4 and 6 g/l for

method is

=200rpm

Linear

real waste water

different)

Concentration

Concentration

=50-250 mg/1

= 250 mg/1 (on

Contact time

the basis of

=up to 300min

adsorption

Temperature =

capacity)

30°C

Contact time

=240 min

Biochar from

Zn

Surface area

pH = 2-6

1

Langmuir model pH = 4(onthe

Jiang, Huang, ct al.

pine (softwood)

= 219.35

Dose = 25 g/l

Nonlinear

basis of

(2016)

Pore volume

Agitation speed

adsorption

= 0.125

= 120rpm

capacity)

Concentration

Salinity

= 0-3.5 mM

= 0.01 M (on the

(isotherm study)

basis of

Contact time = 24h

adsorption

Temperature = 25°C

capacity)

Salinity = up to 0.3 M

Biochar from

Zn

Surface area

Do

2.31

Freundlich

Do

Jiang, Huang, ct al.

jarrah

= 309.29

model

(2016)

(hardwood)

Pore volume

Nonlinear

= 0.146

Batch Adsorption Process of Metals and Anions

TABLE 4.4 (Continued)

Summary of Parameters and Optimized Conditions for Batch Adsorption of Zinc

Adsorbent

Adsorbate

Surface Area

(m2/g), Pore

Volume

(cm’/g), Pore

Size (nm) pHzpc

Experimental

Conditions

Adsorption Capacity (mg/g)

Thermodynamic Parameters

Kinetic

Model and

Curve Fitting

References

Isotherm Maximum

Model and Adsorption

Curve Fitting Conditions

Fungal dead mass composite with bentonite

Zn

pH = 2-8

Dose = 0.05-0.3 g/l

Agitation speed

= 120rpm

Concentration

=50-225 mg/l

Contact time = up to 120min

Temperature =30°C-58°C

Salt and surfactant do not affect the adsorption process

78.5

A H° =44.097 kJ/mol

AG° = negative

AS° = 173.84J/K mol

Pseudo

second-order

model

Linear

Langmuir model pH = 5 Linear Dose =0.05 g/l

Concentration = 200 mg/l Contact time = 30 min Temperature = 51°C

Rashid et al. (2016)

Metakaolinbased geopolymer (MKG) (batch and column study)

Zn

Surface area

= 39.24

pH = 2-8

Dose = 0.4-2 g/l

Agitation speed

=200rpm

Concentration

=25-600 mg/l

Contact time

=5-90 min

Temperature = 10°C-50°C

74.53

Pseudo

second-order

Langmuir model pH = 6.39 Dose =2 g/l Temperature = 25°C

Contact time = 40 min

Kara et al. (2017)

Remediation of Essential Elements

(continued)

O'

TABLE 4.4 (Continued)

Summary of Parameters and Optimized Conditions for Batch Adsorption of Zinc

Surface Area

(m2/g), Pore Volume

Adsorption

Capacity

(cm’/g), Pore

Experimental

Adsorbent

Adsorbate Size (nm) pHzpc

Conditions

(mg/g)

Biogenic clem entai selenium nanoparticles

Zn

pH = 3-7

Dose = 5 ml of 0.22 g/l solution

Concentration

=5.8-215 mg/1

Contact time

=1-960 min

62.1

Magnetic

Zn Surface area

pH =4-10

2.15 mmol/g

hydroxyapatite

= 142.5

Dose = 0.05-5 g/l Concentration

= 10-4-10’2 mol/1

(isotherm study)

Contact time

= 15 min-2days Temperature

=25°C

(140.63 mg/g)

Graphene oxide

Zn

pH =4-8

Dose = 0.1 g/l

Concentrations 1

mg/1 (pH study)

Contact timc = up to

120 min

Temperature = 25°C

345

Kinetic

Isotherm Maximum

Thermodynamic

Model and

Model and Adsorption

Parameters

Curve Fitting

Curve Fitting Conditions References

Langmuir model pH=3.9 Jainet al. (2015)

