A surfactant-modified coal fly ash was developed as a multifunctional adsorbent for the removal of organic pollutants from wastewater. Sodium dodecyl sulfate (SDS) was used to modify the surface of coal fly ash (CFA). The modified CFA was characterized using scanning electron microscopy (SEM), surface porosity analyzer, thermogravimetric analysis (TGA) and Fourier transform infrared (FTIR) spectroscopy. The results showed that loading CFA with SDS not only improved the functionality and surface morphology of the raw ash for the adsorption of organic pollutants, but also enhanced its thermal stability. The efficiency of the modified fly ash was tested in terms of removal of two non-polar organic pollutants namely chlorobenzene (CB) and nitrobenzene (NB) from aqueous phase. The maximum uptake capacity of chlorobenzene and nitrobenzene with SDS-modified coal fly ash (SCFA) was 225 mg/g and 90 mg/g, respectively. The kinetic analysis was done by controlled kinetic models, i.e., pseudo first and second order kinetic models. The results showed that adsorption of CB and NB onto SCFA followed a pseudo second order kinetic model. The adsorption of chlorobenzene was exothermic over the modified adsorbent while nitrobenzene showed an endothermic behavior. The isotherm analysis depicted the multilayer adsorption of both pollutants onto the surface of the surfactant modified adsorbent. This work has shown that surface modification using surfactants can be a viable option to enhance the adsorption capacity of fly ash for pollutants removal.

• An adsorbent was synthesized from waste fly ash for the abatement of pollutants from water.

• Surface modifications of ash based adsorbent were analyzed through several characterization techniques.

• Detailed parametric study is done to explore the adsorption behavior of nitro benzene and chlorobenzene pollutants.

• Modification of ash with sodium dodecyl sulfate surfactant proves to be beneficial and it enhances the uptake capacity manifold.

Water pollution is among the major consequences of rapid industrialization in many parts of the world. To ensure sustainable fresh water supplies, effective wastewater treatment technologies are needed. Treatment technologies such as advanced oxidation processes, biochemical, coagulation, ion-exchange, electrolysis, adsorption and reverse osmosis have been deployed for wastewater treatment and conservation (Gupta et al. 2012; Ayanda 2014). The application of wastewater treatment techniques is typically gauged based on installation, operational and maintenance cost at commercial level. The cost of water treatment using different processes ranges from 10 to 450 $/m3 of purified water, except the adsorption process where the cost usually varies from 5 to 200$/m3 of treated water. Adsorption is considered as an attractive technology because of its effectiveness in treating wastewater containing pollutants at low concentration and the availability of different inexpensive materials from industrial and agriculture waste that could be potentially used as adsorbents (Mo et al. 2018; Hossain et al. 2020). Among them, waste fly ash is a promising material that can be utilized as an adsorbent. Wang et al. worked on microwave irradiated coal fly ash and used it as Fenton like catalyst for the treatment of polyacrylamide contaminated water. They reported 75% reduction in total organic carbon (TOC) under optimized experimental conditions (Wang et al. 2019).

He et al. synthesized A-type zeolite from fly ash sampled from thermal power plant for the removal of nickel cations from wastewater. The adsorbent achieved 94% removal efficiency and corresponding uptake capacity of 47 mg/g (He et al. 2020). A low-cost filter media from fly ash was prepared and characterized by Sanas et al. The synthesized filter media was used for the reduction of total solids, biochemical oxygen demand (BOD) and chemical oxygen demand (COD) present in aqueous effluent. With a 10 cm thick layer of ash, they reported 70% reduction in total dissolved solids and 65 and 66% decrease in BOD and COD load, respectively (Sanas et al. 2016). Laghari et al. examined the treatment of burnt coal, in fly ash form, for dyes adsorption from industrial effluent. The results showed that by using optimum dosage (4 g/L) of synthesized adsorbent, there was a significant reduction of chemical oxygen demand (54%), color (76%), turbidity (72%) and total suspended solids (98%) from dye-containing effluent (Laghari et al. 2015). Literature reveals that waste coal fly ash has great prospects in applications for environmental remediation, particularly in wastewater treatment. Considering the potential of fly ash for wastewater treatment, surface modification of coal fly ash without converting it to secondary material could evolve as a straightforward and simple route to synthesize an adsorbent for treatment of wastewater.

