In this study, the adsorption abilities of Russula brevipes (RB), Agaricus augustus (AA), and Fomes fomentarius (FF) were evaluated in Basic Red 18 (BR18) and Remazol Brilliant Blue R (RBBR) biosorption from textile effluent. The adsorbents were characterized via Scanning Electron Microscopy (SEM), Energy Dispersive Spectrometer (SEM-EDS), and Fourier transform infrared spectroscopy (FT/IR). Fomes fomentarius presented a low sorption capacity contrary to the two other fungi (RB and AA). RB and AA were selected as potential adsorbents for BR18 and RBBR, respectively. The maximum BR18 removal efficiencies for 10, 25, and 50 mg/L were obtained after 60 min to be 90, 88, and 86%, respectively. The RBBR adsorption efficiencies were 96.4, 96, and 90% for dye concentrations of 10, 25, and 50 mg/L. The adsorption of BR18 onto the RB biomass followed the Freundlich isotherm, while Langmuir is the best isotherm for RBBR sorption's elucidation onto AA fungus biomass. The removal of BR18 by BR biomass was found to follow the pseudo-second order. In contrast, the adsorption of RBBR onto the AA biomass followed Lagergren's pseudo-first order. For both adsorbents, the adsorption was exothermic, feasible, and spontaneous in nature. Finally, the dyes' biosorption process was perfectly achieved onto fungi biomass via physisorption.

  • Three fungi, Russula brevipes (RB), Agaricus augustus (AA), and Fomes fomentarius (FF) were used for dye adsorption.

  • Basic Red BR18 and Remazol Brilliant Blue RBBR dyes were tested for adsorption.

  • Freundlich describe perfectly the sorption process of BR18 dye onto RB fungus.

  • Langmuir is the best isotherm for RBBR sorption's elucidation onto AA fungus biomass.

Graphical Abstract

Graphical Abstract
Graphical Abstract

Although the textile industry shows subsequent growth and contributes to countries' economies, it still suffers from its toxic effluent (Dos Santos et al. 2007). Indeed, textile wastewater is a seriously harmful industrial effluent (Ogugbue & Sawidis 2011). Textile wastewater is one of the most polluting sources, since it has a hazardous mixture of varied toxic compositions: heavy metal, bleaching reagents, sterilizer, dye, and so on (Ben Mansour et al. 2012; Gita et al. 2017). Dye is the basic component in textile manufacturing and one of the most toxic and stiff elements. Thus dye removal from textile wastewater before its discharge is an obligation (Rawat et al. 2018). Several physical, chemical, and combined physicochemical treatments have been employed (Collivignarelli et al. 2019), Advanced oxidation processes (AOPs) were also applied in dye degradation (Pelin et al. 2020; Saleh et al. 2021a), though the removal of dye via various processes showed some limitations, basically in effectiveness and financial charges (Hadj et al. 2019). Activated sludge (Osman et al. 2004) and activated clay (Hsu et al. 1997) were utilized in the dye adsorption process. Indeed, biosorption seems the most suitable process that esteems with the green chemistry concept. The biosorption passes the mentioned limitation by providing more efficient sorption for the contaminated water with the lowest cost (Robinson et al. 2001). This concept has attracted research attention since 1980, thanks to sorbent availability, effortless accessibility, and environmentally friendly property (Saleh et al. 2019).

Biosorption is an efficient method for dye sorption, various organic pollutants, and heavy metals (Schiewer & Wong 2000; Walker & Weatherley 2000). Sundry types of microorganisms, such as bacteria, algae, and fungi, were used for decolorizing dyes from the industry's effluents (Fu & Viraraghavan 2000; Kumari & Abraham 2007; Jamee & Siddique 2019). Admittedly, biosorption via microorganism present advantages, but its sorption capacity depends on which type of biomass was used (Pankaj & Harleen 2011). Because of their availability, fungus seems to be the best adsorbent among the microorganisms. Fungus owns interesting mechanical characterization against abrasion, and they are chemically stable in most acidic and alkaline mediums (Mittal & Gupta 1996). The fungi may be used in two forms, the dead and the live fungi. The dead biomass is more effective for dye and organic pollutant sorption compared with live fungi (Tsezos & Bell 1989). Nityanand et al. (2006) utilized Fomes fomentarius and Phellinus igniarius in methylene blue (MB) and rhodamine B (RB) biosorption (Nityanand et al. 2006).

