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Due to its widespread consumption, paracetamol (PCT) has emerged as one of the leading contaminants that pollute water. Herein, a PCT removal of 99.6% was achieved using chemically activated carbon (CAC), derived from bamboo sawdust using KOH/FeCl3 as an activating agent, at optimal conditions of PCT (20 mg/L), CAC (0.5 g/L), contact time (90 min), and pH (8). Kinetic study revealed that the PCT adsorption process followed the pseudo-second-order kinetic model (R2 = 0.99), indicating that chemical adsorption dominated the adsorption mechanism. On the other hand, isotherm experimental data were best described by the Langmuir (R2 = 0.98) and Freundlich (R2 = 0.96) models. CAC had a maximum Langmuir monolayer capacity of 188.67 mg/g at a PCT concentration of 120 mg/L. Moreover, the Redlich–Peterson model gave the best fit (R2 = 0.99) to the experimental data, confirming that PCT adsorption was monolayer adsorption onto the heterogeneous surface. Thermodynamically, the PCT adsorption was exothermic, spontaneous, and favorable. The reusability study depicted that CAC can be successfully reused for five consecutive adsorption–desorption cycles. Furthermore, the application of CAC to environmental samples showed interesting results. The overall adsorption study indicated that CAC could serve as a promising adsorbent for eliminating PCT from water.

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  • Bamboo sawdust is an abundant waste material.

  • Highly efficient CAC adsorbent was synthesized from bamboo sawdust.

  • Bamboo sawdust-derived activated carbon showed remarkable PCT removal from aqueous solution.

  • Combined activation of bamboo sawdust (FeCl3 + KOH) resulted in superior removal of PCT from aqueous solution.

  • Application of CAC on real environmental samples indicated promising results.

adsorption, bamboo sawdust, chemically activated carbon, emerging contaminant, paracetamol
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Rapid world population growth and economic expansion resulted in increased domestic and industrial effluent discharge to the environment, imposing a substantial environmental burden (Natarajan et al. 2022). Currently, pharmaceutical compounds have been classified as contaminants of emerging concern (CEC) in wastewater due to the potential adverse health consequences to humans (Escapa et al. 2017; George Nche et al. 2017; Wong et al. 2018). Frequent detection of these contaminants in the aquatic environment is considered a significant environmental risk (Verónica et al. 2011; Lima et al. 2021). Among the pharmaceuticals, paracetamol (PCT) is the most widely used drug for analgesic and antipyretic applications worldwide, with or without prescription (George Nche et al. 2017; Benyekkou et al. 2020). It has been reported that 58–68% of the consumed drug is excreted by human urine (Lima et al. 2019; Natarajan et al. 2021). Due to its wide consumption and poor absorption by the human body, it is continuously released into the environment (Natarajan et al. 2022). Based on previous reports, PCT concentration is 0.5–1.2 ppb and 0.012–0.058 ppb in the conventional wastewater treatment plant (WWTP) influent and effluent, respectively (Natarajan et al. 2022). The US has set a permissible level of PCT in potable water to be 0.0011–0.0013 ppb (Natarajan et al. 2021). Overdose of PCT causes adverse health consequences such as acute hepatic failure, liver damage, protein denaturation, and lipid peroxidation (Verónica et al. 2011; George Nche et al. 2017; Igwegbe et al. 2021). In light of these facts, PCT is an emerging water contaminant that demands research solutions (Lima et al. 2019).

Conventional WWTPs fail to sufficiently remove CEC as they are not explicitly designed to remove residual concentrations of such organic contaminants (Lima et al. 2019). Hence, concerns have been raised among researchers to come up with promising methods for the removal of PCT from water (Goh & Ismail 2020). To this end, various treatment methods, including advanced oxidation processes (AOPs) and adsorption processes, have been implemented to remove PCT from water. AOPs employed for PCT removal include photocatalysis (Thi & Lee 2017), electrochemical oxidation (Periyasamy & Muthuchamy 2018), electro-Fenton process (Orimolade et al. 2020), catalytic ozonation (Ziylan-Yavaş & Ince 2018), UV/H2O2 (Andreozzi et al. 2003), and photo-Fenton (Rad et al. 2015). AOPs can effectively remove CEC, but they are complex, expensive and can generate toxic by-products. Degradation of PCT using AOPs produces by-products such as low molecular weight compounds (Thanh et al. 2020). Approximately 20 transformation products were detected during the PCT degradation by the UV/chlorine AOP process (Patel et al. 2021).

These noted methods are still associated with high operational costs, secondary pollution, and sustainability. Consequently, the wide application of these methods at full scale for emerging contaminant removal is limited. To overcome this challenge, research work has continued. In this regard, an adsorption process is an interesting option from an economic, technical, and environmental point of view due to its ease of operation, no toxic by-product formation, application diversity or ease of being coupled with other existing processes, and low cost (George Nche et al. 2017; Lima et al. 2019; Shi et al. 2019; Benyekkou et al. 2020). Up till now, various adsorbents such as commercial activated carbon (Nguyen et al. 2020; Thanh et al. 2020), biochar (Benyekkou et al. 2020; Bursztyn Fuentes et al. 2020; Nadolny et al. 2020; Kerkhoff et al. 2021; Patel et al. 2021; Tunç et al. 2022), clay (Chauhan et al. 2020), magnetic nanomaterial (Loc et al. 2021), metal–organic framework (Yılmaz et al. 2021), multiwalled carbon nanotubes (Khamis et al. 2011), iron nanoparticles with a freshwater microalga (Praveen Kumar et al. 2021), chitosan magnetic nanobiosorbent (Natarajan et al. 2022), microalgae (Escapa et al. 2017), and groundnut shell (Malesic-Eleftheriadou et al. 2021) have been used to remove PCT from water. Most of these adsorbents have low contaminant uptake capacity (mostly less than 100 mg/g), low adsorption rate, and low regeneration capacity, and the reuse test was reported by only 14% of the authors (Igwegbe et al. 2021), separation difficulty after adsorption (Saucier et al. 2017), and preparation method complexity.

Commercial activated carbon is an efficient adsorbent widely employed for organic and inorganic contaminant removal. However, its challenging preparation technique (Bursztyn Fuentes et al. 2020) and higher cost of preparation (Nourmoradi et al. 2018; Patel et al. 2021) are significant obstacles to the broader application of this adsorbent in wastewater treatment. In this aspect, plant residue or waste biomass-derived activated carbon is a sustainable and double-beneficial water treatment option that has gained current attention among water scientists. Using biomass-based activated carbon in water treatment is an environmental waste management approach and, at the same time, a contaminant remediation strategy. Thus, biomass-derived activated carbon obtained by thermochemical conversion of biomass in an oxygen-limited condition is a promising alternative to commercial activated carbon due to its low cost (Tunç et al. 2022), high surface area (Chahinez et al. 2020; Cunha et al. 2020), good cation exchange capacity, excellent stability (Chahinez et al. 2020), and higher uptake capacity for organic and inorganic contaminants (Sumalinog et al. 2018). The efficiency of biomass-derived activated carbon depends on the feedstock type and the process conditions during thermal conversion (Sumalinog et al. 2018).

Bamboo is one of the most abundant and fast growing (5–12 years) plants in the world. It has several applications due to its unique qualities, such as good mechanical strength and higher carbon content (Lamaming et al. 2022). It is viewed as a sustainable, low-cost, and abundantly available resource suitable for use as an adsorbent (Lamaming et al. 2022). On top of that, bamboo sawdust is a waste of bamboo and used as a wood substitute in traditional and industrial applications. Uncontrollable bamboo sawdust contributes to environmental problems (Lamaming et al. 2022). Considering this, adsorbent preparation from bamboo sawdust for PCT removal from water is a beneficial approach.