Materials

The raw coal fly ash (CFA) was collected from ICI soda ash plant, Khewra Salt Range, Pakistan. The modification of CFA was done by using reagent grade sodium dodecyl sulfate (SDS, Duksan Pure Chemicals, Korea). Nitrobenzene (97%, NB) was purchased from Riedel-de Haën (Germany), hydrochloric acid was acquired from Sigma—Aldrich (China), sodium hydroxide was purchased from Merck (Germany), and chlorobenzene (99.5%, CB) was supplied by RCI Labscan Limited (Thailand).

Material modification

Raw CFA was sieved using W.S. Tyler Ro-Tap Shaker (EW-59986-62) and undersize of 80 mesh Tyler standard screen was collected, washed with distilled water and oven-dried at 105 °C. The dried CFA was then modified using anionic surface-active agent, SDS. Required amount of SDS surfactant was dissolved in the specified amount of distilled water to prepare the surfactant solution of 55 mmol/L. For the activation of the fly ash, CFA powder was mixed in SDS solution in a ratio of 2:125 (W/V, g/mL) and the resultant mixture was stirred using a magnetic stirrer (Wiggen Hauser, MSC digital, USA) at 1,000 rpm for 4 h. The particular ratio of fly ash to surfactant solution was selected to keep the weight ratio of fly ash to surface active agent as 1:1 to avoid aggregation of surfactant molecules on the surface of CFA. After 4 h of mixing, dispersed particles were allowed to settle down and solid residue was collected after filtration. The solid residue was then dried in a vacuum oven (Chincan, DZF 6051, China) at 60 °C for 2 h. The modified CFA was then stored in closed glass bottles for subsequent use. The prepared material was abbreviated as SDS-modified coal fly ash (SCFA).

Batch experimentation

The removal efficiency of CB and NB was estimated from Equation (1):
(1)
where Co and Cf represent initial and final concentrations (ppm) of CB and NB and the equilibrium amount of adsorption (mg/g) was determined by using:
(2)
where ‘V’ is volume (solution) in liters and ‘W’ is adsorbent amount in grams.

Instrumentation

A Fourier transform infrared (FTIR- JASCO-4100) spectrophotometer was used to detect various functional groups present on the surface of the modified sample. In this regard, the transmittance spectrum was recorded within the 4,000–500 cm−1 wavenumber range. Thermal behavior of CFA and SCFA was analyzed using thermogravimetric analyzer (Q600 SDT, TA instruments, USA). The accurate weight sample was heated at a rate of 10 °C/min from atmospheric to 800 °C under continuous flow rate of N2 set at 20 mL/min. Field emission scanning electron microscope (FESEM, MIRA3 TESCAN) was used to capture the images of CFA and SCFA for surface morphology analysis. Surface area and pore size distribution were determined by analyzing the CFA and SCFA through Micromeritics ASAP 2020 surface area analyzer. During analysis, the sample was degassed under vacuum at high temperature and then N2 adsorption-desorption curve was recorded to determine the surface area and pore size distribution.

Material characterization

The FTIR scans of CFA and SCFA are illustrated in Figure 1(a). The broad band around 3,440 cm−1 and the peak corresponding to 1,639 cm−1 can be assigned to O–H stretching and bending vibrations, respectively. This indicates the presence of molecular water in the samples and the intensification of these peaks in case of SCFA suggests that activation process probably induced more water in the fly ash (Eteba et al. 2022). The characteristic band appearing in CFA at 1,111 cm−1 may be associated with the asymmetric stretching vibrations of Si-O-Si and Si-O-Al (Tanzifi et al. 2017). In SCFA, the increase in the intensity and range of this band indicates the electrostatic interactions of the polar active surfactant with the Si-O and Al-O bonds in the ash. The shifting of this band towards lower wavenumber, i.e. 1,053 cm−1, probably resulted from the interactions between –SO4 vibrations and Si-O-Si stretching in SCFA.
Figure 1

(a) FTIR spectra of raw and surfactant modified fly ash. (b) Thermal degradation profiles of CFA and SCFA (solid line: weight loss, dotted lines: derivative weight).

Figure 1

(a) FTIR spectra of raw and surfactant modified fly ash. (b) Thermal degradation profiles of CFA and SCFA (solid line: weight loss, dotted lines: derivative weight).

