Removal of toxic zinc from water/wastewater using eucalyptus seeds activated carbon: non‐linear regression analysis

Abstract

In the present study, a novel activated carbon was prepared from low‐cost eucalyptus seeds, which was utilised for the effectively removal of toxic zinc from the water/wastewater. The prepared adsorbent was studied by Fourier transform infrared spectroscopy and scanning electron microscopic characterisation studies. Adsorption process was experimentally performed for optimising the influencing factors such as adsorbent dosage, solution pH, contact time, initial zinc concentration, and temperature for the maximum removal of zinc from aqueous solution. Adsorption isotherm of zinc removal was ensued Freundlich model, and the kinetic model ensued pseudo‐second order model. Langmuir monolayer adsorption capacity of the adsorbent for zinc removal was evaluated as 80.37 mg/g. The results of the thermodynamic studies suggested that the adsorption process was exothermic, thermodynamically feasible and impulsive process. Finally, a batch adsorber was planned to remove zinc from known volume and known concentration of wastewater using best obeyed model such as Freundlich. The experimental details showed the newly prepared material can be effectively utilised as a cheap material for the adsorption of toxic metal ions from the contaminated water.

1 Introduction

Owing to recent industrialisation coupled with improper waste disposal methods, large amounts of heavy metals have been discharged into the environment. Some examples of heavy metals are copper, chromium, cadmium, cobalt, zinc, lead, nickel, arsenic and iron [1, 2, 3]. Some of the heavy metals are required by human beings in small amounts albeit most of them are harmful even at low concentrations and toxic at higher concentrations [4, 5, 6]. Heavy metals specifically are more dangerous owing to their non‐biodegradability. A side effect of non‐biodegradability is bioaccumulation of toxic heavy metals in living organisms which causes detrimental effects [7, 8]. Prominent sources of heavy metals are battery manufacturing facilities, mining facilities, metallurgy, transport, dying facilities, paint industry, power and construction industries [9, 10, 11, 12]. Added to the conventional use of zinc for galvanising and alloying it is also used to produce cotton fabrics of antimicrobial and UV protecting properties [13]. Zinc, although required in small amounts for healthy function of organisms, at higher concentrations may cause hazardous effects in organisms [14, 15, 16, 17]. The maximum acceptable limit of zinc in drinking water has been fixed at 5 mgl⁻¹ [18]. Therefore, the effective removal of zinc from aquatic environment is highly crucial.

A plethora of techniques for the removal of toxic metal ions from water/wastewater have been developed namely evaporation, chemical precipitation, filtration, ion exchange, solvent extraction, electrochemical treatment, reverse osmosis, and membrane separation processes [19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30]. Since all of the above mentioned require high initial investment or have high running costs which supersedes the importance of treating waste water, In comparison adsorption seems to fare well against the others. Furthermore these methods prove to be either useless or too expensive to operate at low metal concentrations [31, 32, 33, 34]. Activated carbon is arguably the best adsorbent for the process however due to high costs the process has not seen mass scale acceptance in industries. Until recently researchers were trying to improve existing adsorbents namely iron oxide‐coated sand [35], a porous cellulose carrier modified with polyethyleneimine [36], iron‐coated granular activated carbon [37] and modified chitosan [38] however none of them improved the cost factor. Hence scientists around the world are looking for low cost alternatives to activated carbon and the answer seems to be agricultural wastes. Use of agricultural wastes as adsorbents improves the economic feasibility of the adsorption process. Consequently scientists have ventured into various low cost alternatives namely peat, orange peel, cork biomass, lignocellulosic substrate, coir, banana peel, Botrytis cinerea, Azadirachta indica bark, olive mill residue, rice bran, activated sludge, algal waste, extracellular polymeric substances, lignin, bagasse fly ash, physic seed hull, algae, barely straw, etc. [39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49]. Low‐priced and abundant accessibility of agricultural waste eliminates the need for regeneration processes.