Chemical activation of biomass-based carbon is known to improve the adsorptive capacity of the material due to the increment of surface area and formation of desirable surface functional groups. Most often, acid (H3PO4, H2SO4, and HCl) (Marqués et al. 2015; Benyekkou et al. 2020), alkaline (NaOH and KOH) (Li et al. 2018b; Wong et al. 2018), and salt (ZnCl2, K2CO3, and FeCl3) (Lima et al. 2019; Paredes-Laverde et al. 2019; Kerkhoff et al. 2021) activation methods were extensively reported. It is well known that the surface properties of carbon (surface area and porosity) derived from biomass can be improved by KOH activation, leading to an increase in adsorptive capacity (Ouyang et al. 2020). In contrast, the combined activation of plant residue-based carbon employing two or more chemicals for PCT removal is rarely reported (Reguyal et al. 2016). However, chemical modification using one activating agent has been extensively reported. In this regard, FeCl3 activation of spherical biochar (Loc et al. 2021), palm fiber activation with ZnCl2 (Grisales-Cifuentes et al. 2021), and innovative activated carbon derived from orange peels with FeCl3 activation (Tomul et al. 2019) were some of the single chemical activation methods reported for removal of PCT from water. Chemical activation of biomass with FeCl3 introduces extra adsorption sites (Fe–O) on the adsorbent's surface, which interact with pharmaceutical pollutants for enhanced removal (Reguyal et al. 2016; Zhao et al. 2018; Chen et al. 2019). Due to the benefits of single chemical activation using FeCl3 and KOH, combining KOH and FeCl3 activation would offer a synergistic benefit by improving the adsorbent surface properties (surface area and porosity) and incorporating desired additional adsorption sites (Fe–O) onto the adsorbent surface. In this work, bamboo sawdust was used for the PCT removal for the first time. Moreover, the combined activation of bamboo sawdust using FeCl3 and KOH for PCT removal from water is where the novelty of this research work resides. Environmental samples were collected from secondary WWTP effluent and analyzed to assess the adsorptive efficiency of chemically activated carbon (CAC). Adsorption process parameters such as initial PCT concentration, adsorbent dose, contact time, and pH were optimized using a one-factor at a time approach. Also, PCT adsorption kinetics, isotherm, thermodynamics, and adsorbent regeneration tests were conducted in batch mode.

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Chemicals and instruments

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PCT standard (C8H9NO2) with purity >99.7% was received from Cadila Pharmaceuticals Ltd. in Addis Ababa, Ethiopia. Analytical grade chemicals such as FeCl3·6H2O, KOH, HCl, NaOH, and NaCl were purchased from Rankem chemical supplier (Ethiopia). These analytical grade chemicals were used without further purification. The adsorbent's Fourier transform infrared (FTIR) spectra were recorded in the wavenumber range 500–4,000 cm−1 on a Spectrum 65 PerkinElmer-FTIR. The activated carbon's crystal structure was studied using the X-ray diffraction (XRD; Rigaku MiniFlex 600 Benchtop) analysis. The PCT concentrations in aqueous solutions were analyzed using a UV–Vis spectrophotometer (UV1610, China) at 243 nm.

Preparation of adsorbents

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The adsorbent synthesis was the same as reported by Wakejo et al. (2022). Locally available bamboo sawdust was collected and washed with ultrapure water. It was then oven-dried and pulverized to a particle size of less than 850 μm using a coffee grinder (RRH Grain Mill Electric Spice Nut and Coffee Grinder). Bamboo-based adsorbents such as bamboo sawdust carbon (BSC) (without chemical treatment), FeCl3 activated carbon (FAC), KOH activated carbon (KAC), and CAC derived from bamboo sawdust with combined (FeCl3·6H2O + bamboo sawdust + KOH) chemical activation were prepared for PCT removal. Bamboo sawdust was chemically treated (FeCl3·6H2O + bamboo sawdust + KOH) using a magnetic stirrer at 80 °C and 600 rpm for 2 h. The weight-to-weight ratio of bamboo sawdust to FeCl3·6H2O was 5:1, and the weight-to-volume ratio of bamboo sawdust to KOH (1 M) was 1:5. Next, chemically treated bamboo sawdust was dried in an oven (vacuum) at 60 °C. Chemically treated bamboo sawdust was then carbonized at 700 °C for 60 min with a 10 °C/min heating rate in a carbolite furnace to synthesize CAC. The CAC was washed with ultrapure water until the pH became neutral and then dried at 120 °C. Afterwards, CAC was ground to a particle size of less than 150 μm and stored in airtight glass bottles for the subsequent adsorption studies. Other bamboo-based adsorbents such as FAC, KAC, and BSC were prepared via a similar synthesis route for comparative analysis. Figure 1 presents the schematic procedure for synthesizing bamboo sawdust-derived adsorbents.
Figure 1
Synthesis procedure for the bamboo sawdust-derived adsorbents.
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Synthesis procedure for the bamboo sawdust-derived adsorbents.

Figure 1
Synthesis procedure for the bamboo sawdust-derived adsorbents.
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Synthesis procedure for the bamboo sawdust-derived adsorbents.

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Screening of the adsorbents

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An adsorbent screening test was conducted to select the best adsorbent for PCT removal from water. In different conical flasks, an adsorbent dosage of 0.05 g was added to 50 ml of PCT solution (20 mg/L). The samples were agitated at 200 rpm and 25 °C for 60 min. After adsorption, the used adsorbent was separated from the solution using filtration. The filtrate was then analyzed using UV–Vis spectrophotometer for PCT determination. The PCT removal efficiencies of the adsorbents were evaluated, and the bamboo-based adsorbent with the highest PCT removal efficiency was used in the subsequent adsorption study.

Characterization of the adsorbent

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The major characterization techniques employed for the bamboo sawdust-derived raw and CAC include XRD, FTIR, Brunauer, Emmett, and Teller (BET) surface area, and pH of the point of zero charge (pHpzc) characterization techniques. Further information on characterization techniques for CAC was given in our previous work (Wakejo et al. 2022). Surface functional groups of the synthesized CAC were identified using Spectrum 65 PerkinElmer-FTIR for 4,000–400 cm−1 (resolution: 4 cm−1, no of scans: 16) using KBr pellets. The crystalline phase and purity of the CAC and BSC were analyzed using the XRD analysis. The XRD analysis was carried out employing Cu Kα radiation to generate X-rays at 1.54441 Å wavelength at experimental conditions: 15 mA, 40 kV, and 2θ ranging from 10° to 60°. Moreover, BET surface areas of the activated carbon were evaluated with nitrogen adsorption–desorption at 77°K using the SA-9600 Series Surface Area Analyzer (Horiba Instruments, Inc). The BSC and CAC surface morphology was studied using a Carl Zeiss Gemini field emission scanning electron microscope (FE-SEM) operating at 20 kV.

PCT analysis

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PCT was analyzed using a spectrophotometer (UV1610, China) at 243 nm. The PCT analysis wavelength (243 nm) was obtained by running a wavelength scan in a UV–Vis spectrophotometer (200–400 nm) range. Standard PCT solutions: 0, 5, 10, 15, 20, 25, 30, 35, and 40 mg/L were prepared and employed for plotting the standard calibration curve. PCT concentration in an aqueous solution was calculated using Equation (1):
(1)
where X is the PCT concentration (mg/L) and Y is the solution's UV–Vis spectrophotometer absorbance reading at 243 nm.

