Synthesis and Application of Calcined Magnetic Biochar Composite for the Enhanced Removal of As^III and As^V from Aqueous Solutions

Abstract

The presence of high levels of arsenic in water bodies is a global health threat and requires efficient removal technologies. Calcined magnetic biochar composite (CMBC) was synthesized for the adsorptive removal of As^III and As^V from aqueous solutions. Different characterization techniques were performed. The experiments were conducted under various conditions such as adsorbent dosages, initial concentrations, contact time, and pH levels. The results of the Langmuir adsorption isotherm model revealed that the maximum adsorption capacities (q_max) were 53.21 mg g^-1 for As^III and 210.97 mg g^-1 for As^V. The substantial difference could be the negatively charged species bind strongly to the iron oxide surface through both electrostatic attraction and chemisorption, at the studied pH (7.0). Whereas As^III showed weaker interactions with the adsorbent composite. Additionally, the Freundlich isotherm model confirmed favorable adsorption by representing (n > 1) for As^III and As^V, indicating favorable adsorption on a heterogeneous surface formed during calcination. The PSO kinetics is best fitted for kinetic study, demonstrating across chemisorption processes for removing As^III and As^V. The findings of this study showed that the prepared adsorbent composite can be valuable for developing impactful strategies to remediate arsenic-contaminated water.

Keywords:
calcination; arsenic adsorption; magnetic biochar composite; impactful strategy; mechanism

Introduction

Arsenic (As), a naturally occurring metalloid with an atomic number of 33, ranks as the 20^th most abundant element on the crust of the Earth. It is well-known for its toxic effects on human and aquatic life.¹ The primary contributors to arsenic contamination in groundwater are natural and anthropogenic activities, such as weathering of arsenic-rich minerals and the improper discharge of effluents from the metallurgical and mining industries, and the use of arsenic-based pesticides.² Two forms of arsenic (i.e., organic and inorganic) are predominantly existed in nature. The organic arsenic is bound to elements like hydrogen and carbon, while inorganic arsenic is bonded with chlorine, oxygen, or sulfur.³ Inorganic arsenic is mostly found as As^III species (HAsO₃^2-, H₂AsO₃^-, and AsO₃^3-) and As^V species (HAsO₄^2-, H₂AsO₄^-, and AsO₄^3-) in aqueous solution.⁴ In addition, As^III is around 60 times more poisonous, stable, soluble, and mobile than As^V due to its electronic configuration.⁵ The World Health Organization⁶ (WHO) has recommended the allowable limit of arsenic in drinking water is 10 μg L^-1. More than 200 million people are exposed to arsenic levels exceeding the permissible limit in about 105 countries globally.⁷ Arsenic is highly toxic to humans causing respiratory and cardiovascular diseases, neurological diseases, muscular weakness, hyper pigmentation, skin thickening, and increasing risk of cancer as well as diabetes.⁸ Besides, arsenic contamination also exerts severe toxic effects on aquatic plants and animals. In aquatic plants, arsenic exposure can inhibit seed germination, suppress photosynthesis, reduce chlorophyll synthesis, impair nutrient uptake, and induce oxidative stress through excessive reactive oxygen species (ROS) generation.⁷ Furthermore, arsenic accumulation in aquatic macrophytes and algae can disturb cellular metabolism and negatively affect growth and biomass production.⁸ In aquatic animals such as fish, crustaceans, and benthic organisms, arsenic exposure may cause physiological and biochemical alterations including oxidative stress, enzymatic inhibition, reproductive toxicity, immune dysfunction, and behavioral disorders.⁸,⁹ Prolonged arsenic accumulation through aquatic food chains can further threaten ecosystem stability and biodiversity, making arsenic pollution a serious ecological concern in addition to its human health impacts.⁷-⁹ Therefore, developing advanced technologies for its effectively removal from drinking water is very important.⁹,¹⁰ Also, the applications of efficient materials have been successfully tested to meet As removal objectives including alumina,¹¹ activated carbon,¹² adsorbent resin,¹³ silica gel,¹⁴ and zeolite.¹⁵

Over the past decades, different methods have been used for As removal from aqueous solutions including precipitation,⁶ membrane separation,¹⁵ ion exchange,¹⁰ oxidation and coagulation,⁹ permeable reactive barriers,¹⁶ and adsorption.⁶,¹⁷ Compared with other arsenic removal techniques, adsorption has attracted significant attention because of its operational simplicity, low energy requirement, high removal efficiency, easy regeneration, and reduced sludge generation.⁶,⁹,¹⁷ Membrane-based technologies often require high operational pressure and suffer from membrane fouling,¹⁵ whereas coagulation and precipitation processes generate large volumes of secondary sludge that require additional disposal treatment.⁹ Similarly, ion exchange systems are relatively expensive and their performance can be affected by competing ions present in water.¹⁰ In contrast, adsorption systems are comparatively economical, environment-friendly, and highly adaptable in decentralized water treatment applications, particularly in developing regions where low-cost and sustainable treatment technologies are needed.¹⁷,¹⁸ However, every adsorbent has distinct physicochemical properties, which shows various adsorption mechanisms and performance. Furthermore, activated carbon offers strong adsorption capacity and a large surface area but relatively its high production cost restricts its extensive use. Although other adsorbents such as adsorption resin, silica gel, and alumina are hindered by drawbacks like the narrow adsorption surface and the fabrication of polyacrylamide remains technically challenging. Therefore, developing cost effective and environment-friendly adsorbents with high removal efficiency for As-contaminated water is essential.⁶,¹⁶ In recent years, new high performance adsorbent platforms such as ionic liquid-modified electrospun nanofibers have been shown to be highly effective for metal recovery from wastewater demonstrating greater adsorption affinity and performance compared to traditional adsorbent materials.¹⁷

