Removal of Cr (III) from wastewater by using raw and chemically modified sawdust and corn husk

World Health Organization

WHO

National Environmental Quality Standards

NEQS

United States Environmental Protection Agency

US EPA

heavy metals

HMs

sawdust

SD

corn husk

CH

Sustainable Development Study Center

SDSC

Center for Advanced Studies in Physics

CASP

raw sawdust

RSD

raw corn husk

RCH

acid-treated sawdust

ATSD

acid-treated corn husk

ATCH

base-treated sawdust

BTSD

base-treated corn husk

BTCH

detergent-treated sawdust

DTSD

detergent-treated corn husk

DTCH

atomic absorption spectroscopy

AAS

scanning electron microscope

SEM

Fourier transform infrared

FTIR

percentage removal efficiency

% RE

pseudo-first-order

PFO

pseudo-second-order

PSO

Environmental defilement has been considered as a cardinal issue accelerating with the rise in global world population. Water-related illnesses are also increasing and about 1.1% of world population does not have access to safe water for drinking reported by United Nations association report (Muhaisen 2017). Heavy metals (HMs) contamination in water is becoming a serious concern and gaining attention for the last decade (Berenjkar et al. 2019; Kou et al. 2020). The increasing expansion in industrialization and urbanization resulted into vast quantity of release of heavy metals in the environment (Sewwandi et al. 2012). HMs such as copper (Cu), lead (Pb), nickel (Ni), chromium (Cr), arsenic (As), cadmium (Cd), zinc (Zn), aluminum (Al), and mercury (Hg) enter water from various industrial sources. They are highly destructive due to their persistence and non-biodegradability in the environment. Thus, the elimination of HMs is necessary to lessen their threatening effects due to their toxic nature, recalcitrant behavior, and bioaccumulation in living organisms (Ahmed et al. 2019; Chen et al. 2019).

Among the HMs, chromium (Cr) is a substantial environmental concern and abundant metal used in different industrial processes (Miretzky & Cirelli 2010; Vinodhini & Das 2010). Chromium, in the environment, exists in six oxidation states, but the most significant ones are the trivalent chromium Cr (III) and hexavalent chromium Cr (VI) (Miretzky & Cirelli 2010). Chromium (III) is 300 times less deadly in nature than chromium (VI), and its minute quantity is essential for both plants and animals’ normal metabolic functioning. However, Cr (III) can cause health hazards (Miretzky & Cirelli 2010). Cr (III) mainly enters from weathering of Cr containing rocks, industrial discharge, leather tanning industry, electroplating, alloys, and processing units. In water, the pH is the main factor for Cr (III) solubility. Under basic pH, Cr (III) precipitates out, and at acidic pH, it solubilizes. Cr accumulates mainly in roots and shoots of plants and bio-accumulates in human beings (Kimbrough et al. 1999). According to World Health Organization (WHO) guidelines and National Environmental Quality Standards (NEQS) of Pakistan, the allowable limit for chromium in portable water is 0.05 μg/ L. Similarly, in the United States Environmental Protection Agency (US EPA) guideline, the permissible limit for chromium in drinking water is 0.1 μg/L (Raza et al. 2017).

Different treatment technologies can remove HMs from wastewater. However, each treatment has its limitations in terms of installment and maintenance cost, sludge production, removal efficiency, ions specificity, and toxicity. So suitable treatments for the removal of HMs from wastewater should be required (Salman et al. 2015; Al-Qodah et al. 2017). Among these, biosorption utilizes dead or inactive biomass for HMs removal from wastewater. Biosorption is termed as ‘the capability of biological matter to uptake HMs from aqueous solutions via metabolically mediated (by the utilization of ATP) or rapid physicochemical ways of assimilation (not utilizing ATP), or the ability of certain forms of inactive, non-living biomass that adsorb HMs from wastewater’ (Volesky 2003; Joo et al. 2010; Shamim 2018).