In this study, the adsorption abilities of Russula brevipes (RB), Agaricus augustus (AA), and Fomes fomentarius (FF) were evaluated in Basic Red 18 (BR18) and Remazol Brilliant Blue R (RBBR) biosorption from textile effluent. These dyes are the most commonly used industrial toxic dyes in textile manufacturing. The Basic Red 18 is an azo cationic dye that presents more than one functional group and is used basically for the textile industry (Fil et al. 2013). Remazol Brilliant Blue is a harmful organic dye (Mechichi et al. 2000). RBBR, which contains anthracene derivatives (Eichlerová et al. 2007), is frequently used in the textile industry because of its high solubility in aqueous solutions (Torgut et al. 2017). Though the removal of Basic Red 18 (BR18) and Remazol Brilliant Blue R (RBBR) from textile wastewater was done efficiently via various processes, these last showed some limitations (Hayat et al. 2015; Routoula & Patwardhan 2020). Therefore, the biodegradation of RBBR, BR18 dye in a biological-based, safe, and eco-friendly method had been preferred more than the other processes (Mallet 2010; Paz et al. 2017). In previous studies, Aspergillus carbonarius (AC) and Penicillium glabrum (PG) were employed for BR18 decolorization (Bouras et al. 2017; Isik et al. 2019). RBBR dye was adsorbed by T. citrinoviride, T. koningiopsis, and Pestalotiopsis (Achmad & Mohamad 2021). Nonetheless, to the best of our knowledge, there is no reported paper on Russula brevipes, Agaricus augustus, and Fomes fomentarius evaluation for BR18 and RBBR bio-sorption abilities. Moreover, the first two fungi present good aptitudes for (BR18) and (RBBR) sorption, contrary to Fomes fomentarius, which does not show any ability for the tested dyes.

Materials

Basic Red 18 (BR18) and Remazol Brillant Blue R (RBBR) were obtained from Sigma–Aldrich. The chemical structure and some properties of the BR18 and RBBR dyes are presented in Table 1. Russula brevipes (RB), Agaricus augustus (AA) and Fomes fomentarius (FF) were obtained from Environmental Biotechnology Laboratory, Mersin University, Turkey. For pH adjustment, sodium hydroxide (NaOH, Sigma–Aldrich) and hydrochloric acid (HCl, Sigma–Aldrich) were used.

Table 1

Chemical structures and some properties of the dyes

Chemical nameChemical structureMolecular formulaMolecular weight (g/mol)UV absorption λmax (nm)
Basic Red 18 (BR18)  C19H25N5Cl2O2 426.34 484 
Remazol Brillant Blue R (RBBR)  C22H16N2Na2O11S3 626.53 590 
Chemical nameChemical structureMolecular formulaMolecular weight (g/mol)UV absorption λmax (nm)
Basic Red 18 (BR18)  C19H25N5Cl2O2 426.34 484 
Remazol Brillant Blue R (RBBR)  C22H16N2Na2O11S3 626.53 590 

Preparation of dead fungi biomass

The fungal biosorbents Russula brevipes, Agaricus augustus, and Fomes fomentarius were collected in Mersin, Turkey. They were brought to the laboratory and washed three times with deionized water to remove contaminants and dried in an oven at 25 °C for 168 h. After the drying step, they were powdered using a grinder and dried at 105 °C for 24 h. The dried, powdered biomass was stored in a desiccator without any further chemical or physical treatment.

Batch experiments

The first step in the batch experiments was the selection of the fungus biomass. The fungus selection experiments were conducted using the three bio sorbents, RB, AA, and FF, and two dyes, BR18 and RBBR. The dyes (BR18 and RBBR) were prepared in a concentration of 25 mg/L and a volume of 50 mL. Bio sorbents were added at the same doses (1 g/L) and agitated at 150 rpm for 1 h at room temperature. The removal efficiency for the concentration of the dye was calculated using Equation (1).
formula
(1)

The effect of pH on BR18 and RBBR adsorptions onto the biomasses was explored on a pH range of 2–10. 1 g/L of the adsorbents was added in a 50 mL solution contains 25 mg/L dyes concentration. The adsorptions occurred at room temperature (25 ± 2 °C) with a rotational speed of 150 rpm for 60 min.

