The removal of Cu2+, Ni2+ and Methylene Blue (MB) from aqueous solution using Luffa Actangula Carbon: Kinetics, thermodynamic and isotherm and response methodology

Groundwater for Sustainable Development 6 (2018) 141–149

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Research paper

The removal of Cu2+, Ni2+ and Methylene Blue (MB) from aqueous solution using Luffa Actangula Carbon: Kinetics, thermodynamic and isotherm and response methodology

T

Shaziya H. Siddiqui Department of Chemistry, Sam Higginbottom University of Agricultural, Technology and Sciences (SHUATS), Allahabad 211007, India

A R T I C L E I N F O

A B S T R A C T

Keywords: Exothermic HYBRID Error analysis Response surface

The removal of Cu2+, Ni2+ and Methylene blue onto agricultural waste Luffa Actangula Carbon (LAC) was carried out. The surface morphology and functional group study for LAC was done by FTIR, SEM and EDAX technique. The data was best fitted by Pseudo 2nd order kinetic model. The equilibrium was attained in 120 min at pH 6 for Cu2+ with maximum adsorption capacity of 12.47 mg g−1 and pH 6 for Ni2+ with maximum adsorption capacity of 6.2 mg g−1 at 30 °C. The equilibrium for MB was attained in 120 min at 30 °C at pH 7 with maximum adsorption capacity of 10.32 mg g−1. The methodology of Response Surface was used to study the process variables like contact time and pH and their interaction with removal efficiency as response. The data was nonlinearly fitted by Freundlich isotherm model for Cu2+ and Ni2+ ion with Regression coefficient of Cu2+ (0.965) and Ni2+ (0.950) whereas in case of MB it was best fitted nonlinearily by Langmuir Isotherm with higher regression coefficient(0.954) and smaller ᵡ2 value. The LAC shows higher adsorption capacity in the order of Cu2+ (12.47 mg g−1) > MB (10.32 mg g−1) > Ni2+ (6.2 mg g−1). The Langmuir monolayer adsorption capacity is in the order of Cu2+ (33.16 mg g−1) > MB (24.84 mg g−1) > Ni2+ (23.84 mg g−1). The data was also predicted by statistical error analysis tool like HYBRID, ARE. The Thermodynamic parameters ΔG°, ΔH°, ΔS° have been decided and it was found that the process was feasible, spontaneous and exothermic in nature.

1. Introduction The heavy metals and dissolved organic compound are the pollutants that are highly toxic to the living system. Cu (II), Ni (II) ions are the toxic pollutants effecting the flora and fauna of the system. The most used heavy metal ion by industries and municipal wastewater is Copper that causes health hazard problems such as affecting the brain, heart, kidney and Liver. The permissible limit of copper given by EPA is 2.0 mg L−1. Excessive level of nickel in water causes adverse effect on health such as causing cancer, skin allergy and lung fibrosis. One of the most important health problem caused by nickel and its compounds are allergic dermatitis (nickel itch) and increases incidence of cancers. The permissible limit for nickel given by EPA is 0.015 mg L−1 in drinking water (Hannachi et al., 2010). Methylene Blue (MB) as one of the dye effluents is considered to be highly toxic affecting the aquatic species through symbiotic process by disturbing natural equilibrium by reducing photosynthetic activity and production due to colorization of water (Rajendaran et al., 2016). The removal of heavy metal and dyes can be carried out by various physiochemical methods like: ion exchange process, metal extraction, chemical precipitation and membrane

separation (Barakat, 2011). These methods have several disadvantages like high operation cost, imperfect removal of heavy metals ions, and lack of selectivity and production of waste during their production. The metal ion removal methods can remove as low as 50 mg L−1. Development of efficient and low-cost separation processes is therefore the most importance (Gupta et al., 2012b) Alternatively related technique used for the removal of heavy metals and dyes are Adsorption process. The most efficient and economic technique adsorption, is used worldwide for removal of heavy metals and dyes. Adsorption is found to be operative at all temperature,pH and recovery of metal and minimum generation of sludge (Saleh and Gupta, 2014). The scientist are trying to evaluate the adsorption capacities of heavy metals and dyes by low cost adsorbents which maybe conventional or non-conventional (Gupta et al., 2009; Gupta et al., 2011a, 2011b). The most widely used adsorbent for the removal of pollutants has been activated carbon. But due to its high cost and less regeneration, its applications are restricted. Whereas, the use of agricultural waste in comparison to activated carbonas a low-cost alternative adsorbent has received considerable attention (Malkoc and Nahoglu, 2005). Various agricultural waste like Cashew nut shell (Kumar et al., 2011) [9], tea

E-mail address: [email protected]. https://doi.org/10.1016/j.gsd.2017.12.008 Received 24 August 2017; Received in revised form 8 December 2017; Accepted 20 December 2017 Available online 24 December 2017 2352-801X/ © 2017 Published by Elsevier B.V.

