The adsorptive removal of Malachite Green (MG) by a novel biochar namely Cassava Rind Carbon (CRC) was studied in a batch system. Moreover, Box-Behnken Response Surface Methodology was used to optimize operating conditions of the adsorption process. Characterization was done by Thermo Gravimetric Analysis (TGA), Attenuated Total Reflectance Fourier Transform Infra-Red Spectroscopy (ATR/FTIR), Brunauer–Emmett–Teller (BET) surface area, Scanning Electron Microscopy (SEM), X-Ray Diffraction (XRD) and pH zero charge point (pHZCP). The pseudo-second-order model and Langmuir model provided the best fit for kinetic and isotherm, respectively. The maximum capacity of dye adsorbed was 932.98 mg/g at 25 °C. The influence of temperature, the mass of adsorbent and the concentration of dye was studied. The optimal amount of adsorbed MG was 1,363.58 mg/g corresponding to 50 °C, 5 mg of CRC and 150 mg/L of dye. According to the high performance exhibited by CRC in this study, Manihot esculenta Crantz waste can be used as a better and low-cost biomass for wastewater decolourization.

INTRODUCTION

Almost 700,000 tons of dyes are produced worldwide each year. About half comes from the textile industry. Among the 100,000 dyes available commercially, 70% are azoic dyes on weight basis (Singh & Arora 2011). Unfortunately, at least 10% of those synthetics dyes are released into the environment. They are one of the most hazardous chemicals found in industrial effluents, so treatment is mandatory. They can reduce light penetration, precluding the photosynthesis of aqueous flora (Chequer et al. 2013). In addition to its application in the silk, wood, cotton, leather, paper, and acrylic industries, Malachite Green (MG) is extensively used in the aquaculture industry worldwide as a biocide to control external fungal and protozoan infections of fish. Consequently, carcinogenic and mutagenic effects on humans may occur if this dye enters into the food chain (Rao 1995).

Different methods to remove dye such as adsorption on various sorbents (layered double hydroxides (El Hassani et al. 2017), magnetic biochar (Zhang et al. 2016), etc.), catalytic/photocatalytic degradation (Zheng et al. 2010); (Khezami et al. 2016) and microbiological decolourization (Mnif et al. 2015) are used. They all have advantages and drawbacks. Due to the high cost and disposal problems, many of these conventional methods for treating dye wastewater have not been widely applied at large scale in the textile and paper industries (Kyzas et al. 2013). Using agricultural wastes like peels as biomass for the production of low cost sorbents for water treatment applications removes an ecological burden (Bhatnagar et al. 2015) and may make adsorption the best solution for wastewater decolourization.

The origin of cassava (Manihot esculenta Crantz) is well documented (Allem 1994). Taxonomically, it belongs to the Euphorbiaceae family and Manihot genus. Among the crops, cassava has the lowest blue water footprint (Gerbens-Leenes et al. 2009). The biomass of our study, the thin outer layer, rough and brown on the outside of cassava tuber, is a non-valorized waste. This permits the reuse of the rest of the peel as better product for animal feed (Ruqayyah et al. 2014). There is no occurrence of the use of the so-called cassava rind and optimization of the adsorption process is needed. Therefore, the present study aims to investigate, on the one hand, the potential of a new biochar for decolorizing a solution containing MG dye and, on the other hand, the optimal process parameter.

MATERIALS AND METHODS

Carbon preparation

The cassava tubers were purchased in a local farm in Djakotomey, Benin (6° 54′ 0.00″ N 1° 43′ 0.01″ E). They were thoroughly washed with distilled water and peeled with a knife. The rind was separated from the peel manually and dried in the sun until all the moisture had evaporated. Then a steel container was filled with the cassava rind and tightly closed. The product was ground and sieved to sizes between 63 and 90 μm. Rajeshwarisivaraj's activation protocol (Rajeshwarisivaraj et al. 2001) was used with some modifications as follows. A mixture of the raw material (10 g) and phosphoric acid (weight ratio 1:1) was heated at 120 °C for 14 h. Then the resulting char was ground and soaked in 200 mL of sodium hydroxide (1 M) for 24 h to remove residual acid and washed with distilled water until the pH was neutral. Finally, the carbon was dried at 60 °C for 6 h and sieved to sizes between 40 and 63 μm.