The effects of the adsorbent doses were investigated by adding different amounts (0.25–2.0) g/L to 50 mL solutions with dye concentrations of 25 mg/L at the optimum pH value. The experiments extended over 60 min and occurred at an agitation speed of 150 rpm at room temperature (25 ± 2 °C).

The effects of contact time and the initial concentration on the adsorption process were explored. Known amounts of the biomasses (1 g/L BR and 0.5 g/L AA) were inserted into 50 mL solutions with different initial concentrations (10, 25, 50 mg/L). The experiments extended over 60 min and occurred at an agitation speed of 150 rpm at room temperature (25 ± 2 °C).

Adsorption isotherms

The isotherm experiments were determined as defined previously (Saleh et al. 2021b). The characteristic of the adsorption equilibrium was estimated using Langmuir (Equation (2)) (Langmuir 1918) and Freundlich (Equation (3)) (Freundlich 1906) isotherm equations.
formula
(2)
formula
(3)
where, qe and Ce are the adsorption capacity (mg/g) and the concentration (mg/L) at the equilibrium. KL and KF are Langmuir and Freundlich respectively. Qmax is the maximum adsorption capacity (mg/g) and 1/n is the heterogeneity factor.

Kinetic studies

Kinetic studies were conducted at different contact times (from 0 to 60 min) using 50 mL dye solution volume and C0 of 10, 25 and 50 mg/L at room temperature. After each experiment, the dye concentrations were spectrophotometrically determined at 484 nm for BR18 and 590 nm for RBBR. The kinetic curves were described by the nonlinear forms of the pseudo-first order model (Lagergren 1898) and the pseudo-second-order model (Ho et al. 1996). The nonlinear forms of the pseudo-first order model and the pseudo-second order model are shown in Equations (4) and (5), respectively.
formula
(4)
formula
(5)
where, qt is adsorption capacity at time t (mg/g), t is the time (min), K1 and K2 are the first and second order kinetic constants, respectively.

Characterization of biosorbent

Scanning Electron Microscopy (SEM, Zeiss Supra 55-Germany) analysis was carried out to analyze the biosorbent surface morphology and surface elemental characteristics were analyzed at the same spot via Energy Dispersive Spectrometer (SEM-EDS, Zeiss Supra 55-Germany) simultaneously. The functional groups at the adsorbents' surfaces were scanned at bands 450–4,000 cm−1 by Fourier transform infrared spectroscopy (FT/IR-6700, Jasco).

Characterization

Scanning Electron Microscopy (SEM) analysis was carried out to analyze the biosorbent surface morphology. The Russula brevipes (RB) consisted of non-uniform random layers that made the surface rough and heterogeneous with stream-like channels (Figure 1(a)). After the adsorption process, the channels were filled with dye particles, making the surface smoother (Figure 1(b)). The surface of Agaricus augustus (AA) is also coarse and heterogeneous (Figure 1(c)). The adsorbed dye reduced the heterogeneity of the AA surface. No spaces were noticed at the surface of AA after the adsorption since the dyes filled the spaces between the AA pieces (Figure 1(d)).

Figure 1

SEM images for (a) Raw RB, upper right corner; (b) RB after the adsorption of BR18, upper left corner; (c) Raw AA, lower right corner; (d) AA after the adsorption of RBBR; lower left corner.

Figure 1

SEM images for (a) Raw RB, upper right corner; (b) RB after the adsorption of BR18, upper left corner; (c) Raw AA, lower right corner; (d) AA after the adsorption of RBBR; lower left corner.

Close modal
Figure 2

FTIR spectra for (a) Raw RB (left) and (b) raw AA (right).

Figure 2

FTIR spectra for (a) Raw RB (left) and (b) raw AA (right).