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2.3. Point of zero charge

factory waste (Malkoc and Nahoglu, 2005), dye groundnut shell (Shukla and Pai, 2005), tobacco dust (Qi and Aldrich, 2008), Banana Peels (Hossain et al., 2012), almond shells (Duran et al., 2011), CNT/ Magnesium oxide composite (Saleh and Gupta, 2014), Aluminium Coated Carbon Nanotubes (Gupta et al., 2011a, 2011b), Multiwalled carbon nanotubes and Titanium Oxide (Gupta et al., 2015),waste rubber tyre derived carbon (Saleh and Gupta, 2014), Carbon Nano tubes (Gupta et al., 2013), orange peel and Fe2O3 nanoparticles (Gupta and Nayak, 2012), bottom ash (Mittal et al., 2010a, 2010b), Rice Husk (Ahmaruzzaman and Gupta, 2011), ZnO/CdO nanocomposite (Saravanan et al., 2015), Alumina/polyamide nanoparticle (Saleh and Gupta, 2012b), ZnO/Ag nanocomposite (Saravanan et al., 2013b), CeO2/V2O5 composite (Saravanan et al., 2013b), PANI/ZnO (Saravanan et al., 2016), nanorod (Saravanan et al., 2015a), Porous Carbon and Fullerene (Gupta and Saleh, 2013), ZnO/ϒ-Mn2O3 (Saravanan et al., 2014), Groundnut-Guar Gum Composite (Ahmad and Haseeb, 2015) etc., are the adsorbents used for the removal of Cu(II), Ni(II) and MB. The adsorbent used i.e. Luffa Actangula or commonly known as ridged gourd or Turai is a cheap vegetable easily available in abundance in northern India. This vegetable is rich in carbohydrate, potassium, fat. The peels of Luffa Actangula contain oleanoic acids, cartenoids and phenolic compounds (Kao et al., 2012) and functional groups like –OH and –COOH. The –OH and –COOH groups act as potential site for the adsorption of pollutants. These groups act as potential site for the adsorption of pollutants. The Luffa Actangula in its carbon form is used for the removal of Cu (II), Ni (II) and Methylene blue. The Response Surface Methodology was used to study the optimum variables like contact time and pH with removal efficiency as response. In order to study the adsorption mechanism and to judge the effectiveness of adsorbent, kinetics and isotherm parameters are discussed in details. The characterization was done to study the elemental, morphological and functional groups present in the adsorbent.

The solid addition method was used to determine the zero surface charge characteristics (pHzpc) of Luffa Actangula carbon (LAC) using 0.1 M KCl (Haseeb and Ahmed, 2017). The pH of the 25 mL solution of KCl in a conical flask was adjusted between 2 and 10 by using 0.5 M HCl and NaOH. After the measurement of pHi (initial pH), 0.1 g of adsorbent was added to a series of solution of different pHi and allowed to equilibrate for 24 h. The final pH of the solutions were then observed and noted. The difference between the initial pH (pHi) and the final pH (pHf) (ΔpH = pHi − pHf) values were then plotted against pHi. The point of intersection of the resulting curve with the abscissa, at which ΔpH = 0, gave the pHzpc value. 2.4. Metal selection test The absorptive nature of LAC was studied using Cu2+, Ni2+, Pb2+, Methylene Blue (MB),2,4-D.dichorophenols. It follows in the order as Cu2+ > > MB > > Ni2+ > > Pb2+ > > 2,4-D dichlorophenol. 2.4.1. Batch adsorption studies The adsorption of Cu2+, Ni2+ and MB was carried in batch mode with 25 mL solution of desired concentration (10–100 mg L−1) and 0.1 g adsorbent in 100 mL conical flask for 24 h after equilibration pollutant samples were filtered and analyzed by AAS. The pH was studied in the range of pH 2–8 and adjusted by using 0.5 M HCl and NaOH. The experiment was performed at pH 7.0 for MB and pH 6.0 for Cu2+ and Ni2+ ion. All the experiments were reported in triplicates. MB concentration was determined by UUV–Visble spectrophotometer with maximum absorbance at 664 nm. The removal percentage (%) and adsorption capacity (qe, mg g−1) of MB, Cu2+ and Ni2+ were calculated using the following relationship:

2. Material and methods 2.1. Chemicals and instruments −1

%=

(Co − Ce ) 100 Co

qe =

(Co − Ce ) V W

(1) (2) −1

The stock solution of 1000 mg L of Cu (II) and Ni (II) were prepared in double distilled water using the salts of copper nitrate, nickel nitrate. A stock solution of Methylene blue dye solution was prepared (500 mg L−1) by dissolving 0.5 g of dye powder in double distilled water to obtain dye concentration. The chemicals purchased were of analytical grade (Gupta et al., 2012a). The adsorbent surface was characterized by scanning electron microscopy (JSM −6510LV). The presence of functional groups in the adsorbent was characterized by FTIR spectroscopy model (Perkin Elmer, USA, model spectrum-BX, range 4000–400 cm−1). The presence of element in the group can be characterized by the EDX model (JSM6510LV). The resultant concentration was determined by atomic adsorption spectroscopy (AAS) model (GBC-902, Australia) for heavy metals. The Methylene blue solution concentration unloaded and loaded before was determined by using a double beam UV–Visible spectrophotometer (PG Instruments, UK). The pH was measured by using pH meter (Elico L1120, India).

Where, Ce is the concentration of adsorbate at equilibrium (mg L ), V is the volume of the solution (L), qe is the adsorption capacity at equilibrium, Co is the initial concentration of the adsorbate (mg L−1) and W is the mass of the adsorbent. The desorption study for Cu2+, Ni2+ and MB was carried out using 0.1 g LAC loaded with 0.1 M HCl, 0.1 M H2C2O4 and 0.1 M HNO3 for 2 h. The supernatant was filtered and then analyzed. 2.5. Error analysis Various Error function are used to evaluate the models by using the EXCEL FUNCTION and Origin Pro8. They are RMSE (Residual Mean Square Error), χ2 (Chi-sqr-test) and HYBRID test. There equations are as follows:

HYBRID =

ARE =

2.2. Preparation of adsorbent The adsorbent was collected from the local market of Allahabad city. The Luffa Actangula peels were washed with double distilled water before use to remove dirt and then dried at 80 °C. The dried material was then placed in silica crucible in the muffle furnace at 750 °C. The resultant carbon was then cooled, grinded and sieved to 50–100 mesh size (Ahmad and Haseeb, 2017). The obtained carbon was then further washed with distilled water and then dried in an oven and used as such for further adsorption studies.

100 P

100 N−P n

∑[ i=1

n

∑[

qe mod el − qecal

i=1

qecal

(qemeas −qecal ) qemeas

] (3)

] (4)

3. Results and discussion 3.1. Characterization The SEM image reveals the adsorbent is quite porous in nature. After adsorption, all the pores sites are occupied by metal ions are shown in Fig. 1(a,b). The Weight (%) element present in LAC was 142

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Fig. 1. SEM micrograph of Luffa Actangula Carbon (a) before (b) after adsorption of Cu (II) ion.

aromatic rings. The shift in the peak from 1069 cm−1 to 1061 cm−1 corresponds to –C-O groups. The peak at 875 cm−1 correspond to aromatic –CH binding. The peak 2922 cm−1 appears after loading due to the presence of alkyl –CH groups responsible for adsorption.

