SPENT COFFEE GROUNDS BIO CHAR AS A LOW-COST ADSORBENT
FOR METHYLENE BLUE REMOVAL FROM AQUEOUS SOLUTION:
OPTIMISATION USING RESPONSE SURFACE METHODOLOGY
Mardawani Mohamad
1, Rizki Wannahari
1, Afnan Azzahra Ahmad Kamal
1, Rosmawani Mohammad
1, Nurul
Akmar Che Zaudin
1, Choong Shwu Hwa
2, and Lim Jun Wei
3,41Faculty of Bioengineering and Technology, University Malaysia Kelantan, Jeli Campus, Locked Bag No. Jeli, Kelantan, Malaysia 2
Faculty of Agro-Based Industry, University Malaysia Kelantan, Jeli Campus, Locked Bag No. Jeli, Kelantan, Malaysia
3
Department of Fundamental and Applied Sciences, University Teknologi PETRONAS, Seri Iskandar, Perak Darul Ridzuan, Malaysia
4
Centre for Biofuel and Biochemical Research, Institute of Self-Sustainable Building, University Teknologi PETRONAS, 32610 Seri Iskandar, Perak Darul Ridzuan, Malaysia
E-Mail: [email protected]
ABSTRACT
This research studied the application of Spent Coffee Ground Bio char (SCGB) for the removal of Methylene Blue (MB) from aqueous solution. The experiments were designed in two methods: classical and optimization by a combination of Response Surface Methodology (RSM) and Central Composite Design (CCD). Batch adsorption studies were carried out to investigate the influence of adsorption parameters, namely, adsorbent dosage, initial concentration and contact time on the response of MB removal (%) and adsorption capacity (mg/g). The interaction effects of the variables to the responses were studied using the three dimensional (3D) surface graph. The optimum conditions for MB removal (%) are adsorbent dosage of 0.2 g, contact time of 27.59 min, and initial concentration of 10.08 mg/L. The optimum conditions for adsorption capacity were found at adsorbent dosage of 0.1 g, contact time of 30 minutes and initial concentration of 30 mg/L. The determination coefficient (R2) of response surface quadratic model has proven significant at a confident level of 92% and 99% for MB removal and MB adsorption capacity, respectively. So, it was concluded that the SCGB can be used as a low-cost adsorbent for MB removal from aqueous solution.
Keywords: spent coffee ground bio char (SCGB), adsorption, methylene blue (MB), response surface methodology (RSM).
1. INTRODUCTION
Water pollution caused by a wide range of colours and dyeing chemicals has become one of the environmental issues that need to be addressed. Large amounts of synthetic dye being discharged along with the untreated water consequently cause adverse effect to the living organism and bring negative impact to the ecosystem, especially the aquatic life. Dyes are synthetic organic compounds that are applied to the substrates to provide colour by adhering to compatible surfaces with bonding, mechanical retention as well as physical adsorption (Bafana et al., 2011). Methylene blue (MB) is a basic aniline dye. Its chemical formula is C16H18N3SCl.
MB is widely used for the manufacturing of textile. However, it raises a lot of toxicology issues to the environment, human beings and animals. Since MB poses significant harm with health effect to nature life, it is quite necessary to establish colour removal techniques which are effective, inexpensive and environmental friendly such as adsorption techniques (Bulut et al., 2007).
Adsorption is the process of adsorbates from the aqueous solution adhering to the surface of the adsorbent. This theory is applied in wastewater treatment. The compounds with colour tend to bind to the surface of the adsorbent materials and synthetic dye will be removed from the effluent. In recent years, a number of alternative adsorbents materials have been studied for the removal of MB from the wastewater. The low cost adsorbents are natural materials from food and agriculture waste which are effective to handle fairly large flow rates and come out
with high quality effluent that is environmental friendly (Jain et al., 2010). Recently materials that have been reported to be used as bio sorbent such as peanut shell (Aadil et al., 2012), raw pine, neem leaf (Gopalakrishnan et al., 2013), coconut shell (Bernard et al., 2013) and banana peel were able to successfully remove dyes from wastewater. Nowadays, coffee is one of the most abundant food wastes due to the increasing demand worldwide (Boonamnuayvitaya et al., 2004). The dripping process of coffee will transform the coffee beans into coffee-ground with micro- or macrospores. Consequently, spent coffee
wastes are small particles (≈20µm) with large surface area
(≈7.5 m2
g-1). Furthermore, the spent coffee waste contains a large amount of organic compounds such as fatty acids, lignin, cellulose, hemicellulose and other polysaccharides (Kim et al., 2014). Instead of disposing them, they can be a perfect source of adsorbent and be used to remove dye from wastewater (Chinmai et al., 2014).