Close modal

The FT-IR spectra of both raw fungal biomass RB and AA present common peaks (Figure 2). At 3,263 cm−1, intense peaks are observed on both spectra that are related to (–OH) stretching; also, it may have represented the stretching of (–NH) groups. Then, the other common peak at 2,924 cm−1 interrelated to (C–H) stretching vibrations. At 1,632 cm−1, one peak detected on raw RB spectra, it is relative to bending (N–H) groups. At range of wave length of 1,555 cm−1, 1,374 cm−1, two peaks were observed and related respectively to (N–H) bending, (–CH3) elongation. Moreover, the peak observed at 533 cm−1 represents (C = O) bending vibration. Finally, a peak identified at 470 cm−1 related to the C–N–C scissoring group. These several functional groups present on both fungal biomass RB and AA (Bayramoglu & Arıcaülay 2008).

Fungal selection

The removal efficiencies and the adsorption capacities are shown in Figure 3. For BR18, the three biomasses had relatively high removal efficiencies. However, RB had the maximum removal efficiency (84%) and adsorption capacity (21 mg/g). The removal efficiencies for AA and FR were 69 and 59%, respectively (Figure 3(a)). The maximum removal efficiency and adsorption capacity of RBBR dye were obtained when the AA biomass was used as an adsorbent. The removal efficiencies and the adsorption capacities for RB and FR were very low (Figure 3(b)). Accordingly, RB was selected for BR18 adsorption while AA was utilized in the adsorption of RBBR.

Figure 3

The removal efficiencies and the adsorption capacities for RB, AA, FF biomasses for (a) BR18 (b) RBBR dyes at experimental conditions (pH 6, initial concentration 25 mg/L, adsorbent amount 1 g/L, and contact time of 60 min).

Figure 3

The removal efficiencies and the adsorption capacities for RB, AA, FF biomasses for (a) BR18 (b) RBBR dyes at experimental conditions (pH 6, initial concentration 25 mg/L, adsorbent amount 1 g/L, and contact time of 60 min).

Close modal

Effects of pH

The effects of pH on the adsorption capacity and the removal efficiency for BR18 and RBBR are shown in Figure 4(a) and 4(b), respectively. The protonation and deprotonation process at the biomass surfaces is controlled by the hydrogen ion concentration (Saleh et al. 2021c). The adsorption of BR18 onto RB biomass increases with the increases in the pH until pH 6. The removal efficiency and the adsorption capacity were 84% and 21 mg/g, respectively. Beyond that (pH 6), the removal efficiency and the adsorption decreased with the increases in pH. Koyuncu & Kul (2020) noticed that the acidic conditions increase the positive charge at the nonliving lichen Pseudevernia furfuracea surface, which repel the cationic dyes and decreases the efficiency (Koyuncu & Kul 2020). At higher pH values, the -OH strong strives for the active sites on the RB surfaces. Another possible reason is that the -OH may be exchanged with dye ions. The maximum removal efficiency of the cationic dye methylene blue by Aspergillus parasiticus was obtaıned at a pH value of 8 (Bouras et al. 2021). For RBBR, the maximum removal efficiency and adsorption capacity were obtained at pH 2, and the pH increase reduced the removal efficiency and the adsorption capacity. The AA biomass achieved an uptake of 78% and an adsorption capacity of 19.5 mg/g. Isik et al. (2021a) successfully utilized polyethyleneimine-modified calcium alginate beads in RBBR adsorption (Isik et al. 2021a). In their works, the removal efficiency decreased with the increases in pH values. Pelosi et al. (2014) demonstrated the pH-RBBR removal curve by the deprotonation of oxygen present in dye at high pH levels (Pelosi et al. 2014). Won et al. (2005) explained the high removal efficiency at lower pH values by the electrostatic forces (Won et al. 2005). The biomass surface gets positively charged at lower pH values, which builds interaction between the negatively charged dye anions and the AA biomass surface.

Figure 4

Effects of pH on the removal efficiencies and the adsorption capacities for (a) BR18 (b) RBBR dyes at experimental conditions (Initial concentration 25 mg/L, adsorbent amount 1 g/L, and contact time of 60 min).