A permeable carbonaceous material known as biochar is produced when biomass feedstock experiences a thermo-chemical breakdown in an oxygen-limited environment. Any organic discarded material, such as forest and agricultural residues, organic municipal solid wastes, algae, sewage sludge, and manures can be used as biomass feedstock.¹⁸-²⁰ Over the past, various feedstock have been utilized to synthesize biochar such as sewage sludge,²¹ peanut shell,²² rape straws,²³ pine sawdust,²⁴ water hyacinth,²⁵ rice husk,²⁶ corncob,¹⁹ spent mushroom,²⁷ dairy manure,²⁸ wheat straw,²⁹ coconut shell,³⁰ eggshell,³¹ parthenium,³² spartina alterniflora,³³ and macroalgae.³⁴ The efficiency of biochar in water and wastewater treatment is mainly due to its special surface properties and surface characteristics such as oxygen rich functional groups, highly negative charge surface area, high carbon content, abundant mineral content, high porosity, and great cation exchange capacity.³⁵ However, these special surface properties and characteristics of the biochar are highly influenced by the type of feedstock and the pyrolysis conditions including contact time, temperature, gas flow, and heating rate.³⁶

Notably, biochar synthesis using corncob feedstock aligns with the principles of sustainability and the circular economy, as agricultural waste can be recycled into value-added adsorbents to control pollution. Current research has shown that biomass-derived biochar can be engineered to synthesize magnetic nano zero-valent iron-supported biochar, which has improved adsorption capacity and a mechanistic advantage for contaminant remediation, highlighting the importance of waste to resource approaches.³⁷ Besides biomass residues, the current trend in circular-economy frameworks involves using plastic waste, particularly polyethene terephthalate (PET) to develop reusable adsorbents for water purification on a sustainable basis, thereby promoting the theory of waste valorization in modern day remediation science.³⁸

Furthermore, metal loading and magnetic modification is important to improve biochar adsorption efficacy, while surface modification and activation significantly enhance its capacity to remove inorganic and organic contaminants.³⁹ For instance, Sahu et al.³⁷ developed a cost-effective magnetic biochar by incorporating nano-zero-valent iron (nZVI) on to the litchi chinensis peel biochar, achieving approximately 95.38% removal of Cr^VI. In another study,⁴⁰ a polyaniline-enhanced magnetic biochar was prepared, demonstrating high removal efficiencies of 141.89 mg g^-1 for Hg²⁺ and 124.78 mg g^-1 for Cu²⁺. In previous studies, magnetic materials have been used for magnetic modification of biochar such as Fe⁰, α-Fe₂O₃, γ-Fe₂O₃, and Fe₃O₄. Magnetically modified biochar has a remarkable ability to adsorb contaminants from polluted water and can be readily separated by an external magnet.⁴¹ However, there are still limited studies reported on the combined effects of magnetic modification and high-temperature calcination on biochar composites for the simultaneous removal of As^III and As^V from aqueous solutions. In particular, the influence of calcination on the physicochemical characteristics, adsorption behavior, pore structure, crystallinity, and adsorption mechanisms of magnetic biochar composites remain unexplored. Therefore, the novelty of the present study lies in the synthesis of a novel calcined magnetic biochar composite (CMBC) derived from low-cost corncob biomass through co-precipitation followed by thermal calcination for enhanced arsenic removal. Unlike conventional biochar adsorbents, the synthesized CMBC integrates magnetic separability, improved pore accessibility, enhanced surface functionality, and increased adsorption active sites, which collectively improve arsenic adsorption performance. The adsorption performance of CMBC was systematically evaluated under varying operational conditions including pH, contact time, adsorbent dosage, and initial arsenic concentration. In addition, adsorption isotherm, kinetic, and mechanistic investigations were systematically carried out to better understand the adsorption behavior and possible removal pathways responsible for arsenic removal. Overall, the integration of magnetic modification with calcination offers a promising, sustainable, and environmentally friendly strategy for developing efficient biochar-based adsorbents for arsenic-contaminated water treatment.

Experimental

Materials and reagents

Sodium arsenate dibasic heptahydrate (Na₂HAsO₄.7H₂O, 98.0%) and sodium (meta) arsenite (NaAsO₂, 99.0%) were purchased from Sigma-Aldrich and used for As^V and As^III stock solutions preparation. Deionized (DI) water was used as the primary solvent for the preparation of different stock and working solutions. The glassware used in the experiments was rinsed with (HNO₃, 65%) and DI water, subsequently vacuum-dried at 100 ºC to ensure complete cleanliness. The initial pH of the As^III and As^V solution was adjusted by a digital pH meter using 0.1 M (HCl, 37%) and 0.1 M (NaOH, 98%) to ensure accuracy and consistency in the experimental procedures. All the chemicals including sodium chloride (NaCl, 99.0%), nitric acid (HNO₃), hydrochloric acid (HCl), iron sulfate heptahydrate (FeSO₄.7H₂O, 99.0%), and iron chloride hexahydrate (FeCl₃.6H₂O, 98.0%) of high-quality grades were purchased from Alfa-Aesar and Sigma-Aldrich.

Biochar synthesis

Corncob biomass was collected from local farmlands in the Rashakai area of District Nowshera, Pakistan. Firstly, the corncob was rinsed several times with water and left to sun-dried for several days to minimize the moisture content. Once sufficiently dried, it was crushed into small parts using a mortar and pestle. The dried samples were transferred to Abdul Wali Khan University Mardan (AWKUM) Environmental Engineering Lab to synthesize biochar. Using a slow pyrolysis method, the samples were processed to make biochar in a locally built biochar machine,⁴² for 1 h at 350 ºC. Subsequently, the prepared biochar was stored in an airtight container to preserve their properties for further experimental works.

Synthesis of calcined magnetic biochar composite (CMBC)

The dried biochar was used alongside Fe₃O₄ in an enhanced chemical co-precipitation method to synthesize the Fe₃O₄-biochar composite. Figure 1 presents the synthesis procedure of calcined magnetic biochar composite (CMBC). Briefly, 5.06 g of FeCl₃.6H₂O and 5.2 g of FeSO₄.7H₂O were dissolved in 100 mL of DI water in a 250 mL beaker. They were mixed vigorously under constant stirring. Then, about 5 g of the corncob derived biochar was slowly introduced into the prepared FeCl₃.6H₂O and FeSO₄.7H₂O solutions, which was stirred at 60 ºC for 30 min until the color of the solution turned dark brownish. The solution was then cooled to room temperature, and NaOH was added until the pH reached 11. Afterwards, the black deposit was collected through filtration using a 0.45 µm filter paper and rinsed with DI water to remove the impurities. Finally, the solid particle was collected using external magnet, thoroughly the particles were then dried at 105 ºC for 3 h.⁴³ Then the dried magnetic biochar (MBC) was calcined in a high-temperature muffle furnace at 800 ºC for 1 h,⁴⁴ and the calcined magnetic biochar (CMBC) was stored in airtight containers to preserve their properties for further experiments.