Almost no significant improvements have been made for the exploitation of eucalyptus seeds as an adsorbent. There is hardly any literature available, particularly with regard to the utilisation of eucalyptus seeds as an adsorbent either directly or in its modified form for the removal of zinc from water/wastewater. In the present studies, eucalyptus seeds were chosen as a raw material for the synthesis of activated carbon and which have been tested for the removal of zinc from the wastewater. The adsorption influencing parameters such as adsorbent dosage, solution pH, contact time, initial zinc concentration, and temperature were optimised in batch mode operations. The adsorption isotherm data was fitted with the different well‐known adsorption isotherm models to predict the adsorption process. In addition, adsorption kinetic data was tested with the different kinetic and mechanism models. Thermodynamic studies were also carried out to explain the adsorption of zinc onto adsorbent. The best obeyed isotherm model was used to design the batch adsorption system. Finally, regeneration ability of the adsorbent was also tested from desorption studies using the hydrochloric acid solution.

2 Experimental

2.1 Adsorbent preparation

Eucalyptus seeds were collected from Nilgiri hills, Tamil Nadu, India. Woody fruit covered Eucalyptus seeds were obtained from Nilgiri hills. Dust and other insoluble impurities were removed from these seeds by rinsing with double distilled water and the resulting reddish brown oil was obtained from wash water. Then the washed seeds were further dried and finely ground. This material was abbreviated as raw Eucalyptus seeds (RES). The adsorbent material was prepared by treating RES with concentrated H₂ SO₄ in the weight proportion of 1:2. Consequently the mixture was placed in a gloomy environment for about 24 hours. The surfeit acid was recovered and the seeds were washed till the supernatant reached a pH of 7.0. The seeds were then dried in a hot air oven at 150°C for about 3 hours and the dried seeds ground to a final sieve size of 0.354 mm and stored in an air tight container. The prepared material is called Eucalyptus seeds activated carbon (ESAC). This prepared activated carbon is utilised as an effective adsorbent for the sequestration of zinc from aquatic environment.

2.2 Adsorbate preparation

Analytical grade chemicals were used for the present study. ZnSO₄. 7H₂ O salt (Merck Chemicals, India) was accurately weighed and liquefying in water to yield a desired solution of 100 mgl⁻¹. The required zinc concentrations were obtained by reducing the stock solution concentration with double distilled water. The zinc concentration in the solution was analysed with atomic adsorption spectrophotometer (AAS, SL 176, Elico Company, India). pH meter (LI 617, Elico Company, India) was used to measure the pH of the test solutions.

2.3 Batch adsorption studies

A 100 ml test sample of known zinc concentration was kept in 100 ml conical flasks for the adsorption experimental study. The required pH was attained by adding drops of 0.1 N hydrochloric acid or 0.1 N sodium hydroxide solutions. Known amount of adsorbent was taken into the available flasks and the whole setup was held in a temperature controlled shaking incubator. This orbital incubation shaker was operating at 180 rpm. On reaching desired contact time, the conical flasks were taken out and the solution was centrifuged. The supernatants were collected and the zinc concentration was measured using AAS. The influencing factors which include adsorbent dosage, solution pH, contact time, initial zinc concentration, and temperature were varied and their effects studied. The removal of zinc from the test sample was arrived at using the following equation

$$\mathrm{Removal}\mathrm{of}\mathrm{zinc}\mathrm{from}\mathrm{wastewater}=\frac{C_o-C_{\mathrm{e}}}{C_o}\times 100$$ (1)

where C_o is initial zinc concentration (mg/l) and C _e is equilibrium concentration in solution (mg/l).

Adsorption equilibrium experiments were studied by varying the initial zinc concentrations from 20 to 100 mgl⁻¹ at optimum conditions. Once equilibrium time was reached, the adsorption mixture was centrifuged and the supernatants were examined for the zinc ion concentration using AAS. The equilibrium adsorption capacity, q _e (mg g⁻¹), is given by the equation

$$q_{\mathrm{e}}=\frac{(C_o-C_{\mathrm{e}})V}{m}$$ (2)

where, C_o is initial zinc concentration in solution (mgl⁻¹), C _e is final zinc concentration in solution (mgl⁻¹), V is volume of wastewater (L) and m is mass of ESAC (g). Adsorption equilibrium data was tested with Langmuir, Freundlich and Dubinin–Radushkevich models. A discontinuous design system for zinc removal was planned with best obeyed isotherm model.