Figure 4

Effects of pH on the removal efficiencies and the adsorption capacities for (a) BR18 (b) RBBR dyes at experimental conditions (Initial concentration 25 mg/L, adsorbent amount 1 g/L, and contact time of 60 min).

Close modal

Effects of adsorbent dose

The effects of the adsorbents doses were investigated and the changes in the removal efficiencies and the adsorption capacities for BR18 and RBBR are shown in Figure 5(a) and 5(b), respectively. For BR18, the removal efficiency increased from 66% to 84% at adsorbent doses of 0.25 and 1 g/L, respectively. After the adsorbent amount of 1 g/L, the increases in the adsorbent doses had little changed the removal efficiency. In contrast, the adsorption capacity decreased with the adsorbent doses increases. The same trend was noticed in the adsorption of RBBR. The removal efficiency increased from 90% at 0.25 g/L dose to reach 96% at 0.50 g/L. Beyond that dose, no noticeable changes were recorded in the RBBR removal efficiency. Also, the adsorption capacity decreased sharply at higher adsorbent doses. Yalvaç & colleagues (2021) presented similar trends for crystal violet removal by Centaurea solstitialis and Verbascum thapsus (Yalvaç et al. 2021).

Figure 5

Effects of the adsorbent dose on the removal efficiencies and the adsorption capacities for (a) BR18 (b) RBBR dyes at experimental conditions (Initial concentration 25 mg/L, pH 6 for BR18 and 2 for RBBR, and contact time of 60 min).

Figure 5

Effects of the adsorbent dose on the removal efficiencies and the adsorption capacities for (a) BR18 (b) RBBR dyes at experimental conditions (Initial concentration 25 mg/L, pH 6 for BR18 and 2 for RBBR, and contact time of 60 min).

Close modal

Effects of initial concentration and the contact time

The changes in the removal efficiencies and the adsorption capacity for BR18 and RBBR corresponding to the initial concentration and the contact time are shown in Figure 6(a)–6(d), respectively. The adsorption of BR 18 onto BR and the adsorption of RBBR onto AA can be considered fast processes. The removal efficiencies sharply increased after the first 5 min for both adsorbents. For 10, 25, and 50 mg/L dyes, the removals of BR18 reached after 5 min 78, 84, and 74%, respectively. The uptakes of RBBR after 5 min for the same initial concentrations were 65, 77, and 75%. The dyes uptakes continued increasing however with a flatter shape. As discussed previously by Saleh et al. (2019) and Isik et al. (2021b), at the start of the adsorption process, the active sites present at the BR and AA surfaces were empty and ready to capture the dyes. At that time the mass transfer from the adsorbate to the adsorbent was high. Thus the removal efficiencies increased sharply. With time, the ready active site numbers decreased as a result from the attaching dyes, so the removal trend became flatter till the steady-state conditions were reached at 60 min. The maximum BR18 removal efficiencies for 10, 25, and 50 mg/L were obtained after 60 min to be 90, 88, and 86%, respectively. The RBBR adsorption efficiencies were respectively 96.4, 96, and 90% for dye concentrations of 10, 25, and 50 mg/L. The adsorption capacities for BR18 dye at initial concentrations of 10, 25, and 50 mg/L were respectively 9, 22, and 43 mg/g. At the same initial concentrations, the RBBR adsorption capacities were 19.3, 48, and 90 mg/g. As the initial concentration increased, the adsorption capacity also increased. The presence of high concentration in the adsorbate side increases the mass transfer between the adsorbate towards the adsorbent because of the diffusion force. Thus the adsorption capacity increased.

Figure 6

Effects of the initial concentration and the contact time on the removal efficiencies and the adsorption capacities for (a) BR18 (adsorbent amount 1 g/L, and pH 6) (b) RBBR (adsorbent amount 0.5 g/L, and pH 2).

Figure 6

Effects of the initial concentration and the contact time on the removal efficiencies and the adsorption capacities for (a) BR18 (adsorbent amount 1 g/L, and pH 6) (b) RBBR (adsorbent amount 0.5 g/L, and pH 2).