Batch adsorption experiment

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Batch sorption experiments were performed in a water bath shaker at constant agitation speed (200 rpm) and temperature (25 °C, except for the thermodynamics study). PCT stock solution (1 g/L) was prepared by dissolving 1 g of pure PCT (>99.7%) in 1 L of ultrapure water. Adsorption equilibrium time was determined by performing batch experiments at different contact times (10, 30, 50, 70, 90, 110, and 130 min), keeping pH = 7.2, PCT concentration of 20 mg/L, adsorbent dose of 0.05 g/L. Adsorption process optimization was carried out considering PCT initial concentration (10–120 mg/L), pH = 2–12, contact time (10–110 min), and adsorbents dose (0.25–1.6 g/L). The pH of the solution was adjusted using 0.1 M HCl and NaOH. All sorption experiments were conducted in a 100 mL conical flask containing 50 mL PCT solution. After adsorption, the adsorbate–adsorbent solution was allowed to settle, and the supernatant was taken and centrifuged at 4,000 rpm for 10 min and then filtered using a 0.45 μm membrane filter. A triplicate of data was taken for each experimental work of kinetics, isotherm, and thermodynamics. Equations (2) and (3) were employed for the evaluation of PCT removal efficiency and adsorption capacity, respectively (Loc et al. 2021):
(2)
The PCT uptake capacity of the adsorbent was obtained from the following equation:
(3)
where C0, Ct, V, and M represent the initial PCT concentration (mg/L), PCT concentration (mg/L) at a given time t (min), V is the solution volume (L), and M is adsorbent mass (g), respectively.

Adsorption kinetic study

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The kinetic study of PCT adsorption onto CAC helps to understand the dynamics of the process and enables the determination of rate constants (Wong et al. 2018). To understand the kinetics of PCT adsorption onto CAC, four kinetic models, such as the pseudo-first-order model (PFO), the pseudo-second-order model (PSO), Elovich, and intraparticle kinetic models, were employed. The kinetic model equations are given in Equations (4)–(7) for pseudo-first-order, pseudo-second-order, Elovich, and intraparticle kinetic models, respectively (Wong et al. 2018). The optimal process conditions obtained for the PCT adsorption (pH = 8.0, PCT con = 20 mg/L, and CAC dose = 0.5 g/L) onto CAC were used to study PCT adsorption kinetics:
(4)
(5)
(6)
(7)
where qe and qt are the amounts of PCT (mg/g) adsorbed per unit mass of CAC at equilibrium and at a time t, respectively, whereas K1, K2, and Kid are the PFO (1/min), PSO (g/mg min), and intraparticle (mg/g min0.5) rate constants, respectively. The α in Equation (6) is the initial adsorption rate (mg/g min), β (g/mg) denotes the change in activation energy rate with surface coverage, and K0 is the correlation constant.

Adsorption isotherm study

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A batch adsorption isotherm study was conducted to understand the distribution of PCT molecules between the solid (CAC) and aqueous phases when the adsorption process reaches equilibrium (Kerkhoff et al. 2021). Isotherm analysis was conducted for the PCT initial concentration (20–120 mg/L), employing other optimal process parameters from the optimization step (pH = 8.0, PCT concentration = 20 mg/L, CAC dose = 0.5 g/L) and at an equilibrium time (90 min). In this study, four isotherm models, including Langmuir, Freundlich, Redlcih–Peterson, and Dubinin–Radushkevich (D–R), were used to analyze the equilibrium PCT adsorption isotherm data using Equations (8)–(11) (Reguyal et al. 2016), respectively. Therefore, PCT adsorption process optimal parameters were employed to analyze the PCT adsorption isotherm data:
(8)
(9)
(10)
(11)
where qe is the uptake capacity of the CAC at equilibrium (mg/g), b (L/mg) is the Langmuir constant, qm (mg/g) is the maximum uptake capacity of the CAC, and Ce is the concentration PCT at equilibrium in solution (mg/L). The maximum adsorption capacity (qm) and b were evaluated from the slope and intercept of the Ce versus Ce/qe plot. KF (mg/g)(L/mg)(1/n) in Equation (9) denotes the Freundlich isotherm constant, whereas (1/n) indicates adsorption intensity and heterogeneity degree of the surface. β (L/mg) and A (L/g) are the Redlich–Peterson model constants. K stands for adsorption energy constant in the D–R model, qm refers to the theoretical saturation capacity (mg/g), and ε is the Polanyi potential, calculated from Equation (11). From the Langmuir isotherm equation, an essential parameter of adsorption (RL), separation factor, is expressed in Equation (12):
(12)
where C0 (mg/L) and KL (L/mg) are the initial PCT concentration and Langmuir isotherm constant, respectively. The separation factor, RL, indicates the favorability and nature of isotherm: (i) RL = 0 refers to irreversible isotherm, (ii) RL between 0 and 1, 0 < RL < 1 indicates favorable isotherm, (iii) RL = 1 represents linear isotherm, (iv) RL > 1 shows unfavorable isotherm (Stylianou et al. 2021). The Dubinin–Raduskevich (D–R) model can be evaluated using Equation (13):
(13)

The constant K in the D–R model is the slope of the plot of ln qe versus ε2, and the adsorption capacity, qm (mg/g) is represented by the intercept.

Adsorption thermodynamic study

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The effect of temperature on the PCT removal by CAC was studied for 25, 35, 45, and 55 °C at an optimum condition obtained in the previous steps. The essential parameters of the thermodynamic study, namely, Gibbs free energy change (ΔG0), enthalpy change (ΔH0), and entropy change (ΔS0), were evaluated to understand the thermodynamic nature of the PCT adsorption process. Van't Hoff equation was used to determine ΔG0 as written in Equation (14):
(14)
Based on Equation (14), terms such as T, R, and K0 represent temperature (K), universal gas constant (8.314 J/K mol), and the dimensionless thermodynamic constant, respectively. The relationship between ΔG0 and the other two parameters can be evaluated using the third principle in thermodynamics expressed in Equation (15):
(15)
where ΔG0, ΔH0, and ΔS0 refer to Gibbs free energy change (J/mol), enthalpy change (J/mol), and entropy change (J/mol K), respectively. Equations (14) and (15) were combined to generate a new formula for the Van't Hoff equation expressed in Equation (16). Based on Equation (16), ΔG0 and ΔS0 of the process can be evaluated from the plot of ln K0 (Y-axis) versus T−1 (X-axis):
(16)

Adsorbent reusability study

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An adsorbent reuse test was conducted to investigate the feasibility of the adsorbent for further applications. The regeneration experiment was conducted at optimum PCT adsorption process conditions obtained in the previous steps. Various solvents such as hot water, methanol, NaOH, HCl, and NaOH + methanol were used for PCT desorption and optimized to achieve the best result. These solvents were employed in previous studies (Lima et al. 2019; Chauhan et al. 2020; Thanh et al. 2020; Kerkhoff et al. 2021; Gómez-Avilés et al. 2022) to desorb PCT from various adsorbents.

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Adsorbent characterization results

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The detailed analysis of adsorbent characterization results such as XRD, BET, and pHpzc of the adsorbent has been described in our previous work (Wakejo et al. 2022) and highlighted here to ease the reader. The XRD analysis of CAC confirmed that magnetite and hematite iron species were observed on CAC at 30.1, 35.6, 43.2, 57.2, and 33.2, respectively. This result is confirmed by FTIR analysis of CAC which showed the presence of iron species (Fe–O–Fe) at 540 cm−1. These characterization results implied that the treatment of bamboo sawdust with FeCl3·6H2O resulted in the incorporation of iron species (Fe–O) onto CAC surface, which then became an additional adsorption site for PCT removal. Moreover, the BET analysis result indicated that combined chemical activation (FeCl3·6H2O + KOH) increased the specific surface area from 565.095 to 1,158.050 m2/g. The pHpzc of the CAC adsorbent was determined to be 6.5 (Wakejo et al. 2022). The FTIR spectra of the adsorbent materials such as BSC and CAC before adsorption, after adsorption (CAC-PCT), and adsorbate (PCT) are displayed in Figure 2. The CAC and BSC spectra revealed significant structural differences. The surface tuning activity via chemical activation of the bamboo sawdust has resulted in the incorporation of desirable surface functional groups. This phenomenon is vital for PCT adsorption onto the CAC. The peaks observed in CAC at 3,543–3,456 cm−1, 2,918–2,835 cm−1 (Wakejo et al. 2022), and 1,052 cm−1 (Ma et al. 2022) of the FTIR spectra correspond to –OH, C–H, and C–O as shown in Figure 1. Moreover, the spectra observed at 540 cm−1 represent Fe–O–Fe (Ma et al. 2022) stretching vibration on the surface of the CAC. The FTIR spectrum of CAC shows that iron was successfully attached to the surface of the CAC and played its role during the adsorption of PCT. After adsorption of PCT onto CAC, the peaks observed at 3,543–3,456 cm−1 (broad peak) and 2,918–2,835 cm−1 were shifted to 3,410 and 2,913 cm−1, forming small intensity peaks. Moreover, the peaks represented by C–O and Fe–O–Fe were disappeared. Overall, the spectral peak shifting, intensity reduction, and disappearance of the peaks after adsorption revealed that these functional groups were participated during the adsorption of PCT onto CAC.
Figure 2
FTIR spectra of BSC, CAC, and CAC after PCT adsorption (CAC-PCT), and PCT.
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FTIR spectra of BSC, CAC, and CAC after PCT adsorption (CAC-PCT), and PCT.