Kinetic studies for adsorption process was conducted using 0.1 gram of adsorbent in a test sample of initial zinc concentrations ranging from 20 to 100 mgl⁻¹ in a sets of conical flasks at a constant temperature of 30°C and at a constant pH of 5.0 in a temperature controlled shaking incubator. At predestined time, the adsorbent–adsorbate mixtures were collected and this mixture was centrifuged. The zinc concentration in the supernatant was analysed with AAS. The adsorption capacity at preset time t, q_t (mg g⁻¹), is given by the equation

$$q_t=\frac{(C_o-C_t)V}{m}$$ (3)

where, C_t is zinc concentration in solution at time t (mgl⁻¹). Kinetics data was fitted into pseudo‐first order, pseudo‐second order and Elovich models. The mechanism of adsorption process was found out by fitting the kinetics data into two adsorption models namely intraparticle diffusion and Boyd kinetic models.

Thermodynamic experiments were conducted for test samples of diverse initial zinc concentrations ranging from 20 to 100 mgl⁻¹, at a constant pH of 5.0 in the ESAC dose of 0.1 g of adsorbent for an equilibrium time of 10 min (optimum conditions) in a temperature controlled shaking incubator. The temperature was varied from 30–60°C. After attainment of equilibrium time, the adsorption mixtures were withdrawn from the shaker and then it was centrifuged. The supernatant was analysed for zinc ions concentration using AAS. The data was then fixed to thermodynamic equations and thermodynamic quantities estimated.

3 Results and discussion

3.1 Adsorbent characterisation studies

The adsorbents such as RES and ESAC were analysed by Fourier transform infrared (FTIR) and scanning electron microscopic (SEM) studies to identify the surface functional grounds and surface morphology, respectively. The corresponding images were shown in Figs. 1 and 2, respectively. The importance of this characterisation is to check whether the proper surface modification was done in the ESAC images because of the effects of concentrated sulphuric acid on it. More porous surface was available in the ESAC image as compared with the RES image. Similarly much functional groups were available on the ESAC than the RES. These characteristics clearly showed that the ESAC has adequate adsorption competency for zinc removal from wastewater.

Fig. 1.

FTIR spectrum of before and after adsorption

Fig. 2.

SEM image of RES and ESAC at different magnifications

FTIR analysis of RES, ESAC and ESAC‐zinc were shown in Fig. 1. The FTIR study was carried out by using the total reflectance in the range between 450–4000 cm⁻¹. In Fig. 1 a, the peak observed at 3317.38 cm⁻¹ was assigned to O‐H stretching vibration of water and alcoholic groups. The peaks at 2924.44 and 2853.86 cm⁻¹ are due to the presence of –CH₂ – vibrations. The peaks at 1608.09 and 1451.51 cm⁻¹ was assigned to C=C and C–H groups on the surface of RES. The peak at 1316.56 is due to the presence of –CH₂ – bending vibration. The peak at 1225.47 cm⁻¹ represents the –COO– vibration. A long peak observed at 1025.76 cm⁻¹ is because of C–H group. Fig. 1 b shows that the peak at 3221.95 cm⁻¹ was corresponding to –OH group. The peak at 1508.48 cm⁻¹ is the presence of –C=C–C– aromatic ring stretch. The intense broad band was observed at 1156.14 and 1035.90 cm⁻¹ confirmed the stretching pulsation of C–H bonds. Fig. 1 c shows that the peaks at 3197.92 cm⁻¹ was corresponding to the stretching vibration of O–H. The intense broad band at 1156.14 and 1035.90 cm⁻¹ indicates that the presence C–H groups. There was the disappearance and new peaks were arrived in Fig. 1 c. The results showed the enough chemical functional activities were available on the surface of the ESAC for zinc adsorption. Fig. 1 c indicated the zinc adsorption was sturdily happened on the surface of the ESAC. This was evidenced by the disappearance of peaks, shifting of peaks and arrival of new peaks in Fig. 1 c when it was compared with Fig. 1 b. This finally indicates that the required functional groups were available with ESAC for the zinc removal.