Close modal

Adsorption isotherm

Langmuir and Freundlich's models were used to study the adsorption isotherms for BR18 removal by BR and RBBR removal by AA biomass. To increase the precision and to avoid any error in the data transformation process, Origin software (version 2019) was utilized to fit the non-linear forms for both isotherm models (Boulinguiez et al. 2008; Belhachemi & Addoun 2011). Table 2 shows the results fitting to the non-linear forms of the isotherms.

Table 2

Isotherms fitting results

IsothermParameterBR18 onto BRRBBR onto AA
Langmuir KL 0.070 ± 5.334E-4 0.599 ± 0.059 
Qmax 124.802 ± 0.693 117.909 ± 4.387 
Reduced Chi-square 0.166 2.976 
R-square (COD) 0.998 0.998 
Adj. R-square 0.988 0.997 
Freundlich Kf 9.271 ± 0.016 40.915 ± 3.722 
1/n 0.776 ± 0.04348 0.480 ± 0.062 
Reduced Chi-square 0.1468 25.968 
R-square (COD) 0.999 0.989 
Adj. R-square 0.999 0.979 
IsothermParameterBR18 onto BRRBBR onto AA
Langmuir KL 0.070 ± 5.334E-4 0.599 ± 0.059 
Qmax 124.802 ± 0.693 117.909 ± 4.387 
Reduced Chi-square 0.166 2.976 
R-square (COD) 0.998 0.998 
Adj. R-square 0.988 0.997 
Freundlich Kf 9.271 ± 0.016 40.915 ± 3.722 
1/n 0.776 ± 0.04348 0.480 ± 0.062 
Reduced Chi-square 0.1468 25.968 
R-square (COD) 0.999 0.989 
Adj. R-square 0.999 0.979 

The removal of BR18 by the RB biomass has high correlation coefficients for both isotherms. However, Freundlich had a higher correlation coefficient and lower error value. According to the Freundlich isotherm, the adsorption of BR18 onto the RB biomass occurred on a heterogeneous surface through multilayers (Zhou et al. 2019). In contrast, the adsorption of RBBR onto AA biomass was found to follow the Langmuir isotherm for the same reasons. In this isotherm, the adsorption occurs in a homogenous monolayer, and the adsorption is limited by finite numbers of active sites at the adsorbent surface. According to the Langmuir isotherm, no interaction between the adsorbed matters will be present (Siwek et al. 2019). The adsorption of malachite green onto low-cost adsorbent from the exudate of Lannea coromandelica (Houtt) also followed the Langmuir isotherm (Mate et al. 2021). For both BR18 and RBBR, the adsorption was found to be favorable since the n-factor lies in the range of 1–10, and RL (RL = 1/ (1 + KL ×Co)) is between 0 and 1.

Adsorption kinetics

Lagergren's pseudo-first-order and pseudo-second-order models were used to represent the kinetic terms for the adsorptions of BR18 onto BR and RBBR onto AA. The nonlinear curves for Lagergren's pseudo-first-order and pseudo-second-order models for BR18 and RBBR dyes are shown in Figures 7 and 8, respectively. The removal of BR18 by BR biomass was found to follow the pseudo-second-order (higher R2 and lower chi-square error). Yildirim (2020) utilized a crosslinked Pleurotus ostreatus-based bio-composite in malachite green (MG) and methylene blue (MB) adsorption. The adsorptions of both cationic dyes were found to follow the pseudo-second-order (Yildirim 2020). In contrast, the adsorption of RBBR onto the AA biomass followed Lagergren's pseudo-first-order. Bouras and colleagues (2021) stated that the adsorption of phenol red dye onto Aspergillus parasiticus followed Lagergren's pseudo-first-order (Bouras et al. 2021). The kinetic parameter and the statistical error calculations for the fitting process were obtained with the aid of Origin software (version 2019), as shown in Table 3.