residual errors was examined using diagnostic plots for predicted versus actual values of responses.
2. MATERIALS AND METHODS
2.1 Preparation of spent coffee grounds bio char (SCGB)
The spent coffee grounds (SCG) collected from a certain coffee shop was washed and rinsed with water until the brown colour of the water turned clear. Then, it was sun dried once to be stored. For pre-treatment of SCG sample, porcelain crucibles were filled with dried SCG and introduced into the muffle furnace. The target temperature for the production of bio char is 500 oC. The porcelain crucibles filled with SCG were kept in the muffle furnace for 4 hours for pyrolysis. The SCG bio char was grinded and sieved using a sieving machine. The bio char powder was collected and kept in a desiccator and used for further analysis.
2.2 Batch adsorption studies
A stock solution of MB (1000 mg/L) was prepared in distilled water, and the working solutions were prepared from successive dilution of stock solution. For batch adsorption studies, the constant parameters in this study are determined, namely, pH (pH 8), temperature (30
o
C), agitation speed of orbital shaker (150 rpm) and volume of methylene blue (MB) solution (50 mL). Optimization parameters that were studied in this study, were, adsorbent dosage (0.1 g to 0.2 g), contact time (10 min to 30 min) and initial concentration of MB solution (10 mg/L to 30 mg/L).
UV-Vis spectrophotometer Spectroquant Pharo 300 was used to measure the absorbance reading of MB solution. The percentage of MB removal was calculated using Equation 1 and the adsorption capacity was calculated using Equation 2. The data was then inserted in Design Expert software for analysis.
Percentage of MB removal, Y (%) =
(Co−Cf
Co × 100%) (1)
Where, Co is initial concentration and Cf is final
concentration of the MB solution.
Adsorption Capacity, 𝑞𝑒(𝑚𝑔/𝑔) =(𝐶𝑜−𝐶𝑚𝑓)×𝑉 (2)
Where, V is the volume of MB solution in litre and m is the mass of adsorbent in the unit of gram.
2.3. Experimental design and Response Surface Methodology (RSM)
In the setting of CCD in Design Expert software (version 10.0), the independent variables were A (adsorbent dosage), B (contact time) and C (initial concentration), while the response variables were % (MB removal) and qe (adsorption capacity). CCD allowed each
independent variable to range in three levels: the low level (-1), the centre level (0) and the superior level (+1), which are shown in Table-1. A total of 20 experiments were performed. The regression model of experimental data was obtained using empirical polynomial equation, the statistical significance of the model and the regression term were evaluated by variance analysis (ANOVA).
Table-1. Real variables with their respective coded values.
Variable Code Unit Real values Coded values
Low Centre High Low Centre High
Adsorbent dosage A g 0.1 0.15 0.2 -1 0 +1
Contact time B min 10 20 30 -1 0 +1
Initial concentration C mg/L 10 20 30 -1 0 +1
2.4 Surface characteristic
The morphology and elemental analysis of the SCGB surface were observed using a JEOL JSM-IT100 Scanning Electron Microscopy.
3. RESULT AND DISCUSSIONS
3.1 Classical experiments
The classical experiments were performed by varying a single factor while keeping the others at a specified value. The effect of adsorption parameters including: adsorbent dose (0.1 g, 0.15 g and 0.2 g), contact time (10 min, 20 min and 30 min), and initial concentration (10 mg/L, 20 mg/L, and 30 mg/L) on the MB removal efficiency was investigated.