SEM studies of RES and ESAC were shown in Fig. 2. Analysis of these SEM images revealed the formation pores in the ESAC during the activation and the porous network structures when it was compared with the RES. The porous morphology in the ESAC image may be due to the dehydration of water molecules during its activation procedures. The size and shapes of the pores are irregular and interconnected. The wide distribution of pores in the ESAC indicated the water uptake throughout the material and the presence of void volume in it. The unequal pore sizes in the ESAC may be of cross linking in nature. The porous structures were appeared to be more compact in ESAC than the RES. These pores may be the areas provided for the penetration of water molecules and the interaction sites were available to form secondary bonds with zinc ions.

3.2 Parameter optimisation

Zinc removal from contaminated water by using ESAC was greatly controlled by the pH of the test sample because pH is an appreciable factor. The influence of pH on zinc ions adsorption has been elucidated in Fig. 3 a. The zinc ions adsorption at low pH level was found to be very low. Further when pH was increased from 2.0, the zinc adsorption was raised rapidly and maximum removal was attained at the pH of 5.0, beyond that the adsorption was reduced gradually (pH > 5.0). The maximum removal of 99.87% was attained in the pH of 5.0 at 30°C. Therefore pH = 5.0 was taken as finest pH level for supplementary studies. The reason for the above mentioned phenomenon may be explained by two theories. At less pH values, the presence of hydronium ions contending with zinc ions to the surface of the adsorbent which reduced the adsorbent capacity for zinc removal. Conversely for high pH values, zinc ions reacted with hydroxyl ions to yield zinc precipitates, which ultimately decreased the quantity of free zinc ions available for adsorption and thus overall adsorptive capacity dropped. The charge density of the adsorbent surface (σ _o ) was evaluated by the titration of potentiometric analysis. The meeting point of surface charge density on ESAC with pH was found to be 4.3. This implies that the adsorbent surface will be positively charged below 4.3 (pH < pH_pzc) and the surface becomes negatively charged beyond pH of 4.3 (pH > pH_pzc). Thus at lower values of pH, H⁺ ions get adsorbed rather than zinc ions and at higher values of pH, metal hydroxide complexes are formed hampering the adsorption process.

Fig. 3.

Parameter optimisation for zinc removal by ESAC

Adsorbent dose plays a significant role in the process of adsorption. Adsorption experiments were conducted for adsorbent dose in the range of 0.02–0.16 g at pH = 5.0 and the experimental data represented in Fig. 3 b. It is clear from Fig. 3 b that the adsorption increases rapidly up to a value of 0.1 g and remains fairly constant beyond 0.1 g of adsorbent. The reason for these results is the number of active sites is increased when ESAC dose is increased. The increase in adsorptive capacity was ascribed to the raise in the number of active sites present initially. However on further addition, the zinc adsorption remains fairly constant beyond 0.1 g this is due to the relatively low equilibrium concentration, low driving force and the available active sites gradually decreased. Since the removal of 99.48% was obtained at optimum conditions, adsorbent dose of 0.1 g was used as optimum adsorbent dose henceforth.

The experiment was carried out by varying contact time from 2 to 16 min for an initial zinc concentrations ranging from 20 to 100 mgl⁻¹ at a constant pH of 5.0 with 0.1 g of ESAC. The results were represented in Fig. 3 c. It is notiable from Fig. 3 c that the zinc adsorption raised rapidly with increasing contact time up to 10 min and additional raise in time has no appreciable consequence on zinc adsorption. The reason may be that initially a large surface area provides abundant surface active sites for zinc adsorption whereas as time passes ESAC surface may have been completely exhausted resulting in no further adsorption process. Since beyond 10 min no appreciable increase in % removal was observed for all zinc concentrations, the equilibrium time was fixed as 10 min for further experiments.

