Biosorption and Isotherm Modeling of Heavy Metals Using Phragmites australis

Abstract

This study investigates the biosorption of heavy metal ions (Pb, Fe, Cu, Cd, Zn, and Mn) from wastewater using the powdered biomass of Phragmites australis (common reed) under varying conditions, including temperature, pH, retention time, plant powder size, and biosorbent weight. The results showed that plant powder size significantly influenced the biosorption efficiency, with the 0.5 mm diameter powder yielding the highest removal rates for the heavy metal ions. The optimal temperature for biosorption was found to be between 30 and 50 °C, achieving up to 99.94% removal for Pb. The ideal pH for the biosorption of all metals was seven, and the best retention time for ion removal was 30 min, with a mean biosorption rate of 99.82% for Fe. A biosorbent weight of 10 g/L was also identified as the most effective for metal ion removal. Furthermore, two forms of P. australis, dry pieces and powdered biomass, were tested, with the powdered biomass exhibiting a superior biosorption performance. FTIR analysis revealed the involvement of carboxyl and hydroxyl functional groups in the biosorption process, while SEM imaging confirmed the surface interactions between metal ions and the plant material. The adsorption of heavy metals onto P. australis was effectively described by both Langmuir and Freundlich isotherm models, indicating a mix of monolayer coverage and heterogeneous interactions. The Langmuir model showed the highest adsorption capacities for Mn²⁺ (6.29 mg/g) and Cd²⁺ (5.10 mg/g), with strong affinities for Pb²⁺ (K_L = 0.0122 L/mg), Fe²⁺ (K_L = 0.0137 L/mg), and Cu²⁺ (K_L = 0.0130 L/mg). Similarly, the Freundlich model indicated favorable adsorption (n > 1) for all ions. Cu²⁺ and Fe²⁺ had the highest adsorption intensities (n = 2.06), with the strongest capacities being observed for Fe²⁺ (K_f = 0.231) and Cu²⁺ (K_f = 0.222). These findings confirm the high potential of P. australis as a sustainable and eco-friendly biosorbent.

1. Introduction

Heavy metal contamination in aquatic environments, resulting from both anthropogenic activities and natural processes, poses a significant threat to biodiversity and ecosystem health. Prominent heavy metals found in water include cadmium, chromium, lead, mercury, and zinc, which can enter water bodies through industrial discharges, agricultural runoff, and urban waste. These contaminants are particularly concerning due to their persistent nature and ability to bioaccumulate in aquatic organisms, leading to detrimental effects on individual species and the broader ecological community [1]. For instance, these metals bioaccumulate in aquatic organisms, causing reproductive failure, growth inhibition, and increased mortality rates, which ultimately destabilize food chains and reduce species diversity [2]. Furthermore, the contamination of aquatic systems poses significant risks to human health, as heavy metals enter the food chain and drinking water supplies. Chronic exposure to lead is associated with neurological disorders and kidney damage, while cadmium can cause respiratory and gastrointestinal complications [3]. Copper, though essential in trace amounts, becomes toxic at higher concentrations, leading to liver damage and anemia. The severity of these health effects depends on the type of metal exposure, the level, and individual susceptibility. To protect public health, the World Health Organization (WHO) has established maximum guideline values for drinking water: 0.010 mg/L for Pb, 0.003 mg/L for Cd, 2.0 mg/L for Cu, 0.3 mg/L for Fe, 3.0 mg/L for Zn, and 0.1 mg/L for Mn [4]. Exceeding these limits can result in chronic toxicity and ecosystem disruption, emphasizing the urgent need for effective removal strategies [4]. Therefore, addressing heavy metal pollution is essential to safeguard both ecological integrity and public health.

Various industries, such as the petrochemical, paint, tanning, textile manufacturing, healthcare, and fertilizer production industries, are significant contributors to heavy metal pollution [5]. In the oil extraction sector, wastewater is particularly concerning, as it contains elevated concentrations of heavy metals such as lead, cadmium, chromium, and nickel, alongside organic and inorganic pollutants [6]. These contaminants are present in concentrations ranging from micrograms per liter (µg/L) to milligrams per liter (mg/L), depending on the source and processing methods, posing substantial risks to both environmental and human health [6,7]. Consequently, the oil industry, a major contributor to soil, water, and air pollution, necessitates effective wastewater treatment solutions. Conventional methods such as physical filtration, adsorption, chemical precipitation, oxidation, and coagulation have been widely employed [7]. However, biological techniques, including biosorption and bio-removal, are gaining attention due to their environmental safety, cost-effectiveness, and accessibility for treating wastewater from municipal, agricultural, industrial, and petroleum sources [8].

