Removal of organic dyes from wastewater by adsorption has advantages over conventional materials due to its low cost, abundance, adsorption capacity, and recycling. In this context, this study aims to evaluate the adsorption capacity of methylene blue in commercial babassu coconut mesocarp biochar. For this, biochar was characterized using physico-chemical parameters, proximate analysis, specific surface area (SBET) and surface functional groups. Batch-tests were carried out to identify the influence of biochar dose, initial dye concentration, granulometric fraction and time in the adsorptive process. The mixture was kept on a rotary shaker at room temperature, and the concentration was determined in a UV-VIS spectrophotometer. Results were analyzed using kinetic and isotherm models. The SBET of the commercial biochar was of 484.9 m² g− 1. The optimal conditions were using a biochar dose of 5 g L− 1, initial dye concentration inferior to 300 mg L− 1 and biochar granulometric fraction inferior to 0.15 mm. Elovich kinetic model (R2 > 0.8742) was most suitable to represent the MB adsorption onto babassu coconut mesocarp biochar. The equilibrium adsorption data were best described by the Langmuir model (R2 > 0.9897), with qm = 67.6 mg g− 1.
Research Article
Adsorption of Methylene Blue on Babassu Coconut (Orbignya speciosa) Mesocarp Commercial Biochar
https://doi.org/10.21203/rs.3.rs-1510328/v1
This work is licensed under a CC BY 4.0 License
Version 1
posted 29 Apr, 2022
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organic dye
adsorption isotherms
kinetic models
Dyes are chemical substances frequently used in the industry to provide stable and bright colors to a wide variety of products and materials (XUE et al., 2022). The wastewater from industries such as paper and cellulose, paint, rubber, plastic, textile, cosmetics, food, and hospitals are the primary contamination source by synthetic dyes in water bodies (SONWANI et al., 2020).
Synthetic dyes are used by industries mainly due to their low cost and the ease of producing different colors compared to available natural dyes (YAO et al., 2020). Currently, there are over 100,000 commercial dyes worldwide and approximately 280,000 tons of dyes are discharged into the water flow every year in the textile sector (KISHOR et al., 2021).
These organic molecules have potential toxicity, carcinogenicity, non-biodegradability properties, and can cause eye irritation, vomiting and reduced cardiac output (DAWOOD et al., 2017; NIDHEESH; ZHOU; OTURAN, 2018; XUE et al., 2022). When discarded in water bodies, dyes can interrupt sunlight penetration, reduce photosynthetic capacity and reoxygenation in aquatic environments (OVEISI et al., 2018). Consequently, these substances are considered as hazardous environmental pollutants.
Synthetic dyes are resistant to conventional biological treatment of wastewater due to their complex molecular structure and chemical stability (NIDHEESH; ZHOU; OTURAN, 2018). Flocculation, membrane filtration, advanced oxidation, coagulation, and adsorption have been implemented for wastewater treatment with synthetic dyes (AHMAD et al., 2020; GANG et al., 2021; XUE et al., 2022). Among these technologies, the use of adsorbent materials for water purification has gained attention due to their ease of operation, efficiency, and low cost (VRÎNCEANU et al., 2019; LI et al., 2019; AHMAD et al., 2020; GANG et al., 2021; XUE et al., 2022). This method can remove several types of synthetic dye without generating harmful substances and residues.
An ideal adsorbent must have the ability to be easily manufactured, economically viable, and have a high capacity for adsorption (GANG et al., 2021). In this context, the applicability of biochar in water treatment is gaining interest due to its sustainability and low production cost (CHOUDHARY et al., 2020).
Biochar can show a developed pore structure and high specific surface area with diverse functional groups that is advantageous for synthetic dye removal via various chemical and physical forces of attraction (XUE et al., 2022, GIRI et al., 2022). For example, biochar obtained from Chinese Fan-Palm showed adsorption capacity of 21.4 mg g− 1 for the removal of malachite green (GIRI et al., 2022). The maximum adsorption capacity of methyl orange from aqueous solution with mimosa derived biochars was 12.3 mg g− 1 (NGUYEN et al., 2021). Activation process can enhance the adsorption capacity. For instance, activated soybean-cake based biochar reached over 800.0 mg g− 1 removal of Rhodamine B and Congo Red from aqueous solution (ZHANG et al., 2022). Activated biochar produced from ashitaba biomass showed adsorption capacity higher than 400 mg g− 1 for the removal of methylene blue (XUE et al., 2022).
In the last years, the search for new biochar applied to synthetic dye removal has increased. In the researched literature, it was verified that the use of the babassu coconut mesocarp (Orbignya speciosa), has been little explored as an adsorbent of synthetic dye. Babassu coconut activated biochar is commonly commercialized in Brazil for residential water filters. In this context, the objective of this study was to evaluate the adsorption capacity of commonly used cationic dye (methylene blue) on activated babassu coconut mesocarp commercial biochar to determine the influence of operational factors on cationic dye adsorption including time, dye concentration, biochar dose and granulometric fraction.
2.1 Materials
Activated biochar from babassu coconut mesocarp with a particle size of 2.40–2.90 mm was purchased directly from a Brazilian supplier. The material was disintegrated with a mortar and sieved (mesh 30, 45, 65, 100 and bottom) Methylene blue (MB, C6H18N3SCl) dye of analytical grade was used as target dye pollutant.