Figure 2
FTIR spectra of BSC, CAC, and CAC after PCT adsorption (CAC-PCT), and PCT.
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FTIR spectra of BSC, CAC, and CAC after PCT adsorption (CAC-PCT), and PCT.

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FE-SEM was used to examine the morphological differences in chemically activated and raw BSC. Figure 3(a) shows that the raw BSC morphology has a regular and tubular structure with no pores. However, Figure 3(b) indicates that it has a rough surface with several cavities, voids, and pores disturbed on the surface of the activated carbon. FE-SEM image demonstrated that chemical activation resulted in the formation of pores on the surface of the activated carbon. Moreover, the FE-SEM image result agrees with the BET result of the adsorbent, which presented a significant increment in specific surface area after chemical activation. The FE-SEM analysis result showed that the formation of pores on the adsorbent surface after chemical activation is consistent with the previous report (Tunç et al. 2022). Specific surface area of the CAC was 1,158 m2/g, whereas the specific surface area of the BSC was 565 m2/g. The significant increase in surface area is due to the formation of pores on the surface of activated carbon. On the other hand, the point of zero charge of the CAC was 6.5. This result indicates that the surface charge of the CAC was positive for a solution pH less than 6.5 and negative for a solution pH above 6.5. The XRD analysis showed that hematite (2θ (°) = 30.1, 35.6, 43.2, and 57.2) and magnetite (2θ (°) = 33.2) iron were successfully incorporated onto the surface of the CAC, which played one of the crucial roles in the PCT adsorption process. Overall, the porous structure of the adsorbent shown by the FE-SEM image, surface functional groups indicated by FTIR, and the higher specific surface area (BET) supported the experimental findings of the higher PCT removal capacity of the CAC.
Figure 3
SEM micrographs of carbon derived from bamboo sawdust. (a) BSC and (b) CAC.
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SEM micrographs of carbon derived from bamboo sawdust. (a) BSC and (b) CAC.

Figure 3
SEM micrographs of carbon derived from bamboo sawdust. (a) BSC and (b) CAC.
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SEM micrographs of carbon derived from bamboo sawdust. (a) BSC and (b) CAC.

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PCT adsorption

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Adsorbent screening

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Bamboo-based adsorbent materials, namely, BSC, FAC, KAC, and CAC, were used to remove PCT from the aqueous solution. The PCT removal efficiencies of these adsorbents are shown in Figure 4. As shown in Figure 4, BSC, FAC, KAC, and CAC application as adsorbents for PCT removal from the water had resulted in 43.65, 65.69, 84.69, and 98.05% PCT removal, respectively. Adsorbent screening test was conducted at PCT initial concentration (25 mg/L), adsorbent dose (0.5 g/L), contact time (60 min), and pH (7.2). All the chemical activation (modifications) gave higher removal than the unmodified (raw) bamboo adsorbent. This is because chemical modification improved the adsorbents' surface area and surface properties, resulting in higher PCT removal. In particular, the simultaneous activation of bamboo sawdust with FeCl3 and KOH has remarkably eliminated PCT compared to the raw BSC and the individual chemical activation (either using FeCl3 or KOH). The reason for the higher removal of PCT using CAC is because of its high surface (1,158 m2/g), which is significantly higher than the raw BSC (565 m2/g), and the involvement of the newly emerged surface functional groups on the CAC that promoted the PCT adsorption process (Tomul et al. 2019; Benyekkou et al. 2020). Activation with FeCl3 provided an additional Fe–O sorption site (Zhao et al. 2018; Tomul et al. 2019; Lung et al. 2021) in addition to forming –OH, C–H, and C–O functional groups during chemical activation. To this end, this study applied CAC (FeCl3 + KAC) for all its adsorption experiments. The side benefit of ferric chloride activation of the bamboo sawdust is its magnetic properties because of the iron supported on the CAC, which is helpful for the separation of the adsorbent.
Figure 4
PCT removal efficiencies of bamboo-based adsorbents.
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PCT removal efficiencies of bamboo-based adsorbents.

Figure 4
PCT removal efficiencies of bamboo-based adsorbents.
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PCT removal efficiencies of bamboo-based adsorbents.

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Effect of pH on PCT removal

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The influence of pH on the adsorptive removal of PCT by CAC is given in Figure 5. PCT is a weak electrolyte that can exist in two forms, non-ionized (acid) and ionized (base) forms depending on its pKa value (9.38) and the pH of the solution (Taylor et al. 2015; Igwegbe et al. 2021). When the pH of the solution is less than the pKa value of PCT, it mainly exists in neutral and non-ionized form (Moussavi et al. 2016). In this study, PCT adsorption onto CAC was not significantly affected by varying pH from 2 to 8. At this pH range, PCT molecules mainly exist in neutral or non-ionic forms (Moussavi et al. 2016) that led to negligible electrostatic attraction. However, a further increase in pH from 8 to 12 notably decreased PCT removal from 99.68 to 93.85%. This can be explained by considering the pKa value of PCT (9.38) and the point of zero charge of CAC adsorbent (6.5). The surface of CAC is negatively charged above pHpzc (6.5). In contrast, it is positively charged below the solution pH of 6.5. Solution pH higher than the pKa value of PCT (9.38) did not favor the adsorption of PCT onto CAC due to electrostatic repulsion between the negatively charged adsorbent surface and anion of PCT (Praveen Kumar et al. 2021). In this regard, a pH of 8 was considered an optimal pH for PCT adsorption onto CAC. Other previous studies (Taylor et al. 2015; Natarajan et al. 2021) have also reported a similar trend for the influence of pH on the adsorption of PCT onto various adsorbents.
Figure 5
Effect of pH on the removal of PCT by CAC.
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Effect of pH on the removal of PCT by CAC.

Figure 5
Effect of pH on the removal of PCT by CAC.
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Effect of pH on the removal of PCT by CAC.

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Effect of contact time

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The effect of contact time on PCT adsorption was studied for contact time ranging from 20 to 120 min at PCT (20 mg/L), CAC (0.5 g/L), and pH (8.0). As depicted in Figure 6, PCT adsorption onto CAC was increased from 95.22 to 99.72% when contact time was increased from 20 to 90 min. The increase in PCT removal with time is related to the time required by the PCT molecules to come in contact with the CAC. In this study, the synthesized CAC adsorbent material has a high surface area, providing higher adsorption active sites for the PCT molecule. Thus, PCT adsorption requires enough time for the adsorption until the CAC saturates. However, a further increase in contact time did not significantly increase PCT removal. This is because of the attainment of equilibrium (Natarajan et al. 2021). The equilibrium time determined for the adsorption of PCT onto CAC was (90 min). Hence, contact time (90 min) was taken as an optimal time for PCT adsorption onto CAC adsorbent.
Figure 6
The effect of adsorption contact time on the removal of PCT by CAC.
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The effect of adsorption contact time on the removal of PCT by CAC.