Characterization

The thermal behaviour of the raw material was studied using a LABSYS EVO TGA 1150 (Setaram Instrumentation, France). The Thermo Gravimetric Analysis (TGA) experiment was conducted under the following conditions: initial temperature 50 °C, final temperature 600 °C and heating rate of 10 °C/min with an Argon flow rate of 25 cm3/min.

A combination of the Attenuated Total Reflectance (ATR) (VARIAN 800 by Scimitar Series, Australia) and the Fourier Transform Infra-Red Spectroscopy (FTIR) (GLADIATR by Pike Technologies, USA) allows the determination of surface functional groups of two products: raw material and Cassava Rind Carbon (CRC). The spectra were recorded in the range of 400–4,000 cm−1 with 50 scans collected at 4 cm−1 resolution.

The Brunauer–Emmett–Teller (BET) equation was used to obtain the specific surface areas. Pore volume analysis was performed using the Barrett–Joyner–Halenda (BJH) method. Before each measurement on QUADRASORB SI (Quantachrome, Germany), the samples were first degassed at 150 °C for 24 h. Then, the measurements were conducted through the adsorption of nitrogen, at liquid nitrogen temperature, onto the biopolymer surface.

Scanning Electron Microscopy (SEM) analysis was performed using a PHENOM XL (Phenom-World, The Netherlands) with an accelerating voltage of 10 kV. CRC powder was spread on carbon tape adhered to a SEM stage. Before imaging, the samples were coated with a thin gold layer to improve the image quality.

X-Ray Diffraction (XRD) was also performed at room temperature under ambient air conditions, using Cu Kα1 radiation (ʎ = 1.54060 Å) at 10 mA, 30 KV and a 2θ angle ranging from 2° to 90° (Phaser D2 Diffractometer, Broker, USA).

Adsorption measurements

A 1,000 mg/L stock solution was prepared by dissolving an exact amount of MG dye (Riedel de Haen, Germany) in distilled water. The different concentrations of MG were prepared from this stock solution. The solutions used for pH adjustment, NaOH 0.1 M and HCl 0.1 M, were of analytic grade. Batch adsorption experiments were done at 300 RPM. The supernatants were separated by centrifugation at 7,500 RPM for 2 min (Sigma Laborzentrifugen, Germany) and collected by using disposable syringes. The MG residual concentrations in the solutions were determined by monitoring the absorbance with a UV-visible spectrophotometer DR 6000 with RFID Technology (Hach Lange, Germany) at 663 nm, where maximum absorbance was observed. The amount of MG adsorbed per unit mass of the adsorbent at equilibrium Qe (mg/g) was calculated as follows. 
formula
1
where Ci and Ce are respectively the initial and the equilibrium concentration of MG (mg/L), V is the volume of solution (L) and W is the mass of adsorbent (g).

To determine the effect of pH, the adsorption of dye molecules was investigated over a pH range of 3 to 9. The activated carbon (5 mg) was added into the dye solution (50 mL, 100 mg/L) and the mixture was shaken at room temperature (25 ± 1 °C) for 3 h before centrifugation. Moreover, in the same range of pH, the pHZPC was measured as follows: 50 mL of KNO3 solution (0.1 M) with 0.1 g of CRC for 48 h of agitation at room temperature (25 ± 1 °C).

Adsorption kinetics experiments were carried out on 250 mL dye solution (100 mg/L, pH = 7) mixed with 0.05 g of activated carbon at room temperature (25 ± 1 °C) for 2 h. Few millilitres of the solution was sampled using disposable syringes at various time intervals.