2.2 Biochar characterization
The previously prepared material was characterized in terms of its physical-chemical parameters (pH, point of zero charge - pHpcz, ΔpH, electrical conductivity – EC, cation exchange capacity – CTC), proximate analysis (moisture content – M, ash content, volatile matter - VM, and fixed carbon - FC), specific surface area (SBET), pore volume (Vp) and surface functional groups. The procedures and references used in the characterization assays are described in Table 1.
| Parameter | Procedure | Reference |
|---|---|---|
| pH | 1:2.5 ratio of biochar and deionized water was used. The samples were homogenized with a glass rod for 5 minutes and left for 60 minutes rest until pH determination | EMBRAPA (1997) |
| ΔpH | For the determination of ΔpH, it was determined pH(KCl) using a 1:2.5 ratio of biochar and 1 M solution of KCl. ΔpH was obtained by the difference between pH(KCl) and pH(H2O) | EMBRAPA (1997) |
| EC | 1:1 ratio of biochar and deionized water. The solution was kept under constant agitation for 5 minutes and left for 60 minutes rest until EC determination | IAC (1991) |
| SBET, Vp | The analyzes were performed by adsorption of nitrogen at -195.85°C using the adsorption equipment (ASAP 2020 Plus), with samples degassed at 100°C under vacuum for 24 hours before measurement. The surface area (SBET) and pore volume (Vp) were determined by the Brunauer-Emmet-Teller (BET) method | AMBROZ et al. (2018) |
| M, VM, and FC | To determine M, the sample was dried at 105 ± 2°C until constant weight; the sample was then heated at 950 ± 20°C for 7 min to determine the VM; and for ash determination, the sample was heated at 750 ± 15°C for 4 h. the FC is determined using Eq. 1. \(\text{F}\text{C} \left(\text{\%}\right) = 100-\text{M}\left(\text{\%}\right)-\text{V}\text{M}\left(\text{\%}\right)\) (1) | ASTM D-1762-84 (ASTM, 2013) |
| Functional groups | Fourier transform infrared spectroscopy (FTIR) analyzes were performed in a Shimadzu IRP Pretige-41 spectrophotometer. For analysis, the sample was mixed with potassium bromide (KBr) to form pellets and thus submitted for analysis. The recorded spectra range from 400 to 4000 cm− 1 | SILVERSTEIN et al. (2007) |
2.3 Adsorption experiments
Adsorption experiments were conducted using a solution of MB in distilled water. Batch tests were conducted to determine the influence of operational factors on MB adsorption including time, biochar dose and granulometric fraction (ROY et al., 1992).
To evaluate the dose influence, dosages of 1–5 g L− 1 of < 0.15mm biochar was added to the 225 mg L− 1 MB and MB solution. The initial dye concentration was studied adding 5 g L− 1 of < 0.15mm biochar to different concentrations of MB solution (150–600 mg L− 1). To evaluate the influence of the granulometric fraction, 5 g L− 1 of biochar in five different granulometric fractions (< 0.15, 0.15, 0.25, 0.40 and 0.60 mm) was added to a 225 mg L− 1 MB solution. To evaluate the influence of time in the adsorption process, aliquots were collected after 0, 2.5, 5, 10, 20, 40, 60, 80, 100, 120, 180, 240 min and 24 h of experiment.
All the adsorption experiments were performed at natural pH of dye solution (pH = 6.3) at room temperature 26.0 ± 1°C. The adsorption tests were carried out in conical flasks of 50 mL that were agitated on an orbital shaker table at 100 rpm. All batch adsorption tests were performed in triplicate and the results reported represent the average of these replicates.
At the end of each experiment, an aliquot was collected, centrifuged (8000 rpm for 5 minutes), diluted, and the dye concentration was determined by UV-VIS spectrophotometry (model K37-UVVIS from KASVI) using a quartz vessel with a 10.0 mm optical path. Absorbance was measured at wavelengths 664 nm for MB dye. The concentration of MB in solution was obtained using the Lambert-Beer equation. The percentage adsorption and adsorption capacity at time t, qt (mg g− 1), was calculated using Eqs. (2) and (3), respectively:
| \(Removal efficiency \left(\%\right) = \frac{100\times ({C}_{0}-{C}_{t})}{{C}_{0}}\) | (2) |
|---|---|
| \({q}_{t}=\frac{({C}_{0}-{C}_{t})\times V}{m}\) | (3) |
where, C0 and Ct are the initial concentration and the concentration of dye at time t (mg L− 1), respectively. V is the volume of the solution containing dye (L), and m is the mass of biochar (g).
The equilibrium experiments were conducted at 26°C for 24 h, whereby the initial MB concentration was between 150 and 600 mg/L, and initial biochar dose was between 1 and 5 g L− 1. The percentage adsorption and adsorption capacity at equilibrium, qe (mg g− 1), was calculated using Eqs. (4) and (5), respectively:
| \(Adsortpion capacity \left(\%\right) = \frac{100\times ({C}_{0}-{C}_{e})}{{C}_{0}}\) | (4) |
|---|---|
| \({q}_{e}=\frac{({C}_{0}-{C}_{e})\times V}{m}\) | (5) |
where, C0 and Ce are the initial concentration and the concentration of dye at equilibrium (mg L− 1), respectively. V is the volume of the solution containing dye (L), and m is the mass of biochar (g).