Figure 6
The effect of adsorption contact time on the removal of PCT by CAC.
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The effect of adsorption contact time on the removal of PCT by CAC.

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Effect of PCT initial concentration

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Adsorbate initial concentration plays a significant role in the adsorption process. Initial adsorbate concentration can be an important driving force in overcoming mass transfer resistance between aqueous and solid phases (Mondal et al. 2016). Figure 7 represents the effect of PCT initial concentration over the PCT concentration range of 10–120 mg/L. The removal efficiency decreased from 99.97 to 77.76% when PCT increased from 10 to 120 mg/L. The decrease in PCT removal with PCT initial concentration is due to the limited adsorption sites and a decrease in intraparticle diffusion (Wong et al. 2018). Here, 20 mg/L PCT concentration was taken as an optimal concentration of PCT for investigating the adsorptive capacity of the CAC adsorbent. Most of the previous works considered PCT concentration of 20 mg/L or less for evaluating the adsorptive capacity of various adsorbents (Marqués et al. 2015; Yanyan et al. 2018; Rahman & Nasir 2020). As PCT is present in trace quantity in surface water, a low concentration of PCT should give high removal percentage (Natarajan et al. 2021).
Figure 7
The effect of PCT initial concentration on PCT removal using CAC adsorbent.
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The effect of PCT initial concentration on PCT removal using CAC adsorbent.

Figure 7
The effect of PCT initial concentration on PCT removal using CAC adsorbent.
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The effect of PCT initial concentration on PCT removal using CAC adsorbent.

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Effect of adsorbent dose

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The effect of the adsorbent dose profile was studied by varying the CAC dose from 0.125 to 1.6 g/L for 20 mg/L PCT concentration. As presented in Figure 8, it was observed that PCT removal increased from 92.45 to 99.65% when the adsorbent dose increased from 0.125 to 0.5 g/L. This is because an increase in mass results in more available sorptive surface area and, as a result, more active sorption sites (Mondal et al. 2016). As depicted in Figure 7, an adsorbent dose of 0.5 g/L gave almost complete removal of PCT from 20 mg/L PCT solution. Thus, increasing the CAC dose beyond 0.5 g/L has no significant increase or benefit. Besides, an increase in adsorbent dose is directly related to the operational cost (Shi et al. 2019). In the environment, PCT is present at ppb level, hence using a high quantity of the adsorbent will not increase adsorption capacity (Natarajan et al. 2021). In light of these facts, a CAC dose of 0.5 g/L is considered optimal for PCT removal at predetermined PCT initial concentration, contact time, and pH values.
Figure 8
The effect of CAC dose on the removal of PCT from aqueous solution.
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The effect of CAC dose on the removal of PCT from aqueous solution.

Figure 8
The effect of CAC dose on the removal of PCT from aqueous solution.
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The effect of CAC dose on the removal of PCT from aqueous solution.

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Adsorption kinetics

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The time profile of PCT adsorption onto the CAC was described by conducting an adsorption kinetic study employing various kinetic models. The kinetic study helps to understand the mechanism of the PCT adsorption process (Benyekkou et al. 2020). In this work, four kinetic models, including the pseudo-first-order equation, the pseudo-second-order equation, Elovich, and intraparticle kinetic models, were considered for the PCT adsorption kinetic data analysis. The results of PCT adsorption kinetic parameters are described in Table 1. The linear regression plots of the adsorption kinetic models are presented in Figure 9(a)–9(d). Initially, the fast PCT adsorption rate seems to be due to the high concentration of PCT and ample active sites on CAC. The adsorption rate gradually declined due to the attainment of equilibrium. PCT adsorption onto CAC followed a pseudo-second-order kinetic model having the highest coefficient of determination (R2 = 0.999) compared to other kinetic models. Also, the calculated uptake capacity of CAC at equilibrium (qe,cal) is close to the experimentally obtained (qe,exp) value. Accordingly, the PSO model provided the best fit for the PCT adsorption experimental data, as shown in Figure 9(b). These adsorption kinetic model results suggest that the adsorption of PCT by CAC was dominated by the chemisorption process, which agrees with the findings of the previous works (Sumalinog et al. 2018; Spessato et al. 2020; Praveen Kumar et al. 2021; Tunç et al. 2022). The intraparticle diffusion model was used to evaluate the rate-controlling step of the adsorption process (Ngeno et al. 2016). As the constant (K0) of the intra-particle model increases, the role of surface sorption in the rate-controlling step increases.
Table 1

Kinetic models and values of their parameters

Pseudo-first-order modelPseudo-second-order model
K1 (1/min) qe,cal (mg/g) qe,exp (mg/g) R2 K2 (g/mg min) qe,cal (mg/g) qe,exp (mg/g) R2 
0.07403 39.90 3.685 0.916 0.198 39.90 40.02 0.999 
Intraparticle model
Elovich
Kid (mg/g min1/2) K0 R2 α (mg/g min) β (g/mg) R2 
0.300 37.343 0.881 3.654 38.153 0.908  
Pseudo-first-order modelPseudo-second-order model
K1 (1/min) qe,cal (mg/g) qe,exp (mg/g) R2 K2 (g/mg min) qe,cal (mg/g) qe,exp (mg/g) R2 
0.07403 39.90 3.685 0.916 0.198 39.90 40.02 0.999 
Intraparticle model
Elovich
Kid (mg/g min1/2) K0 R2 α (mg/g min) β (g/mg) R2 
0.300 37.343 0.881 3.654 38.153 0.908  
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Figure 9
Kinetic models of PCT adsorption onto CAC: (a) pseudo-first-order, (b) pseudo-second-order, (c) Elovich, and (d) intraparticle models.
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Kinetic models of PCT adsorption onto CAC: (a) pseudo-first-order, (b) pseudo-second-order, (c) Elovich, and (d) intraparticle models.

Figure 9
Kinetic models of PCT adsorption onto CAC: (a) pseudo-first-order, (b) pseudo-second-order, (c) Elovich, and (d) intraparticle models.
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Kinetic models of PCT adsorption onto CAC: (a) pseudo-first-order, (b) pseudo-second-order, (c) Elovich, and (d) intraparticle models.

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The intraparticle model linear plot of qt versus t0.5 is depicted in Figure 9(d). Furthermore, a plot of the qt versus t0.5 presented in Figure 10 indicated multilinear stages of PCT adsorption onto CAC. The observed multilinear regions of the plot of qt versus t0.5 suggested that PCT adsorption is controlled by more than one adsorption mechanism. The multi-linear regions of adsorption can be described by the sorption of solute by porous adsorbents consisting of three consecutive steps (Balarak et al. 2021). The first region represents the external adsorption process. The second region refers to the intraparticle diffusion region with gradual adsorption that occurs when intraparticle diffusion is rate-limiting. However, intraparticle diffusion is the sole rate-limiting step for the regression line passing through the origin. Otherwise, it can be one of the rate-limiting steps of adsorption. The final step is the equilibrium stage, where the intraparticle diffusion rate declines due to the lower adsorbate concentration. In this study, the plot of qt versus t0.5 revealed the involvement of several mechanisms during PCT adsorption onto CAC. Thus, liquid film and intraparticle diffusion controlled the rate of the PCT molecule diffusion.
Figure 10
Multilinear plot of intraparticle diffusion model.
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Multilinear plot of intraparticle diffusion model.

Figure 10
Multilinear plot of intraparticle diffusion model.
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Multilinear plot of intraparticle diffusion model.