3.1.1 The effect of adsorbent dosage
Figure-1(a) shows the main effect plot of adsorbent dosage versus percentage of MB removal. Based on the result shown in Figure-1(a), the percentage removal of MB dye increased with the increase of adsorbent dosage. At adsorbent dosage of 0.10 g, 0.15 g and 0.20 g, the results obtained for dye removal percentage were 81.57%, 84.83% and 87.97%, respectively. The results indicated that the increase of adsorbent dosage could increase the adsorption of MB dye. This could be explained as the increase of adsorbent dose increased the number of sorption sites at the adsorbent surface to be exposed for the interaction with the dye particles. Thus, it increased the percentage of dye removal from the solution where other variables were set as constant (Ofomaja, 2008).
result shown in Figure-1(b), the adsorption capacity decreased with the increase of adsorbent dosage. At adsorbent dosage of 0.10 g, 0.15 g and 0.20 g, the results obtained for adsorption capacity were 8.04, 5.63 and 4.28, respectively. The decline of adsorption capacity along with the increase of adsorbent dosage might be due to the overlapping of adsorption sites when there was aggregation of adsorbent particles (Garg et al., 2003). Consequently, the adsorptive capacity of adsorbent was not fully utilized and the adsorption capacity became lower. Moreover, high adsorbent dosage could introduce shielding effect of the dense outer layer of the cells, preventing the adsorbate to be adsorb on adsorbent surface (Tumin et al., 2008). A similar result was also showed by the study on the adsorption of copper by Elais Guineensis kernel activated carbon. It showed that the adsorption capacity decreased sharply with the increase of adsorbent dosage at 1.5 g (Tumin et al., 2008).
3.1.2 The effect of contact time
Figure-2(a) shows the main effect plot of contact time versus percentage of MB removal. Based on the result shown in Figure-2(a), the percentage removal of MB dye increased with the increase of contact time. At contact time of 10 minutes, 20 minutes and 30 minutes, the results obtained were 80.28%, 85.93% and 87.07%, respectively. The result showed a rapid increase from the contact time between 10 minutes to 20 minutes and slightly slow down after 20 minutes. The increase of percentage of MB removal was rapid initially and then slightly slow down because it almost attained equilibrium. Initially, the rate of adsorption is very high due to large and highly available surface area of adsorbent. After the dye molecules attached to the adsorption site of the adsorbent, longer time was needed for dye to be diffused into the interior active adsorption sites of the adsorbent. Therefore, increase of contact time allowed the whole adsorption process to occur, the rate of adsorption was increasing in this stage until it reached equilibrium (Wannahari et al., 2018; Mogaddasi et al., 2010).
Figure-2(b) shows the main effect plot of contact time versus adsorption capacity. Based on the result shown in Figure-2(b), the adsorption capacity was increasing with the increase of contact time. At contact time of 10 minutes, 20 minutes and 30 minutes, the results obtained
for adsorption capacity were 5.70, 5.82 and 6.25, respectively. The sharp and fast increase of adsorption capacity might be attributed to a large availability of vacant adsorption sites for adsorption during the initial stage. In this stage, the longer the adsorbate is in contact with the dye binding sites of the adsorbent, the higher the adsorption capacity. When the process reached equilibrium, which most of the binding sites had been filled by the dye particles, the adsorption capacity might be decreased for further dye removal by increasing contact time (Deniz, 2013).
3.1.3 The effect of initial concentration
Figure-3(a) shows the main effect plot of initial dye concentration versus percentage of MB removal. Based on the result shown in Figure-3(a), the percentage removal of MB decreased with the increase of initial concentration. For initial concentration of 10 mg/L, 20 mg/L and 30 mg/L, the results obtained for dye removal percentage were 88.36%, 85.57% and 79.71%, respectively. The study from Sharma & Uma (2010) showed a similar trend as the percentage of MB dye removal increased when the initial concentration of MB was decreased. The removal of dye was so efficient with lower initial concentration due to the availability of many vacant sites for adsorption of dye particles. Therefore, percentage of dye removal was higher with lower initial concentration. With constant adsorbent dosage, the increase of initial concentration might cause the saturation of binding sites. This might prevent free dye particles in the solution to be adsorbed and led to lower percentage of dye removal (El-Wakil et al., 2015).