Table 1 Adsorption Kinetics for the adsorption of Cu2+, Ni2+ and MB on Luffa Carbon. Parameters Pseudo 1st order qe(cal) qe(exp) k1 R2 Pseudo 2nd order qe(cal) qe(exp) k2 R2 Intraparticle diffusion Kid C R2

Cu2+

Ni2+

MB

2.08 12.47 0.085 0.7128

1.05 6.2 0.078 0.864

12.16 10.32 0.046 0.359

12.5 12.47 6.40 1

6.25 6.2 0.287 0.999

10.41 10.32 −9.25 1

0.035 12.21 0.880

0.156 5.132 0.716

0.003 10.28 0.729

3.2. Response surface methodology of adsorption of Cu2+ and Methylene Blue The Central Composite design the most popular method is used to study the Response Methodology by using the statistical software Minitab 18. The method is used to study the response of operating variables like contact time, pH with yield as % removal. The experimental factors included are contact time (5–180 min) and pH (2–8) with their removal efficiency is studied. The 13 trials were run to study the effect of two independent variables (X1= contact time and pH and X2= adsorption capacity) and response as % removal efficiency with a test run of (−1,0,1). The quadratic equation explains the statistical relationship between the selected variables and response in terms of coded factors as shown in the following equations:

analyzed by EDAX. The wt (%) composition of Carbon, Oxygen, Potassium, Phosphorous and Copper are shown in Table 1 and Fig. 2(a, b). The spectra of FTIR for LAC loaded and unloaded are shown in Fig. 3. The peak at 3748 cm−1 assigned to minerals –OH groups. The peak at 1580 cm−1 can be attributed to the stretching of C˭C bonds of

Y(Cu2 +) = −96063 + 29.5x1 + 15228x2−0.00106x1*x1−603 × 2*x2 −2.36 × 1*x2

Fig. 2. EDAX spectra of Luffa Actangula Carbon (a) before (b) after adsorption with Cu (II) ion.

143

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Fig. 3. FTIR Spectra of Luffa Actangula Carbon (a) before (b) after adsorption with Cu (II) ion.

pH. At lower pH the H+ ions presence will hurdle the cationic pollutants resulting in lower attachment of pollutants on the site. At lower pH the surface of the adsorbent is always protonated which reduces the extraction of cations due to electrostatic repulsion. At high pH, some of the functional groups present on the surface of adsorbent becomes negatively charged leading to increase in electrostatic interaction between adsorbents and cationic pollutants (Homagai et al., 2010; Mallampati and Valiyaveettil, 2012). Removal of Cu (II) ion increases with increase in solution pH. The hydrolysis products as a function of pH are as follows: In the pH range 2–5, the dominant species are Cu2+ and CuOH+, above 6.3 the copper occur as insoluble Cu (OH)2(s). At pH 6, there are three species: Cu2+ (in very small quantity), CuOH+ and Cu (OH)2 (in large quantity)(Mallampati and Valiyaveettil, 2012). The reason of metal hydroxide formation is due to buffering using NaOH solution. The metal ions in aqueous solution exist predominantly as [M (H2O)6]2+. The ions in hydroxide forms react with [M(H2O)6]2+ to form insoluble metal hydroxide dehydrate as follows (Sadeek et al., 2015).

Y(MB) = −3010342 + 143.7x1 + 582274x2−0.000832x1*x1−28156x2*x2 −13.92x1*x2 Where X1= contact time and x2= adsorption capacity in mg g−1 The results of central composite design shown in Fig. 4(a and b) in form of surface and contour plots for the removal of Cu2+ ion by LAC and regression analysis is shown in Table 5 and for removal of Methylene blue by LAC as shown in Fig. 4(c and d) and Table 6. The Figure shows the response in terms of % removal. The figure shows that the removal efficiency and capacity increases and become constant after 120 min with maximum yield of more than 95%. The values of multiple R2 was 57.49% (Cu2+) and 55.85%(MB) for effect of contact time could be explained by quadratic and reduced quadratic models respectively as shown in Tables 5, 6. 3.3. Contact time study The adsorption rate is one of the important parameters for batch adsorption studies. The adsorption of Cu2+, Ni2+ and MB onto LAC may take place through multiple steps such as external film diffusion, intraparticle diffusion and interaction between pollutants and active sites of adsorbent. External film diffusion is a fast process so it is not a rate limiting step. The adsorption of metal ions and dye was studied in the range of 5–180 min at 30 °C of 50 mg L−1 metals ion and dye solution. The maximum adsorption in case of Cu2+, Ni2+ and MB was attained at 120 min with maximum adsorption capacity in the range of Cu2+(12.47 mg g−1) > MB(10.32 mg g−1) > Ni2+(6.2 mg g−1). The metal and dye ions uptake on the adsorbent surface may indicate that most of the reactant sites are exposed for the interaction of metal ions and dye. The presence of various group i.e. hydroxyl which forms a complex between adsorbate and adsorbent surface causing faster adsorption.