2.4 Adsorption kinetics
The adsorption kinetics was used to model experimental data to understand the performance of the adsorption process and underlying mechanisms. For this, three nonlinear kinetic models were applied using Origin 9.1 software. The models applied are shown in Table 2. Based on the results obtained, the uptake rate of the solute and retention time of the adsorption experiment was determined. The experimental data fit to the models were analyzed using coefficient of determination (R²) and the adjusted coefficient of determination (R²adj).
| Model | Equation | Parameters | Reference |
|---|---|---|---|
| Pseudo-first order | \({q}_{t}={q}_{e}(1-exp(-{k}_{p1}t\left)\right)\) | qt and qe are the adsorption capacity (mg g− 1) at time (t) and equilibrium, respectively; and kp1 is the pseudo-first order (PFO) rate constant (L min− 1) | NGUYEN et al. (2021) |
| Pseudo-second order | \({q}_{t}=\frac{ {q}_{e}^{2}{k}_{p2}t}{1+{q}_{e}{k}_{p2}t}\) | qt and qe are the adsorption capacity (mg g− 1) at time (t) and equilibrium, respectively; and kp2 is the pseudo-second order (PSO) rate constant (g mg− 1min− 1). | NGUYEN et al. (2021); |
| Elovich model | \({q}_{t}=\frac{1}{b}ln(1+abt)\) | qt is the adsorption capacity (mg g− 1) at time (t) a is the initial velocity due to dq/dt with qt = 0 (mg g− 1 min− 1), b is the desorption constant of the Elovich model (g− 1 mg− 1) and t is the time (min). | CAPONI et al. (2017) |
2.5 Adsorption isotherms
The condition of the equilibrium studies was selected using experimental data obtained in the adsorption studies. The experimental conditions used were 5 g L− 1 of biochar dosage with granulometric fraction < 0.15mm biochar added to initial MB concentration of 225–420 mg L− 1 MB solution. An aliquot was collected after 24h to ensure equilibrium was reached.
The equilibrium experimental data was modeled using Langmuir I, Freundlich, Langmuir II and Temkin models which were implemented to fit the dye adsorption isotherm data. The Langmuir model assumes homogeneous adsorption energy on the adsorbent surface and that the transmigration of the solute molecules does not occur on the surface of the adsorbent (GIRI et al., 2022); the Freundlich isotherm model is applicable in the studies of adsorption on rough and multisite (heterogonous) surfaces (MAJD, et al., 2022); and the Temkin isotherm model is assumed as a multi-layer process (MAJD, et al., 2022). The model is purely empirical. These adsorption models and the respective linearized equations are given in Table 3.
The parameters for each model were obtained by plotting experimental data. For the Langmuir model, a graph of Ce/qe versus Ce yields a straight line with slope (1/qm) and intercept (1/(Kaqm)) is obtained. For the Freundlich model, a graph of log qe versus log Ce yields a straight line with slope of value 1/n and intercept is equal to log KF. For the Temkin model, a graphical analysis of ln Ce versus qe yields a straight line with slope of β, and at the intercept, β ln A was plotted (GIRI et al., 2022). The experimental data fit to the models were analyzed using R², R²adj, Pearson -r and residual sum of squares (RSS).
Model | Equation | Linearized equation | Parameters | Reference |
|---|---|---|---|---|
Langmuir I | \({\text{q}}_{\text{e}}=\frac{{\text{q}}_{\text{m}}{\text{K}}_{\text{L}}{\text{C}}_{\text{e}}}{1+{\text{K}}_{L}{\text{C}}_{\text{e}}}\) | \(\frac{{\text{C}}_{\text{e}}}{{\text{q}}_{\text{e}}}=\left(\frac{1}{{\text{q}}_{\text{m}}}\right){\text{C}}_{\text{e}}+\frac{1}{{\text{q}}_{\text{m}}{\text{K}}_{\text{L}}}\) | Ce (mg L− 1) is the equilibrium concentration, qe (mg g− 1) is the amount of dye adsorbed at equilibrium, qm (mg g− 1) and KL (L mg− 1) are Langmuir constants related to adsorption capacity and energy of adsorption, respectively | GIRI et al. (2022); MARQUES et al. (2019) |
Freundlich | \({\text{q}}_{\text{e}}= {\text{K}}_{\text{F}}{\text{C}}_{\text{e}}^{1/\text{n}}\) | \({\text{l}\text{o}\text{g} \text{q}}_{\text{e}}=\left(\frac{1}{n}\right)log {\text{C}}_{\text{e}}+log {\text{K}}_{F}\) | KF (mg g− 1)(L mg− 1)1/n is the Freundlich adsorption constant and 1/n is a measure of the adsorption intensity | GIRI et al. (2022) |
Langmuir II | \({\text{q}}_{\text{e}}=\frac{{\text{q}}_{\text{m}}{\text{K}}_{\text{L}}{\text{C}}_{\text{e}}}{1+{\text{K}}_{L}{\text{C}}_{\text{e}}}\) | \(\frac{1}{{\text{q}}_{\text{e}}}=\left(\frac{1}{{\text{q}}_{\text{m}{K}_{L}{C}_{e}}}\right)+\left(\frac{1}{{q}_{m}}\right)\) | Ce (mg L− 1) is the equilibrium concentration, qe (mg g− 1) is the amount of dye adsorbed at equilibrium, qm (mg g− 1) and KL (L mg− 1) are Langmuir constants related to adsorption capacity and energy of adsorption, respectively | MARQUES et al. (2019) |
Temkin | \({q}_{e}=\left(\frac{RT}{b}\right)ln\left({K}_{T}{C}_{e}\right)\) | \({q}_{e}=\left(\frac{RT}{b}\right)ln{C}_{e}+\left(\frac{RT}{b}\right)ln{K}_{T}\) | b (J mol− 1) is the Temkin constant related to adsorption heat, KT (L mg− 1) is the Temkin constant, R is the universal ideal gas constant (8.31 J mol− 1 K− 1), and T (K) is the absolute adsorption temperature | XUE et al. (2022); GIRI et al. (2022) |
3.1 Biochar characterization
The results obtained from the physico-chemical characterization and proximate analysis of coconut biochar are shown in Table 4.