In recent years, biosorption and adsorption methods have emerged as promising solutions for removing heavy metal ions from industrial wastewater [9,10]. Plant waste materials, such as fruit peels and ground plant residues, are particularly advantageous due to their abundance, low cost, and high adsorption capacities [9,10]. For instance, dried lemon peels effectively adsorb lead and cadmium due to their high cellulose and pectin content, while orange peels remove copper and zinc through ion exchange mechanisms [11]. Banana peels, which are rich in carboxyl and hydroxyl functional groups, exhibit high adsorption capacities for chromium and nickel [12], and pomegranate peels, with their porous structure and active binding sites, are effective in removing arsenic and mercury [13]. These plant wastes, which are often unsuitable for animal feed and are typically discarded through burning [14], represent a sustainable resource for wastewater treatment. Recent studies have emphasized the potential of Phragmites australis, commonly known as common reed, in the biosorption of heavy metals from wastewater. P. australis biomass is widely available and highly feasible for use in biosorption applications due to its rapid growth rate, high biomass yield, and strong adaptability to diverse environmental conditions. Its widespread distribution across freshwater marshes, riverbanks, and irrigation canals makes it a renewable and abundantly accessible resource that requires minimal cultivation or processing. The plant’s cellular structure and biochemical properties help it to effectively absorb contaminants such as lead, cadmium, and chromium, significantly reducing their concentrations in polluted water bodies. Its high phenotypic plasticity allows it to thrive in environments with fluctuating nutrient levels, a critical feature for maintaining its biosorption capacity across different conditions, making it a promising candidate for phytoremediation applications [15,16].

This study aims to optimize the use of Phragmites australis for the biosorption of heavy-metal-contaminated wastewater. Key parameters such as temperature, pH, contact time, and biomass characteristics will be investigated to enhance biosorption efficiency and elucidate the underlying mechanisms. The ultimate goal is to develop a scalable and sustainable phytoremediation strategy for the treatment of industrial wastewater.

2. Materials and Methods

2.1. Preparation of Plant Biosorbents

Phragmites australis (common reed) was collected from agricultural areas along the banks of the Euphrates River (latitude 33.4292807″ N; longitude 43.2750694″ E). The collected biomass was meticulously cleaned, first with tap water to remove surface impurities, followed by rinsing with double-distilled water (DDW) to ensure purity. The cleaned biomass was then prepared for two distinct experimental setups. In the first one, the biomass was air-dried and cut into dried pieces of varying sizes. In the second step, the biomass was dried, ground into powder, and sieved using stainless steel sieves to achieve particle sizes ranging from 0.106 mm to 2 mm. All prepared samples were stored in a dry environment to maintain their integrity for subsequent biosorption experiments. All chemicals used were of analytical grade (≥99% purity) and obtained from Merck, Darmstadt, Germany, and Fluka, Buchs, Switzerland.

2.2. Characterization of P. australis

The potentiometric titration technique was employed to determine the point of zero charge (pHpzc) of P. australis. To achieve this, a set of 0.1 M NaCl solutions were prepared in 100 mL flasks. The initial pH (pH_i) of each solution was adjusted between 1 and 11 using 0.1 M NaOH or 0.1 M HCl using a pH-meter model Inolab pH 7110 (WTW, Weilheim, Germany). The final volume in each flask was precisely set to 25 mL. Subsequently, 0.5 g of P. australis was introduced into each solution, followed by agitation at 150 rpm for 48 h. After this period, the final pH (pH_f) was recorded. The difference between the initial and final pH values (ΔpH = pH_i − pH_f) was plotted against pH_i, and the pHpzc was identified as the point where ΔpH = 0 on the x-axis. Scanning electron microscopy (SEM; Inspect S50, FEI Company, Eindhoven, The Netherlands) was used to investigate the surface morphology of both raw and metal-treated biomass. A mixed solution containing heavy metals (zinc, iron, manganese, lead, cadmium, and copper) at 100 ppm each was prepared and combined with 1 g of P. australis plant powder. The mixture was allowed to settle for two hours and then analyzed. Additionally, the functional groups responsible for metal uptake in untreated and treated biosorbents were examined using Fourier transform infrared (FTIR) spectroscopy (PerkinElmer, Rodgau, Germany). For this analysis, samples were dried, mixed with potassium bromide KBr (Merck, Darmstadt, Germany) at a 1:10 ratio, finely ground, and pressed into pellets. The KBr background was subtracted, and all spectra were plotted on the same absorbance scale.

2.3. Batch Biosorption Experiments

The biosorption process was studied using various analytical methods with a 100 mL working volume of metal solutions, each at a 100 mg/L concentration of zinc (Zn²⁺), cadmium (Cd²⁺), iron (Fe²⁺), lead (Pb²⁺), copper (Cu²⁺), and manganese (Mn²⁺) obtained from Fluka Analytical (Buchs, Switzerland). These solutions were placed in 250 mL volumetric flasks. To optimize the experimental conditions, the first step was to assess the impact of the biosorbent form of P. australis by comparing powdered and whole-piece dried biomass. Then, 1 g of biosorbent was added to each flask (100 mL), and the mixtures were incubated for 60 min at 30 °C and pH 7, with a constant agitation speed of 150 rpm. The solution pH was carefully adjusted and maintained using 0.1 M NaOH or 0.1 M HCl. To further refine the biosorption process, the effects of key operational parameters were examined, including pH (3–8), temperature (30 °C for control conditions and 20–60 °C for experimental variations), contact time (5–120 min), controlled biomass particle sizes (0.106, 0.5, 1, 1.5, and 2 mm) to systematically evaluate the impact of particle size on adsorption efficiency, and biosorbent weight (1–20 g/L). The initial adsorbate concentration was fixed at 10 g/L. The most favorable pH condition was then applied for further study of the biosorption capacity. Control solutions of Zn, Cd, Fe, Pb, Cu, and Mn (without P. australis) were prepared under identical conditions to serve as reference samples. After biosorption, all samples underwent centrifugation at 5500 rpm for 30 min at room temperature, followed by filtration through a 0.45 µm filter paper, and metal concentrations were determined using flame atomic absorption spectroscopy (FASS GBC Scientific Equipment, Braeside, Australia). This procedure was consistently applied in subsequent experiments to identify the most effective biosorbent form for further applications. The biosorption efficiency of metal ions was calculated using Equation (1):