The major advantage of bio-adsorption is that it is based on natural organic biological materials, which have the properties of sequestering HMs and reducing the concentration of HMs from ppm to ppb (Lim & Aris 2014; Salman et al. 2015), and it is easily available and easy to process. Furthermore, agriculture waste products are considered an efficient bio-sorbent because these waste products are enriched with lignocellulosic materials and are found to be an inexpensive, eco-friendly, and readily available alternative material for HMs removal (Arunkumar et al. 2014).

The mechanism of biosorption includes the physical binding (electrostatic force of attraction or Van der Waals force of attraction) or chemical binding (exchange of ions) of the metal ions, chelation, complexation, reduction, and precipitation (Kanamarlapudi et al. 2018). The adsorption properties of biosorbents can be enhanced by chemical modifications. The chemical modification increases the functional groups attached to the surface of biosorbents, which help to sequester HMs and increase the biosorption capacity (Pothan et al. 2002; Hasar 2003).

Sawdust (SD) is produced by sawmills when the wood is processed for different purposes. The wooden powder, which is considered as a residue, is known as SD. In addition, SD is used to warm houses as a minor fuel (Singh et al. 2011). Corn husk (CH) is the leafy part of corn that is peeled off from the corn ear. It is different from a leaf in respect to structure and function. It is considered a valuable bio-sorbent because of its adsorption capacity for HMs and dyes. Rafatullah et al. (2009) experimented, the biosorption of Cu (II), Ni (II), Pb (II), and Cr (III) by using SD and investigated the effects of operational parameters and kinetics studies. Gunatilake (2016) studies the elimination of Cr (III) by using biochar produced from SD and rice husk. Similarly, Yu et al. (2001) performed analysis for eradication of Cu and Pb by using maple sawdust and showed 90% removal efficiency. A study for the elimination of Cr (VI), Pb (II), Cu (II), and Hg (II) used sawdust. Another examination was carried by Lin et al. (2019) showed corn husk (CH) had bio-sorption ability for mercury (Hg). Although many studies have utilized SD and CH to treat Cr (III) from wastewater, the usage of detergent powder for activation of SD and CH has not been investigated yet. Therefore, this study aims to explore the influence of administering chemical modifications to the SD and CH on enhancing the biosorption of Cr (III) from the aqueous solutions. The chemical treatment utilized sulfuric acid (H₂SO₄), sodium hydroxide (NaOH), and detergent powder. The study aimed at: (a) Removal of Cr (III) from wastewater to reduce its harmful impacts on the public, aquatic life, and environment. (b) Chemical treatment of SD and CH with an acid, a base, and a detergent powder to activate attached functional groups. (c) Characterization of biosorption capacity of sawdust and corn husk, before and after treatment with chemicals (d) Effects of operating parameters (pH, contact time, biosorbent dose, and temperature). (e) Estimating comparative isotherm models to understand the biosorption process. (f) Estimating the adsorption kinetic models and thermodynamic parameters for elimination of Cr (III) from aqueous solution.

The schematic overview of the entire procedure was adopted by El-Saied et al. (2017) and Duru et al. (2019), but due to changed environmental conditions, the process was modified to some extent.

An SD sample was collected from a saw mill located in a small town named Bahoru, district Nankana Sahib, Pakistan. A CH sample was collected from a street vendor of corn in Muslim Town, Lahore, Pakistan. Both these samples were carried to the laboratory of Sustainable Development Study Center (SDSC) of Government College University, Lahore, for further processing.

SD and corn husk CH were used as biosorbent materials, as both were readily available. Both SD and CH samples were thoroughly rinsed with deionized water many times to take off impurities and dust particles. After that, the samples were oven-dried (Oven Memmert UM200, Germany, available at the laboratory) at 70 °C for 24 hours to remove excess moisture. In addition, the biosorbents were allowed to chill at room temperature and crushed into a fine powder using a grinder (IKA, Grinder MF 10B, Germany, available at the laboratory). The fine powder of SD and CH was then sieved through a small particle size of 4 mesh size. Finally, these raw samples were stored in dry plastic jars separately, and these samples were ready for further batch-scale processing.