[Cu(H2O)6]2 +2OH− →Cu(H20)2(OH)2 + 2H2O[Ksp= 2·2*10−20] Ni2++H+ +OH− →Ni(OH)+ +H+ Ni2+ +2H2O→Ni(OH)2+2H+ The pHz (point of zero charge) is the point at which the functional groups does not take part in the pH of the solution. The pHz of LAC was found to be around 7.0. Adsorption of cations will be favourable at pH values higher than pHzpc, whereas the adsorptions of anions will be favourable at pH values lower than pHz (Jiang et al., 2015). The point of zero charge is also related to surface acidity low acid surface group concentration. The point of zero charge value of LAC is higher than the pH value which shows the basic nature of the adsorbent (Sardella et al., 2015).

3.4. Effect of pH 3.5. Adsorption kinetics

It is one of the important parameter for adsorption of pollutants. The metal ion removal was observed at pH 6 and for Methylene blue at pH 7 as shown in Fig. 5. It has been observed that removal percentage of cationic pollutants (Cu2+, Ni2+ and MB) increases with increase in

The Kinetic data gives the information about the mechanism of biosorption which is important for efficiency of adsorption process. The 144

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Fig. 4. (a) Surface Plots of LAC for the removal of Cu (II) ion (b) Contour plots of LAC for the removal of Cu(II) ion(T = 30 °C, pH = 6, 50 mg L−1) (c) Surface plots of LAC for the removal of MB (d) Contour plots of LAC for the removal of MB ion(T = 30 °C, pH = 7, 50 mg L−1).

t 1 t = qe 2 + qt k2 qe

design parameters can be optimized by controlling the biosorption rate of the removal process because the system controls the adsorbate residence time and reactor dimension. As a result, the predicted biosorption rate is the most important factor for the biosorption system design. The kinetic models studied are Pseudo 1st order, Pseudo 2nd order and Intraparticle Diffusion. Pseudo 1st order is generally expressed as follows:

log(qe − qt ) = log qe −

k1 t 2.303

(6)

Intraparticle Diffusion equation is generally expressed as follows:

qt = kid t 1/2 + C

(7)

Where, k1 is the pseudo 1st order rate constant in min−1, qt is the adsorption capacity (the amount of pollutant absorbed at time t) in mg g−1, qe is the adsorption capacity (the amount of pollutant adsorbed at equilibrium) in mg g−1, k2 is the pseudo second order rate constant (mg L−1 min−1), Kid is the intraparticle rate constant and C is the intercept. To understand the applicability of the model, a plot of log (qeqt) vs t, t/qt vs t and Kid vs t1/2 are shown in Table 1. According to the values given in Table 1, pseudo 1st order model

(5)

Pseudo 2nd order equation is generally expressed as follows (Mittal et al., 2010a, 2010b): 145

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Table 1, the intercept value is greater than zero and it increases with increase in concentration of metal ion as compared to mass film control diffusion. The results show that the boundary layer diffusion is the controlling step.

Table 2 Adsorption Isotherm for the adsorption of Cu2+, Ni2+ and MB on Luffa Carbon. Parameters Langmuir isotherm Qm b R2 RMSE HYBRID ARE ᵡ2 Freundlich isotherm n Kf R2 RMSE HYBRID ARE ᵡ2 Temkin isotherm B1 KT R2 RMSE HYBRID ARE ᵡ2 D-R isotherm Qm β E R2 RMSE HYBRID ARE ᵡ2 Halsey isotherm nH KH R2 RMSE HYBRID ARE ᵡ2