(a) (b)
Figure-1. The effect of adsorbent dosage on (a) MB removal (%) and (b) adsorption capacity (mg/g).
(a) (b)
Figure-2. The effect of contact time on (a) MB removal (%) and (b) adsorption capacity (mg/g).
(a) (b)
Figure-3. The effect of initial concentration on (a) MB removal (%) and (b) adsorption capacity (mg/g).
81.57 84.83 87.97 81.00 82.00 83.00 84.00 85.00 86.00 87.00 88.00 89.00
0.00 0.10 0.20 0.30
Per ce n ta g e o f M B r em o v a l (% )
Adsorbent dosage (g)
8.04 5.63 4.28 0.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00 9.00
0.00 0.10 0.20 0.30
Ad so rp tio n c a p a city , (m g /g )
Adsorbent dosage (g)
80.28 85.93 87.07 79.00 80.00 81.00 82.00 83.00 84.00 85.00 86.00 87.00 88.00
0 20 40
Per ce n ta g e o f M B r em o v a l (% )
Contact time (min)
5.70 5.82 6.25 5.60 5.70 5.80 5.90 6.00 6.10 6.20 6.30
0 20 40
Ad so rp tio n c a p a city (m g /g )
Contact time (min)
88.36 85.57 79.71 79.00 80.00 81.00 82.00 83.00 84.00 85.00 86.00 87.00 88.00 89.00
0 20 40
Pe rc en ta g e o f M B r em o v a l (% )
Initial concentration (mg/L)
3.20 5.82 8.74 0.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00 9.00 10.00
0 20 40
Ad so rp tio n c a p a city (m g /g )
3.2 Response surface methodology
Table-2 shows the experimental responses using CCD model. The maximum percentage of MB removal was 95.86% with the operating conditions of 0.2 g of adsorbent dosage (A), 30 minutes of contact time (B) and 10 mg/L of initial concentration (C). This indicated that increasing amount of adsorbent and contact time with low initial concentration of MB solution might increase the effectiveness of the adsorption process. The highest adsorption capacity was 12.54 mg/g with the operating conditions of 0.1 g of adsorbent dosage, 30 minutes of contact time and 30 mg/L of initial concentration. To determine the relationship between the independent variables and its corresponding response, several types of model, namely, linear, 2FI, quadratic and cubic model have been tested. The program recommends quadratic model for MB removal (%) with adjusted R-squared 0.8569 compared with adjusted R-squared of linear (0.7594), 2FI (0.7675) and cubic (0.9139). Even the value of adjusted R-squared of cubic is superior, but the result of predicted R-squared is lower (-8.6354) compared with linear (0.6594), 2Fl (0.4499), and quadratic (0.3484). For MB adsorption capacity, the program also recommends quadratic model with adjusted R-squared 0.9934 compared with adjusted R-squared of linear (0.8212), 2FI (0.9247) and cubic (0.9982). Even the value of adjusted R-squared of cubic is superior, but the result of predicted R-squared of cubic is lower (0.7315) compared with linear (0.8212), 2Fl (0.9247), and quadratic (0.9562). Hence, the quadratic model was suggested for both MB removal (%) and MB adsorption capacity, as suggested by the software.
Regression analysis was performed to fit the response function of MB removal (%) and MB adsorption
capacity. The final empirical models for MB removal (%) and MB adsorption capacity in terms of coded factors after excluding the insignificant terms are shown in Equations (3) and (4), respectively.