The fine powder of SD and CH was chemically treated with H₂SO₄ (1M), NaOH (0.5M), and detergent powder (0.5 g per gram of biosorbent). A 500 mL of an acid (H₂SO₄), base (NaOH), and detergent were assorted with 10 g of biosorbents in a 1,000 mL beaker. After that, the beakers were subjected to a hot plate (DAIHAN Scientific Co., Ltd, Hotplate Stirrer, MSH-20D, Korea, available at the laboratory) attached with a magnetic stirrer at a mixing speed of 300 rpm for 2 hours at 25 °C. The solution was then filtered and washed several times with deionized water. Further, it was oven-dried (Oven Memmert UM200, Germany, available at the laboratory) at 50 °C for 16 hours and stored for further analysis.

All the chemical materials used in this experiment were analytical grade. CrCl₃, high concentrated H₂SO₄, pure NaOH, HNO₃, HCl, and NaNO₃, and detergent powder (ionic) were used for the preparation of the stock solution. The stock chromium (III) solution of 1,000 ppm was produced by mixing 3.1 g of chromium chloride (CrCl₃) in 1,000 mL distilled water. Further, stock solutions were placed in a plastic bottle and labeled, and placed in the fridge for further use.

Batch-scale experiments were performed to remove Cr (III) from the aqueous solution by using raw SD (RSD), acid-treated SD (ATSD), base-treated SD (BTSD), detergent-treated SD (DTSD), raw CH (RCH), acid-treated CH (ATCH), base-treated CH (BTCH), and detergent-treated CH (DTCH). In an Erlenmeyer flask, a 100 ml solution containing Cr (III) ions with an initial concentration of 513.7230 mg/L was assorted with 1 g of biosorbents. Then, these flasks were allowed to mix thoroughly in an incubator shaker at 300 rpm. After 2 hours, the process was stopped, and the sample was filtered in a vacuum filtration with the help of Whatman's filter paper grade 1. To estimate the final concentration of Cr (III) in water suspension atomic absorption spectroscopy (AAS) (Thermo Scientific, iCE 3000 Series AA spectrometer, USA) was used. This whole experiment was repeated in triplicates.

The raw and chemically modified biosorbents were described by using scanning electron microscope (SEM) and Fourier transform infrared (FTIR). The SEM (JSM-6480, Tokyo, Japan, available at Center for Advanced Studies in Physics (CASP) of Government College University, Lahore) analysis was carried out to analyze the surface morphology (topography and composition) of raw and chemically modified SD and CH at 200 μm, 100 μm, and 50 μm. FTIR (JASCO, FT/IR-6600, USA, available at the laboratory) analysis was carried out in a spectral sequence of 4,000–400 cm⁻¹ to characterize the attached surface functional groups of SD and CH.

The pH, at which the net charge on the surface of biosorbent becomes zero, is termed as the point of zero charge (PZC). In the biosorption of Cr (III) ions by using raw and chemically modified SD and CH, the PZC was determined by the mass titration method. Three solutions having a certain range of initial pH were formed by utilizing HNO₃ and NaOH. However, the background electrolyte was NaNO₃. A 25 ml of solution, having each initial pH value, was poured into six conical flasks and a distinct amount of biosorbents were added to it. A solid friction of 0.05, 0.1, 0.5, 1, 5 and 10% were prepared and placed in shaker for 24 hours. The final pH value was noted and a graph was plotted between the amount of biosorbents and final pH value. The PZC was noted and the surface of biosorbents has positive charge below this pH value and negative charge above this pH value (Chand et al. 2009).

A batch-scale experiment was performed to examine the impacts of various operational factors on the process of biosorption. Some of these parameters, such as pH, the time of contact, a dose of adsorbent, and temperature, were analyzed for the biosorption of Cr (III) ions present in an aqueous sample by utilizing RSD and RCH, and the optimum biosorption parameters were evaluated.