Figure 1.
Synthesis procedure of biochar and calcined magnetic biochar composite (CMBC).

Adsorption experiments

Batch adsorption experiments were conducted to evaluate the adsorption capacity and removal efficiency of CMBC for As^III and As^V. For this purpose, As^III and As^V stock solutions of 1000 mg L^-1 strengths were prepared by dissolving an appropriate amount of sodium (meta) arsenite (NaAsO₂) and sodium arsenate dibasic heptahydrate (Na₂HAsO₄.7H₂O) in 1000 mL of DI water. However, before the adsorption study, each stock solution was diluted to a concentration of 40 mg L^-1. All adsorption experiments were carried out in 250 mL conical flask with 100 mL of the prepared As^III and As^V solutions. The effect of the initial pH was examined by changing the solution pH from 2.0 to 9.0 after adding 0.4 g of adsorbent into 100 mL of the 40 mg L^-1 As^III and As^V stock solution, and the flasks were subjected to a rotatory shaker in constant shaking at 150 rpm for 3 h at room temperature (23 ± 2 ºC). To evaluate the effect of adsorbent dose, various amounts of adsorbent (0.1, 0.2, 0.3, 0.4, and 0.5 g) were added into 100 mL of the 40 mg L^-1 of As^III and As^V solutions. Adsorption isotherms were studied by adding 0.4 g of adsorbent to 100 mL of As^III and As^V solutions with varying concentrations (10, 20, 30, 40, 50, 60, and 70 mg L^-1) in 250 mL conical flasks and pH of the solutions were adjusted to about 7.0. The flasks were subjected to a rotatory shaker for constant shaking at 150 rpm for 3 h at room temperature (23 ± 2 ºC). Furthermore, for adsorption kinetics studies, 0.4 g of adsorbent was accurately weighed into 250 mL conical flasks containing 100 mL of the 40 mg L^-1 As^III and As^V solutions. The pH of the solution was adjusted to 7.0 and then the mixture was shaken at 150 rpm at a room temperature of 23 ± 2 ºC for predetermined intervals of 30, 60, 90, 120, 150, and 180 min. The remaining concentration in the filtrate was analyzed by using inductively coupled plasma optical emission spectroscopy (ICP-OES) (Thermo scientific, iCAP 600, United Kingdom) after filtration, and the removal efficiency (RE / %) and adsorption capacity (q_e),⁴⁵ was calculated by the given equations 1 and 2:

(1) $q_{\text{e}}=\frac{\left({\text{C}}_{\text{o}}-{\text{C}}_{\text{e}}\right)\text{V}}{\text{m}}$

(2) $\text{RE}=\frac{{\text{C}}_{\text{o}}-{\text{C}}_{\text{e}}}{{\text{C}}_{\text{o}}}\times 100$

where q_e is the amount of As^III and As^V adsorbed on the CMBC at the equilibrium time (mg g^-1), V is the volume of the solution (mL), C_o and C_e are the initial and equilibrium As^III and As^V concentrations (mg L^-1), respectively, and m represent the amount of adsorbent (g).

All adsorption experiments were conducted in a single-solute system utilizing DI water to evaluate the intrinsic adsorption capacity of CMBC under controlled laboratorial conditions, free of competing ions or complex water networks. Each adsorption experiment was conducted in triplicates, and the mean values were used. The values given are averages of three separate readings and the error bars denote the standard deviation. The measurements were in good experimental precision and reliability with a relative standard deviation (RSD) of the measurements in general being within 3%.

Equipment

In this study, inductively coupled plasma optical emission spectroscopy (ICP-OES) (Thermo scientific, iCAP 6500, United Kingdom) was used to test the remaining As^III and As^V concentration in the filtrate. The equipment system was equipped with an integrated hydride generation unit and the measurements were taken in 189.0, 193.7, and 197.0 nm. Also, the emission line As 189.0 nm was used to overcome spectral interferences and generate reliable results. Fourier transform infrared spectroscopy (FTIR) (Thermo-Nicolson7500, USA) was used to determine various functional groups in the synthesized material composite and performed using KBr disc method and measured as wavenumber (cm^-1). The infrared spectroscopy was used in the range of 400-4000 cm^-1. The surface morphology and pore size were determined using a scanning electron microscope (SEM) with the following specifications: energy: 30 kV, magnification (max): 300,000×, resolving power (max): 2.3 nm (JSM5910, JEOL, Japan). Energy-dispersive X-ray spectroscopy (EDX) (Oxford instrument, INCA200, UK, analysis range: boron to uranium) was used to determine the elemental composition of the samples. The X-ray diffraction (XRD) analysis (JDX-3532, JEOL, Japan) is used to determine of the adsorbent composite crystal structure. The diffractograms were obtained using Cu Kα radiation, 40 kV, 40 mA with the scanning speed of 0.2° min^-1 and the diffraction angle ranges 10-80°. In addition, the total pore volume and average pore size of the adsorbent composites were determined from nitrogen adsorption/desorption isotherms at 77 K using an automated gas sorption analyzer. The specific surface area was obtained by the Brunauer-Emmett-Teller (BET) method, while the pore size distribution was obtained by the Barre-Joyner-Halenda (BJH) method (Micromeritics, Gemini VII 2390, Japan).