The temperature influence on the zinc adsorption was deliberated by varying temperature from 303 to 333 K for the different initial zinc concentrations ranging from 20 to 100 mgl⁻¹ at a constant pH of 5.0, 10 min of equilibrium time, 0.1 g of ESAC. The result was shown in Fig. 3 d. It was clear that zinc adsorption was decreased with raise in temperature. The results indicating that adsorption process may be exothermic. Decline in the exterior activity of the adsorbent may be attributed for the reduction in removal. The maximum percentage removal was obtained at 303 K for all initial concentration of zinc ions hence 303 K was regarded as the optimum temperature for the process.

3.3 Adsorption isotherm

The consequence of initial concentration data was chosen to check the ability of different adsorption isotherm models. The zinc concentration influence on the removal of zinc was examined by varying the zinc concentration from 20 to 100 mgl⁻¹ at a constant pH of 5.0 and equilibrium time of 10 min with 0.1 g of ESAC. The results of the experimental studies were shown in Fig. 4 a. The figure clearly shows the zinc adsorption decreases as initial zinc concentration increases beyond 20 mgl⁻¹. This may be due to the inadequate availability of active sites of the adsorbent at higher zinc ions concentration.

Fig. 4.

Equilibrium model tested results for the adsorption of zinc onto ESAC

Isotherms play an integral part in predictive modelling procedures which are used for the construction of discontinuous system. In this study, the adsorption equilibrium data was fitted into various isotherms models namely, Langmuir [50], Freundlich [51] and Dubinin–Radushkevich [52]. These models are mathematically represented as follows:

The Langmuir model is:

$$q_{\mathrm{e}}=\frac{q_{\mathrm{m}}{K}_{\mathrm{L}}{C}_{\mathrm{e}}}{1+K_{\mathrm{L}}{C}_{\mathrm{e}}}$$ (4)

The Freundlich model is

$$q_{\mathrm{e}}=K_{\mathrm{F}}{C}_{\mathrm{e}}^{1/n}$$ (5)

The Dubinin–Radushkevich model is

$$q_{\mathrm{e}}=q_{\mathrm{m},\mathrm{D}}\exp \left(-\beta {\left(RT\ln \left(1+\frac{1}{C_{\mathrm{e}}}\right)\right)}^2\right)$$ (6)

Mean free energy, E is

$$E=\frac{1}{\sqrt{2\beta }}$$ (7)

where q _m is the Langmuir monolayer adsorption capacity (mg g⁻¹), K _L is the Langmuir constant (l mg⁻¹), K _F is the Freundlich constant [(mg g⁻¹) (l mg⁻¹) ^(1/n)] sometimes called Freundlich adsorption capacity, n is Freundlich exponent constant, q _m,D is Dubinin–Radushkevich monolayer adsorption capacity (mg g⁻¹), β is adsorption energy constant, E is the mean free energy (kJ mol⁻¹) and T is temperature of adsorption system maintained (K). The initial zinc ion concentration was varied from 20 to 100 mgl⁻¹. Adsorption equilibrium data was fitted with the different isotherm equations and predicted images were presented in Fig. 4 b. The calculated adsorption isotherm parameters, determination of correlation coefficient (R ²) values and error values were listed in Table 1. The best fitted adsorption models can be identified by either R ² values or error functions. Freundlich model (R ² = 0.9973) provide the finest result for the adsorption system as compared with the Langmuir (R ² = 0.9153) and Dubinin–Radushkevich models (R ² = 0.8444). This sheds light on the character of adsorption process; here it is described by multilayer adsorption process. The value of n was found to be greater than one which indicates the zinc adsorption onto ESAC was physical adsorption.

Table 1.