Close modal

The minor peaks observed in the band range of 2,800–3,000 cm−1 in SCFA are assigned to the C-H symmetric and asymmetric stretching vibrations corresponding to –CH2 and –CH3 alkyl groups. The new sharp peaks appearing in SCFA at 1,384 and 1,429 cm−1 may correspond to the C-H bending vibrations of alkane and strong S = O stretching of sulfate in SDS. The doublet bands at 798 and 788 cm−1 and the peak at 563 cm−1 can be attributed to the rocking motion associated with CH2 groups and C-C present in the hydrocarbon part of the surfactant. The appearance of these bands in the FTIR scan of SCFA clearly indicates the presence of surfactant on the fly ash surface. The thermogravimetric (TG) and derivative thermogravimetric (DTG) profiles of CFA and SCFA are presented in Figure 1(b). The degradation of both samples can be viewed in terms of three distinct regions. The first region (up to 100 °C) covers the loss of moisture in CFA and SCFA and, as a result, approximately 2% and 0.5% weight loss was observed in this region, respectively. The second region (100–450 °C) is showing desorption of water of hydration along with devolatilization of both CFA and SCFA, thereby, 2% and 1.5% weight loss can be seen, respectively. A kink in the DTG curve of SCFA in the second degradation region is attributed to thermal decomposition of the carbon chain of surfactant in the sample, thus confirming its deposition on CFA. The third stage spans between 450 and 700 °C and approximately 10 and 7% weight loss are experienced by CFA and SCFA, respectively. This weight loss is attributed to the decomposition of residual coal present in the ash (Aslam 2022). The third region is represented by a large peak in the DTG curve and a shift of peak temperature towards lower value for SCFA (∼574 °C) as compared to CFA (610 °C) can also be observed. The resistance to thermal degradation by CFA is probably due to the strong bonding and electrostatic interactions of zeolitic material with alumina and silica present in the ash (Li & Ishiguro 2016; Nguyen et al. 2018). The tailing region in TGA curve represents the residual weight of the samples and it is more in SCFA than CFA which probably resulted from the charring of the organic chain present in SCFA (Tanzifi et al. 2017; Siddiqui et al. 2018; Şenol et al. 2020).

The SEM micrographs of CFA and SCFA are presented as Figure 2(a) and 2(b), respectively. CFA has a rugged surface having irregular, broken, needle-like, spherical, and angular particles, and a network of agglomeration can also be observed on the surface. This heterogeneity in the morphological features of the CFA is imparted by the combustion process and any change in its parameters.
Figure 2

SEM micrographs of (a) raw CFA and (b) SCFA.

Figure 2

SEM micrographs of (a) raw CFA and (b) SCFA.

Close modal

After modification with anionic surfactant, the reduction in the surface roughness of fly ash is observed, this is probably caused by the organic layer developed after the modification with SDS. The disappearance of broken, needled and spherical particles can be noticed in Figure 2(b). The SCFA surface looks desolated, having numerous cracks and fractures, which could be beneficial for the adsorption of pollutants.

The porosity features (i.e., Barrett-Joyner-Halenda (BJH) pore size distribution and Brunauer-Emmett-Teller (BET) surface area) of CFA and SCFA are presented in Figure S1. The BET surface area of the CFA slightly changed from 9.07 m2/g to 9.46 m2/g after surfactant treatment. In the pore size distribution graph, SCFA curve is broadened and lies above the CFA curve, which indicates that surfactant treatment produces more mesopores. As a result, average pore width (inset table) in SCFA is 88.7 Å as compared to 172.9 Å average pore width of CFA surface pores.

Interaction of anionic surfactant with CFA surface both electrostatically (through –SO3− groups) and hydro-phobically (through dodecyl chain) promote the rupture of low-energy intermolecular bonds and reform the CFA surface which is also supported through SEM images. This modification in the surface texture and porosity enhances the adsorption capability of CFA as noticed in the subsequent adsorption experiments.