Statistical analysis

Microsoft Excel (2016) was employed for data analysis. Match 3 software (version 3.15, Crystal Impact GbR, 2023) was employed for peak analysis, crystallinity, and phase identification. Origin Pro software (version 9.0, OriginLab Corporation, Northampton, MA, USA, 2012) was employed for data fitting, analysis, and visualization of experimental results and crystallinity (%) of the material was calculated by the given equation 3:

(3) $\text{crystallinity}=\frac{\text{area of crystalline peaks}}{\text{total area of peaks}}\times 100$

The linear and nonlinear adsorption isotherms data were comprehensively studied using the Freundlich model and Langmuir model, which are stated as follows (equations 4-7) and employed in recent studies.³,¹⁵

(4) $ln{q}_{\text{e}}=ln{\text{K}}_{\text{f}}+\frac{1}{\text{n}}ln{\text{C}}_{\text{e}}$

(5) $q_{\text{e}}=\frac{q_{max}{\text{K}}_{\text{L}}{\text{C}}_{\text{e}}}{\text{1}+{\text{K}}_{\text{L}}{\text{C}}_{\text{e}}}$

(6) $\frac{{\text{C}}_{\text{e}}}{q_{\text{e}}}=\frac{1}{q_{max}{\text{K}}_{\text{L}}}+\frac{{\text{C}}_{\text{e}}}{q_{\text{e}}}$

(7) $q_{\text{e}}={\text{K}}_{\text{f}}{\text{C}}_{\text{e}}$

where C_e represent the concentration of As^III and As^V at equilibrium (mg L^-1), q_max denotes the maximum adsorption capacity of the CMBC (mg g^-1), q_e represent the equilibrium adsorption capacity (mg g^-1), K_f and 1/n are the Freundlich constant and indicates the intensity and adsorption capacity (mg g^-1) (mg L^-1)^1/n, respectively, K_L is the Langmuir constant that reflects the affinity of binding sites (L mg^-1). The linear and nonlinear adsorption kinetics data were comprehensively studied using pseudo-first-order (PFO) and pseudo-second-order (PSO) of kinetics models,¹⁰ expressed as in equations 8-11:

(8) $ln\left(q_{\text{e}}-q_{\text{t}}\right)=ln{q}_{\text{e}}-{\text{k}}_1\text{t}$

(9) $q_{\text{t}}=q_{\text{e}}\left(1-{\text{e}}^{-\text{k1t}}\right)$

(10) $\frac{\text{t}}{q_{\text{t}}}=\frac{1}{{\text{k}}_{\text{2}}{q}_{\text{e}}}+\frac{\text{t}}{q_{\text{e}}}$

(11) $q_{\text{t}}=\frac{{\text{k}}_{\text{2}}{q}_{\text{e}}\text{t}}{1+{\text{k}}_{\text{2}}{q}_{\text{e}}\text{t}}$

where q_t denotes the adsorption capacity (mg g^-1) at time t (min), k₁ (min^-1) and k₂ (g mg^-1 min^-1) represent the rate-constant for the adsorption of PFO and PSO of kinetics models, respectively.

Results and Discussion

Characterization results

Figures 2a-2c show the SEM images of the prepared adsorbent composites. It demonstrates a rough and porous structure with visible cavities and uneven surface morphological characteristics of the biochar structure,³⁹ as illustrates in Figure 2a. Such characteristics can provide additional loaded sites for Fe precipitations. In comparison to biochar, CMBC depicts a rougher and compact surface, marked by distinct granular features, as shown in Figure 2b. However, in CMBC the presence of iron-based complexes such as iron oxides or hydroxides is evident and suggests successful magnetization and calcination. These particles are distributed across both the external and internal surface of the adsorbent composite.⁹ Furthermore, the CMBC revealed a more heterogeneous structured compared to the biochar composite (BC), which may improve the adsorption capacity of CMBC for As^III and As^V from aqueous solutions.⁴⁶ Figure 2c presents the SEM image of CMBC after arsenic adsorption and named As-loaded CMBC. It revealed that the As-loaded CMBC demonstrated more aggregated particles along with partially smooth surface. Additionally, the observed shrink in pore space and formation of particle clusters reveal that arsenic has stuck to the surface, filling active sites and blocking certain pores in the line of the reported study,³⁹ confirmation of successful adsorption onto CMBC.

Figure 2.
SEM images (a) corncob biochar, (b) calcined magnetic biochar, (c) As-loaded adsorbent composite and (d) zoom in on As-loaded adsorbent composite.

Table 1 shows the elemental compositions of BC, CMBC and As-loaded CMBC, and the EDX spectra are presented in Figures 3a and 3b. The results demonstrated considerable changes in the elemental compositions during thermal treatment and magnetic modification. In BC, carbon was the dominant element with 81.51 wt.%, which reflects the carbon-rich structure due to the pyrolysis of biomass. In contrast, in CMBC, the C content decreased abruptly and remained 12.65 wt.%, probably because of the partial burning and deterioration of volatile organic compounds (VOCs) in high-temperature calcination, which are consistent with the findings reported in previous studies.⁴⁷,⁴⁸ Similarly, the oxygen content also dropped significantly highlighting the reduction of oxygen-containing functional groups, which is usually witnessed throughout thermal decomposition and calcination.⁴⁹ Notably, the Fe content was the predominant element with a 82.01 wt.% in CMBC, but not detected in BC, which affirms the successful loading of iron oxides on to the biochar. The imparting of Fe is essential to improve magnetic characteristics and adsorption capacity of the adsorbent.⁵⁰ Other elements including Cu, K, Zn, Mg, and Ca were found to significantly reduce in CMBC (Table 1), because of the exchange of Fe-species and vaporization. Additionally, the presence of Na and P in CMBC indicates the participation of chemical reagents utilized during synthesis. The appearance of 0.56 wt.% in As-loaded CMBC indicated the successful arsenic adsorption onto the prepared adsorbent composite (Table 1). Generally, these changes affirm the successful modification of BC into CMBC, and the modified elemental properties greatly support its possible uses in environmental remediation measures.

Table 1.
Results of the EDX analysis of BC, CMBC, and As-loaded CMBC

Element	BC		CMBC		As-loaded CMBC
	wt.%	at.%	wt.%	at.%	wt.%	at.%
C	81.51	86.95	12.65	38.09	0.56	1.48
O	14.59	11.68	2.22	5.02	27.35	54.59
Na	−	−	0.91	1.44	−	−
Mg	0.13	0.06	−	−	−	−
Si	0.39	0.17	0.40	0.51	1.29	1.47
P	−	−	0.40	0.47	2.01	2.07
Al	0.22	0.10	−	−	0.8	0.95
Cl	0.40	0.15	0.69	0.70	0.17	0.15
Zn	0.09	0.02	−	−	−	−
Ca	0.06	0.03	−	−	0.28	0.22
Fe	−	−	82.01	53.11	64.73	37.01
K	2.40	0.79	0.72	0.66	0.21	0.18
Cu	0.21	0.05	−	−	0.55	0.27
As	−	−	−	−	0.56	0.24

Figure 3.
Results of the EDX analysis of (a) BC and (b) CMBC.