Results on zinc adsorption onto ESAC isotherms: parameters, correlation coefficient values and SSE, RMSE values for the adsorption of Zn(II) ions onto the ESAC

Equilibrium models	Parameters
Langmuir	q m, mg g−1	80.37
	K L, lmg−1	1.25
	R 2	0.9153
	SSE	695.1
	RMSE	8.788
Freundlich	K F, (mg g−1)(lmg−1)(1/n))	42.2
	n	3.839
	R 2	0.9973
	SSE	22.34
	RMSE	1.575
Dubinin–Radushkevich	q m,D, mg g−1	70.07
	β	1.304 × 10−4
	R 2	0.8444
	SSE	1276
	RMSE	11.91

3.4 Studies on kinetic and mechanism for zinc adsorption

Kinetic results for the adsorption of zinc onto ESAC were shown in Fig. 5. The removal of zinc shows a rapid increase in the initial stage because the ESAC consists of more number of empty and high affinity active sites in it which permits to provide the less resistance during the primary adsorption stage. Further increase in contact time indicates adsorption rate slowed down and finally it was reached adsorption equilibrium. Kinetics for the adsorption of zinc onto ESAC was discussed with pseudo‐first order [53], pseudo‐second order [54] and Elovich kinetic models [55].

Fig. 5.

Kinetic model tested results for the adsorption of zinc onto ESAC

The pseudo‐first order is

$$q_t=q_{\mathrm{e}}(1-\exp (-k_{1}t))$$ (8)

Pseudo‐second order model is

$$q_t=\frac{q_{\mathrm{e}}^2{k}_{2}t}{1+q_{\mathrm{e}}{k}_{2}t}$$ (9)

The Elovich model is

$$q_t=(1+{\beta }_E)\ln (1+{\alpha }_E{\beta }_{E}t)$$ (10)

where k ₁ is pseudo‐first order constant (min⁻¹), k ₂ is pseudo‐second order constant (g mg⁻¹ min⁻¹), α_E is primary rate of adsorption (mg g⁻¹ min⁻¹), and β_E is desorption constant (g mg⁻¹). The kinetic parameters, R ², sum of squared error (SSE) and root mean squared error (RMSE) values were evaluated by fitted with kinetic data to the above stated kinetic models (Table 2). R ² values and error functions can be used to discover the finest adsorption kinetic model for the elimination of zinc from wastewater. Highest R ² with low error values were observed for pseudo‐second order model when compared with other reported models. The deliberated q _e, cal for pseudo‐second order model was found to be roughly equal to q _e, exp values, which goes on to prove that the pseudo‐second order model best obeyed the kinetic data. The results indicate zinc adsorption onto ESAC followed pseudo‐second order kinetics. The kinetic model gives a fairly good understanding of the adsorption process however, it fails to calculate the mechanism involved in removal of zinc ions from wastewater by the ESAC. Hence to understand the mechanism of adsorption process it is important to calculate the rate proscribed step in the adsorption process. The adsorption kinetic data were pertained to the intraparticle diffusion [56] and Boyd kinetic [57] models and the results were shown in Fig. 6.

Table 2.

Results on zinc adsorption onto ESAC kinetics: parameters, correlation coefficient values and SSE, RMSE values for the adsorption of Zn(II) ions onto the ESAC

Kinetic models	Parameters	Zinc concentration, mgl−1
		20	40	60	80	100
Pseudo‐first order equation	k 1, min−1	0.6007	0.5456	0.5398	0.6564	0.6255
	q e, cal, mg g−1	19.68	38.69	55.36	70.35	82.39
	R 2	0.9908	0.9874	0.9916	0.983	0.9636
	SSE	3.893	21.68	28.94	90.03	263
	RMSE	0.5273	1.245	1.438	2.536	4.334
Pseudo‐second order equation	k 2, g mg−1 min−1	0.04297	0.01866	0.01307	0.01345	0.01096
	q e, cal, mg g−1	21.67	43.04	61.53	77.05	90.41
	q e, exp, mg g−1	20.15	39.32	56.68	72.19	85.58
	R 2	0.9965	0.9933	0.9934	0.9968	0.9933
	SSE	1.465	11.57	22.74	17.14	48.53
	RMSE	0.3235	0.9091	1.275	1.107	1.862
Elovich kinetic equation	α, mg g−1 min−1	124.4	13.21	8.261	18.96	12.38
	β, g mg−1	0.3679	1.948	3.196	3.615	4.559
	R 2	0.9681	0.948	0.9615	0.9747	0.9857
	SSE	13.48	89.39	133.1	133.8	103.2
	RMSE	0.9814	2.527	3.083	3.092	2.745

Fig. 6.