MB removal, Y (%) = 85.67 + 3.20A + 3.40B - 4.33C - 0.68AB - 1.51 AC +
0.12 BC + 2.48A2– 3.01B2– 1.21 C2 (3)
Adsorption capacity, qe (mg/g) = 5.70 - 1.88A + 0.27B +
2.77 C - 0.17AB – 0.96 AC+
0.16 BC + 0.77 A2 - 0.18 B2 - 0.21 C2 (4)
Table-2. Experimental design matrix and response values.
Run Adsorbent
dosage (g), (A)
Contact time (min), (B)
Initial concentration
(mg/L), (C)
Removal of MB (%)
Adsorption capacity (mg/g)
1 0.15 20 10 88.05 2.93
2 0.15 20 20 86.94 5.80
3 0.10 20 20 81.80 8.18
4 0.15 20 20 85.12 5.67
5 0.15 20 30 79.56 7.96
6 0.20 30 30 82.50 6.19
7 0.15 20 20 87.11 5.81
8 0.15 20 20 87.56 5.84
9 0.15 30 20 86.22 5.75
10 0.10 10 30 73.74 11.06
11 0.20 10 30 79.12 5.93
12 0.10 10 10 81.55 4.08
13 0.20 30 10 95.86 2.40
14 0.10 30 10 87.16 4.36
15 0.15 20 20 83.86 5.59
16 0.15 10 20 77.78 5.19
17 0.10 30 30 83.63 12.54
18 0.20 10 10 89.19 2.23
19 0.20 20 20 93.19 4.66
20 0.15 20 20 86.08 5.74
Table-3. Analysis of variance (ANOVA) for response surface quadratic model.
Source Sum of
squares df
Mean of
square F-value p-value Remarks
a. MB removal (%)
Model 469.58 9 52.18 13.64 0.0002 Significant
A-Adsorbent
dosage 102.27 1 102.27 26.73 0.0004 Significant
B-Contact time 115.53 1 115.53 30.20 0.0003 Significant C-Initial
concentration 187.14 1 187.14 48.91 < 0.0001 Significant
AB 3.71 1 3.71 0.97 0.3478 Not significant
AC 18.27 1 18.27 4.78 0.0538 Not significant
BC 0.12 1 0.12 0.032 0.8616 Not significant
A2 16.92 1 16.92 4.42 0.0618 Not significant
B2 24.99 1 24.99 6.53 0.0286 Significant
C2 4.02 1 4.02 1.05 0.3293 Not significant
R-squared 0.9247
b. MB adsorption capacity (mg/g)
Model 122.36 9 13.60 316.88 < 0.0001 Significant A-Adsorbent
dosage 35.39 1 35.39 824.90 <0.0001 Significant
B-Contact time 0.75 1 0.75 17.59 0.0018 Significant
C-Initial
concentration 76.65 1 76.65 1786.58 <0.0001 Significant
AB 0.23 1 0.23 5.26 0.0447 Significant
AC 7.36 1 7.36 171.55 <0.0001 Significant
BC 0.21 1 0.21 4.85 0.0523 Not significant
A2 1.63 1 1.63 37.93 0.0001 Significant
B2 0.093 1 0.093 2.17 0.1713 Not significant
C2 0.12 1 0.12 2.69 0.1318 Not significant
R-squared 0.9965
In the experimental design, the significance of every source of variation was determined by p-value. If the value of p-value is less than 0.0500, it indicates that the result data is not random and the model terms are statistically significant (Nordin et al., 2019; De Araújo et al., 2005). From Table-3(a) for MB removal (%), Model F-value was 13.64 and p-value was 0.0002, which indicated the model was significant. Table-3(b) for MB adsorption capacity (mg/g) also concluded as a significant model, which was the model F value 316.88 and p- value < 0.0001. In the case of MB removal (%), the following terms were significant with p-value less than 0.05: adsorbent dosage (A), contact time (B), initial concentration (C) and squared effect of contact time (B2). Moreover, adsorbent dosage (A), contact time (B), initial concentration (C), interaction effect between adsorbent dosage and contact time (AB) and interaction effect
B: contact time (min) A: adsorbent dosage (g)
(a)
C: initial concentration (mg/L) A: adsorbent dosage (g)
(b)
C: initial concentration (mg/L) B: contact time (min)
(c)
Figure-5. 3D plots: (a) the effect of contact time and adsorbent dosage, (b) the effect of initial concentration and adsorbent
dosage and (c) the effect of initial concentration and contact time on the MB removal (%).