Pollutant removal process parameters

The effect of SCFA dosage on the removal efficiency of CB and NB is shown in Figure 3. It is evident that the removal efficiency of both pollutants increases with higher solid to liquid ratio up to 0.2 mg/L. Further increase in ratio does not affect the percent removal probably because of thermodynamic equilibrium. Corresponding to equilibrium, SCFA gives almost ∼15% higher removal than CFA for chlorobenzene (CB). Similarly, for NB, around ∼ 25% improvement in removal efficiency can be noticed by using SCFA. Higher removal of pollutants with SCFA may be linked to the surface functional groups as discussed in the FTIR characterization. At a fixed amount of SCFA, the maximum removal of CB was 90% while it was 40% for NB. The higher removal of CB is probably because of its higher electronegativity compared to NB. Since both benzene derivatives (NB and CB) are un-ionizable compounds, ion-exchange, metal anionic surface coordination and electrostatic interactions cannot be considered. Therefore, the adsorption of NB and CB can be supported by ion-dipole interaction, hydrophobic interaction and hydrogen bonding mechanisms (Qin et al. 2007). Keeping in view the asymptotic behavior at higher solid to liquid ratio, the adsorbent dosage was kept constant at 0.2 mg/mL for further adsorption experiments.
Figure 3

Effect of dose of solid sorbent (a) CB onto SCFA; (b) CB on CFA; (c) NB on SCFA; and (d) NB on CFA.

Figure 3

Effect of dose of solid sorbent (a) CB onto SCFA; (b) CB on CFA; (c) NB on SCFA; and (d) NB on CFA.

Close modal

Effect of initial pH

The initial pH of solution plays a significant role in the removal of CB and NB because it not only affects adsorbate but also influences the surface characteristics of adsorbents. The response on uptake of SCFA against varying initial solution pH is presented in Figure 4(a). The effect of pH in terms of point of zero charge for CFA and SCFA is also summarized in Figure 4(b). The point of zero charge (PZC) of CFA and SCFA is 8.6 and 8.0, respectively. The sorbent surface gains net negative charge when the solution pH is higher than PZC and becomes positively charged for pH of solution lower than PZC.
Figure 4

(a) Effect of initial pH (initial concentration = 50 ppm, volume = 100 mL, dosage = 0.2 mg/mL, time = 1 h, T = 30 °C ± 1) on uptake of nitro- and chlorobenzene on SCFA. (b) Point of zero charge analysis of raw FA and SFA.

Figure 4

(a) Effect of initial pH (initial concentration = 50 ppm, volume = 100 mL, dosage = 0.2 mg/mL, time = 1 h, T = 30 °C ± 1) on uptake of nitro- and chlorobenzene on SCFA. (b) Point of zero charge analysis of raw FA and SFA.

Close modal

Figure 4(a) reveals that the uptake capacity of SCFA for CB increases with increasing pH while it decreases with increasing pH for NB. At pH < pHPZC, SCFA will have net positive charge and attract the electronegative chlorine (–Clδ). As a result, uptake slowly increases from 195 mg/g to 220 mg/g. Furthermore, at pH > pHPZC, the adsorbent surface is negatively charged but the adsorption of CB continues to rise from 220 mg/g to 240 mg/g because of electropositive carbon ring which is attracted towards the negative surface of the adsorbent (Aramendía et al. 2003). On the other hand, the behavior of NB is opposite that of CB. It is observed that the increase in solution pH led to a gradual decrease in the NB uptake because of the reduction in the surface positivity of SCFA. This indicates that the dominating nucleophilic oxygen atom (δO = N+–O) has high affinity towards the adsorbent surface due to strong electrostatic force of attraction. But this attraction diminishes as the surface gets negative (i.e., pH > PZC) and it causes strong electrostatic repulsion with the adsorbate, which is induced by the nitro group (δO = N+–O) in nitrobenzene. Thus, the adsorption occurs because of the inductive effect of the benzene ring. Overall, the adsorption of CB is higher than NB, because chlorobenzene possess a high magnitude of the inductive effect, become more reactive (less non-polar, low dipole value) to the electrophilic attack, as compared to nitrobenzene (Heaney 1970).

Kinetic and isotherm studies

The effect of adsorption time on the uptake of CB and NB is presented in Figure S2 and it is observed that the removal of both benzene derivatives increases with time. The initial rapid increase reflects the availability of abundant vacant sites. The adsorption of CB is equilibrated at ∼ 225 mg/g while NB settled at 90 mg/g. Further contact of SCFA with pollutants showed no substantial improvement in the uptake. The experimental data was further analyzed by applying the kinetic models to explore the mechanism of adsorption. The mathematical expressions of both pseudo first and second order kinetic models are presented in Table 1.