Figures 4a-4c presents the results of FTIR analysis of BC, CMBC, and As-loaded CMBC in the range of 400-4000 cm^-1. The FTIR spectra of BC showed a low absorbance peak at a range of 1032.5 cm^-1 which is assigned to CO functional group and peak around 1620-1650 cm^-1 due to C=O group.⁴²,⁵¹ The positional shifts and transmittance variations particularly at 1600 and 1000-1200 cm^-1 indicate that iron and surface functional groups interact chemically. The shifts in peaks at 685.8, 533.0, and 439.8 cm^-1 indicate the Fe−O band vibrations, confirming the successful magnetization of BC,⁴⁴,⁵² as shown in Figure 4b. Furthermore, the bands at 1557.9, 1053, and 1032 cm^-1 indicate the bending vibrations of the C=C, C−O−C, and O−H functional groups, respectively.⁴²,⁵³ The bands noted at 2321.8 and 2087.9 cm^-1 in CMBC and As-loaded CMBC are aligned to the –CH₂ and –CH₃ groups, but the absorbance of the bands were reduced after arsenic adsorption,² as shown in Figure 4c. The disappearance or reduction of C−O and –OH peaks at 3400 and 1000-1200 cm^-1 infers the oxygen-containing and hydroxyl groups in arsenic binding. Whereas, the shifted or new bands in the Fe−O region 400-900 cm^-1 indicate the creation of inner spectral complexes between iron oxides and arsenic species,⁹,³⁹ as illustrated in Figure 4c. These changes in peak shifting and band intensity are the primary indicators of chemical binding/complexation and justify chemical characterization to elucidate the mechanisms. Analogous focus on surface chemical interactions towards detection and interpretation of trace contaminants has also been described in high-technology voltametric sensing systems utilizing functionalized nanocomposites.⁵⁴ However, such spectral feature changes suggest effective arsenic adsorption which is most likely accomplished by processes, such as electrostatic attraction, ligand exchange, and complexation.

Figure 4.
Results of the FTIR (a) BC, (b) CMBC, and (c) As-loaded CMBC.

Figures 5a-5c illustrate the XRD patterns of BC, CMBC, and As-loaded CMBC. The crystalline forms of powdered materials including biochar reveals the presence of mineral phases.⁵⁶ Results showed that the BC exhibits 35.3% crystallinity, and two broad peaks were observed at 2θ = 15º and 21º in the XRD pattern of BC (Figure 5a) and the characteristics of the semi-crystalline structure of cellulose parallel to its usual diffraction profile.⁵⁶ In contrast, CMBC exhibits 20.63% crystallinity and the decline could be the incorporation of iron oxide and thermal effects introduced by lattice strain and disturb carbon ordering.⁵⁷ Following arsenic adsorption, the crystallinity further drops to 5.1% due to high surface complexation and the formation of amorphous metal-arsenate, which distorts the framework and slightly weakens the diffraction planes.⁵⁸ Various diffraction peaks were observed at 2θ = 30.24, 35.81, 43.27, 53.74, 57.65, and 62.89º, which can be indexed to the (220), (311), (400), (422), and (440) crystal planes magnetite (Fe₃O₄), respectively.⁴⁴,⁵⁹,⁶⁰ Also, the cubic magnetite is the major component in the composite material.⁵⁹ However, no any new crystalline phase was detected after adsorption, but the intensity of the XRD peaks were slightly weakened, which are in agreement with the findings reported earlier.⁴⁴

Figure 5.
XRD pattern (a) BC, (b) CMBC and (c) As-loaded CMBC.

Figures 6a-6b present the distributions of pore sizes and surface areas of BC and CMBC before and after magnetization and calcination. The pore properties were found to be significantly changed after the modification. Specifically, the mean pore size of BC and CMBC was 151.11 and 209.66 Å, respectively, which indicates that the pore size increased upon calcination. In addition, BJH pore analysis showed that the average pore diameter (adsorption branch) was found to rise to 255.74 Å (CMBC) compared to 180.89 Å (BC), whereas the BJH pore diameter (desorption branch) was found to decrease to 390.16 Å (CMBC) compared to 803.39 Å (BC). Table 2 shows the results for BET specific surface area. Sample BC shows 0.7937 m² g^-1 as compared to CMBC (4.5569 m² g^-1), indicating of an enhanced surface exposure and pore access after the modification. Based on the values of pore sizes, which are mostly in the 2-50 nm range, the modified material could be considered mesoporous. Moreover, high temperature devolatilization and pore unblocking during magnetization and calcination are attributed to increase the pore width. Generally, the incorporation of magnetic mineral phases has the potential to reorganize the carbon skeleton, leading to pore merging and the opening of wider mesoporous channels.⁶⁰ Overall, the BET/BJH results confirm that calcination transformed BC into a more accessible porous composite (CMBC), which is more desirable for adsorption processes.

Figure 6.
Results of the BET analysis (a) BC, (b) CMBC.

Table 2.
Results of the BET analysis of the BC and CMBC

Adsorbent	Surface area / (m2 g-1)	Pore size / Å
BC	0.7937	151.11
CMBC	4.5569	209.66

Effect of pH

The initial pH of the solution is an important factor in As^III and As^V adsorption because it directly influences the adsorbent-adsorbate interaction.⁴⁵ The removal efficiency of As^III and As^V by CMBC was investigated in ranges pH 2.0-9.0. Figure 7a illustrates the effect of solution pH on the sorption capacity and removal efficiency of As^III and As^V by CMBC. The maximum removal efficacy of As^III and As^V is reached at pH 7.0 and 8.0, respectively. As the pH gradually increased to 9.0, the removal efficiency of As^III decreased significantly, while the removal rate of As^V remained constant at pH 8.0, but slightly decreased at pH 9.0. When the pH is below 7.0, As^III mainly exist in the form of H₃AsO₃ and above 7.0 HAsO₃^2– and H₂AsO₃^– are formed.⁶¹ While As^V generally exists in the form of H₂AsO₄^– and H₃AsO₄ in the pH below 5.0. However, the surface of the adsorbent becomes protonated under these acidic conditions, rising a positive charge that increase electrostatic attraction with the negatively charged As^V.⁶² In this study, the removal of As^III did not change much with pH, indicating that a dominant complexation mechanism was profound which was less likely impacted by pH alterations. On the other hand, As^V showed consistently high removal within the pH ranges due to strong electrostatic interactions with the surface of the adsorbent that was protonated.