$$Biosorption efficiency \left(\%\right)={\displaystyle \frac{\left({\mathit{C}}_{\mathit{i}}-{\mathit{C}}_{\mathit{f}}\right)}{{\mathit{C}}_{\mathit{i}}}}\times \mathbf{100}$$

where C_i and C_f are the initial and final (or equilibrium) metal concentrations, respectively. To ensure the accuracy, reliability, and reproducibility of the results, all measurements were conducted in duplicate, and the average values are reported.

2.4. Adsorption Isotherm Models

To evaluate the adsorption behavior of heavy metal ions onto the biosorbent, the experimental data were fitted using the Langmuir and Freundlich isotherm models [17]. These models provide insights into the adsorption capacity, surface characteristics, and adsorption mechanisms. The Langmuir model was employed to assess the adsorption capacity and evaluate the affinity of the adsorbent for metal ions. The nonlinear form of the Langmuir equation is given by

$${\mathit{q}}_{\mathit{e}}={\displaystyle \frac{{\mathit{q}}_{\mathit{m}\mathit{a}\mathit{x}}·{\mathit{K}}_{\mathit{L}}·{\mathit{C}}_{\mathit{e}}}{\mathbf{1}+{\mathit{K}}_{\mathit{L}}·{\mathit{C}}_{\mathit{e}}}}$$

(1)

where K_L and q_max represent the Langmuir constants for adsorption energy and maximum adsorption capacity, respectively. C_e is the equilibrium concentration of the metal ions in the solution (mg/L), and q_e is the amount of metal ions adsorbed at equilibrium (in mg/g). The Langmuir parameters q_max and K_L were determined using the Origin software to assess adsorption quantitatively [17].

The Freundlich isotherm model, on the other hand, describes adsorption on a heterogeneous surface with multilayer adsorption, where adsorption sites have varying affinities for the adsorbate. The nonlinear form of the Freundlich equation is expressed as

$${\mathit{q}}_{\mathit{e}}={\mathit{K}}_{\mathit{f}}· \mathit{C}{\mathit{e}}^{\mathbf{1}/\mathit{n}}$$

(2)

where K_f and n are Freundlich constants, with K_f representing the adsorption capacity of the adsorbent and n indicating the adsorption intensity. These constants were determined by fitting the experimental data to the nonlinear form of the Freundlich isotherm equation using nonlinear regression in the Origin software. The data were plotted as q_e versus C_e, and the best-fit values for K_f and n were obtained. The strength of the fit was evaluated based on the R² value.

The equilibrium parameter, R_L, a dimensionless constant separation factor, can also be used to represent the Langmuir adsorption isotherm, as shown in Equation (3):

$${\mathit{R}}_{\mathit{L}}={\displaystyle \frac{\mathbf{1}}{\mathbf{1}+{\mathit{K}}_{\mathit{L}}{\mathit{C}}_{\mathit{i}}}}$$

(3)

where C_i is the starting concentration in mg/L and K_L is the Langmuir constant. The values of R_L were calculated for a concentration of 100 mg/L for all of the metal ions.

2.5. Statistical Analysis

All experimental data were analyzed using one-way ANOVA. Additionally, all experiments were conducted in triplicate to ensure reliability and reproducibility, with the results presented as means ± standard error (S.E.). Statistical analyses were performed using SPSS software (2023), with significance set at p < 0.05. For the isotherm models (Langmuir and Freundlich), all required calculations, regression analyses, and figures were generated using Origin 8 software.

3. Results and Discussion

This study explored the influence of key variables—pH, temperature, retention time, controlled powder sizes, and weight ratio—on the biosorption capacity of P. australis for the removal of heavy metals at a fixed initial concentration of 100 mg/L. Understanding the influence of these variables on the biosorption capacity of common reed is crucial for optimizing the maximum removal of heavy metals.

3.1. Determination of the Point of Zero Charge (pHpzc)

The point of zero charge (pHpzc) is a key parameter in biosorption studies, providing insights into the surface charge characteristics of a material and its adsorption behavior. In this study, the pHpzc of P. australis biomass was determined to be 6.2 (Figure 1), indicating a negatively charged surface at pH levels above 6.2 and a positive charge below this point. This finding is crucial, as it identifies the optimal pH range for heavy metal adsorption, which is dependent on surface charge. Compared with other plant-based biosorbents, P. australis exhibits a pHpzc similar to that of Moringa oleifera bark, which was reported as 6.0 [18], while Yohimbe bark shows a slightly higher pHpzc of 7.1 [19]. These findings underscore the importance of pHpzc as a key parameter in evaluating and optimizing biosorbent performance.