Table 1

Model equations and regression results

Kinetic modelRegression resultsCBNB
Pseudo first order

qe & qt are equilibrium and instantaneous uptake (mg/g) and k1 (min−1), first order rate constant
qe,cal 224.9 99.55
k1 (min−12.036 0.961
R2 0.927 0.966
Pseudo second order

k2 (g mg−1 min−1), second order rate constant
qe,cal (mg g−1233.6 100.8
k2 (min−1 g mg−10.022 0.046
R2 0.99 0.978
Kinetic modelRegression resultsCBNB
Pseudo first order

qe & qt are equilibrium and instantaneous uptake (mg/g) and k1 (min−1), first order rate constant
qe,cal 224.9 99.55
k1 (min−12.036 0.961
R2 0.927 0.966
Pseudo second order

k2 (g mg−1 min−1), second order rate constant
qe,cal (mg g−1233.6 100.8
k2 (min−1 g mg−10.022 0.046
R2 0.99 0.978

Figure 5

Adsorption isotherms of CB (a) and NB (b) onto SCFA (volume = 100 mL, dosage = 0.2 mg/mL, T = 30 °C ± 1, solution pH, time = 1 h).

Figure 5

Adsorption isotherms of CB (a) and NB (b) onto SCFA (volume = 100 mL, dosage = 0.2 mg/mL, T = 30 °C ± 1, solution pH, time = 1 h).

Close modal

Adsorption equilibrium was investigated using two and three parameter models as summarized in Table S1 (Chen et al. 2022; Nirmala et al. 2022). The Freundlich isotherm model is suitable for evaluating the heterogeneity of the surface and to investigate multilayer adsorption. The Dubinin Radushkevich (D-R) isotherm model explains the adsorption on heterogeneous surfaces on the basis of gaussian energy distribution. Its parameters are temperature dependent and through them, one may be able to differentiate the physical and chemical adsorption mechanism by evaluating the value of mean free energy per unit molecule of adsorbate. The Hill isotherm model assumes cooperative adsorption phenomenon where the adsorbate influences the other binding sites of the same homogeneous adsorbent. Khan and Koble Corrigan (KC) isotherm models are generalized and represent both Langmuir and Freundlich isotherms under limiting conditions of solution concentration. At low concentrations, these models reduce to Langmuir isotherm and at higher concentrations, they approach the Freundlich isotherm model (Al-Ghouti & Da'ana 2020).

The isotherm model parameters obtained through nonlinear regression of experimental data are presented in Table 2. The Freundlich isotherm reasonably fits the data and produces a fairly high R2 (>0.97) for both CB and NB pollutants. The Freundlich constant, KF, varies from 2.81 × 10−4 to 3.57 × 10−5 with increase in temperature for CB, indicating that it is an exothermic adsorption. For NB, the KF extends from 7.08 × 10−9 to 5.89 × 10−3 when the temperature changes from 293 to 323 K, suggesting the endothermic nature of adsorption. According to D-R isotherm, the value of mean free energy (Ed) is less than 8 kJ/mol for all temperatures. This reflects that the adsorption follows the physisorption mechanism where hydrophobic/organic interactions play a role in the removal of CB and NB from the polluted water (Siddiqui et al. 2018; Şenol et al. 2020).

Table 2

Isotherm parameters value for adsorption of CB and NB onto SFA at different temperatures