The impact of pH on biosorption of HM ions by RSD and RCH was estimated by adjusting the initial pH ranging from 0 to 8. The 100 mL aqueous solution having a 513.7230 mg/L of initial concentration of Cr (III) ions was used. The pH of the solutions was maintained by using 1.0 M HCl and 1.0 M NaOH. In a 500 ml flask, 1 g of biosorbents was added in 100 ml of the metal-containing aqueous solution. The solution was then placed in a magnetic stirrer at 300 rpm for 2 hours at 25 °C. Then, the solution was strained, and the concentration of unadsorbed Cr (III) ions in the filtrate residual were estimated using an Atomic Absorption Spectrophotometer (Thermo Scientific, iCE 3000 Series AA spectrometer, USA).

The impact of contact time on the biosorption of HM ions by RSD and RCH was estimated by studying the biosorption at different intervals of time (30 min, 60 min, 90 min, 120 min, 150 min, and 180 min). The 100 mL aqueous solution having a 513.7230 mg/L of initial concentration of Cr (III) ions was used. In a 500 ml flask, 1 g of biosorbent was added in 100 ml of the metal-containing aqueous solution. The mixture was then placed in a magnetic stirrer at 300 rpm for different intervals of time (30 min, 60 min, 90 min, 120 min, 150 min, and 180 min) at room temperature and optimum pH. Then, the solution was strained and the concentration of unadsorbed Cr (III) ions in the filtrate residual were estimated by using an atomic absorption spectrophotometer (Thermo Scientific, iCE 3000 Series AA spectrometer, USA).

The impact of different amounts of RSD and RCH on the adsorption of HM ions was estimated by changing the amount of RSD and RCH. Different biosorbents dosages ranging from 0.25 g to 1.25 g were used in 100 ml of metal-containing solution. The 100 mL aqueous solution having a 513.7230 mg/L concentration of Cr (III) ions was used. In a 500 ml flask, a different dose of adsorbent was added in 100 ml of the metal-containing aqueous solution. The mixture was then placed in a magnetic stirrer at 300 rpm for 2 hours at room temperature and optimum pH. Then, the solution was strained and the concentration of unadsorbed chromium (III) ions in the filtrate residual were estimated by using atomic absorption spectrophotometer (Thermo Scientific, iCE 3000 Series AA spectrometer, USA).

The impact of temperature on biosorption of HM ions by RSD and RCH was estimated by changing the temperature from 15° to 45 °C. The 100 mL aqueous solution having a 513.7230 mg/ L of initial concentration of Cr (III) ions was used. In a 500 ml flask, 1 g of biosorbents was added in 100 ml of the metal-containing aqueous solution. The mixture was then placed in a magnetic stirrer at 300 rpm at different temperatures for 2 hours and optimum pH. Then, the solution was strained and the concentration of unadsorbed metal ions in the filtrate residual was estimated by using atomic absorption spectrophotometer (Thermo Scientific, iCE 3000 Series AA spectrometer, USA).

Mathematical manipulations of the results were manifested by estimating the % RE, adsorption isotherm models, kinetics models, and thermodynamic parameters for the biosorption of raw and chemically treated SD and CH.

The initial concentrations of HM ions were used for modeling adsorption isotherms. The Langmuir isotherm model and the Freundlich isotherm model were commonly used, and data were fitted to these models. In addition, the amount of Cr (III) adsorbed on biosorbent was fitted graphically for comparing the biosorption capacity and percentage removal efficiency (% RE) of raw and chemically modified SD and CH.

The adsorption kinetics modeling enabled studying the rate of biosorption with time (Kapur & Mondal 2014). To present the kinetics equation highlighting the biosorption of Cr (III) on raw and chemically modified SD and CH, two main kinetics models were employed to evaluate the experimental data. These models are pseudo-first-order kinetics (PFO) and pseudo-second-order kinetics (PSO).

where the value of q_t represents time of adsorption (min)(mg/g); k₁ represents the first-order rate constant (1/min); q_e represents the adsorption amount at equilibrium (mg/g) (Li et al. 2007; Kapur & Mondal 2014).

where the value of q_t represents time of adsorption (min)(mg/g); k₂ represents the second-order rate constant (g/mg/min); q_e represents the adsorption amount at equilibrium (mg/g) (Li et al. 2007; Kapur & Mondal 2014).