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Adsorption isotherms

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The adsorption equilibrium studies are important for understanding the mechanism of adsorbate–adsorbent interactions. Likewise, the results of the equilibrium studies could be employed to determine the extent of uptake of the adsorbate by the adsorbent (El-Azazy et al. 2021). The PCT adsorption isotherms have been plotted for Langmuir, Freundlich, Redlich–Peterson, and D–R and presented in Figure 11, and the calculated isotherm model parameters are tabulated in Table 2. The adsorption capacity of CAC for PCT increased with an increase in initial PCT concentration, showing that the adsorption sites get the chance to contact the adsorbate. However, after the exhaustion of the adsorption sites of the adsorbent at a particular concentration, the adsorption remains unaffected by initial concentrations (Atugoda et al. 2021).
Table 2

Isotherm models and values of their parameters

Langmuir
Freundlich
qm (mg/g) b R2 KF (mg/g) (L/mg)1/n n R2 
188.67 0.489 0.98 52.70 7.98 0.96 
Redlich–PetersonDubinin–Radushkevich (D–R)
Β (L/mg) A (L/g) R2 qm (mg/g) K R2 
0.71 71.37 0.99 133.96 1.34 × 10−8 0.77 
Langmuir
Freundlich
qm (mg/g) b R2 KF (mg/g) (L/mg)1/n n R2 
188.67 0.489 0.98 52.70 7.98 0.96 
Redlich–PetersonDubinin–Radushkevich (D–R)
Β (L/mg) A (L/g) R2 qm (mg/g) K R2 
0.71 71.37 0.99 133.96 1.34 × 10−8 0.77 
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Figure 11
Isotherm models plots for PCT adsorption: (a) Langmuir, (b) Freundlich, (c) Redlich–Peterson, and (d) Dubinin–Radushkevich.
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Isotherm models plots for PCT adsorption: (a) Langmuir, (b) Freundlich, (c) Redlich–Peterson, and (d) Dubinin–Radushkevich.

Figure 11
Isotherm models plots for PCT adsorption: (a) Langmuir, (b) Freundlich, (c) Redlich–Peterson, and (d) Dubinin–Radushkevich.
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Isotherm models plots for PCT adsorption: (a) Langmuir, (b) Freundlich, (c) Redlich–Peterson, and (d) Dubinin–Radushkevich.

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The separation factor, RL, which is based on the Langmuir model, was used to identify the adsorption favorability of adsorbate onto adsorbent (El-Azazy et al. 2021); thus, if RL is >1, then the process is not favorable for adsorption, while if RL = 1, then the adsorption is linear. The adsorption process is favorable and spontaneous if the value of RL is between 0 and 1. On the other hand, if RL = zero, then the adsorption process is irreversible. In this work, the calculated RL value is 0.02, which is between 0 and 1, indicating that the adsorption of PCT onto CAC is favorable. The maximum monolayer adsorption capacity is 188.67 mg/g. The linear isotherm model analysis revealed that Langmuir (R2 = 0.98) and Freundlich (R2 = 0.96) models described the PCT isotherm data well, as shown in Figure 9. This indicates that the adsorption behavior of the PCT onto CAC cannot be explained using only one isotherm model. Instead, it can be explained by the combination of the two models. This result is further elaborated by analyzing the Redlich–Peterson isotherm because this model is a mix of Langmuir and Freundlich isotherms (Ayawei et al. 2017). The Redlich–Peterson isotherm model (R2 = 0.99) gave the best fit to the experimental data confirming that the PCT adsorption onto the CAC is a combined process. These results suggested that the PCT adsorption onto CAC is monolayer adsorption onto the heterogeneous surface and agrees with the previous work (Li et al. 2018a). From the Freundlich isotherm, 1/n indicates the intensity of Freundlich adsorption (Shokoohi et al. 2019; Alnajrani & Alsager 2020). In this study, 1/n for PCT adsorption is 0.12, a value between 0 and 1, showing preferential PCT adsorption onto CAC.

Thermodynamic study

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PCT adsorption thermodynamic analysis was conducted using thermodynamic parameters, i.e., ΔS0, ΔH0, and ΔG0 with varying temperatures (25–55 °C). Table 3 describes the estimated values of the thermodynamic parameters for PCT adsorption onto the CAC. Thermodynamic parameters of PCT adsorption onto CAC were evaluated using Equations (14)–(16), and the results are given in Table 3.

Table 3

Values of thermodynamic parameters for PCT adsorption onto CAC

Temperature (K)ΔG0 (KJ/mol)ΔH0 (KJ/mol)ΔS0 (KJ/mol·K)
298.15 −13.771 − 88.287 − 0.256 
308.15 −66.78 
318.15 −5.803 
328.15 −5.825 
Temperature (K)ΔG0 (KJ/mol)ΔH0 (KJ/mol)ΔS0 (KJ/mol·K)
298.15 −13.771 − 88.287 − 0.256 
308.15 −66.78 
318.15 −5.803 
328.15 −5.825 
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Table 3 presents negative values for all the thermodynamic parameters (ΔH0, ΔS0, and ΔG0). Negative values of ΔG0 showed the spontaneity of the sorption process (Huang et al. 2018). These thermodynamic study results show that higher temperatures decreased PCT adsorption onto the CAC. The negative values of change in enthalpy (ΔH0) for PCT adsorption showed that the PCT sorption was an exothermic process (Kerkhoff et al. 2021). Exothermic adsorptive nature (Loc et al. 2021) was observed due to a negative ΔH0 value. A negative ΔS0 value for the sorption of PCT onto CAC displayed less disorder at the liquid–solid interphase resulting in an effortless bond formation (Natarajan et al. 2022). Finally, the change in Gibbs free energy ΔG0, determined using Equation (15), showed negative values for all the temperatures (25, 35, 45, and 55 °C), indicating spontaneous adsorption (Paredes-Laverde et al. 2019).

Reusability study

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The efficiency of the adsorbent in treating PCT-laden wastewater can be explained by its reusability for practical applications on a large scale (Show et al. 2021). The reuse capacity of the adsorbent shows its economic feasibility. PCT desorption optimization tests were done using solvents such as hot water, methanol, NaOH, HCl, and NaOH + methanol to obtain maximum desorption results. The PCT removal efficiency of CAC after the first adsorption–desorption cycle with 0.3 M NaOH, methanol, 3% NaOH + methanol, and 0.3 M HCl was 60.3, 40.25, 63.62, and 90.24%, respectively.

Consequently, 0.3 M HCl was used as a desorbing solution for PCT throughout the reuse study. The removal of PCT varied from 98.97 to 80.34% after five consecutive adsorption–desorption cycles, as shown in Figure 12. This result revealed that CAC could be effectively employed for five consecutive adsorption cycles, capable of removing 80% of PCT from water at the fifth cycle. Similar studies reported higher desorption of PCT from the adsorbent (rhamnolipid-based chitosan magnetic nanosorbents) (Natarajan et al. 2022). The regeneration study results (Figure 12) indicated that the PCT removal efficiency of CAC was faintly diminished after each cycle and then nearly constant in the fifth cycle. Hence, the reusability of the CAC up to five consecutive cycles for PCT removal with higher removal efficiency shows the promising potential of the CAC for application in emerging contaminant (PCT) removal.
Figure 12
PCT removal efficiency of CAC per each usage cycle.
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PCT removal efficiency of CAC per each usage cycle.

Figure 12
PCT removal efficiency of CAC per each usage cycle.
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PCT removal efficiency of CAC per each usage cycle.

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Comparison of CAC with other adsorbents

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The bamboo sawdust-derived activated carbon was compared with other adsorbents used in previous works to remove PCT from water, as shown in Table 4. The adsorption process is highly dependent on the operational parameters such as adsorbent dose, initial pollutant concentration, pH, temperature, contact time; thus, the sorption conditions were presented for adsorption of PCT using various adsorbents. Maximum removals of PCT have been reported for each adsorbent at optimum operating conditions. Most of the previous studies showed that PCT adsorption onto various adsorbents followed Langmuir isotherm and pseudo-second-order kinetic models. However, isotherm models such as Sips, Dubinin–Radushkevich, Temkin and Freundlich have also been reported for the adsorption of PCT onto different adsorbents. The optimal adsorption process condition, fitness of isotherm, and kinetic models with experimental data depend on the specific interactions between PCT and proposed adsorbents.