Isotherm modelParametersChlorobenzene (CB)
Temperature (K)
Nitrobenzene (NB)
Temperature (K)
293303313323293303313323
Freundlich KF 2.8 × 10−4 2.3 × 10−4 5.4 × 10−4 3.6 × 10−5 7.1 × 10−9 1.1 × 10−6 3.9 × 10−4 5.9 × 10−3
nF 0.213 0.215 0.235 0.202 0.201 0.248 0.344 0.417
R2 0.975 0.985 0.985 0.979 0.993 0.990 0.996 0.979
Dubinin-Radushkevich (D-R) qm 11,856 10,937 8,767 12,124 6,787 4,422 2,347 2,104
KDR 2.6 × 10−4 2.8 × 10−4 2.9 × 10−4 3.6 × 10−4 0.01 0.006 0.003 0.002
Ed 0.043 0.042 0.042 0.037 0.007 0.008 0.012 0.014
R2 0.965 0.979 0.983 0.972 0.978 0.973 0.968 0.918
Hill Qs 27,148 5,286 3,416 10,325 4.7 × 107 1.5 × 106 1.5 × 106 6.3 × 106
KH 48.42 34.51 34.08 47.69 1,508 1,024 1,974 5,831
nH 4.890 5.825 6.194 5.499 4.978 4.032 2.912 2.398
R2 0.967 0.981 0.985 0.972 0.991 0.986 0.994 0.972
Koble Corrigan AKC 4.272 3.981 3.882 3.068 1.352 1.374 2.492 2.736
BKC −0.011 −0.010 −0.009 −0.009 − 0.014 − 0.009 − 0.011 − 0.009
nKC 1.304 1.289 1.281 1.273 0.811 0.896 0.851 0.895
R2 0.945 0.948 0.943 0.940 0.988 0.981 0.987 0.996
Khan Isotherm qm 23,440 10,122 4,993 631 210 787 405 8718
bk 7.6 × 10−5 1 × 10−4 1.3 × 10−4 2 × 10−4 1.2 × 10−4 3.8 × 101 2.1 × 10−4 2.6 × 10−4
ak −101.6 −101.8 −101.7 −102.2 −104 −102 −13.85 −101.81
R2 0.982 0.989 0.999 0.993 0.996 0.991 0.997 0.989
Isotherm modelParametersChlorobenzene (CB)
Temperature (K)
Nitrobenzene (NB)
Temperature (K)
293303313323293303313323
Freundlich KF 2.8 × 10−4 2.3 × 10−4 5.4 × 10−4 3.6 × 10−5 7.1 × 10−9 1.1 × 10−6 3.9 × 10−4 5.9 × 10−3
nF 0.213 0.215 0.235 0.202 0.201 0.248 0.344 0.417
R2 0.975 0.985 0.985 0.979 0.993 0.990 0.996 0.979
Dubinin-Radushkevich (D-R) qm 11,856 10,937 8,767 12,124 6,787 4,422 2,347 2,104
KDR 2.6 × 10−4 2.8 × 10−4 2.9 × 10−4 3.6 × 10−4 0.01 0.006 0.003 0.002
Ed 0.043 0.042 0.042 0.037 0.007 0.008 0.012 0.014
R2 0.965 0.979 0.983 0.972 0.978 0.973 0.968 0.918
Hill Qs 27,148 5,286 3,416 10,325 4.7 × 107 1.5 × 106 1.5 × 106 6.3 × 106
KH 48.42 34.51 34.08 47.69 1,508 1,024 1,974 5,831
nH 4.890 5.825 6.194 5.499 4.978 4.032 2.912 2.398
R2 0.967 0.981 0.985 0.972 0.991 0.986 0.994 0.972
Koble Corrigan AKC 4.272 3.981 3.882 3.068 1.352 1.374 2.492 2.736
BKC −0.011 −0.010 −0.009 −0.009 − 0.014 − 0.009 − 0.011 − 0.009
nKC 1.304 1.289 1.281 1.273 0.811 0.896 0.851 0.895
R2 0.945 0.948 0.943 0.940 0.988 0.981 0.987 0.996
Khan Isotherm qm 23,440 10,122 4,993 631 210 787 405 8718
bk 7.6 × 10−5 1 × 10−4 1.3 × 10−4 2 × 10−4 1.2 × 10−4 3.8 × 101 2.1 × 10−4 2.6 × 10−4
ak −101.6 −101.8 −101.7 −102.2 −104 −102 −13.85 −101.81
R2 0.982 0.989 0.999 0.993 0.996 0.991 0.997 0.989

For the three-parameter isotherm models, Hill isotherm shows a good correlation with the experimental data (i.e. R2 > 0.94) for both NB and CB. The nH value of Hill isotherm model for both CB and NB adsorption is greater than one, which revealed the positive cooperativity in binding (Tanzifi et al. 2017). However, the qs obtained from Hill isotherm model does not follow the exothermic nature of CB, i.e. qs decreases with increase in temperature, but remains constant for NB adsorption. Consequently, the Hill isotherm is not suitable for describing the mechanism of adsorption of CB and NB. The regression of isotherm data using the Koble Corrigan model gives the lowest R2 for CB among all tested isotherm equations. But the R2 is fairly high for the experimental isotherm data of NB. Besides this, nKC is less than 1 for NB adsorption data as shown in Table 2. This indicates that the KC model is not suitable, despite a good correlation coefficient (Ayawei et al. 2017). The Khan isotherms produce high regression coefficient and the uptake calculated through this model agrees with the exothermic nature of CB and endothermic behavior of NB as exhibited by the qs. Therefore, this model can be considered suitable for the adsorption of CB and NB onto SCFA.