3.2. Effect of the Biomass’s Physical Form

This study explores the influence of the physical form of P. australis biomass—powdered versus non-powdered (dry pieces)—on its efficacy in heavy metal biosorption. The experiment was conducted under controlled conditions, including a temperature of 30 °C, a pH of 7, a retention time of 60 min, and a biosorbent weight of 10 g/L. A pH of 7 was chosen to ensure a net negative charge on the surface, thus enhancing its affinity for cationic heavy metal ions through electrostatic interactions. The initial findings highlight a marked increase in biosorption efficiency for powdered biomass compared with dry pieces (Figure 2). Statistical analysis using ANOVA revealed highly significant differences (p < 0.0001) in biosorption capacity between the two biomass forms and across the examined heavy metals. Additionally, the least significant difference (LSD) test at p > 0.05 further validated these distinctions, with an LSD value of 2.678, underscoring the superior performance of powdered biomass in heavy metal removal. It was found that plant powder biomass had much better mean values than those recorded for dry biomass pieces, as presented in Figure 2. The biosorption efficiency of the powdered form followed the following order: Fe > Pb > Cu > Mn > Cd > Zn, indicating distinct variations in binding affinity for different heavy metals. These findings suggest that the increased surface area and enhanced accessibility of active sites in the powdered form, combined with the favorable electrostatic interactions at the pH of 7, contribute to its improved biosorption performance.

3.3. Optimization of the Biosorption Parameters

3.3.1. Effect of pH

The biosorption efficiency of P. australis biomass for heavy metals (Cu, Cd, Mn, Fe, Zn, and Pb) was strongly influenced by pH (Figure 3), with the optimal performance being observed at pH 7–8, just above the point of zero charge (pHpzc = 6.2). Statistical analysis (p < 0.0001) confirmed the significant differences in metal uptake based on pH. At pH values below the pHpzc (3–6), the biomass surface, which carried a positive charge, repelled metal cations, leading to reduced biosorption efficiency. As the pH increased beyond the pHpzc (6–8), the biomass surface became negatively charged, enhancing electrostatic attraction and promoting greater metal ion uptake. Among the metals tested, Fe and Pb showed the highest biosorption efficiencies (over 95% at pH 7), likely due to their strong affinity for functional groups such as carboxyl and hydroxyl on the biomass surface. The observed decrease in biosorption efficiency at pH 8 for most metals may be attributed to minor precipitation effects. In contrast, Cd and Zn showed comparatively lower efficiencies, reaching about 42% and 51%, respectively, at pH 7, likely due to intrinsic differences in their binding affinities for the biomass. Interestingly, at pH 8, a slight decrease in biosorption efficiency was observed for most metals, possibly due to minor precipitation effects. These findings underscore the critical role of pH in modulating the surface charge of P. australis biomass and its subsequent impact on biosorption efficiency, with pH 7 being identified as the optimal condition for maximizing the removal of heavy metals. This is consistent with previous studies, such as that of Lesage et al. [20], who reported that P. australis achieves maximum biosorption of heavy metals at a neutral to slightly alkaline pH, with minimal contribution from precipitation. Similarly, Bonanno and Lo Giudice [21] demonstrated that P. australis effectively accumulates heavy metals from water and sediments at pH 7–8, attributing the removal to biosorption rather than precipitation. These findings align with our results, confirming that the observed metal removal at pH 7–8 is primarily due to biosorption by P. australis biomass. Cellulose contains a high percentage of hydroxyl (-OH) functional groups, which can participate in metal ion binding. As the pH increases, these functional groups can deprotonate, enhancing their ability to interact with metal cations through electrostatic attraction and complexation. The overall ability of a biosorbent to bind cations can be quantified by its cation exchange capacity (CEC) at a given pH; however, biosorption is a complex process that also involves mechanisms such as complexation, precipitation, and physical adsorption. P. australis has a high cellulose content, but lignin and hemicellulose also contribute to its biosorption capacity by providing additional functional groups, such as carboxyl and phenolic groups. Polysaccharides such as cellulose, along with structurally related biopolymers such as chitin and chitosan, are widely used in water treatment due to their ability to adsorb a variety of contaminants, including heavy metals, dyes, phenols, pesticides, and detergents. The pH of the solution strongly influences the biosorption process, as it affects the charge of functional groups on the biomass surface. Torres [22] reported that the pH plays a key role in determining metal uptake, as a more negatively charged biosorbent surface generally enhances the adsorption of positively charged metal cations. For many heavy metals, biosorption efficiency increases at a neutral to slightly alkaline pH (typically between 6.5 and 8.0) due to reduced competition with hydrogen ions (H⁺) and increased electrostatic attraction between the metal cations and the biosorbent. However, the optimal pH range varies depending on the specific metal and biosorbent, as some metals exhibit different binding affinities and solubility characteristics at different pH levels. An optimal pH of 7 was selected for further biosorption experiments.