Mechanism model tested results for zinc adsorption onto ESAC

The adsorption mechanism was best explained with intraparticle diffusion model [56] which is generally prohibited in the batch process of adsorption. This model is

$$q_t=k_p{t}^{1/2}+C$$ (11)

where k_p is constant of intraparticle diffusion (mg g⁻¹ min^−0.5) and C is thickness of liquid film. By applying kinetic data in (11), the model values and R ² are evaluated and the kinetic parameters listed in Table 3. Owing to changeable extents of adsorption process in primary and final stages, dual nature is observed in the adsorption of zinc onto ESAC. During first periods, the zinc removal was owed to the frontier layer diffusion but in the later periods the zinc removal was due to particle diffusion. The diffusion plot was linear but it does not pass through the origin. This indicates the particle diffusion is not only the step to control the process but other process may be operating simultaneously. In general, adsorption step may be assumed as rapid and this step considered as insignificant, however, this is important to discriminate between film and particle diffusion for the design point of view. Boyd model [57] was applied to identify the dawdling step in the zinc removal by ESAC.

Table 3.

Results on zinc adsorption onto ESAC mechanism: parameters, correlation coefficient values and SSE, RMSE values for the adsorption of Zn(II) ions onto the ESAC

Models	Mechanism parameters	Zinc concentration, mgl−1
		20	40	60	80	100
intraparticle diffusion model	kp , mg g−1 min−1/2	3.668	7.411	10.63	12.91	15.43
	C, mg g−1	7.276	13.34	19	27.12	30.7
	R 2	0.3857	0.4471	0.7427	0.7149	0.7476
	SSE	259.5	949.9	888.6	1510	1825
	RMSE	4.159	7.958	7.967	10.38	11.42
Boyd model	B	0.3792	0.3563	0.3444	0.4008	0.3582
	q e, cal, mg g−1	19.66	38.49	55.23	70.5	83.18
	R 2	0.8501	0.8405	0.8473	0.8471	0.8457
	SSE	63.3	274	527.4	809.6	1115
	RMSE	2.126	4.424	0.6138	7.604	8.925

Boyd model is

$$F=\frac{q_t}{q_{\mathrm{e}}}=1-\frac{6}{{\pi }^2}\exp (-Bt)$$ (12)

The above equation may be rewritten as

$$q_t=q_{\mathrm{e}}(1-0.6085\exp (-Bt))$$ (13)

where F is the portion of zinc adsorbed at a time t, and Bt is geometrical function of F. The line does not pass through the starting point which specifies that the zinc adsorption onto the ESAC was mostly due to film diffusion. Hence, zinc removal is affected by both internal and external diffusion.

3.5 Thermodynamic study

The thermodynamic parameters such as enthalpy (ΔH ^o ), entropy (ΔS ^o ) and free energy (ΔG ^o ) were calculated by using the following representations

$$\mathrm{\Delta }{G}^o=-RT\ln (K_c)$$ (14)

$$\log K_c=\frac{\mathrm{\Delta }{S}^o}{2.303R}=\frac{\mathrm{\Delta }{H}^o}{2.303RT}$$ (15)

where K _c is the coefficient of distribution which is the ratio of zinc concentration on solid phase to zinc concentration in liquid phase at equilibrium, R is universal gas constant and T is adsorption system temperature. Fig. 7 showed the data from the temperature influencing adsorption studies was used to the check thermodynamic equations. Furthermore, the associated thermodynamic variables namely ΔG^o , ΔH^o and ΔS^o were estimated and it was tabulated (Table 4). The decrease in ΔG^o values by raising the temperature values indicates that adsorption process is physical type. The negative value of ΔH^o and ΔS^o states that the zinc adsorption onto ESAC was exothermic and enthalpy driven mechanism, respectively. The values of ΔG^o listed in Table 4 show that the process of zinc adsorption onto ESAC was spontaneous and feasible.

Fig. 7.

Thermodynamic studies for the adsorption of zinc onto ESAC

Table 4.