Figure 7.
Effect of various parameters on As^III and As^V adsorption onto CMBC (a) initial pH, (b) initial As^III and As^V concentrations, (c) contact time and (d) adsorbent dose.

Effect of adsorbent dose

The adsorbent dosage of CMBC plays a key role in the effective removal of As^III and As^V from aqueous solutions. In this study, the adsorbent dosage varied from 0.1 to 0.5 g under the studied conditions. The experiments were conducted for CMBC at a temperature of 25 ºC, equilibrium contact time of 180 min, an initial As^III and As^V concentrations of 40 mg L^-1, and the pH was unadjusted. The samples were shaken in the pre-decided time intervals during a 150 rpm shaking condition. The adsorbent dose effects the equilibrium between the adsorbent-adsorbate, leading to differences in the removal efficacy.⁶³ A minor change in the adsorbent dose can affect As^III and As^V removal and would directly impact the effectiveness of the treatment system. The effect of adsorbent dosage of CMBC on percentage removal of As^III and As^V is presented in Figure 7d. The percentage As^III and As^V removal remained 97.5 and 98.6% to 99 and 99.7%, respectively, using the adsorbent dosage from 0.1 to 0.5 g. There was little increase in both As^III and As^V removals after 0.4 g of adsorbent dose. The results illustrate that rising the adsorbent dosage notably improved the removal effectiveness due to the availability of more active adsorption sites.³⁹ The reason of no further increase in the removal of both As^III and As^V could be due to the results of the agglomeration of the adsorbent particles, which decreased surface area and active sites for adsorption.⁶⁴

Effect of initial concentration and adsorption isotherms

The effect of the initial As^III and As^V concentrations on As^III and As^V removal is an important aspect of the effectiveness of the isotherm models and to find out the maximum adsorption capacity (mg g^-1). The adsorption experiments were performed using initial As^III and As^V concentrations ranging from 10 to 70 mg L^-1. During these experiments all other factors affecting the adsorption process were kept constant, such as the adsorbent dosage was fixed at 0.4 g L^-1, pH 7.0, and the temperature was 25 ºC. To ensure proper contact time samples containing CMBC were stirred for 3 h at 150 rpm, and the results are illustrated in Figure 7b. It shows that the CMBC exhibits outstanding performance for both As^III and As^V with removal effectiveness remained above 98% for all investigated initial concentrations (10 to 70 mg L^-1), which demonstrated that a larger number of active sites are available on the adsorbent surface. However, when the initial concentration increased, the removal efficiency gradually declines over the period of the reaction. On further increasing the initial concentrations of As^III and As^V the number of arsenic ions exceeds the available active adsorption sites leading to a decline in the removal efficacy as a result of site saturation.⁶⁵ Therefore, the result of the adsorbent shows a declining trend for adsorption process on increasing the initial concentrations.

The equilibrium between the adsorbent and adsorbate in a liquid entrusts depends on different influencing factors such as the initial concentration of the adsorbate, surface area and characteristics of the adsorbent.⁴⁵ The Langmuir isotherms model is an ideal monolayer adsorption model that assumes that all the adsorption sites on the adsorbent surface have corresponding adsorption potentials that there is no interaction between the adsorbed molecules.⁶⁶ The Freundlich isotherm model is compatible for adsorption on heterogeneous surfaces and recommend that adsorption capacity may continuously increases at high adsorbate concentrations allowing for multilayer adsorption.⁶⁷ In this study, the Langmuir isotherms constant K and q_max were obtained by fitting the experimental data to the Langmuir model through the linear plot of C_e/q_e and C_e as represented in Figures 8a and 8b. However, linear fitting was used to find out the Langmuir constant and correlation coefficient (R²). The maximum Langmuir adsorption capacities q_max and R² values were 53.21 and 0.956 mg g^-1 for As^III, and 210.97 and 0.950 mg g^-1 for As^V, respectively. Furthermore, the Freundlich constants n and K_f were determined from the plot of log q_e and log C_e, as illustrated in Figures 8c and 8d. However, the R² values for Freundlich isotherm were 0.981 for As^III and 0.989 for As^V, respectively. All values of the isotherm constants for both Freundlich and Langmuir models are summarized in Table 3. Therefore, the higher R² values, the Freundlich isotherms model could better describe the As^III and As^V adsorption onto the adsorbent than Langmuir isotherm.

Figure 8.
Adsorption isotherm model for As^III and As^V removal onto CMBC (a) Langmuir isotherm for As^III, (b) Langmuir isotherm for As^V, (c) Freundlich isotherm for As^III, (d) Freundlich isotherm for As^V.

Table 3.
Langmuir and the Freundlich isotherm parameters of the model for the adsorption of As^III and As^V on calcined magnetic biochar

Adsorbent	Arsenic species	Langmuir model parameters			Freundlich model parameters
		qmax / (mg g-1)	KL / (L mg-1)	R2	Kf / (mg g-1) (mg L-1)1/n	n	R2
CMBC	AsIII	53.21	0.377	0.956	14.51	1.92	0.981
CMBC	AsV	210.97	0.097	0.950	29.52	1.95	0.989

To obtain more statistically reliable parameters, nonlinear regression was applied to the original isotherm equations, and the results are shown in Table 4. Also, nonlinear fitting curves are shown in Figures 9a-9d. Nonlinear regression does not transform variables and does not alter the original error structure of the data. The nonlinear Langmuir model had lower q_max values than the linear model, indicating that linearization overestimates adsorption capacity, especially at low concentration levels. Equally, the nonlinear Freundlich fit yielded parameter estimates that were not like those obtained with linear regression, underscoring the sensitivity of isotherm constants to the fit the technique. Although characterized by differences, the nonlinear Freundlich model has shown a strong correlation with experimental data R² = 0.999, which justifies the hypothesis of adsorption of a heterogeneous surface having versatile energy binding sites.