Table 4

Various materials used for the adsorptive removal of PCT from water

AdsorbentCapacity (maximum uptake) in mg/gOperational conditionsIsotherm and kinetics data best fit modelsAdsorbent capacity (maximum uptake in mg/g)PCT removal (%)References
Green synthesized iron nanoparticles with fresh microalgae – pH = 3.0, temperature = 303 K, salinity (NaCl) = 20 mg/L, and adsorbent dose = 105 mg/L Langmuir model (R2 = 0.994) and pseudo-second-order kinetic model (R2 = 0.998) 11.62 98.6% from pure water and 91.3% from river water Praveen Kumar et al. (2021)  
Chitosan magnetic nanosorbents 96.3 Contact time = 60 min, pH = 5.0, and temperature = 303 K Langmuir isotherm (R2 = 0.99) and pseudo-second-order model (R2 = 0.99) 96.3 96.7 Natarajan et al. (2022)  
Activated carbon synthesized from spent tea leaves 59.2 PCT = 10 mg/L, adsorbent dose = 0.5 g, pH = 3, and reaction time = 60 min Langmuir isotherm model (R2 = 0.970) and obeyed the pseudo-second-order kinetics model (R2 = 0.999) 59.2 – Wong et al. (2018)  
Fe(III)-based metal–organic framework-coated cellulose paper – Initial PCT concentration = 35.60 mg/L, pH = 6.44, agitation time = 167.06 min, and adsorbent dosage = 0.8435 g/L Pseudo-second-order kinetic models (R2 = 0.99) and Langmuir model (R2 = 0.99) – 89.75 Yılmaz et al. (2021)  
Commercial activated carbon 121 Adsorbent dose = 1.0 g/L, pH = 7.0, temperature = 298 K, and PCT initial con. ∼100–1,200 mg/L Redlich–Peterson (R2 = 0.993), Avrami model (R2 = 0.997), and Elovich model (R2 = 0.991) 221 (taken from Langmuir model) – Thanh et al. (2020)  
Activated carbon 15.90 Adsorbent dose = 0.16 g/100 mL, PCT con. = 11.52 mg/L, and contact time = 90.52min Langmuir (R2 = 0.996), Temkin (R2 = 0.998), and pseudo-second-order kinetic model (R2 ≥ 0.99) 15.90 99.24 Tunç et al. (2022)  
Activated carbon from Butia capitata endocarp 100.6 Equilibrium time = 180 min Langmuir model (R2 = 0.971) and Elovich (R2 = 0.994) 100.60 – Kerkhoff et al. (2021)  
Nanosized hematite-assembled carbon spheres 49.9 Equilibrium time = 120 min, temperature = 598 K, and pH = 7.0, adsorbent dose = 2 g/L Langmuir model (R2 ≥ 0.994) and pseudo-second-order (R2 ≥ 0.975), and Elovich models (R2 ≥ 0.979) 49.90 – Loc et al. (2021)  
Silica microspheres 89.0 Contact time = 30 min, pH = 5.0, PCT = 20 mg/L, temperature = 303 K, and sorbent dose = 100 mg/L Freundlich isotherm (R2 = 0.99) and second-order kinetic model (R2 = 0.99) 89.0 96.7 Natarajan et al. (2021)  
Carbon-based adsorbents from brewery waste – Equilibrium time = 20 min, pH = 4, and adsorbent = 0.45 g Langmuir isotherm (R2 = 0.994) 30.8 98.3 Nadolny et al. (2020)  
Groundnut shell 3.02 – Langmuir (R2 = 0.99) and Sips model (R2 = 0.99)   – N'diaye & Bollahi (2019)  
CAC 188.67 PCT con = 20 mg/L, CAC dose = 0.5 g/L, contact time = 90 min, pH = 8.0, and temperature = 298 K Langmuir, Freundlich, and Redlich–Peterson isotherm models and pseudo-second-order model 188.67 99.6 This study 
AdsorbentCapacity (maximum uptake) in mg/gOperational conditionsIsotherm and kinetics data best fit modelsAdsorbent capacity (maximum uptake in mg/g)PCT removal (%)References
Green synthesized iron nanoparticles with fresh microalgae – pH = 3.0, temperature = 303 K, salinity (NaCl) = 20 mg/L, and adsorbent dose = 105 mg/L Langmuir model (R2 = 0.994) and pseudo-second-order kinetic model (R2 = 0.998) 11.62 98.6% from pure water and 91.3% from river water Praveen Kumar et al. (2021)  
Chitosan magnetic nanosorbents 96.3 Contact time = 60 min, pH = 5.0, and temperature = 303 K Langmuir isotherm (R2 = 0.99) and pseudo-second-order model (R2 = 0.99) 96.3 96.7 Natarajan et al. (2022)  
Activated carbon synthesized from spent tea leaves 59.2 PCT = 10 mg/L, adsorbent dose = 0.5 g, pH = 3, and reaction time = 60 min Langmuir isotherm model (R2 = 0.970) and obeyed the pseudo-second-order kinetics model (R2 = 0.999) 59.2 – Wong et al. (2018)  
Fe(III)-based metal–organic framework-coated cellulose paper – Initial PCT concentration = 35.60 mg/L, pH = 6.44, agitation time = 167.06 min, and adsorbent dosage = 0.8435 g/L Pseudo-second-order kinetic models (R2 = 0.99) and Langmuir model (R2 = 0.99) – 89.75 Yılmaz et al. (2021)  
Commercial activated carbon 121 Adsorbent dose = 1.0 g/L, pH = 7.0, temperature = 298 K, and PCT initial con. ∼100–1,200 mg/L Redlich–Peterson (R2 = 0.993), Avrami model (R2 = 0.997), and Elovich model (R2 = 0.991) 221 (taken from Langmuir model) – Thanh et al. (2020)  
Activated carbon 15.90 Adsorbent dose = 0.16 g/100 mL, PCT con. = 11.52 mg/L, and contact time = 90.52min Langmuir (R2 = 0.996), Temkin (R2 = 0.998), and pseudo-second-order kinetic model (R2 ≥ 0.99) 15.90 99.24 Tunç et al. (2022)  
Activated carbon from Butia capitata endocarp 100.6 Equilibrium time = 180 min Langmuir model (R2 = 0.971) and Elovich (R2 = 0.994) 100.60 – Kerkhoff et al. (2021)  
Nanosized hematite-assembled carbon spheres 49.9 Equilibrium time = 120 min, temperature = 598 K, and pH = 7.0, adsorbent dose = 2 g/L Langmuir model (R2 ≥ 0.994) and pseudo-second-order (R2 ≥ 0.975), and Elovich models (R2 ≥ 0.979) 49.90 – Loc et al. (2021)  
Silica microspheres 89.0 Contact time = 30 min, pH = 5.0, PCT = 20 mg/L, temperature = 303 K, and sorbent dose = 100 mg/L Freundlich isotherm (R2 = 0.99) and second-order kinetic model (R2 = 0.99) 89.0 96.7 Natarajan et al. (2021)  
Carbon-based adsorbents from brewery waste – Equilibrium time = 20 min, pH = 4, and adsorbent = 0.45 g Langmuir isotherm (R2 = 0.994) 30.8 98.3 Nadolny et al. (2020)  
Groundnut shell 3.02 – Langmuir (R2 = 0.99) and Sips model (R2 = 0.99)   – N'diaye & Bollahi (2019)  
CAC 188.67 PCT con = 20 mg/L, CAC dose = 0.5 g/L, contact time = 90 min, pH = 8.0, and temperature = 298 K Langmuir, Freundlich, and Redlich–Peterson isotherm models and pseudo-second-order model 188.67 99.6 This study 
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Environmental application