Results of the thermodynamic studies for the adsorption of zinc onto ESAC

Initial zinc concentration, mgl−1	ΔHo , kJ mol−1	ΔSo , Jmol−1 K−1	ΔGo , kJ mol−1
			30°C	40°C	50°C	60°C
20	−101.633	−248.71	−16.737	−10.481	−9.138	−7.905
40	−36.399	−86.793	−10.117	−9.183	−8.458	−7.467
60	−20.334	−43.329	−7.149	−6.820	−6.433	−5.822
80	−13.510	−25.829	−5.603	−5.526	−5.203	−4.837
100	−12.419	−26.116	−4.486	−4.272	−3.990	−3.706
Initial zinc concentration, mgl−1			Kc values
			30°C	40°C	50°C	60°C
20			768.231	56.143	30.056	17.382
40			55.497	34.088	23.331	14.823
60			17.083	13.749	10.976	8.191
80			9.246	8.363	6.943	5.739
100			5.935	5.165	4.420	3.815

3.6 Design of a discontinuous system

A discontinuous system was designed to calculate the amount of ESAC required to treat known concentration of zinc with known volume of zinc solution. This can be done based on the best obeyed isotherm model (Freundlich). A schematic representation of a discontinuous system was represented in Fig. 8 a. This system was used to decrease the zinc concentration from initial level (C_o ) to final level (C ₁) for a known volume of zinc solution (V) with ESAC amount (M). Moreover, the adsorption capacity of ESAC was changed from initial adsorption capacity (q_o ) to final adsorption capacity (q ₁).

Fig. 8.

Design results of the discontinuous system

A zinc balance over the schematic representation is given as

$$V(C_o-C_1)=M(q_1-q_o)=M{q}_1$$ (16)

At equilibrium conditions C ₁ = C_e and q ₁ = q_e .

The adsorption isotherm study indicates Freundlich model best obeyed the equilibrium data. Hence Freundlich equation was applied for the discontinuous system design.

The above (16) is rearranged to give

$$M=\frac{(C_o-C_{\mathrm{e}})}{q_{\mathrm{e}}}V=\frac{(C_0-C_{\mathrm{e}})}{K_{\mathrm{F}}{C}_{\mathrm{e}}^{1/n}}V$$ (17)

Using (17), a plot of M vs V for initial zinc concentration of 20 mgl⁻¹ for different removal percentage for volume of zinc solution varying from 1.0 to 10 l was represented in Fig. 8 b. This figure indicates that the quantity of ESAC was required to treat the known zinc concentration with required volume.

3.7 Desorption studies

The regenerative and reuse of the adsorbent are the important factor in the point of cost effective.

Desorption study was done by using 0.2 M HCl solution. The experiment was carried out to verify the possible reuse of ESAC (Figure not shown). These experiments followed the electrostatic interaction mechanism and the bounds were corrupted by HCl. The use of 0.2 mol/l was suitable for the zinc ions desorption process from the used ESAC. 30 min of contact time is adequate to regenerate the used ESAC. The results demonstrate that the desorption process efficiency in each cycle was determined and the results illustrated that after the fifth cycle, the adsorption capacity was reduced. Finally the regeneration experiments in this study designate that ESAC can be employed as a proficient adsorbent for wastewater treatment.

4 Conclusion

In the present study, ESAC was profitably used for the elimination of zinc from the wastewater. FTIR analysis showed the sufficient functional were available on the adsorbent surface for the sequestration of zinc. Thermodynamic study of the process proved the adsorption process to be exothermic and spontaneous and thermodynamic parameters were calculated. The equilibrium data obeyed the isotherm model as: Freundlich > Langmuir > Dubinin–Radushkevich with respect to its corresponding R ² and error values. The pseudo‐second order model best obeyed the kinetic data for zinc adsorption. Further the mechanism of adsorption was limited by both external and internal diffusion. In addition, dosage of ESAC was required to eliminate the zinc from aquatic environment by constructing a discontinuous system. It can be concluded that ESAC can able to act as a better adsorbent for the elimination of toxic zinc such as heavy metals from water/waste water.