Table 4.
Nonlinear Langmuir and the Freundlich isotherm parameters of the model for the adsorption of As^III and As^V on calcined magnetic biochar

Adsorbent	Arsenic species	Langmuir model parameters			Freundlich model parameters
		qmax / (mg g-1)	KL / (L mg-1)	R2	Kf / (mg g-1) (mg L-1)1/n	n	R2
CMBC	AsIII	17.528	3.501	0.977	2.697	0.089	0.999
CMBC	AsV	16.064	16.549	0.953	3.572	0.023	0.999

Figure 9.
Nonlinear adsorption isotherm model for As^III and As^V removal onto CMBC (a) Langmuir isotherm for As^III, (b) Langmuir isotherm for As^V, (c) Freundlich isotherm for As^III, (d) Freundlich isotherm for As^V.

The comparison of linear and nonlinear isotherm analyses reveals that the nonlinear regression data yield more realistic and statistically robust adsorption parameters. Linear regression, on the other hand, provides a convenient initial analysis. Both methods agree that adsorption of As^III and As^V on CMBC is desirable and is dominated by heterogeneous surface interactions, rather than ideal monolayer adsorption.

Effect of contact time and adsorption kinetics

The effectiveness of a fast adsorption process of toxic pollutants from water environment plays an important role in determining the overall operational cost of treatment technologies. Therefore, for the sustainable and cost-effective operation of a treatment system, it is necessary to enhance the adsorption kinetics and carefully evaluate the effect of contact time. Figure 7c shows variation in contact time with the percentage removal of As^III and As^V. The adsorption process proceeded at a rapid rate during the initial stage, and the adsorbent demonstrated high removal efficacy within the first 30 min. Approximately 70% of As^III and 75% of As^V were removed by CMBC from the aqueous solutions. The adsorbent shows a high rate of As^III and As^V adsorption due to the higher number of pores and functional groups on the adsorbent surface of the composite.⁶⁸ As time proceeds, the adsorption rate of As^III and As^V reduced by decreasing the active sites and available pores. Furthermore, the adsorbent reached equilibrium with 99 As^III and 99.7% As^V removal efficiency in 180 min. It is expected that extending the time may decrease the active adsorption sites and after reaching the equilibrium time very little adsorption may occur.⁶⁹

Kinetic studies are a significant aspect of the adsorption mechanism, as they offer insight into the rate and basic process of adsorption. In this study, both the PFO and PSO kinetic models were used to evaluate and find out the most suitable model for explaining As^III and As^V adsorption behavior. The values of theoretical q_e and k₁ were determined by using a linear fitting of the plot between ln(q_e−q_t) and t (time), as presented in Figures 10a and 10b. The R² values for the PFO kinetic model were 0.815 for As^III and 0.877 for As^V, respectively. Furthermore, the PSO kinetic model may also explain the rate of adsorption. However, the adsorption capacity and the values of rate constant k₂ and q_e were determined by employing linear curve fitting of the plot between t/q_t and t (Figures 10c and 10d). The correlation coefficient R² values for the PSO kinetic model was 0.990 for As^III and 0.995 for As^V, respectively. The PFO and PSO kinetic parameters of the model are presented in Table 5, indicating that the rate of adsorption was significantly by chemisorption mechanism.⁶⁹ Based on the higher R² values, the PSO kinetic model could better describe the As^III and As^V adsorption onto the adsorbent than PFO.

Figure 10.
Adsorption kinetic models for As^III and As^V adsorption onto CMBC. (a) PFO of kinetic for As^III, (b) PFO of kinetic for As^V, (c) PSO of kinetic for As^III, (d) PSO of kinetic for As^V.

Table 5.
Comparison of PFO and PSO kinetic models, reaction constants of calcined magnetic biochar with experimental data

Adsorbent	Arsenic species	PFO			PSO		Experimental
		qe / (mg g-1)	k1 / min-1	R2	k2 / (g mg-1 min-1)	R2	qe / (mg g-1)
CMBC	AsIII	9.188	0.031	0.815	0.010	0.990	9.906
CMBC	AsV	12.323	0.036	0.877	0.013	0.995	9.98

To enhance the accuracy of the kinetic analysis, nonlinear regression was also used based on the original equations for PFO and PSO. The nonlinear fitting results are given in Table 6, and the fitting curves are presented Figures 11a-11d. The q_e values of As^III and As^V were 9.507 and 9.701 mg g^-1, with R² values of 0.855 and 0.896, respectively, on the nonlinear PFO model. By contrast, the nonlinear PSO model was more consistent with the experimental data, with rate constant k₂ of 0.005 and 0.007 g mg^-1 min^-1 for As^III and As^V, respectively, and correlation coefficients R² of 0.968 and 0.988, respectively. The q_e values calculated using the nonlinear PSO model (10.710 mg g^-1 As^III and 10.696 mg g^-1 As^V) were quite close to the experimentally determined adsorption equilibrium capacities. Overall, the linear and nonlinear kinetic analyses indicate that the PSO model is the most appropriate for describing the adsorption process. This implies that chemisorption, i.e., valence forces or electron exchange between the arsenic species and functional groups on the CMBC surface, predominates as the rate-controlling step. Compared with several previously reported biochar-based and iron-modified adsorbents, CMBC demonstrated promising arsenic removal performance under near-neutral pH, with rapid initial adsorption and high removal efficiency within 180 min. The adsorption performance can be attributed to the combined effects of magnetic iron oxide phases, improved pore accessibility after calcination, and the presence of active surface sites capable of binding arsenic species. As shown in Table 7, CMBC exhibited comparatively higher adsorption capacity for As^V than several previously reported biochar-based and iron-modified adsorbents, while maintaining effective arsenic removal under near-neutral pH conditions.