3.3.2. Effects of Temperature and Biosorption Time

To investigate the influence of temperature on the biosorption efficiency of heavy metals, the biosorption performance of Pb, Zn, Fe, Mn, Cd, and Cu was evaluated across a range of temperatures (20–60 °C). The results revealed a clear temperature-dependent relationship, with significant increases in efficiency being observed up to an optimal temperature range of 30–50 °C, followed by a decline at 60 °C, as illustrated in Figure 4a. At a low temperature of 20 °C, the biosorption efficiency was notably low for all tested metals. Among the metals, Pb demonstrated the highest biosorption efficiency, peaking between 30 and 50 °C before slightly decreasing at 60 °C. Zn, Cu, and Cd showed optimal biosorption at 30–40 °C, with a decline beyond this range, while Fe and Mn reached their maximum efficiency at 50 °C. The observed trends suggest that temperature significantly influences biosorption thermodynamics, with positive enthalpy changes (ΔH°) indicating an energy-driven process. The initial increase in efficiency is likely due to enhanced metal ion kinetics and improved biomass–metal interactions, while the decline at higher temperatures may result from biomass degradation, binding site saturation, or changes in metal oxidation states. These findings are consistent with previous studies, underscoring the importance of temperature optimization in biosorption processes for effective heavy metal removal [22]. A key advantage of our results is the ability to achieve high biosorption efficiency at 30 °C, making it a cost-effective and practical option compared with other plant biomasses such as Eichhornia crassipes and Saccharum officinarum, which require temperatures above 50 °C for optimal adsorption efficiency [23]. This reduces energy costs and operational limitations, enhancing the feasibility of large-scale applications. To further optimize the biosorption process, the effect of reaction time on metal removal efficiency was investigated (Figure 4b). The study revealed a progressive increase in metal uptake over time, with the highest removal rates being observed between 30 and 120 min. Initially, at 5 min, the removal efficiencies were relatively low across all metals (Cu = 52.85%, Cd = 31.03%, and Pb = 42.69%). However, as the reaction time increased, significant improvements in metal removal were observed, reaching optimal levels by 30 min. Beyond this point, removal efficiencies plateaued, with only minor variations at 60 and 120 min, indicating that equilibrium was achieved within 30–60 min. This study demonstrates that a retention time of 30 min and a temperature of 30 °C are sufficient to achieve optimal removal for most metals, minimizing energy consumption and processing costs while ensuring effective heavy metal removal.

3.3.3. Effects of Powder Size and Weight Ratio on Biosorption

Understanding the effects of powder size and weight ratio on biosorption is crucial for optimizing heavy metal removal efficiency, as these parameters directly influence the availability of binding sites and the overall performance of biosorbents. As shown in Figure 5, this study demonstrates that the biosorption efficiency of heavy metals (Pb, Zn, Fe, Mn, Cd, and Cu) using P. australis biomass is highly dependent on the biosorbent weight ratio, with an optimal concentration of 10 g/L for most metals (Figure 5a). Beyond this concentration, efficiency plateaus or decreases due to the saturation of active binding sites. This saturation effect was also observed in a study using Citrus sinensis peels [9]. Notably, Pb (97.31%) and Fe (98.59%) exhibited high biosorption efficiencies, consistent with their strong affinity for functional groups such as carboxyl, hydroxyl, and amine groups present in the biomass [24]. In contrast, Zn (33.06%) and Cd (43.17%) showed lower efficiencies due to the weaker binding affinity, while Mn (60.6%) displayed intermediate behavior. These results underscore the potential of plant biomass as a low-cost and sustainable biosorbent for heavy metal removal while highlighting the importance of optimizing biosorbent weight to avoid inefficiencies caused by saturation. Regarding the effect of P. australis powder size on biosorption, the study reveals that biosorption efficiency varies significantly with particle size. Smaller powder sizes (e.g., 0.106 mm) generally yield lower efficiencies, while optimal performance is achieved at intermediate sizes (0.5 to 1 mm) (Figure 5b). However, efficiency declines at larger sizes (e.g., 2 mm), likely due to the reduced surface area and limited accessibility of binding sites. These findings align with previous studies on plant-based biosorbents. For instance, Sharma and Devi [25] demonstrated that optimizing the particle size in snail shell dust enhances heavy metal ion removal, emphasizing the importance of surface area and binding site availability. Similarly, research on Opuntia fuliginosa and Agave angustifolia showed that a particle size of 572 µm achieved a 93% removal efficiency for Pb²⁺ [24,25,26]. Overall, the study highlights that increasing biosorbent weight enhances biosorption efficiency by providing more binding sites for heavy metal ions, thereby increasing biosorption capacity. However, careful optimization of both weight and particle size is essential to maximize efficiency and avoid saturation or surface area limitations.

ANOVA revealed significant differences (p < 0.0001) in biosorption between heavy metals and powder sizes. Powder size significantly affected the biosorption of all metals, as confirmed by the LSD test (value = 0.9004 at p < 0.05). Similarly, biosorbent weight also had a significant impact on metal biosorption (p < 0.0001), with the LSD test supporting these differences (value = 2.102 at p < 0.05).