Table 3

Lagergren's pseudo-first-order and pseudo-second-order for the adsorption of BR18 and RBBR onto the BA and AA biomasses

BR18RBBR
1st order kinetic model 
Concentration (mg/L) 10 25 50 10 25 50 
k1 (1/min) 0.476 ± 0.107 0.453 ± 0.098 0.459 ± 0.085 0.431 ± 0.022 0.331 ± 0.012 0.431 ± 0.098 
qe (mg/g) 8.578 ± 0.192 21.122 ± 0.489 40.837 ± 0.792 19.116 ± 0.113 47.628 ± 0.252 84.726 ± 2.193 
Reduced Chi-sqr 0.146 0.941 2.474 0.050 0.243 18.878 
R-square (COD) 0.990 0.998 0.992 0.999 0.999 0.987 
Adj. R-square 0.988 0.987 0.991 0.999 0.999 0.984 
2nd order kinetic model 
Concentration (mg/L) 10 25 50 10 25 50 
k2 (g/mg.min) 0.146 ± 0.053 0.0532 ± 0.018 0.030 ± 0.009 0.065 ± 0.003 NA NA 
qe (mg/g) 8.838 ± 0.186 21.822 ± 0.463 42.070 ± 0.713 19.615 ± 0.050 45.744 ± 1.840 82.737 ± 3.411 
Reduced Chi-sqr 0.076 0.467 1.119 0.050 16.25 37.228 
R-square (COD) 0.995 0.995 0.998 0.999 0.964 0.975 
Adj. R-square 0.994 0.994 0.996 0.999 0.955 0.968 
BR18RBBR
1st order kinetic model 
Concentration (mg/L) 10 25 50 10 25 50 
k1 (1/min) 0.476 ± 0.107 0.453 ± 0.098 0.459 ± 0.085 0.431 ± 0.022 0.331 ± 0.012 0.431 ± 0.098 
qe (mg/g) 8.578 ± 0.192 21.122 ± 0.489 40.837 ± 0.792 19.116 ± 0.113 47.628 ± 0.252 84.726 ± 2.193 
Reduced Chi-sqr 0.146 0.941 2.474 0.050 0.243 18.878 
R-square (COD) 0.990 0.998 0.992 0.999 0.999 0.987 
Adj. R-square 0.988 0.987 0.991 0.999 0.999 0.984 
2nd order kinetic model 
Concentration (mg/L) 10 25 50 10 25 50 
k2 (g/mg.min) 0.146 ± 0.053 0.0532 ± 0.018 0.030 ± 0.009 0.065 ± 0.003 NA NA 
qe (mg/g) 8.838 ± 0.186 21.822 ± 0.463 42.070 ± 0.713 19.615 ± 0.050 45.744 ± 1.840 82.737 ± 3.411 
Reduced Chi-sqr 0.076 0.467 1.119 0.050 16.25 37.228 
R-square (COD) 0.995 0.995 0.998 0.999 0.964 0.975 
Adj. R-square 0.994 0.994 0.996 0.999 0.955 0.968 
Figure 7

(a) Lagergren's pseudo-first-order for BR18 adsorption, (b) pseudo-second-order for BR18 adsorption.

Figure 7

(a) Lagergren's pseudo-first-order for BR18 adsorption, (b) pseudo-second-order for BR18 adsorption.

Close modal
Figure 8

(a) Lagergren's pseudo-first-order for RBBR adsorption, (b) pseudo-second-order for RBBR adsorption.

Figure 8

(a) Lagergren's pseudo-first-order for RBBR adsorption, (b) pseudo-second-order for RBBR adsorption.

Close modal

Adsorption thermodynamic

The Gibbs free energy, enthalpy, and entropy for the removal of BR18 by BR biomass and RBBR by AA biomass were determined at different temperatures (298, 303, 308, and 313 K). The relationship between the 1/T and the ln K is presented in Figure 9(a) and 9(b) for BR18 and RBBR, respectively.

Figure 9

The relationship between normal logarithm of K and the inverse of temperature for (a) BR18 (b) RBBR.

Figure 9

The relationship between normal logarithm of K and the inverse of temperature for (a) BR18 (b) RBBR.