Table 6.
Comparison of nonlinear PFO and PSO kinetic models, reaction constants of calcined magnetic biochar with experimental data

Adsorbent	Arsenic species	PFO			PSO		Experimental
		qe / (mg g-1)	k1 /min-1	R2	k2 / (g mg-1 min-1)	R2	qe / (mg g-1)
CMBC	AsIII	9.507	0.041	0.855	0.005	0.968	10.710
CMBC	AsV	9.701	0.045	0.896	0.007	0.988	10.696

Figure 11.
Nonlinear adsorption kinetic models for As^III and As^V adsorption onto CMBC. (a) PFO kinetics for As^III, (b) PFO kinetics for As^V, (c) PSO kinetics for As^III, (d) PSO kinetics for As^V.

Table 7.
Performance comparison of CMBC with previously reported adsorbents for As^III and As^V removal from aqueous solutions

Adsorbent	Arsenic species	Working pH	Contact time / min	qmax / (mg g-1)	Reference
CMBC	AsIII	7.0	180	53.21	present study
CMBC	AsV	7.0	180	210.97	present study
FMBC	AsV	5.0	90	28.49	46
EDB-CuO	AsV	2.0-3.0	240	26.10	70
FRKF	AsIII	neutral condition	60	45.50	71
FRKF	AsV	4.0	90	34.00	71
FC-EFBB	AsIII	not clearly specified	not clearly specified	31.40	72
FC-EFBB	AsV	approximately 5.0	not clearly specified	15.20	72
FC-RHB	AsIII	not clearly specified	not clearly specified	30.70	72
FC-RHB	AsV	approximately 5.0	not clearly specified	16.90	72
PTh@Fe	AsIII	optimized pH studied	optimized contact time studied	7.57	73
PTh@Fe	AsV	optimized pH studied	optimized contact time studied	8.62	73

Adsorption mechanism

The arsenic adsorption on CMBC depends on a cooperative set of interactions including electrostatic attraction, surface complexation, redox potential, and precipitation/co-precipitation. Figure 12 presents the possible adsorption mechanism using the prepared adsorbent composite. Real aquatic conditions usually involve the coexistence of contaminants, and cooperative pathways of adsorption/interaction are enhanced when contaminants interact with one another. Recent combined treatment systems have demonstrated that antibiotics and heavy metals can be removed simultaneously, prompting the design of adsorbents and mechanisms for use in complex contaminated water.⁷⁴ Thus, the cooperative interactions suggested in the present study can be used mechanistically to enhance the remediation of arsenic in aqueous solution. Primarily, the adsorbent composite contains plentiful oxygenated functional groups, such as C=O, −OH, and −COOH are produced during the iron impregnation and calcination. These functional groups act as active sites, building potent inner-sphere complexes with H₂AsO₃ and H₂AsO₄^–, a phenomenon consistently demonstrated in recent studies.⁷⁵ The iron oxide particles that are embedded in CMBC tend to possess a positive surface charge. The positive electrostatic forces are crucial because they attract negatively charged H₂AsO₄^– ions. As a result, the attraction enhances the initial adsorption of arsenic onto the surface of the adsorbent. Recent studies confirmed this phenomenon, illustrating the magnitude of these electrostatic forces and their contribution to the high effectiveness of adsorption.⁷⁶ Similarly, negatively charged sulfonate group attract the positive charged amine group in Fe-Mn-Zr tri-metal oxide/polyaniline nanocomposite and congo dye complex system.⁷⁷ Also, the prevalence of pore-filling on adsorbent composite as a prominent physisorption mechanism is well articulated.⁷⁸ The redox reactions are crucial in the process of arsenic removal. Oxidation of As^III to As^V is positively linked to redox cycling of iron, and in this case, the reactive Fe species and the newly formed iron (hydr)oxides promote arsenite oxidation and the formation of iron oxide through the complexation of arsenite with arsenate. Recent research has shown that iron-based media can oxidize As^III simultaneously and increase the removal efficiency by converting it to a more strongly adsorbing form, As^V.⁷⁹ In addition, Fe-carrying mineral processes (e.g., goethite/ferrihydrite systems) yield highly reactive intermediates that facilitate As^III oxidation and the redox mechanism of Fe.⁸⁰ The Fe³⁺ species found on the CMBC surface can convert As^III into As^V. This transformation is significant as As^V shows a greater tendency to bond with metal oxides, facilitating its immobilization in water.⁸¹ This process simultaneously reduces arsenic toxicity while improving retention. Finally, CMBC promotes the precipitation or co-precipitation of arsenic with iron compounds (such as FeAsO₄, Fe(OH)₃–As complexes), securing arsenic within insoluble mineral forms, a process confirmed in field research utilizing iron-loaded biochar in soil and water treatment.⁸²

Figure 12.
The possible adsorption mechanism using the prepared adsorbent composite.

Conclusions

In summary, a highly efficient CMBC was facilely synthesized using corncob biochar to remove As^III and As^V from aqueous solutions. Characterization results affirm the successful amendment of BC into CMBC where multiple properties demonstrate its diverse elemental, mineralogical and morphological attractions to achieve the reliable and sustainable As^III and As^V removal potentials. Experimental results revealed that the maximum removal of As^III and As^V was 99 and 99.7% with the initial concentration of 40 mg L^-1 and 0.4 g adsorbent dose, and an equilibrium time of 180 min. The adsorption of As^III and As^V was well defined by the Freundlich isotherm and PSO kinetic model. The maximum Langmuir adsorption capacities of CMBC for As^III and As^V were 53.21 and 210.97 mg g^-1, respectively. Calcination demonstrates in improving the performance of magnetic biochar, thereby advancing the design of environment-friendly and sustainable biomass-based adsorbents for water purification. The findings of this study showed that the prepared adsorbent composite is a promising alternative adsorbent option for the effective removal of As^III and As^V from aqueous environment.

Data Availability Statement

Data are available on request from the authors.

Acknowledgments

We gratefully acknowledge the CNPq (404874/2023-1, 304672/2023-8), PPGQTA and FURG. This work was partially support by the HEC of Pakistan under the National Research Program for Universities (7019/KPK/NRPU/R&D/HEC/2017).

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Edited by

• Editor handled this article:
  Adriana Nunes Correia (Associate)

Publication Dates

• Publication in this collection
  03 Aug 2026
• Date of issue
  2026

History

• Received
  19 Mar 2026
• Accepted
  22 June 2026