Cu2+

Ni2+

MB

33.16 0.229 0.8554 0.006 −13.14 −10.22 8.82

23.84 0.02 0.9329 0.0038 −10.07 7.837 0.58

24.84 0.212 0.954 0.0027 −11.83 −9.20 1.31

3.00 9.78 0.96542 0.0073 −0.65 −0.65 2.10

1.489 0.919 0.950 0.0013 −7.44 −5.79 0.42

2.47 6.27 0.8827 0.0122 −3.933 −3.05 3.35

6.074 3.39 0.9233 0.362 123.06 95.7 0.124

3.953 3.00 0.8826 2.455 132.5 103.05 5.70

7.527 1.310 0.9090 0.857 60.93 47.39 1.40

25.63 4*107 1118.5 0.838 1.435*10−13 −7.67*10−14 −5.968*10−14 6.4913*10–27

8.28 6*106 409.8 0.723 4.331*10–13 −1.197*10−15 −4.192*10−15 1.089*10–28

16.26 5*107 1000 0.733 4.33*10−13 −1.197*10−15 −4.192*10−15 1.089*10–28

0.89 18.54 0.822 0.7173 4.193 14.6 2.058

0.130 1.368 0.864 0.929 −35.7 −125.07 7.19

0.616 5.06 0.833 0.064 9.639 33.73 0.024

3.6. Adsorption isotherm The distribution of adsorbate molecules within the adsorbent at equilibrium can be explained by adsorption Isotherm. To study the adsorption behaviour of adsorbent in aqueous solution, a correlation between adsorption capacity and residual concentration has been done. Several isotherm equations are available in the literature; five of them are selected for the study: Langmuir, Freundlich, Temkin, D-R and Halsey equations. The Langmuir isotherm model is explained by two ways in adsorption process: First, the adsorption process occurs at homogenous surface in the adsorbent. Secondly, maximum monolayer adsorption occurs when absorbed molecules form a saturated layer on the surface of the adsorbent. All the adsorption sites involved are energetically identical and the intermolecular forces decreases as the distance from the adsorption surface increases (Singha and Das, 2013). The Langmuir adsorption model can be represented by following equation:

qe =

1

qe = KF Cen

ΔG°(KJ/Mol K)

ΔH°(KJ/Mol)

ΔS0(KJ/Mol K)

R2

−3.80 −3.59 −3.08

−9.43

−0.018

0.6919

−0.75 −1.86 −3.02

21.6

0.0736

0.9425

−5.68 −4.95 −4.49

−15.72

−0.033

0.9887

(9)

Where, Kf and n are the constant related to adsorption capacity and intensity respectively and qe is the adsorption capacity at equilibrium (mg g−1). Temkin Isotherm model is given as

qe = B1 ln kt + B1 ln ce

2+

Cu 303 313 323 Ni2+ 303 313 323 MB 303 313 323

(8)

Where, b is the constant related to affinity of binding sites and energy of adsorption (L mg−1), Ce is the equilibrium concentration (mg L−1), qe is the absorbed metal ion (mg g−1), qm is the monolayer adsorption capacity (mg g−1), The heterogeneous surface of the adsorbent can be explained by Freundlich Isotherm using an empirical equation. The adsorption capacity of the adsorbent is related to the concentration of absorbed metal ions at equilibrium. Freundlich Isotherm model is represented by following equation

Table 3 Thermodynamic studies for the adsorption of Pb2+, Cu2+ and Ni2+ ions on Luffa Carbon. Temperature

qm bCe 1 + bCe

(10)

Where, Kt is the equilibrium binding constant (L mg−1) and B1 related to heat of adsorption, B1 = RT/b, T is the absolute temperature in Kelvin, R is the universal gas constant (8.314 J Mol K−1). The Dubinin-Radushkevich Isotherm (D-R) (Mittal et al., 2009) is more general than the Langmuir Isotherm, because it does not assume a homogenous surface or constant sorption potential.

ln qe = ln qm − β∈2

(11)

Where, qm is the theoretical saturation capacity and e is the Polanyi potential which is equal to RT ln(1+1/Ce) where R (8.314 J Mol−1 K−1) is the gas constant and T is the absolute temperature, b is a constant related to the mean free energy of adsorption per mole of the adsorbate (mol2 KJ−2). Halsey Isotherm is given as

show inapplicability in describing the adsorption process of Cu2+, Ni2+ and MB due to low regression coefficient and qecal is not equal to qeexp, whereas in case of pseudo 2nd order model as shown in Table 1, qecal=qeexp and have high regression coefficient. This proves that Cu2+, Ni2+ and MB follows pseudo 2nd order kinetic model. The intraparticle diffusion model for adsorption process is divided into three stages: the rapid surface adsorption stage, the gradual inward diffusion stage and the final equilibrium stage. The intercept value gives the idea of boundary layer thickness which means larger is the intercept greater is the boundary layer thickness. As the value given in

ln qe = [(

1 1 1 )ln kH − ( ) ] nH nH Ce

(12)