| Physico-chemical parameters | |
|---|---|
| pH(H2O) | 9.7 ± 0,1 |
| pH(KCl) | 9.3 ± 0,1 |
| ΔpH | -0.4 |
| EC (µS cm− 1) | 3970 ± 20 |
| SBET (m2 g− 1) | 484,94 |
| Vtotal (cm3 g− 1) | 0,1935 |
| Vmicro (cm3 g− 1) | 0,1626 |
| Amicro (cm3 g− 1) | 416,74 |
| Proximate analysis | |
| Moisture (%) | 11.3 ± 0.1 |
| Volatile matter (%) | 9.3 ± 0.5 |
| Ash content (%) | 6.6 ± 0.3 |
| Fixed carbon (%) | 84.1 ± 0.3 |
The pH values of biochar are typically basic, ranging from 8 to 10 (FEITOSA et al., 2020). This is probably due to the presence of carbonate ash, basic salt, and basic cation (AHMAD et al., 2012; FEITOSA et al., 2020). Furthermore, the presence of such ions can influence EC values. From the results, it is possible to observe that the ΔpH is negative, which implies a negative charge balance in the biochar, which may favor the adsorption of cationic species.
FTIR analysis was used to identify some characteristic functional groups of the commercial biochar used. Figure 1 shows the spectra found.
In the FTIR spectrum of biochar, it is possible to observe that even after the process of obtaining the material some oxygenated functional groups can still be found, which is positive in the process of adsorption of methylene blue, since these functional groups can be directly related to the adsorption potential of biochar. The presence of these oxygenated functional groups can be evidenced in the spectrum by the two peaks at 3786 cm− 1 and 3699 cm− 1 and a broad band centered at 3425 cm− 1 that can be correlated to the stretching of the hydroxyl group (OH) and by two bands related to the stretching of the carbonyl group (C = O) at 1836 cm− 1 and 1087 cm− 1 (SILVERSTEIN, et al., 2007). The functional groups found are similar to those reported in the literature (AHMAD et al., 2014).
The surface area of the activated biochar was of 484.94 m2 g− 1, and the volume and micropore area were 0.1626 cm3 g− 1 and 416.74 m2 g− 1, respectively. The micropore is an essential characteristic in the adsorption process, and it is developed during the carbonization and activation process. The adsorption-desorption isotherms of N2 (g) and the pore size distribution of commercial activated biochar are shown in Figs. 2 and 3.
It is observed that the isotherm obtained in Fig. 2 types I(a), characteristic of microporous adsorbents below ~ 1 nm according to the IUPAC classification (AMBROZ et al., 2018). This can be confirmed in Fig. 3 with a narrow pore width distribution with a maximum value at 0.58 nm. The micropore plays an essential role in the adsorption process. Although there is no analysis of the activated biochar precursor material used in this work, the surface area and pore volume of activated biochar is probably higher due to micropores developed after the carbonization process and activation of the precursor material.
It was observed that commercial biochar has an intermediate ash content (6.6%) but below the maximum concentration reported by the company (< 12%) and within the established by the EN 12915-1 standard (< 15%) for materials intended for water filtration (EN, 2009). The ash represents the amount of inorganics present in the biochar that in high concentration can impair the adsorption process by blocking the biochar pores, and this ash concentration is mainly characteristic of the type of biomass used (CASTIGLIONI et al., 2022). The increase in the concentration of ash and fixed carbon depends on the conversion process used in the production of coal, which also causes a reduction in the content of moisture and volatile material. This leads to a decrease in hydrogen, nitrogen, and oxygen content and an increase in carbon content. A higher fraction of lignin in the precursor material favors an increase in the fixed carbon content (MAIA et al., 2021).
3.2 Adsorption studies
3.2.1 Effect of biochar dose, initial dye concentration and granulometric fraction
Figure 4 depicts the influence of the initial MB concentration, biochar dose, and granulometric fraction on the mean percentage of MB removed after 24 h of experiment. In general, MB adsorption capacity increased with the biochar dosing from 1.0 to 5.0 g L− 1, reduced with the increase of MB concentration from 150 to 600 mg L− 1 and reduced with the increase of granulometric fraction. There was a drastic reduction in the MB adsorption capacity when biochar initial dye concentration was increased from 300 to 375 mg L− 1 and granulometric fraction changed from < 0.15 to 0.15 mm.