Thermodynamics study

Table 3

Thermodynamics parameters for the adsorption of benzene derivatives onto SCFA

Nitrobenzene
ΔHo (kJ mol−1)ΔS° (kJ mol−1 K−1)ΔG° (kJ mol−1) temperature (K)
ΔG° (kJ mol−1) temperature (K)
293 K303 K313 K323 KΔHo kJ mol−1)ΔS° (kJ mol−1 K−1)293 K303 K313 K323 K
60 −10.79 ± 0.02 −0.029 ± 0.0004 −2.35 −2.06 −1.77 −1.48 41.22 ± 4.99 0.123 ± 0.014 5.12 3.88 2.65 1.42
120 −7.62 ± 0.02 −0.014 ± 0.0002 −3.65 −3.51 −3.37 −3.23 28.81 ± 0.21 0.085 ± 0.0006 3.91 3.05 2.21 1.35
180 −7.59 ± 0.08 −0.011 ± 0.0001 −4.58 −4.48 −4.37 −4.27 18.26 ± 0.26 0.054 ± 0.0007 2.47 1.93 1.39 0.85
260 −7.27 ± 0.04 −0.006 ± 0.00009 −5.45 −5.39 −5.32 −5.26 10.08 ± 0.14 0.031 ± 0.0004 0.89 0.58 0.26 −0.05
350 −7.09 ± 0.10 −0.004 ± 0.00005 −5.98 −5.94 −5.91 −5.87 6.02 ± 0.07 0.021 ± 0.0002 −0.21 −0.42 −0.63 −0.84
Nitrobenzene
ΔHo (kJ mol−1)ΔS° (kJ mol−1 K−1)ΔG° (kJ mol−1) temperature (K)
ΔG° (kJ mol−1) temperature (K)
293 K303 K313 K323 KΔHo kJ mol−1)ΔS° (kJ mol−1 K−1)293 K303 K313 K323 K
60 −10.79 ± 0.02 −0.029 ± 0.0004 −2.35 −2.06 −1.77 −1.48 41.22 ± 4.99 0.123 ± 0.014 5.12 3.88 2.65 1.42
120 −7.62 ± 0.02 −0.014 ± 0.0002 −3.65 −3.51 −3.37 −3.23 28.81 ± 0.21 0.085 ± 0.0006 3.91 3.05 2.21 1.35
180 −7.59 ± 0.08 −0.011 ± 0.0001 −4.58 −4.48 −4.37 −4.27 18.26 ± 0.26 0.054 ± 0.0007 2.47 1.93 1.39 0.85
260 −7.27 ± 0.04 −0.006 ± 0.00009 −5.45 −5.39 −5.32 −5.26 10.08 ± 0.14 0.031 ± 0.0004 0.89 0.58 0.26 −0.05
350 −7.09 ± 0.10 −0.004 ± 0.00005 −5.98 −5.94 −5.91 −5.87 6.02 ± 0.07 0.021 ± 0.0002 −0.21 −0.42 −0.63 −0.84

Table 4

Isosteric enthalpy of adsorption of CB and NB onto SCFA

Uptake, qe (mg/g)100150200250300
CB, ΔHx (kJ/mol) −7.12 ± 0.09 − 7.06 ± 0.05 − 7.01 ± 0.03 − 6.96 ± 0.01 −6.93 ± 0.009
NB, ΔHx (kJ/mol) 17.03 ± 0.64 13.72 ± 0.37 11.78 ± 0.25 10.46 ± 0.18 9.47 ± 0.14
Uptake, qe (mg/g)100150200250300
CB, ΔHx (kJ/mol) −7.12 ± 0.09 − 7.06 ± 0.05 − 7.01 ± 0.03 − 6.96 ± 0.01 −6.93 ± 0.009
NB, ΔHx (kJ/mol) 17.03 ± 0.64 13.72 ± 0.37 11.78 ± 0.25 10.46 ± 0.18 9.47 ± 0.14

The authors acknowledge the support of Higher Education Commission, Pakistan through National Research program for Universities for funding this research through project 8039/Punjab/NRPU/R&D/HEC/2017. In addition, Department of Chemical Engineering, UET, Lahore is also acknowledged.

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

The authors declare there is no conflict.

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