3.4. Fourier Transform Infrared Spectroscopy Analysis

Fourier transform infrared (FTIR) spectroscopy analysis of P. australis biosorbents before and after exposure to a multi-ion solution containing various heavy metals was used to highlight key functional groups involved in biosorption (Figure 6). A previous study on the adsorption of heavy metals by P. australis demonstrated that the biomass exhibits a high capacity for metal uptake, with the adsorption process being strongly influenced by the initial metal concentration, pH levels, and specific plant tissues used [27]. Peaks at 3365–3423 cm⁻¹, attributed to -OH and -NH stretching, confirm the role of hydroxyl and amine groups in metal binding. Carboxyl (-COOH) groups also played a crucial role, as evidenced by peaks at 1660–1734 cm⁻¹ (-COO⁻) and 1640–1653 cm⁻¹ (-COOH). These shifts indicate ion exchange, where hydrogen ions are replaced by metal cations, forming stable complexes. The Pb(II) exhibited stronger interactions with carboxyl groups than Cd(II), aligning with previous studies on fungal biomass. Additionally, carbonyl (-C=O) and ether (-C-O) groups contributed to biosorption, with -C=O stretching at 1226–1400 cm⁻¹ and -C-O stretching at 1049–1200 cm⁻¹. Metal adsorption led to peak shifts, confirming surface modifications. Unlike A. rubescens, P. australis showed peaks at 850–894 cm⁻¹ (-C-N bonding in amines), suggesting protein-based interactions in biosorption. The decrease in peak intensities in metal-loaded samples compared with the control suggests reduced bond stretching due to hydrogen ion exchange with heavy metals. The results of this study are confirmed by Li et al. [28] in their comparative study on the potentiality of phosphorus-accumulating organism biomasses in the biosorption of Cd(II), Pb(II), Cu(II), and Zn(II) from aqueous solutions, which demonstrated that the -COO and -C=O groups are responsible for the uptake of Zn ions. Furthermore, the results of this study also agreed with those of Akar et al. [29] in their study on the removal of Pb from an aqueous solution using Cucumis melo, which demonstrated that hydroxyl and carboxyl groups were responsible for the uptake of lead ions. Overall, FTIR data confirm that biosorption in P. australis occurs via ion exchange, complexation, and electrostatic interactions involving hydroxyl, carboxyl, amine, carbonyl, and ether groups. Peak shifts indicate chemical modifications upon metal binding, with variations between species reflecting differences in biochemical composition and metal affinity. These findings reinforce the role of key functional groups in determining biosorption efficiency.

3.5. SEM Biomass Investigation

The morphology of the raw and metal-treated biomass was investigated using SEM (Inspect S50, FEI company, Eindhoven, The Netherlands). The SEM analysis of P. australis before and after exposure to a heavy metal mixture, as shown in Figure 7, reveals significant morphological transformations, highlighting the impact of metal adsorption on the biosorbent’s surface structure. In the untreated sample (Figure 7a), the surface appears relatively smooth, with well-defined fibrous structures characteristic of plant cell walls. This observation aligns with previous studies [30], which reported similar structural integrity in unmodified plant biomass. However, after treatment with heavy metals, the surface of P. australis exhibits increased roughness and porosity, accompanied by visible cracks and flaking (Figure 7b). These alterations suggest significant structural modifications, likely due to metal ion interactions through mechanisms such as ion exchange and complexation. Furthermore, the presence of small deposits on the biosorbent surface indicates successful metal adsorption, consistent with the findings of Kaleem et al. [31]. Similar morphological changes have been reported in other plant-based biosorbents, reinforcing the efficiency of P. australis in heavy metal removal [32]. These results support the potential application of this biomass as an effective biosorbent for heavy metal remediation, providing insights into its suitability for wastewater treatment and environmental detoxification.

3.6. Isotherm Studies

The Langmuir and Freundlich isotherm models synergistically characterize heavy metal biosorption by plant biomass. The Langmuir model describes monolayer chemisorption (q_max) and binding affinity (K_L) for specific functional groups, such as carboxyl, phenolic, acetamido, amido, amino, sulfhydryl, hydroxyl, and ester groups. This makes the model particularly suitable for systems where strong and specific interactions, such as ion exchange or complexation, dominate the adsorption process. In contrast, the Freundlich model captures the inherent heterogeneity of lignocellulosic biomass through its multilayer adsorption parameters (K_f, 1/n), reflecting variable binding energies and surface complexity. This dual-model approach effectively describes both the binding of specific metals to oxygen-containing groups and the broader, non-ideal adsorption behavior typical of biosorbents, as supported by previous studies [17,18]. Together, these models can be used to obtain a robust mechanistic understanding of the biosorption process.

3.6.1. Langmuir Isotherm

Table 1. Langmuir and Freundlich isotherm parameters for heavy metal adsorption onto P. australis.