Close modal

The results for multiplication of slopes with the universal gas constant were enthalpy changes for the adsorption of BR18 and RBBR. The enthalpies for the adsorptions of BR18 onto BR biomass and RBBR onto AA were −98.01 and −126.82 kJ/mol, respectively. Both of the adsorptions were exothermic since the changes in the enthalpy were negative. In contrast, the adsorption of malachite green onto Lannea coromandelica was endothermic with positive sign value for enthalpy (Mate et al. 2021). The change in the entropy was found by multiplying the line intercepts with the universal gas constant. The entropy changes for the removal of BR18 and RBBR were −312.37 and −399.21 J/mol.K, respectively. The negative signs of the entropy changes for both adsorptions indicate reductions in the randomness of the BR and AA surface at the end of the adsorption process (Dawood et al. 2017). In a previous study, the change in the entropy for the Congo red adsorption onto Eichhornia crassipes (BSEC) biomass was positive (Roy & Mondal 2019). The Gibbs free energy was calculated as shown in the equation. The Gibbs free energies for the adsorption of BR18 onto BR at temperatures of 298, 303, and 308 K were −4.29, −3.37, and −1.80 kJ/mol, respectively (Table 4). The Gibbs free energies for RBBR removal by AA were −7.86, −5.86, and −3.87 kJ/mol (Table 4). The adsorption processes were found to be feasible and spontaneous in nature for both dyes (Gibbs's free energies are negative) (Biswas et al. 2020). The spontaneously occurring of biosorption of cationic dyes was reported previously in many researches (Nethaji et al. 2013; Mittal et al. 2015). Also, the adsorptions of BR18 onto BR and RBBR onto AA were physisorption since the values of Gibbs free energy are lower than 20 kJ/mol (Hikmat et al. 2014). In addition to that, the lower temperatures were found to be more favorable since the Gibbs' free energy values increased with temperature.

Table 4

Thermodynamic parameter for the BR18 and RBBR

BR18
RBBR
T (°C)ΔH (kJ/mol)ΔS (J/mol.k)ΔG (kJ/mol)ΔH (kJ/mol)ΔS (J/mol.k)ΔG (kJ/mol)
25 −98.01 −312.37 −4.93 −126.82 −399.21 −7.86 
30   −3.37   −5.86 
35   −1.8   −3.87 
BR18
RBBR
T (°C)ΔH (kJ/mol)ΔS (J/mol.k)ΔG (kJ/mol)ΔH (kJ/mol)ΔS (J/mol.k)ΔG (kJ/mol)
25 −98.01 −312.37 −4.93 −126.82 −399.21 −7.86 
30   −3.37   −5.86 
35   −1.8   −3.87 

To sum up all the reported results, Russula brevipes and Agaricus augustus successfully fulfilled their role as sorbent biomass respectively for Basic Red (BR18) and Remazol Blue R (RBBR). In contrast, Fomes fomentarius did not present sorption efficiency. The Basic Red (BR18) was adsorbed thoroughly onto RB fungus with a removal efficiency of 90% (for a concentration of 10 mg/L). AA fungus was the best biosorbent for Remazol Blue R (RBBR) removal (removal efficiency reached 96% for a 10 mg/L concentration). The adsorption of BR18 onto RB biomass increased with the increases in the pH until pH 6. Beyond that (pH 6), the removal efficiency and the adsorption decreased with the increases in pH. For RBBR, the maximum efficiency and adsorption capacity were obtained at pH 2, and pH increase reduced the removal efficiency and the adsorption capacity. The adsorption of BR 18 onto BR and the adsorption of RBBR onto AA can be considered fast processes. The removal efficiencies sharply increased after the first 5 min for both adsorbents. The adsorption of BR18 onto RB was described by Freundlich isotherms. Nevertheless, Langmuir was the suitable isotherm for RBBR sorption onto AA. The kinetic study showed that the removal of BR18 sorption onto RB was shadowed by a pseudo-first-order model, while the RBBR sorption onto AA was followed by a pseudo-second-order model. Thermodynamic adsorption's analysis confirms that the sorptive nature of the tested dyes is physisorption. Briefly, RB and AA biomass fungi showed promising performance for textile dye removal, which leads to use as efficient bio, green, ecofriendly, and low-cost adsorbents.

All relevant data are included in the paper or its Supplementary Information.

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