Adsorption isotherms were determined by measuring the depletion of MG concentration after the adsorption reached equilibrium. For these experiments, CRC (5 mg) was added into dye solutions (50 mL) of different concentrations from 50 to 100 mg/L with a pH value of 7. The mixture was shaken in a double-jacketed beaker in which temperature was maintained at 25 °C with a thermostat (JP Selecta Frigiderm, Spain) for 1 h before centrifugation.

Box-Behnken Response Surface Methodology (BB RSM)

The Response Surface Methodology, which uses a Box-Behnken experimental design, is a standard statistical tool mostly used for process optimization with minimum number of experiments (Ferreira et al. 2007). The process variables were the adsorption temperature (X1), dose of absorbent (X2), and initial dye concentration (X3), while the response variable was the amount of MG adsorbed per unit mass of the adsorbent (Y). A minimum number of 15 experiments is recommended by the Box-Behnken design to optimize the process parameters. This includes the three repeat runs. The upper limit, central point and lower limit of the variables coded ‘−1’, ‘0’, and ‘1’ are (20, 35, 50 °C), (5, 7.5, 10 mg) and (50, 100, 150 mg/L), respectively. Conditions and results of the experiment are listed in Table 1. The central points, the upper and lower limits were fixed based on the potential observed on isotherm at 25 °C results as well as on the preliminary experimental runs. The BB RSM polynomial equation used to model the amount of adsorbed MG from the water is represented in Equation (2). 
formula
2
where Y is the predicted response, β0 is a constant, βi is the linear coefficient, βij is the interaction coefficients, βii is the quadratic coefficients, and Xi and Xj are the coded values of the process variables. The results of experiments were analysed using statistical computing software Minitab 17 utilizing the model equation and the analysis of variance (ANOVA).
Table 1

Experimental data of BB RSM

Run X1 (°C) X2 (mg) X3 (mg/L) Y (mg/g) 
20 100 776.28 
50 100 971.59 
20 10 100 479.88 
50 10 100 494.67 
20 7.5 50 322.29 
50 7.5 50 330.18 
20 7.5 150 937.66 
50 7.5 150 973.17 
35 50 483.43 
10 35 10 50 247.63 
11 35 150 1,282.20 
12 35 10 150 694.37 
13 35 7.5 100 639.84 
14 35 7.5 100 635.89 
15 35 7.5 100 643.78 
Run X1 (°C) X2 (mg) X3 (mg/L) Y (mg/g) 
20 100 776.28 
50 100 971.59 
20 10 100 479.88 
50 10 100 494.67 
20 7.5 50 322.29 
50 7.5 50 330.18 
20 7.5 150 937.66 
50 7.5 150 973.17 
35 50 483.43 
10 35 10 50 247.63 
11 35 150 1,282.20 
12 35 10 150 694.37 
13 35 7.5 100 639.84 
14 35 7.5 100 635.89 
15 35 7.5 100 643.78 

RESULTS AND DISCUSSION

Characterization

The TGA curves of the raw material in (Figure 1) show two types of weight loss. The first one occurs at 100 °C and corresponds to the dehydration of the material. The maximum depletion of mass (40%) is around 300 °C. The degradation of hemicellulose happens in the range 241–297 °C, while α-cellulose and lignin in the fibre degrades at 297–353 °C. The thermal decomposition of lignin occurs within 353–500 °C (Sampathkumar et al. 2015). At 350 °C, most of a lignin-cellulose mixture disappears (Singh et al. 2009) and, after 400 °C, total degradation is complete (Rodriguez et al. 2012).
Figure 1

TGA curves of cassava rind biomass.

Figure 1

TGA curves of cassava rind biomass.