The dosage of 5 g L− 1 promoted the adsorption of all MB mols in solution (Fig. 4a). An elevated dosage of biochar increased the number of surface adsorption sites, leading to a higher adsorption capacity and impacting upon the biochar dosage at which equilibrium adsorption occurred. Nguyen et al (2021) reported that the increase in agro-waste biochar dose and methyl orange concentration affect the adsorption capacity. The authors describe that concentration of biochar up to 5 g L− 1 favored adsorption of methyl orange. However, the excess of adsorbent may lead to its aggregation and a consequent decrease in surface area (NGUYEN et al., 2021). For this reason, this dosage was selected for further experiments.
Figure 4b shows that MB adsorption capacity was significantly dependent on the initial concentration of the MB solution. A higher initial MB concentration, with the same dose of biochar (5 g L− 1) and granulometric fraction (< 0.15 mm), resulted in decreased adsorption capacity. Thus, the initial MB concentration should preferentially not exceed 300 mg L− 1 to remove the majority of MB (> 90%). As there was little change in the initial concentration of 450 to 600 mg L− 1, for further studies, the initial concentrations of 150–450 mg L− 1 was selected.
The granulometric fraction used in the adsorption studies was determinant in the adsorption capacity of MB from the solution (Fig. 4c). For a fixed initial dye concentration (225 mg L− 1) and biochar dose (5 g L− 1), adsorption was effective when using finer biochar particles (< 0.15 mm). For particles with diameter equal or superior to 0.15 mm, adsorption capacity decreased under 50%. For this reason, the granulometric fraction < 0.15 mm was selected for further experiments.
3.2.2 Effect of contact time
Figure 5 illustrates the overall changes and correlation between the initial concentration, time, and adsorption capacity. It could be seen that the initial concentration was positively correlated with the removal efficiency, that is, higher initial MB concentration promoted a higher and faster removal efficiency. The cationic dye was almost completely adsorbed at low concentration, while at high concentration, the adsorption sites on the surface of babassu coconut mesocarp biochar were insufficient for the cation to occupy (XI et al., 2022). The equilibrium was reached around 240 min.
There was an apparent change in reaction rate between the initial MB concentrations of 150–300 and 375–450 mg L− 1. Until 40 min, more than 60% of saturation was obtained for initial MB concentration of 150–300 mg L− 1, while for initial MB concentrations of 375–450 mg L− 1, the removal efficiency was under 40%. According to Nguyen et al. (2021), the adsorption process of methyl orange onto agro-waste biochar can be separated and described in three stages. During the first stage, there was a steeper concentration gradient between the biochar and the solution; thus, there was a relatively rapid increase in the adsorption rate. During the second stage, this concentration gradient decreased with the number of surface adsorption sites and there was a gradual increase in mass removal and adsorption efficiency. On the third stage of adsorption, the reaction system had reached adsorption equilibrium (NGUYEN et al., 2021).
Analyzing Fig. 5, the first stage of the adsorption is between 0 and 40 min, where there was a relatively rapid increase in the adsorption rate, especially for initial concentration of 150–300 mg L− 1. Later, in the second stage, from 40–120 min, there was a gradual increase (approximately 10%) in the MB removal. The third stage of adsorption occurred at initial MB concentrations of 225–375 mg/L between 120 and 240 min, whereby the reaction system had reached adsorption equilibrium. For this reason, these concentrations were selected for the equilibrium studies.
3.3 Kinetic models
The experimental kinetic curves of MB adsorption on babassu coconut mesocarp biochar were constructed at different initial dye concentration (150, 225, 300, 375, and 450 mg L− 1) and the respective data were fitted using PFO, PSO and Elovich models. These results are shown in Fig. 6 and Table 5.
To compare and assess the fitting of the kinetic models, the coefficient of determination (R²) and the adjusted coefficient of determination (R²adj) was utilized; a higher R² and R²adj indicates a better model. Based on the R² and R²adj, in Table 5, the PSO kinetic model fitted the experimental data better than the PFO kinetic model. Additionally, qe calculated from the PSO model was higher than that determined from the PFO model. The PSO and PFO kinetic models both assume that the MB adsorption may be governed by chemisorption and physical adsorption mechanisms (NGUYEN et al., 2021).
Based on the statistical parameters (R² > 0.8742) and (R²adj > 0.8602) (Table 5), it can be clearly observed that the Elovich model was the most suitable to represent the MB adsorption onto babassu coconut mesocarp biochar. At lower initial dye concentrations, the parameter “b” (g mg− 1) from the Elovich model was higher. This fact shows that the MB adsorption capacity was favored at initial concentrations of 150 mg L− 1. This finding is similar to that observed by CAPONI et al. (2017) when studying the adsorption of malachite green dye onto kaolin clay.
Table 5. Kinetic parameters for the adsorption of MB onto babassu coconut mesocarp biochar
3.4 Adsorption isotherms
To comprehend the association between the quantity of MB adsorbed per unit weight of biochar and the equilibrium of MB concentration in solution, a series of four different types of adsorption isotherms were applied and verified. Results of data modeling with Langmuir I, Freundlich, Langmuir II and Temkin are reported in Table 6 and Fig. 7.
Based on the statistical parameters (Pearson- r > 0.9949), (R² > 0.9897) and (R²adj > 0.98801) (Table 6), the best isotherm fit was using the Langmuir model. This advocates that the Langmuir isotherm model simulates the adsorption experiment, to a good extent. From the plot, the maximum (monolayer) adsorption capacity, qm, was determined to be 67.6 mg g− 1. From previously reported studies (LIU et al., 2019; ZHANG et al., 2021; XI et al., 2022), biochar exhibited the ability to remove MB from water and the mechanism was explained by Langmuir adsorption models. Additionally, in this study, KL was found to be 0.0137, which further confirms that the biochar can absorb MB dye efficiently, conforming to the Langmuir model.