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The removal of PCT by CAC was tested on different water matrix, including ultrapure water, tap water, and real wastewater. Previous studies indicated that pharmaceutical contaminant removal was correlated well with the UV254 reduction and confirmed that it could be an indicator to control the performance of pharmaceuticals adsorption in tertiary treatment (Alves et al. 2018). Moreover, the studies suggested UV254 as a handy indicator for approximating pharmaceutical contaminant removal in practical applications where direct pharmaceutical concentration quantification is not available (Zietzschmann et al. 2014). Herein, three different sets of experiments were conducted for pure water, tap water, and WWTP effluent to investigate the effect of water background matrix (background organic matter) on the PCT adsorption using CAC. On the other hand, the wavelength scan of PCT showed maximum absorbance at 243 nm. The UV254 and UV243 were used to estimate PCT removal from real environmental samples. Before spiking PCT to the water samples, UV254 and UV243 were 0, 0; 0, 0; and 0.232, 0.343 for ultrapure, tap and real wastewater, respectively. After spiking PCT to water samples, the UV254 and UV243 were 0.857, 1.167; 0.878, 1.177; 1.174, 1.592 for ultrapure, tap, and real wastewater, respectively. The absorbance increase is directly related to the spiked amount of PCT in the water samples. Herein, the increase in UV243 is more significant than the increase in UV254. This is ascribed to the maximum absorbance of PCT at UV243. Thus, the decrease in absorbance at 243 nm is also directly correlated with decrease in PCT concentration in environmental samples. Adsorption experiment was conducted at optimum parameters obtained in the previous steps. Adsorbent dosage was varied (0.5, 1.5 and 2.0 g/L) to achieve the maximum removal of PCT from real environmental samples. All the tested adsorbent doses resulted in UV254 and UV243 absorbance values less than the initial absorbance of the samples (unspiked initial samples). This shows that CAC can successfully remove PCT in the presence of complex organic matter.

On the other hand, this can be explained using UV254 and UV243 reduction after adsorption. Figure 13(a)–13(c) depicts a UV254 reduction of 99.85, 99.95, and 100% and a UV243 reduction of 99.45, 99.61, and 100% for ultrapure water using 0.5, 1.5, 2.0 g/L CAC, respectively. Similarly, it shows UV254 reduction of 91.45, 95.68, and 100% and UV243 reduction of 90.22, 93.27, and 100% using CAC dose of 0.5, 1.5, and 2.0 g/L. Interestingly, the UV254 reduction of 82.53, 86.65, and 91.22%, and UV243 reduction of 79.39, 81.32, and 87.31% using CAC doses of 0.5, 1.5, and 2.0 g/L, respectively, were achieved for the real wastewater sample. The UV254 removal correlated well with the pharmaceutical removal, which is confirmed as an indicator to control the performance of the adsorption of the pharmaceuticals with μGACs in tertiary treatment. The observed difference in UV254 and UV243 reduction for the three samples is due to the difference in organic matter, which competes during the adsorption process. These results indicate that CAC has higher removal efficiency for PCT in actual wastewater, which contains various ions and organic matter. To have a broader view of CAC application in real wastewater treatment, further studies on the comparative evaluation of analysis methods such as high-performance liquid chromatography (HPLC) and UV–Vis analysis (UV254) (Zietzschmann et al. 2014) are highly encouraged. Moreover, the CAC adsorbent needs to be tested for multiple pharmaceutical contaminant removal in real wastewater samples using HPLC for pharmaceutical contaminant quantification. Here, CAC was prepared at a higher temperature (700 °C) but at a low carbonation time (60 min). Depending on the time of carbonation, a higher adsorbent preparation temperature is associated with a higher cost. Therefore, further studies can optimize the carbonation temperature and time of CAC preparation process, which is important for the economic evaluation of the adsorbent material.
Figure 13
The effect of water matrix on percentage UV254 and UV243 reduction using CAC adsorbent dose: (a) 0.5 g/L, (b) 1.5 g/L, and (c) 2.0 g/L.
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The effect of water matrix on percentage UV254 and UV243 reduction using CAC adsorbent dose: (a) 0.5 g/L, (b) 1.5 g/L, and (c) 2.0 g/L.

Figure 13
The effect of water matrix on percentage UV254 and UV243 reduction using CAC adsorbent dose: (a) 0.5 g/L, (b) 1.5 g/L, and (c) 2.0 g/L.
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The effect of water matrix on percentage UV254 and UV243 reduction using CAC adsorbent dose: (a) 0.5 g/L, (b) 1.5 g/L, and (c) 2.0 g/L.

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Mechanism of PCT adsorption

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The adsorption mechanism of PCT adsorption onto CAC was examined to reveal the nature of the adsorption process. The adsorption mechanism could occur by hydrogen bonding, n–π and π–π interactions between the PCT and CAC (Yılmaz et al. 2021). Hydrogen bonding interactions between N–H and O–H groups of PCT and carbonyl groups of CAC could occur during the adsorption process (Yılmaz et al. 2021). Hydrogen bonding formations were suggested by decreasing band intensity in the FTIR spectrum at 3,456 cm−1 (–OH) and 1,052 cm−1 (C–O) (Paredes-Laverde et al. 2019; Loc et al. 2021). Another vital mechanism involved is the n–π interaction between the aromatic rings of PCT molecules and O atoms of CAC. Moreover, the π–π interaction between the aromatic rings in CAC with the aromatic rings of PCT molecules may have played a significant role (Paredes-Laverde et al. 2019; Loc et al. 2021). Additionally, Lewis acid–base interaction can occur between the Fe–O in CAC as Lewis acid and nitrogen/oxygen sites as Lewis base (Yılmaz et al. 2021) because PCT is a weak electrolyte that coexists in both non-ionized and ionized forms of PCT. The pKa value of PCT is 9.38. In PCT adsorption onto CAC, the electrostatic attraction was insignificant for solution pH from 2 to 8. In contrast, electrostatic repulsion significantly affected the PCT removal for pH above 9. This is ascribed to strong electrostatic repulsion between the ionized form of PCT and the negatively charged surface of CAC (Loc et al. 2021). The mechanism of PCT adsorption onto CAC is illustrated in Figure 14.
Figure 14
The proposed mechanism of PCT adsorption onto CAC.
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The proposed mechanism of PCT adsorption onto CAC.

Figure 14
The proposed mechanism of PCT adsorption onto CAC.
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The proposed mechanism of PCT adsorption onto CAC.

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CAC was successfully prepared at 700 °C, characterized, and applied for PCT sorption. The adsorption process parameters (initial PCT concentration, pH, contact time, and CAC dose) were optimized using a one-factor at a time approach. Accordingly, optimal conditions (CAC = 0.5 g/L, pH = 8.0, time = 90 min, and PCT concentration = 20 mg/L) were obtained. At these optimum conditions, PCT removal of 99.6% was achieved. The PCT adsorption was influenced by varying the initial PCT concentration, pH, contact time, and CAC dose. Various sorption isotherm models, kinetic and thermodynamic equations were applied to sorption data. Isotherm study showed that the adsorption of PCT onto the CAC surface was in a monolayer on the heterogeneous surface of CAC with a maximum monolayer Langmuir sorption capacity of 188.68 mg/g. Pseudo-second order gave the best fit for the adsorption study. The process of PCT adsorption onto the CAC was exothermic (negative ΔH), spontaneous, and favorable. Application of the CAC in real wastewater samples showed remarkably good results. However, further studies need to be conducted to investigate the feasibility of using CAC for other pharmaceutical contaminants. Overall, the CAC is a low-cost, efficient, and reusable adsorbent with a promising potential for application in PCT removal from water.

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The Africa Center of Excellence for Water Management (ACEWM), Addis Ababa University, Ethiopia, is acknowledged for its financial support.

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

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The authors declare there is no conflict.

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