The combination of ATR and FTIR allows the attenuation of the incident radiation and provides infrared spectra without the water background absorbance. Infrared techniques are fast, accurate, and low-cost for biomass analysis (Dowell et al. 2013). In Figure 2, CRC spectrum has fewer adsorption bands than the raw material spectrum. This indicates that various functional groups present in raw material spectrum disappeared after activation. It can be noticed that C = O stretch of aldehyde of hemicellulose in the raw material at 1,732 cm−1 disappears on CRC spectrum. It is also observed in raw material spectrum at 1,156 cm−1 that there is C-O-C asymmetrical stretching of hemicellulose and cellulose. In the same spectrum at 1,031 cm−1 C-O, C = C, and C-C-O stretching can be attributed to C-O-C asymmetrical stretching of hemicellulose, cellulose, and lignin (Sills & Gossett 2012). In the CRC spectrum, only cellulose and lignin bands were observed, indicating that hemicellulose content was lost during activation. At 980 cm−1, C-O valence vibration of cellulose can be observed (Schwanninger et al. 2004). In the raw material spectrum, as well as CRC spectrum at 2,917 cm−1 and 2,850 cm−1, there is C-H stretching of lignin (Kubo & Kadla 2005).
Figure 2

FTIR/ATR of raw material and CRC.

Figure 2

FTIR/ATR of raw material and CRC.

The SEM micrographs show that the particle size of the raw material (Figure 3(a)) decreases after treatment (Figure 3(b)). The specific surface areas of CRC given by BET model is 2.38 m2/g and the volume of pore is 5.65 10−3 cm3/g with an average pore diameter of 9.48 nm. A very low specific surface area was also found with other lignin materials (Abdelaziz & Hulteberg 2017). The XRD pattern (Figure 4) depicts that CRC is amorphous in nature and the broad peaks indicate that CRC particles may be nanometric in scale.
Figure 3

(a) SEM image of raw material. (b) SEM image of CRC.

Figure 3

(a) SEM image of raw material. (b) SEM image of CRC.

Figure 4

X-ray diagram of CRC.

Figure 4

X-ray diagram of CRC.

Effect of pH

In the adsorption process, pH is an important factor. Figure 5 represents the influence of initial pH on the amount of MG adsorbed per unit mass of the adsorbent. The variation between final and initial pH was also plotted versus the initial pH to evaluate the pHZPC. The value at which pH final was equal to pH initial was accepted to be pHZPC, and the charge surface is neutral at this pH value (the value of pHZPC of CRC is 6.98). Even when the solution is very acidic, the amount of MG adsorbed is significant. At the pH values corresponding to that of initial MG solutions, the amount of MG adsorbed increases significantly. The basic pH zone is the optimal and the amount of MG adsorbed slightly increases. The negative electrostatic forces may be favourable to the adsorption (change of surface charges with cationic dye MG and CRC). At pH values below pHZPC, MG uptake was low because of the presence of H+ ions that compete with cationic MG for similar adsorption sites. At pH > pHZPC, the adsorption process is favourable and the amount of dye adsorbed is higher.
Figure 5

Influence of initial pH and determination of point of zero charge of CRC.

Figure 5

Influence of initial pH and determination of point of zero charge of CRC.

Adsorption kinetics

Two models were applied to investigate the adsorption kinetic processes of the MG on the CRC. The Lagergren's pseudo-first-order model and the pseudo-second-order model (Ho & McKay 1999) are used and expressed respectively as: 
formula
3
 
formula
4
where Qt (mg/g) is the adsorption capacity at the time t (min), Qe (mg/g) is dye adsorption capacity at the adsorption equilibrium. k1 (min−1) and k2 (g·mg−1·min−1) are the dynamics constants.
As can be seen in Figure 6, both pseudo-first- (dot) and pseudo-second- (line) order models suit the experimental data. However, kinetics parameters for pseudo-first-order are Qe = 478.6373 mg/g and k1 = 0.3485 min−1 and kinetics parameters of pseudo-second-order are Qe = 495.3173 mg/g and k2 = 0.0017 g·mg−1·min−1. According to the values of R2 of 0.9912 and 0.9995 for pseudo-first- and pseudo-second-order respectively, the pseudo-second-order better describes the kinetic of the reaction.
Figure 6

Fit to the experimental data by kinetic models.

Figure 6

Fit to the experimental data by kinetic models.