The isotherm models with their error analysis are shown in Table 2 and Fig. 6(a,b). According to the regression coefficient and error values, the Cu2+ and Ni2+ ions are best fitted by Freundlich Isotherm as shown in Fig. 6(b) and Table 2. The higher the regression value and lower ᵡ2 and RSC value, the Freundlich isotherm model is best fitted. The value 146

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Table 4 Comparative study for the adsorption capacity of various adsorbents for the removal of Cu2+, MB and Ni2+ ions. Metals

Adsorbent

Experimental condition

Qmax(mg g−1)

Reference

Cu2+

Black Carrot Residue Pleurotus Cornucopiae Watermelon Seed hull Nanofibres Graphene Oxide with Titanium Oxide L-methonine montimorrinolinate LAC Cashew nut shell Daucus carota Almond Shell Graphene Oxide Nanofibres Alkali treated pineappleresidue LAC Clay honeycomb Monoliths Poly NAN Ospheres WOX/C nanowire Purolite(SST60) Cation exchanger LAC

pH = 5, T = 293 pH = 5, T = 293 K pH = 5, T = 293 K pH = 5.5 pH = 5, T-293 K pH = 5, T = 293 pH = 6, T = 303 K pH = 5, T = 293 K pH = 5, T = 293 K pH = 6, T = 293 K pH = 8, pH = 4.5, T = 293 k pH = 4–6, T = 303 K pH = 6, T = 303 K pH = 7, T = 293 K

8.88 25.25 33.90 204.00 56.0 90.9 33.16 18.86 6.03 22.22 110.2 156.70 17.56 23.84 3

(Güzel et.al., 2008; Saleh and Gupta, 2012a) (Saravanan et al., 2015a) (Akaya and Güzel., 2013; Saleh and Gupta, 2012b) (Ding et al., 2016; Saravanan et al., 2013a) (Saravanan et al., 2013b) (Ahmad and Hassan, 2017; Saravanan et al., 2016) [Present Study] (Danis, 2010) (Güzel et al., 2008; Saleh and Gupta, 2012a) (Kiliç et al., 2013; Saravanan et al., 2015b) (Chen et al., 2016; Saravanan et al., 2014) (Ding et al., 2016; Saravanan et al., 2013a) (Rao and Khan, 2017; Sardella et al., 2015) [Present Study] (Gatica et al., 2013; Singha and Das, 2013)

pH = 7 t = 1 min pH = T = 293 K

20 1188.3 131

(Cheng et al., 2014; Shukla and Pai, 2005) (Zhang et.al., 2017; Yu et al., 2016 (Moselhy and Kamal, 2018; Zhang et al., 2017)

pH = 7, T = 303 K

24.84

[Present Study]

Ni2+

MB

Table 5 Response Surface Regression for the removal of Cu(II) ion by LAC. Source

DF

Adj SS

Adj MS

F-Value

P-Value

Model Linear x1 x2 Square x1*x1 x2*x2 2-Way Interaction x1*x2 Error Lack-of-Fit Pure Error Total

5 2 1 1 2 1 1 1 1 7 3 4 12

5098.36 2297.25 1114.26 1182.99 730.86 455.57 369.95 2070.25 2070.25 3769.45 3769.02 0.43 8867.81

1019.67 1148.62 1114.26 1182.99 365.43 455.57 369.95 2070.25 2070.25 538.49 1256.34 0.11

1.89 2.13 2.07 2.20 0.68 0.85 0.69 3.84 3.84

0.214 0.189 0.193 0.182 0.538 0.388 0.435 0.091 0.091

11632.76

0.000

Fig. 5. Effect of pH for the adsorption of Cu (II), Ni (II) and MB on Luffa Actangula Carbon (T = 30 °C, 120 min, 50 mg L−1). Table 6 Response Surface Regression of MB by LAC. Source

DF

Adj SS

Adj MS

F-Value

P-Value

Model Linear x1 x2 Square x1*x1 x2*x2 2-Way Interaction x1*x2 Error Lack-of-Fit Pure Error Total

5 2 1 1 2 1 1 1 1 7 3 4 12

3456.72 1624.15 742.47 881.68 496.67 282.27 279.18 1335.90 1335.90 2762.66 2758.40 4.26 6219.38

691.34 812.07 742.47 881.68 248.34 282.27 279.18 1335.90 1335.90 394.67 919.47 1.07