Table 6. Comparison of the applied isotherms and their parameters for adsorption of MB dye using Babassu coconut mesocarp biochar
A comparison of qm from various reports for MB adsorption in Table 7 indicates that the qm varied across a wide range of 6.8–667 mg g− 1. Engineering biochars enhanced using a catalyst or advanced method may possess a large qm, such as surfactant-modified activated carbon with a qm of 371.8 mg g− 1 (XUE et al., 2022) and nitrogen-doped alkali-leaching sludge-based biochar with a qm of 300.4 mg g− 1 (XI et al., 2022); whilst normal biochars had a lower qm of 6.8 (ZHANG et al., 2021) and 26.5 mg g− 1 (XI et al., 2022).
The qm of biochar may be affected by biochar characteristics, experimental conditions, and the time to equilibrium (NGUYEN et al., 2021). The reduction of biochar grain size can be an alternative to chemical alteration of the biochar. Lately, ball milling has received increasing attention as an approach to manufacture advanced nano-materials due to its high efficiency and eco-friendly features (ZHANG et al., 2021). In this study, it was observed that small changes in the granulometric fraction drastically affects the adsorption capacity.
Adsorbent | Original material | Dose (g L− 1) | SBET (m² g− 1) | qm (mg g− 1) | Temperature (°C) | Reference |
|---|---|---|---|---|---|---|
Biochar | Pig manure | 10 | ni | 16.3 | 25 | LONAPPAN et al. (2016) |
Biochar | Banana pseudostem | 0.5 | 1.2 | 87.3 | 25 | LIU et al. (2019) |
Phosphomolybdic acid modified biochar | Banana pseudostem | 0.5 | 3.7 | 146.2 | 25 | LIU et al. (2019) |
Biochar nanocomposite (ball milled) | Bamboo stakes | 1 | 316.1 | 180.3 | 20 | YU et al. (2021) |
Biochar | Hickory chip | 0.4 | 3.8 | 6.8 | ni | ZHANG et al. (2021) |
Biochar (ball milled) | Hickory chip | 0.4 | 143.3 | 185.07 | ni | ZHANG et al. (2021) |
H2O2 modified biochar (ball milled) | Hickory chip | 0.4 | 9.2 | 310.12 | ni | ZHANG et al. (2021) |
Magnetic biochar | Sewage sludge | 0.5 | 45.5 | 186.0 | 25 | ZENG et al. (2021) |
Biochar | Sludge | 0.5 | 123.4 | 26.5 | 25 | XI et al. (2022) |
Magnetic biochar | Sludge | 0.5 | 316.6 | 300.4 | 25 | XI et al. (2022) |
Surfactant-modified activated carbon | Raw ashitaba waste | 0.05 | 368.6 | 371.8 | 25 | XUE et al. (2022) |
Porous carbon | Polypropylene and Microcystis aeruginosa | 0.8 | 2140 | 667 | ni | LI et al. (2022) |
Activated carbon | Coriandrim sativum | 8 | 193 | 94.9 | 25 | SOUZA et al. (2022) |
Commercial biochar | Babassu coconut mesocarp | 5 | 484.9 | 67.6 | 26 | This work |
| ni – not informed | ||||||
The Freundlich model assumes heterogeneous adsorption. By having the (n) parameter, Freundlich isotherm can describe the heterogeneity of the surface, since homogeneous surfaces have n=1 (MAJD et al., 2021). In this study, it was found n to be 4.08, which indicates adsorption is favorable. The suitability of the Temkin isotherm model was also verified with the same experimental data. The values of KT and b were found to be 0.3092 L mg-1 and 210.75 J mol-1, respectively.
Based on the fit of the isotherm models, we may conclude that the adsorbent surfaces are homogenous once an adsorbate occupies a site; following this, every adsorption site has an equal affinity to the adsorbate. The high values of the index of heterogeneity, with n value of 4.08 (Table 6), suggest favorable adsorption conditions, highlighting the potential for heterogeneous adsorption with physical binding forces and highlight the potential for heterogeneous adsorption with physical binding forces (LONAPPAN et al., 2016; NGUYEN et al., 2022).
Activated babassu coconut mesocarp commercial biochar was for the removal of methylene blue from water. Dye adsorption capacity of this adsorbent was tested varying time of contact, initial concentration of dye, biochar dose and biochar granulometric fraction. Overall, the optimal conditions were found for biochar dosage of 5 g L− 1, initial dye concentration inferior to 300 mg L− 1 and biochar granulometric fraction inferior to 0.15 mm. During the first stage of the adsorption (0 to 40 min), the adsorption efficiency was > 60%. The reaction rate then increased gradually to 240 min. The adsorption kinetic and isotherm was best described by Elovich and monolayer adsorption model, respectively. Finally, the activated babassu coconut mesocarp commercial biochar is an alternative and promising adsorbent for water treatment.
Acknowledgements
We acknowledge the Brazilian Institute of Space Research (INPE) for the SBET analysis presented in this work.
The authors declare no competing interests.
The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.