Contact time =240 min (equilibrium time, maximum adsorption at 120 min) concentration =5.8 mg/1

Pseudo

second-order

model

Linear

Langmuir model pH = 8 Feng cl al. (2010)

Linear Dose =0.1 g/l

Contact lime

= 24h

Pseudosecond-model Nonlinear

Langmuir model pH = 5 Sitko et al. (2013)

Nonlinear Contact lime

= 30 min

Batch Adsorption Process of Metals and Anions

TABLE 4.4 (Continued)

Summary of Parameters and Optimized Conditions for Batch Adsorption of Zinc

Surface Area

(m2/g), Pore

Volume Adsorption Kinetic Isotherm Maximum

(cm’/g), Pore Experimental Capacity Thermodynamic Model and Model and Adsorption

Adsorbent

Adsorbate Size (nm) pHzpc Conditions (mg/g) Parameters Curve Fitting Curve Fitting Conditions References

Sodium

Zn pH = 2-6 59.2 Langmuir model pH = 6 Adeli et al. (2017)

dodecyl-coated

Dose = up to 1 g/l Linear Dose = 1 g/l

magnetite

Concentration SDS amount

nanoparticles

=5-50 mg/1 = 37.5 mg/20 ml

(isotherm study) Salt = 0%

Contact time

=5 min in most

studies equilibrium

achieved in 1 min

Temperature

=25°C

SDS amount

=up to 60 mg/20

ml of SDS

Salt = up to 10%

Single-walled

Zn Surface area pH = 1-12 43.66 Langmuir model pH 8 at 10 mg/1 Lu and Chiu (2006)

carbon

= 423 Dose = 0.5 g/l initial

nanotube

Pore volume Agitation speed concentration

(CNTs)

= 0.43 = 180 rpm pH 7 at 80 mg/1

Concentration initial

= 10-80 mg/1 concentration

(isotherm study) Contact

Contact time time = 60min

=0-360 min Temperature

=25°C

Remediation of Essential Elements 163

TABLE 4.4 (Continued)

Summary of Parameters and Optimized Conditions for Batch Adsorption of Zinc

Surface Area

Adsorbent

Multiwalled carbon nanotube

Adsorbate

Zn

(m2/g), Pore

Volume

Adsorption Capacity (mg/g)

32.8

(em’/g), Pore

Size (nm) pHzpc

Surface area

= 297

Pore volume

= 0.38

Experimental

Conditions

Do

Cross-linked magnetic chitosanphenyl thiourea

Zn

Surface area

= 64.5

pH = l-5

Dose = 0.1 g/1 Agitation speed

= 150rpm Concentration

= 10-400 mg/l

(isotherm study)

Contact lime =up to 120min

Temperature =293-313 K

52

Zinc oxide

Zn

pH =4-8

Dose = 0.5 mg/l Agitation speed =200rpm

Concentration

357

Kinetic

Isotherm Maximum

Thermodynamic

Model and

Model and Adsorption

Parameters

Curve Fitting

Curve Fitting Conditions

Langmuir model pH 9-11 at 10 mg/l initial concentration pH 7 at 80 mg/l initial concentration Contact time = 60 min

References

Lu and Chiu (2006)

Pseudo

Langmuir model pH = 5

Monier and

second-order model

Linear

Linear Contact time

= 100 min

Temperature = 293K

Abdel-Latif (2012)

AH° =-22.23

Pseudo

Langmuir model pH = 8

Sheela et al. (2012)

kJ/mol

second-order

Linear Temperature

AS°= negative

AG° = negative

model

Linear

= 30 °C

= 100-600 mg/l (isotherm study) Contact time

=up to 2h Temperature

=30°C-70°C

164 Batch Adsorption Process of Metals and Anions

The deprotonation of the functional groups on the surface of the adsorbent also helped in increased adsorption of zinc with an increase of pH (Bogusz et al. 2015; Monier and Abdel-Latif 2012). In case of biochar, the increase in pH also increased the removal of zinc from aqueous solution (Bogusz et al. 2015). The rise in pH causes the carboxyl group on the surface of the adsorbent to be deprotonated along with binding of metal ions. In addition to this, there was increase in pH of the solution from 7 to 7.5 on application of the biochar adsorbent. This was attributed to ash content (present within biochar) release into the solution.