1.75 2.06 1.88 2.23 0.63 0.72 0.71 3.38 3.38

0.241 0.198 0.213 0.179 0.561 0.426 0.428 0.108 0.108

862.86

0.000

Fig. 6. Adsorption isotherm for the removal of Cu (II), Ni(II) and MB onto LAC(a) Langmuir (b) Freundlich.

of n is greater than unity which corresponds to the distribution of bonded ions on sorbent surface which is an indication of constant sorption mechanism where sorbate penetrate sorbent and show good adsorption. In case of MB, it is best fitted by Langmuir Isotherm showing monolayer coverage according to R2 and ᵡ2 value as shown in Fig. 6(a) and Table 2.

3.7. Adsorption thermodynamics The effect of temperature for the adsorption of Cu2+, Ni2+ and MB were studied in the temperature range of 303–323 K. The parameters such as change entropy change (ΔS°), enthalpy change (ΔH°) and Gibb free energy (ΔG°) were estimated using the following equation:

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kc =

cs ce

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(13)

ΔG 0 = −RT ln kc

(14)

where, Kc is the equilibrium constant, Cs is the solid phase concentration at equilibrium (mg L−1), Ce is the equilibrium concentration in solution (mg L−1).

log Kc =

ΔS 0 ΔH 0 − 2.303R 2.303RT

(15)

By using Van’t Hoff equation, the value of ΔH° and ΔS° can be calculated. The values of ΔH° and ΔS° were obtained from the slope and the intercept of the plot log Kc vs. 1/T and presented in Table 3. The values of ΔG° are negative with decreasing trend for the adsorption of Cu2+ and MB ion showing spontaneity with decreasing trend in increase in temperature and with increasing trend in case of Ni2+ onto LAC shows the reaction is spontaneous and thermodynamically favourable at high temperature. The negative value of ΔH° and ΔS° in case of Cu2+ and MB ion indicate the Exothermic nature and decrease randomness at adsorbate -adsorbent surface whereas in case of Ni2+ the value of ΔH° and ΔS° are positive in nature indicating endothermic in nature and the randomness at solid/liquid solution interface. 3.8. Comparative study of adsorbent To study the feasibility and comparability of the adsorbent with other non-conventional adsorbent in respect of adsorption capacity, a comparative data has been reported in Table 4. It is evident from the table that LAC has got the highest monolayer adsorption capacity for Cu2+ (33.16 mg g−1), Ni2+ (23.84 mg g−1) and MB (24.84 mg g−1) among all the adsorbents. 4. Conclusion The results of adsorption investigate that the LAC is a suitable and promising alternative adsorbent for the removal of Cu2+, Ni2+ and MB from the industrial effluent. Various parameters such as equilibrium time, pH and initial metal ion concentration were studied for the removal of Cu2+, Ni2+ and MB. LAC shows maximum monolayer adsorption capacity of 33.16 mg g−1 > > 24.84 > > 23.84 in order of Cu2+ > > MB > > Ni2+. The operating variableswas adjusted using the response surface methodology showing the yield of 95% and 80% in case of Cu2+ and MB. It was found that adsorption data for Cu2+ and Ni2+ was best fitted by Freundlich Isotherm demonstrating heterogeneous adsorption and for MB it was best fitted by Langmuir Isotherm demonstrating monolayer adsorption. The Kinetic data was best fitted by Pseudo 2nd order kinetics. The Thermodynamic studies reveals that adsorption of Cu2+ and MB is exothermic in nature whereas for Ni2+ ion it is endothermic in nature. The desorption results demonstrate that LAC could be desorbed upto 90% by 0.1 M HCl. The results demonstrate that LAC is an effective and promising adsorbent for the removal of pollutant. Acknowledgements The Financial assistance to complete the work has been provided to the author by UP-CST (Uttar Pradesh-council of science and technology), Uttar Pradesh, India under the project no: D/352 as Young scientist. I would also be thankful to the editor in chief Prof. Prosun Bhattacharya of Groundwater for sustainable development for helping in the correction as in the figure in Graphical abstract. References Ahmaruzzaman, M., Gupta, V.K., 2011. Rice husk and its ash as low-cost adsorbents in water and wastewater treatment. Ind. Eng. Chem. Res. 50, 13589–13613.

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