Adsorption isotherms

The equilibrium adsorption isotherm is of importance in the design of adsorption systems. Several isotherm equations are available and two important isotherm models were selected in this study. Freundlich model and Langmuir model are given, respectively, by the following equations. 
formula
5
 
formula
6
where Qmax (mg/g) is a single-layer maximum adsorption capacity, Qe (mg/g) is dye adsorption capacity at adsorption equilibrium and Ce (mg/L) is dye concentration at adsorption equilibrium. The constants are n, KF, and KL.
The Langmuir isotherm can be expressed in terms of a dimensionless separation factor, RL which describes the type of isotherm: 
formula
7
where Ci is the initial concentration of MG. The magnitude of RL determines the feasibility of the adsorption process. If RL > 1, adsorption is unfavourable; if RL = 1, adsorption is linear; if RL < 1, adsorption is favourable; and if RL = 0, adsorption is irreversible.
As can be seen in Figure 7, Langmuir model (line) is more accurate than Freundlich model (dot). The RL value was 0.0246 for initial concentration of 100 mg/L indicating the adsorption is favourable. The maximum capacity according to Langmuir model was 932.975 mg/g at 25 °C (Qmax = 932.98 mg/g; KL = 0.3952). The KF value of MG adsorption onto CRC was 428.73 mg/g (L/mg)1/n at 25 °C (KF = 428.73 mg/g (L/mg)1/n; n = 4.49). The values of R2 of Freundlich model and Langmuir model were 0.9478 and 0.9723, respectively. Therefore, monolayer adsorption better explains the adoption mechanism.
Figure 7

Fit to the experimental data by isotherm models.

Figure 7

Fit to the experimental data by isotherm models.

The potential exhibited by the CRC for MG removal is more than that of many adsorbents (167 mg/g, 243.3 mg/g and 432.90 mg/g, respectively, for textile sludge-based activated carbon, activated carbon aerogels derived from sodium carboxymethyl cellulose and activated carbon from Elaeagnus stone).

Thermodynamic study

The thermodynamic parameters measured, based on the optimization results under different temperatures, to establish the adsorption process included changes in standard enthalpy (), standard entropy (), and Gibbs energy () from the transfer of unit mole solute from the solution to the solid–liquid interface.

was calculated using the equation below: 
formula
8
where R is the universal gas constant (8,314 J mol−1), T (K) is the absolute temperature of the solution, and Kd is the distribution coefficient, which is computed as: 
formula
9
 
formula
10

The values of are plotted against 1/T, the values of and are calculated from the slope and intercept of the plot. The negative values obtained at all temperatures (−8.791; −12.775 and −14.948 kJ mol−1 at 293.15; 308.15 and 323.15 K, respectively) studied indicated that the adsorption process is feasible and spontaneous. The positive value (60.34 kJ·mol−1) indicates that the adsorption interaction is endothermic. In addition, the value greater than 20 but less than 80 suggests that the adsorption is physical adsorption and reversible. Moreover, the positive value of ΔS° (0.23 kJ mol−1 K−1) indicates that there is an increase in the randomness in the system of solid–solution interface during MG adsorption process by CRC.

Box-Behnken Response Surface Methodology

The polynomial regression equation was constructed using the BB RSM to establish the correlation analysis between the process variables and that of the response variable. The MG amount (Y) was found to vary from 322.29 mg/g to 1,282.20 mg/g. The final empirical model is given by Equation (11): 
formula
11

The effectiveness of a model equation in predicting the experimental responses can be assessed based on the coefficient of determination (R2). The R2 was estimated as 0.9967 proving that the model is valid. Moreover, the adjusted correlation coefficient R2 (Radj2 = 0.9907) suggests extensive and very acceptable correlation between the independent variables. In addition, the predict R2 (Rpred2 = 0.9473) indicates that the model will predict new observations as accurately as it fits the existing data. The coefficients of the model equation as well as the importance of each of the model parameters are listed in Table 2. The lower the value of p or the higher the value of F, the more significant are the model parameters. Table 2 shows that the model quadratic parameters and are insignificant (p value more than 0.05, confidence level of 95%). A test on the validity of the model is compulsory as it is used to optimize the process. The appropriateness of the model, in addition to R2, is based on the ANOVA. Table 3 shows the results of ANOVA for the model. ANOVA is a statistical technique that subdivides the total variation in a set of data into component parts associated with specific sources of variation for testing hypotheses on the parameters of the model (Huiping et al. 2007). The model F value of 167.06 and p value of 0.000 indicate the validity of the model. From the ANOVA results, it can be concluded that the model predictions using Equation (11) is satisfactory and that the model can be utilized to identify the optimum process conditions.