	Langmuir						Freundlich
Metal Ion	qmax (mg/g)		KL (L/mg)		RL *	R2	Kf (mg/g)		n		R2
	Value	S.E.	Value	S.E.	Value	Value	Value	S.E.	Value	S.E.	Value
Pb2+	4.363	0.965	0.0122	0.0070	0.450	0.904	0.202	0.093	1.981	0.347	0.944
Zn2+	4.573	0.549	0.0086	0.0025	0.537	0.978	0.161	0.038	1.878	0.160	0.986
Fe2+	4.370	0.764	0.0137	0.0070	0.420	0.930	0.231	0.087	2.055	0.306	0.958
Mn2+	6.285	0.94	0.0044	0.0012	0.694	0.987	0.099	0.007	1.588	0.035	0.999
Cd2+	5.101	0.882	0.0040	0.0013	0.710	0.981	0.079	0.024	1.607	0.149	0.984
Cu2+	4.228	0.832	0.0130	0.0074	0.434	0.916	0.222	0.088	2.064	0.323	0.955

* The values of the separation factor R_L were determined at an initial concentration (C_i) of 100 mg/L.

presents the correlation coefficients (R²) for the adsorption of various metal ions, demonstrating values greater than 0.90 for all cases. This indicates a good fit of the experimental data to the Langmuir adsorption isotherm model (Figure 8a). Similarly high (R²) values have been reported in recent studies, such as those by Liu et al. [33], confirming the robustness of the Langmuir model in modeling metal ion adsorption onto various waste biosorbents.

The maximum adsorption capacities, q_max, and Langmuir constants, K_L, were calculated using the Origin software, as shown in Table 1. The adsorption capacities ranged from 4.228 ± 0.832 mg g⁻¹ for Cu²⁺ to 6.285 ± 0.94 mg g⁻¹ for Mn²⁺, suggesting varying affinities for different metal ions. These results are consistent with those of previous studies [31,32,33,34], which also observed such variations. The Langmuir separation factor (R_L) was determined at an initial metal ion concentration of 100 mg/L to evaluate the favorability of adsorption. All R_L values were between 0 and 1, indicating favorable adsorption behavior, which was consistent with the interpretation criteria established by Kumar et al. [35]. The R_L values thus support the applicability of the Langmuir isotherm model, which assumes monolayer adsorption on a homogeneous surface. High correlation coefficients (R² > 0.95) further validate the model’s fit to the experimental data. These results align with those of previous studies [23,24,25,26,27,28,29,30,31] that also demonstrated strong conformity to the Langmuir model for various metal ions. Among the tested ions, Fe²⁺ (0.4205), Cu²⁺ (0.4344), and Pb²⁺ (0.4502) exhibited the lowest R_L values, suggesting a stronger affinity for the adsorbent surface. Conversely, Mn²⁺ (0.6944) and Cd²⁺ (0.7102) presented higher R_L values, indicating that there were fewer adsorption interactions under the same conditions.

3.6.2. Freundlich Isotherm

The relationship between qe and Ce presented in Figure 8b was shown to be significantly correlated with R² more than 0.90. The evaluated constants are shown in Table 1, which reveals the fact that the n values for all metal ions’ adsorption were more than one, indicating that the adsorption process is physical and has a high degree of heterogeneity. A strong affinity (high n value) was not equivalent to a large adsorption capacity (high K_f value). K_f was determined by particle parameters such as size distribution, specific surface area, and surface functional groups. The adsorption isotherms for all metal ions were well fitted to the Freundlich model, with correlation coefficients (R²) greater than 0.9 and n values exceeding 1, as shown in Table 1. The data compiled in Table 1 indicate that the adsorbent was fitted to the Langmuir and Freundlich isotherms. K_f represents the adsorption capacity, with higher values indicating stronger affinity for metal ions. P. australis showed the highest adsorption for Fe²⁺ (0.231), Cu²⁺ (0.222), and Pb²⁺ (0.202), suggesting strong interactions with its functional groups. In contrast, Zn²⁺ (0.161), Mn²⁺ (0.099), and Cd²⁺ (0.080) had lower adsorption, likely due to differences in ionic properties. The adsorption intensity (n > 1) confirmed the favorable adsorption, with Cu²⁺ (2.06), Fe²⁺ (2.06), and Pb²⁺ (1.98) exhibiting the strongest affinity. The lower n values for Mn²⁺ (1.59) and Cd²⁺ (1.61) indicate weaker interactions. These results suggest that P. australis is highly effective for Fe²⁺, Cu²⁺, and Pb²⁺ removal, making it a promising biosorbent for wastewater treatment. However, optimizing surface modifications may enhance its efficiency for lower-affinity metals such as Cd²⁺ and Mn²⁺. The results of this study align with previous research demonstrating the effectiveness of plant-derived materials for heavy metal removal, where adsorption capacity is influenced by factors such as charge, size, and affinity for functional groups on the biosorbent surface. For example, it was reported that P. australis had high adsorption capacities for Pb²⁺ and Cu²⁺, similarly to our findings, where these metals exhibited the highest K_f values. This suggests that P. australis is particularly effective at removing metals with high charge densities. It was reported previously that there was a higher biosorption capacity for Pb²⁺ and Cu²⁺ compared with Zn²⁺, which was consistent with our results [27]. In contrast, the lower adsorption capacities for Zn²⁺, Mn²⁺, and Cd²⁺ in our study align with Torres [22], who reported lower biosorption efficiencies for these metals, likely due to their smaller ionic radii and weaker complexation. The higher n values for Cu²⁺, Fe²⁺, and Pb²⁺ in our study suggest favorable adsorption. Overall, our results reinforce the potential of P. australis as an effective biosorbent, particularly for Pb²⁺, Cu²⁺, and Fe²⁺. Optimizing the biomass, such as through chemical modification, may enhance efficiency for metals such as Zn²⁺, Mn²⁺, and Cd²⁺.