M
B
r
e
m
o
v
a
l
(%
)
M
B
r
emoval
(%
)
M
B
r
e
m
o
v
a
l
(%
B: contact time (min) A: adsorbent dosage (g)
(a)
C: initial concentration (mg/L) A: adsorbent dosage (g)
(b)
C: initial concentration (mg/L) B: contact time (min)
(c)
Figure-6. 3D plots: (1) the effect of contact time and adsorbent dosage, (2) the effect of initial concentration and adsorbent
dosage and (3) the effect of initial concentration and contact time on the MB adsorption capacity (mg/g).
3.3 Process optimisation
RSM was used to find the optimum condition for adsorption process of MB removal. Design expert (ver. 10) was used to compromise between MB removal and MB adsorption capacity while optimising both of these values by selecting the two highest responses from the experimental results. The optimum calculated condition for MB removal (%) was 96.07% and it took place in the condition with 0.2 g of adsorbent dosage and 27.59 minutes of contact time where initial concentration was set as constant at 10.08 mg/L with desirability of 1. The optimum conditions for adsorption capacity were found at adsorbent dosage of 0.1 g, contact time of 30 minutes and initial concentration of 30 mg/L. The adsorption capacity
was up to 12.2973 mg/g at desirability of 0.976. These selected conditions were within the experimental design proposed by the software.
3.4 Surface characterization
The SEM images for surface characterization of the spent coffee ground bio char (SCGB) are presented in Figure-7. SCGB had a rough surface with heterogeneous holes and pores that make a large surface area. That explains why MB dye can be adsorbed effectively onto its surface. The major constituent spectrum of SCGB analyse using energy disperse spectroscopy (EDS) as shown in Figure-8 are carbon (C) 61,10%, followed by Oxygen (O) 19.86%, Chloride (Cl) 6.68% and Potassium (K) 12.36%.
A
ds
o
rpt
io
n
c
apa
c
it
y
(
m
g/
g)
Ads
or
pti
o
n
ca
pa
cit
y
(mg/
g
)
A
ds
o
rpt
io
n
c
apa
c
it
y
(
m
g/
Figure-7. SEM image of spent coffee ground bio char (SCGB) using 750 x magnifications.
Figure-8. EDS spectrum of spent coffee ground bio char (SCGB) at the surface.
4. CONCLUSIONS
In this study, the adsorption of MB from aqueous solution by spent coffee ground bio char (SCGB) was examined. Classical and statistical methods were used for experimental design. Using classical method, the range of different factors was determined for design of experiment in statistical method by RSM. RSM was used to determine the correlation between the response, namely, MB removal (%) and adsorbent capacity (mg/g) and three factors: adsorbent dosage (A), contact time (B) and initial concentration (C). The optimum conditions for the MB removal were found to be at adsorbent dosage of 0.2 g, contact time of 27.59 minutes and initial concentration of 10.08 mg/L. At this optimum condition, the percentage of MB removal was up to 96.07% with desirability of 1. The optimum conditions for adsorption capacity were found at
adsorbent dosage of 0.1 g, contact time of 30 minutes and initial concentration of 30 mg/L. The adsorption capacity was up to 12.2973 mg/g at desirability of 0.976. The SEM image shows that SCGB had a rough surface with heterogeneous holes and pores. From the overall results concluded, the spent coffee ground bio char (SCGB) can be effectively used as low cost adsorbent for Methylene Blue (MB) dye removal from aqueous solution. Also, RSM is a suitable design tool to reduce the number of experiments, correlate the MB removal to the operating parameters and optimize the removal conditions.
ACKNOWLEDGEMENTS
Education via Fundamental Research Grant, R/FRGS/A1300/01155A/003/2018/00559.
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