- AHMAD, M., LEE, S. S., DOU, X., MOHAN, D., SUNG, J. K., YANG, J. E., & OK, Y. S. (2012). Effects of pyrolysis temperature on soybean stover-and peanut shell-derived biochar properties and TCE adsorption in water. Bioresource Technology, 18, 536
- AHMAD, M. A., PUAD, N. A. A., & BELLO, O. S. (2014). Kinetic, equilibrium and thermodynamic studies of synthetic dye removal using pomegranate peel activated carbon prepared by microwave-induced KOH activation. Water Resources and Industry, 6, 18–35
- AMBROZ, F., MACDONALD, T. J., MARTINS, V., & PARKIN, I. P. Evaluation of the BET theory for the characterization of meso and microporous MOFs. Small Methods 2018, Wiley Online Library. https://onlinelibrary.wiley.com/doi/10.1002/smtd.201800173
- ASTM. (2013). American Society for Testing Materials. ASTM D1762-84 Standard Test Method for Chemical Analysis of Wood Charcoal. West Conshohocken, PA: ASTM International
- CAPONI, N., COLLAZZO, G. C., JAHN, S. L., DOTTO, G. L., MAZUTTI, M. A., & FOLETTO, E. L. (2017). Use of Brazilian Kaolin as Potential Low-cost Adsorbent for the Removal of Malachite Green from Colored Effluents.Materials Research, 20,
- CASTIGLIONI, M., RIVOIRA, L., INGRANDO, I., MEUCCI, L., BINETTI, R., FUNGI, M. … BRUZZONITI, M. C. (2022). Biochars intended for water filtration: A comparative study with activated carbons of their physicochemical properties and removal efficiency towards neutral and anionic organic pollutants. Chemosphere, 288(2), 132538. https://doi.org/10.1016/j.chemosphere.2021.132538
- CHOUDHARY, M., KUMAR, R., & NEOGI, S. (2020). Activated biochar derived from Opuntia ficus-indica for the efficient adsorption of malachite green dye, Cu+ 2 and Ni + 2 from water. Journal of Hazardous Materials, 392, 122441
- DAWOOD, S., GUPTA, T., & SEN, T. K. (2017). Adsorptive removal of methylene blue (MB) dye at kaolin clay-water interface: kinetics, isotherm modelling and process design. In: T.K. Sen (Ed.) Clay Minerals: Properties, Occurrence and Uses. p. 209–236,
- EMBRAPA – Empresa Brasileira de Pesquisa Agropecuária. (1997). Manual de Métodos de Análise de Solo (p. 212). Rio de Janeiro: EMBRAPA
- EN. (2009). European Normalization. EN 12915-1 Products Used for the Treatment of Water Intended for Human Consumption. Granular Activated Carbon. Virgin Granular Activated Carbon. Comite Europeen de Normalisation (CEN)
- FEITOSA, A. A., TEIXEIRA, W. G., RITTER, E., RESENDE, F. A., & KERN, J. (2020). Caracterização química de amostras de biocarvão de casca de banana e bagaço de laranja carbonizados a 400 e 600°C. Revista Virtual de Química, 12(4), 901–912
- GANG, D., AHMAD, Z. U., LIAN, Q., YAO, L., & ZAPPI, M. E. (2021). A review of adsorptive remediation of environmental pollutants from aqueous phase by ordered mesoporous carbon.Chemical Engineering Journal, 403,
- GIRI, B. S., SONWANI, R. K., VARJANI, S., CHAURASIA, D., VARADAVENKATESAN, T., CHATURVEDI, P. … PANDEY, A. Highly efficient bio-adsorption of Malachite green using Chinese Fan-Palm Biochar (Livistona chinensis). Chemosphere, 287, Part 3, 132282, 2022.
- IAC – Instituto de Agronômico de Campinas. (2009). Métodos de Análise Química, Mineralógica e Física de Solos do Instituto Agronômico de Campinas. Boletim Técnico, 106, 77
- KISHOR, R., SARATALE, G. D., SARATALE, R. G., FERREIRA, L. F. R., BILAL, M., IQBAL, H. M. N., & BHARAGAVA, R. N. (2021). Efficient degradation and detoxification of methylene blue dye by a newly isolated ligninolytic enzyme producing bacterium Bacillus albus MW407057 Colloids Surface. B, 206, 111947
- LI, L., LV, Y., WANG, J., JIA, C., ZHAN, Z., DONG, Z., & LIU, L. (2022). ZHU, X. Enhance pore structure of cyanobacteria-based porous carbon by polypropylene to improve adsorption capacity of methylene blue. Bioresource Technology, 343, 126101
- LI, L., YANG, M., LU, Q., ZHU, W., & MA, H. (2019). ; DAI, L. Oxygen-rich biochar from torrefaction: A versatile adsorbent for water pollution control.Bioresource Technology, 294,
- LIU, S., LI, J., XU, S., WANG, M., ZHANG, Y., & XUE, X. (2019). A modified method for enhancing adsorption capability of banana pseudostem biochar towards methylene blue at low temperature. Bioresource Technology, 282, 48–55
- LONAPPAN, L., ROUISSI, T., DAS, R. K., BRAR, S. K., RAMIREZ, A. A., VERMA, M. … VALERO, J. R. (2016). Adsorption of methylene blue on biochar microparticles derived from different waste materials. Waste Management, 49, 537–544