3.7. Challenges and Perspectives

Despite promising results under controlled laboratory conditions, the biosorption efficiency of agricultural-waste-based biosorbents can vary significantly in real-world applications, where factors such as competing ions, mixed pollutants, and large-scale operational challenges may influence performance [35]. Actual wastewater systems present a complex mixture of organic and inorganic pollutants, variable pH, temperature, and competing ions that can affect the availability and accessibility of binding sites on P. australis. We acknowledge that controlled experimental conditions do not fully replicate environmental matrices, and future studies should evaluate biosorbent performance in synthetic and real wastewater samples to assess practical robustness. Furthermore, exploring the regeneration and reuse potential of P. australis biomass is crucial for enhancing the cost-effectiveness and sustainability of this approach. The ability to regenerate P. australis using desorbing agents such as HCl or EDTA could allow multiple adsorption–desorption cycles, minimizing biomass waste and facilitating the recovery of valuable metals. Several agricultural waste biosorbents, including orange peels, sugarcane bagasses, and banana peels, have demonstrated successful regeneration over multiple cycles with minimal loss of capacity, underscoring the feasibility of this approach [36,37,38]. Future work should focus on optimizing desorption conditions, assessing regeneration costs, and evaluating long-term biosorbent stability. Scaling up the biosorption process for real-world wastewater treatment is another critical challenge. Although P. australis shows promising adsorption capacity, factors such as biomass harvesting, preparation, and regeneration logistics under operational conditions require thorough evaluation. Transitioning from laboratory-scale studies to pilot-scale investigations is crucial to evaluate the performance of P. australis under industrial conditions, particularly concerning cost and energy efficiency. Economically, P. australis presents a distinct advantage due to its abundance, minimal processing needs, and invasive nature in many regions, offering an ecological co-benefit through biomass harvesting. Our results demonstrate its high adsorption capacity, further supporting its potential as an effective and affordable biosorbent for heavy metal remediation. To facilitate real-world implementation, future research should prioritize a detailed assessment of the scalability of biosorption processes. This includes a detailed evaluation of the logistical costs associated with biomass harvesting, preparation, and regeneration under operational constraints. Compared with energy-intensive and chemically dependent conventional methods such as pyrolysis, biosorption with plant-based materials such as P. australis offers notable advantages in energy efficiency, reduced chemical input, and cost-effectiveness. Physical processes such as adsorption provide a more sustainable alternative for capturing a wide range of contaminants [39]. Phragmites australis demonstrates competitive performance as a biosorbent when compared with more established materials such as activated carbon, algae, and agricultural waste [40]. Its adsorption efficiency for heavy metals typically ranges between 45% and 98%. In contrast, activated carbon offers higher removal efficiencies, often exceeding 95%, but comes at a significantly higher cost, ranging from USD 3 to 5 per kilogram, due to its intensive processing and energy requirements [41]. Agricultural byproducts such as rice husk or sawdust are low-cost alternatives (approximately USD 0.50/kg or less), with moderate to high metal removal capacities (60–90%), though their performance is often enhanced through chemical or thermal activation [42]. Algae-based biosorbents, such as marine algae (Sargassum sp.) and microalgae (Chlorella vulgaris and Spirulina sp.), also show high efficiencies, but their scalability is limited by cultivation costs and environmental constraints [43]. Overall, the use of P. australis presents a sustainable and efficient biosorption solution for heavy metal removal in wastewater treatment systems.

4. Conclusions

This study assessed the potential of Phragmites australis biomass, commonly known as common reed, as an adsorbent for removing heavy metal ions from aqueous solutions. The choice of P. australis was based on its high availability, low cost, and ability to absorb metal ions from the surrounding medium. Additionally, this plant material, which is often considered waste and unsuitable for animal feed, is typically discarded by burning, which contributes to environmental pollution. The cellular structure and biochemical properties of P. australis make it suitable for absorbing heavy metal contaminants and reducing their concentrations in polluted water. The adsorption data were well described by both the Langmuir and Freundlich isotherm models, indicating favorable monolayer adsorption and heterogeneous surface interactions, respectively, with selectivity for specific metals. Thus, P. australis proves to be a highly efficient, eco-friendly, and cost-effective material for the biosorption of heavy metals from wastewater. Future research should focus on optimizing the regeneration of P. australis for repeated use and exploring its applicability in more complex wastewater matrices and large-scale industrial processes.