In the case of adsorption of zinc with magadiite, the difference in adsorption at pH

6.5 and 6.9 was also attributed to competition from hydronium ions (Ide et al. 2011). The titration curve suggests that the hydronium ion replaced the sodium ion of the adsorbent below pH 6.5. Hence, at pH 6.2, the zinc faced the competition from the hydronium ion, which led to its decreased adsorption than at pH 6.9. In addition, the basal spacing also played a major role. The larger amount of adsorption of zinc with magadiite at pH 6.9 for mixed electrolyte solution than at pH 6.2 for aqueous sodium chloride solution was attributed to larger basal spacing (1.64 nm) in the mixed electrolyte solution than in the aqueous sodium chloride (1.59 nm) solution. This led to better intercalation of the zinc ion in the mixed electrolyte.

Effect of Coexisting Ions

The effect of salt addition on sodium dodecyl sulfate-coated iron oxide caused the reduction in removal of zinc (Adeli et al. 2017). The competitive adsorption between sodium and metal ion via the ion exchange mechanism is responsible for decrease in adsorption (Adeli et al. 2017). In addition, salt reduced the adsorption capacity in other adsorbents (Afroze et al. 2016). The charge, weight, atomic radius, and molecular weight of the salt also affect the adsorption capacity of zinc on the adsorbent. The divalent and trivalent species of the salt decreased the removal efficiency more as compared to monovalent species. The effect of ionic strength is attributed to the difference in ionic osmotic pressure, which decreased on increase of ionic strength of the solution (Afroze et al. 2016).

The decrease in adsorption of zinc by biochar occurred in the presence of chloride; however, the effect of nitrate is less influential than that of chloride. The chloride was predicted to form complexes with aliphatic carbonaceous groups present on the surface of the adsorbent. The complexes formed compete with the adsorption sites on the surface of adsorbent, whereas chloride and nitrate ions did not compete. The two different biochar sources showed different interfering capacities. The high content of oxygen groups on the surface of biochar was predicted to be responsible for the higher adsorption capacity, which led to the closely firmed resistance against the interfering ions. This makes the adsorbent less prone to attack by interfering ions as compared to biochar with low oxygen content (Bogusz et al. 2015).

Mechanism

The XPS analysis helped in understanding the mechanism of adsorption of zinc on graphene oxide (Sitko et al. 2013). The analysis of Cis and Ols spectra showed differences before and after adsorption. The difference between the oxygen peaks suggests involvement of the oxygen-containing functional group taking part in adsorption.

The 29Si magic angle spinning NMR spectra of the adsorbent were used to estimate the reason for better adsorption of zinc as compared to cadmium and potassium (Ide et al. 2011). The Q3 and Q4 peaks for cadmium- and potassium-adsorbed samples were lower and comparable for zinc in comparison to the original adsorbent. Hence, the results suggest that intercalation of the cations other than the zinc ion led to significant alteration in the layered structure of magadiite along with suppression of metal adsorption.

Desorption

The hydrochloric acid can be applied in case of desorption of zinc from PVA/EDTA resin (Zhang, Li, et al. 2010), sulfurized activated carbon (Anoop Krishnan et al. 2016), and polymeric resin (Zheng, Li, et al. 2017). In spite of high desorption of zinc from MnFe,O4 and CoFe2O4 nanoparticles by HC1, HNO3 was selected as HC1 leads to higher degradation of the adsorbent (Asadi et al. 2020). In the case of zinc desorption from cross-linked magnetic chitosan-phenylthiourea, EDTA is more effective than hydrochloric acid (Monier and Abdel-Latif 2012). The reason is the desorption mechanism; the hydrochloric acid desorbs the material by ion exchange, whereas the EDTA forms a complex with the metal.

 
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