- MAIA, L. S., SILVA, A. I. C., CARNEIRO, E. S., MONTICELLI, F. M., PINHATI, F. R., & MULINARI, D. R. (2021). Activated Carbons From Palm Fibres Used as an Adsorbent for Methylene Blue Removal. Journal of Polymers and the Environment, 29, 1162–1175. https://doi.org/10.1007/s10924-020-01951-0
- MAJD, M. M., KORDZADEH-KERMANI, V., GHALANDARI, V., ASKARI, A., & SILLANPÄÄ, M. (2022). Adsorption isotherm models: A comprehensive and systematic review (2010 – 2020). Science of The Total Environment, 812, 151334
- MARQUES, J. P., SILVA, E. A. F., PATINHA, C., KASEMODEL, M. C., & RODRIGUES, V. G. (2019). Adsorption of lead (Pb) in weathered tropical soil (Ribeira Valley region – Brazil). Earth Sciences Research Journal, 23(4), 385–395
- NGUYEN, X. C., NGUYEN, T. T. H., NGUYEN, T. H. C., LE, Q. V., VO, T. Y. B., TRAN, T. C. P. … NGUYEN, D. D. (2021). Sustainable carbonaceous biochar adsorbents derived from agro-wastes and invasive plants for cation dye adsorption from water. Chemosphere, 282, 131009
- NIDHEESH, P. V., ZHOU, M., & OTURAN, M. A. (2018). An overview on the removal of synthetic dyes from water by electrochemical advanced oxidation processes. Chemosphere, 197, 210–227
- OVEISI, M., ASLI, M. A., & MAHMOODI, N. M. (2018). MIL-Ti metal organic frameworks (MOFs) nanomaterials as superior adsorbents: synthesis and ultrasound-aided dye adsorption from multicomponent wastewater systems. Journal of Hazardous Materials, 347, 123–140
- ROY, W. R., KRAPAC, I. G., CHOU, S. F. J., & GRIFFIN, R. A. (1992). Batch-type Procedures for Estimating Soil Adsorption of Chemicals. Risk Reduction Engineering Laboratory, Cincinnati, OH. Technical Report. United States Environmental Protection Agency,
- SILVERSTEIN, R. M., WEBSTER, F. X., & KIEMLE, D. J. (2007). Identificação espectrométrica de compostos orgânicos. LTC
- SONWANI, R. K., SWAIN, G., GIRI, B. S., & SINGH, R. S. (2020). RAI, B. N. Biodegradation of Congo red dye in a moving bed biofilm reactor: Performance evaluation and kinetic modeling. Bioresrce Technology, 302, 122811
- SOUZA, C. C., SOUZA, L. Z. M., YILMAZ, M., OLIVEIRA, M. A., BEZERRA, A. C. S., SILVA, E. F. … MACHADO (2022). A. R. T. Activated carbon of Coriandrum sativum for adsorption of methylene blue: Equilibrium and kinetic modeling. Cleaner Materials, 3, 100052
- VRÎNCEANU, N. Q., MOTELICA, D. M., DUMITRU, M., CALCIO, I., TANASE, V., & PREDA, M. (2019). Assessment of using bentonite, dolomite, natural zeolite and manure for the immobilization of heavy metals in a contaminated soil: The Copsa Mica case study (Romania). 176,336–341,
- XI, J., ZHANG, R., YE, L., DU, X., & LU, X. (2022). Multi-step preparation of Fe and Si modified biochar derived from waterworks sludge towards methylene blue adsorption. Journal of Environmental Management, 304, 114297
- XUE, H., WANG, H., XU, Q., DHAOUADI, F., SELLAOUI, L., SELIEM, M. K. … LI, Q.. Adsorption of methylene blue from aqueous solution on activated carbons and composite prepared from an agricultural waste biomass: A comparative study by experimental and advanced modeling analysis.Chemical Engineering Journal, 430, Part 2, 132801, 2022.
- YAO, X., JI, L., GUO, J., GE, S., LU, W., CAI, L. … ZHANG, H. (2020). Magnetic activated biochar nanocomposites derived from wakame and its application in methylene blue adsorption.Bioresource Technology, 122842,
- YU, F., TIAN, F., ZOU, H., YE, Z., PENG, C., HUANG, J. … WEI, X. (2021). GAO, B. ZnO/biochar nanocomposites via solvent free ball milling for enhanced adsorption and photocatalytic degradation of methylene blue. Journal of Hazardous Materials, 415, 125511
- ZENG, H., QI, W., ZHAI, L., WANG, F., & ZHANG, J. (2021). LI, D. Magnetic biochar synthesized with waterworks sludge and sewage sludge and its potential for methylene blue removal. Journal of Environmental Chemical Engineering, 9(5), 105951
- ZHANG, X., TIAN, J., WANG, P., LIU, T., AHMAD, M., ZHANG, T. … SONG, J. (2022). Highly-efficient nitrogen self-doped biochar for versatile dyes’ removal prepared from soybean cake via a simple dual-templating approach and associated thermodynamics. Journal of Cleaner Production, V332, 130069
- ZHANG, Y., ZHENG, Y., YANG, Y., HUANG, J., ZIMMERMAN, A. R., CHEN, H. … GAO, B. (2021). Mechanisms and adsorption capacities of hydrogen peroxide modified ball milled biochar for the removal of methylene blue from aqueous solutions. Bioresource Technology, 337, 125432