Table 2

Estimated coefficients using BB RSM (R2 = 0.9967 and R2adj = 0.9907)

Term Coefficient F p 
Constant  39.98 0.000 
  3.23 0.023 
  −20.37 0.000 
  31.94 0.000 
  0.16 0.877 
  2.66 0.045 
  −0.09 0.929 
  −3.26 0.023 
  0.5 0.639 
  −6.35 0.001 
Term Coefficient F p 
Constant  39.98 0.000 
  3.23 0.023 
  −20.37 0.000 
  31.94 0.000 
  0.16 0.877 
  2.66 0.045 
  −0.09 0.929 
  −3.26 0.023 
  0.5 0.639 
  −6.35 0.001 
Table 3

ANOVA for BB RSM model

Source Degree of freedom (DF) Sum of squares (SS) Mean squares (MS) F p 
Model 1,155,323 128,369 167.06 0.000 
Linear 1,110,482 370,161 481.72 0.000 
Square 5,521 1,840 2.40 0.184 
Interaction 39,320 13,107 17.06 0.005 
Error 3,842 768 – – 
Lack of fit 3,811 1,270 81.59 0.012 
Pure error 31 16 – – 
Total 14 1,159,165 – – – 
Source Degree of freedom (DF) Sum of squares (SS) Mean squares (MS) F p 
Model 1,155,323 128,369 167.06 0.000 
Linear 1,110,482 370,161 481.72 0.000 
Square 5,521 1,840 2.40 0.184 
Interaction 39,320 13,107 17.06 0.005 
Error 3,842 768 – – 
Lack of fit 3,811 1,270 81.59 0.012 
Pure error 31 16 – – 
Total 14 1,159,165 – – – 

Referring to Table 3, temperature, mass of adsorbent and initial concentration show significant effects on the adsorption of MG. Figure 8 shows a 3D response surface plot of mass of adsorbent and initial concentration on the amount of adsorbed MG. When the initial concentration is low and the mass of the adsorbent is high, the quantity of MG uptake is at the lowest value. Therefore, the increasing of the initial concentration and the decreasing of the mass of adsorbent permit the amount of MG adsorbed to reach its maximum. The increase in temperature increases the amount of MG adsorbed. The optimum process conditions estimated using the optimizer tool in Minitab 17 are at a temperature of 50 °C, mass of adsorbent of 5 mg, and dye concentration of 150 mg/L, with the resultant amount of adsorbed MG of 1,363.58 mg/g.
Figure 8

3D surface plot of dose of adsorbent and concentration of dye on MG uptake (Y) for temperature 35 °C.

Figure 8

3D surface plot of dose of adsorbent and concentration of dye on MG uptake (Y) for temperature 35 °C.

CONCLUSION

In this paper, Manihot esculenta Crantz waste was used as biosorbent for wastewater decolourization and the optimization of the adsorption process was studied. Efficient MG adsorption in aqueous solution was carried out using CRC prepared by phosphoric acid activation, and its characterization was done by FTIR/ATR, BET, SEM, and XRD. The adsorption kinetic follows a pseudo-second-order and its isotherm follows Langmuir model. The maximum capacity of MG adsorbed was 932.975 mg/g at 25 °C. The optimum process conditions estimated by the Box-Behnken Response Surface Methodology are at a temperature of 50 °C, mass of adsorbent of 5 mg, and dye concentration of 150 mg/L. The high performance (1,363.58 mg/g) exhibited by CRC in this study shows that the use of Manihot esculenta Crantz waste presents better performance and reduces the cost of adsorptive removal process.

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