## 4 Results  
### Characterization Techniques  
The adsorption process is a complex phenomenon involving many steps; therefore, many factors affect the removal yield of heavy metals from aqueous solutions. Table 3 shows the results for the ultimate and proximate analyses of the biomasses. It was found that carbon contributed most to the bioadsorbent composition, followed by hydrogen. These results were expected, due to the content of such elements in cellulose, hemicellulose, and lignin molecules. Banana peels reported the highest content of cellulose and hemicellulose, which may increase removal yields during adsorption experiments. The removal of heavy metal ions using these lignocellulosic materials is attributed to the presence of functional groups such as hydroxyl, carboxyl, and amines. In this sense, it is important to identify functional groups in bioadsorbents [33]. The presence of the functional groups responsible for the adsorption of lead ions on the surface of bio-adsorbent materials was performed by Fourier Transformed Infrared Spectroscopy (FTIR); this technique shows bands that indicate different wavelengths which are directly proportional to the radiation energies in the infrared range. Figure 1 depicts the FTIR spectrum for bioadsorbents before and after adsorption process. The complexity of lignocellulosic materials, due to the various identified bands, was confirmed. Several peaks were identified at 3400 cm\({}^{-1}\) (OH), 3390.28 cm\({}^{-1}\) (NH), 2931.01 cm\({}^{-1}\) (C-C), 1652.11 cm\({}^{-1}\) (C=C), 1420.81 cm\({}^{-1}\) (C-C), 1339.79 cm\({}^{-1}\) (NO\({}_{2}\)), and 1156.40 cm\({}^{-1}\) (C-O) for all bioadsorbents. After the adsorption process, changes were observed in the width and stretch of some of the bands, especially at 3390 cm\({}^{-1}\) (NH), 2361.19 cm\({}^{-1}\) (-C\(\equiv\)N), 1650.45 cm\({}^{-1}\) (C=C), 1020.66 cm\({}^{-1}\) (OH), and 1156.55 cm\({}^{-1}\) (sulfonamides). Such a phenomenon was attributed to the bonds formed between the heavy metal ions and the active sites of the materials [34]. \begin{table}
\begin{tabular}{c c c} \hline
**Kinetic Model** & **Equation** & **Parameters** \\ \hline Langmuir & \(q_{e}=q_{max}\frac{KC_{f}}{1+KC_{f}}\) & \
\begin{tabular}{c} \(q_{e}\): Adsorption capacity at equilibrium (mg/g); \\ \(C_{f}\): Final concentration of heavy metals (mg/L); \\ \(q_{max}\): Maximum adsorption capacity (mg/g) \\ \end{tabular} \\ \hline Freundlich & \(q=KC_{e}^{\frac{1}{n}}\) &
\begin{tabular}{c} \(q\): Adsorption capacity (mg/g); \\ \(C\)e: Heavy metal concentration at equilibrium (mg/L); \\ \(K\): Freundlich constant (mg/g); \\ \(n\): Heterogeneity factor \\ \end{tabular} \\ \hline \end{tabular}
\end{table} 
Table 2: Mathematical expressions of isotherm models. \begin{table}
\begin{tabular}{c c c c c c c c} \hline
**Biomass** & **Cellulose** & **Hemicellulose** & **Lignin** & **Pectin** & **Carbon** & **Nitrogen** & **Hydrogen** & **Ashes** \\ \hline BP & 20.9 & 7.92 & 18.11 & 2.84 & 36.69 & 0.69 & 3.98 & 7.2 \\ CP & 18.47 & 6.01 & 2.20 & 2.84 & 36.96 & 0.26 & 3.98 & 1.58 \\ YP & 13.08 & 6.47 & 27.73 & 10.98 & 48.14 & 0.18 & 5.44 & 4.85 \\ OPB & 19.90 & 7.00 & 17.11 & 4.88 & 38.27 & 2.03 & 4.71 & 4.23 \\ \hline \end{tabular}
\end{table} 
Table 3: Proximate and ultimate analysis for selected biomasses. The surface chemistry and pore structure of adsorbents make key contributions to an efficient adsorption process. Table 4 shows the results of a Brunauer-Emmett-Teller (BET) analysis. The banana peel biomass reported the highest surface area, despite lignocellulosic residues generally having low surface areas due to the nature of cellulose and hemicellulose [11]. For all biomasses, pore volume was low, which was attributed to the structure of cellulose, lignocellulosic, and lignin, which are characterized by reduced quantities of pores and blocked pores [35].