The thermodynamic parameters for the biosorption of Cr (III) ions by using raw and chemically treated SD and CH can be estimated by employing following equations:

SEM analysis was employed to examine the surface morphology of RSD and pre-treated SD with acid, base, and detergent. The estimation of surface morphology helped to determine the areas of adsorption on SD. The greater the surface area, the higher will be the contact efficiency between pollutants to be removed and SD (Ateş & Özcan 2018).

After modifications with an acid, base, and detergent, the surface of SD becomes smooth and shiny with irregular cavities. The pores, i.e. micropores and mesopores, appeared out onto the surface of the SD. The visibility of pores was due to the degradation of cellulose, lignin, and hemi-cellulosic material, and extermination of extractible material from SD, after chemical modification of the cellulosic structure. The mechanical properties of SD were enhanced after treatment with acid, base and detergent, and pores provide surface area for attachment of metal contaminants onto the surface of SD (Ahmad et al. 2016; M'hamdi et al. 2016; Benyoucef et al. 2020).

After chemical treatment, the heterogeneity of the surface increased due to the removal of the non-cellulosic and small quantity of lignocellulosic material from the surface. The appearance of irregular cavities on the surface was due to excessive delignification of the fibers by NaOH. The fibers showed a smooth surface and hollow-shaped pores (i.e., both macropores and micropores) become visible on the surface. The appearance of both macropores and micropores enhanced the adhesive properties of CH fiber due to the removal of impurities of non-cellulosic material. Thus, the acid, base, and detergent treatment enhanced the adsorption ability of CH by increasing its surface area for attachment of contaminants present in the wastewater (Herlina et al. 2018; Duru et al. 2021).

The spectral peaks in the region around 2,910 cm⁻¹ and 1,363 cm⁻¹ represented the stretching and bending vibrations of the sp³ C-H bond of methyl groups of cellulose, respectively (Zou et al. 2013). A small spectral peak in the region of 2,360 cm⁻¹ and 2,160 cm⁻¹ represented the availability of C ≡ C and C ≡ N groups. Similarly, the spectral band that existed in 1,725 cm⁻¹, characterized the stretching vibration of carboxylic acid (C = O) and esters. The presence of these groups is the indication of xylan, which is present in hemicellulose (M'hamdi et al. 2016). Further, the small spectral band present at 1,725 cm⁻¹ and 1,610 cm⁻¹ highlighted stretching vibrations of carbonyl groups, i.e., aldehyde and ketones (Zou et al. 2013). The band located at 1,507 cm⁻¹ indicated the aromatic ring structure (C = O) deformation in lignin (M'hamdi et al. 2016). Further, the band spectrum from 1,545 cm⁻¹ to 1,454 cm⁻¹ highlighted the deformations of CH₃ and CH₂. A small spectral band at 1,425 cm⁻¹ was the consequence of in-plane bending vibrations of HCH and COH functional groups. At 1,365 cm⁻¹, the adsorption peaks characterized the deformation vibrations of C-H and O-H of alcoholic and phenolic groups linked with cellulose (Sewwandi et al. 2012). The spectral band saw at 1,316 cm⁻¹, and 1,267 cm⁻¹ are associated with vibrations of methoxy groups of lignin. The spectrum variation was due to the delignification of wood during activation with chemicals (M'hamdi et al. 2016). The spectrum's peak at region 1,026 cm⁻¹ corresponded to the C-O stretching vibration modes of primary and secondary alcohols and C-O-C bonding groups. A small peak at 899 cm⁻¹ highlighted the out-plane deformation of the C-H bond (M'hamdi et al. 2016).

The spectral peak at 2,358 cm⁻¹ highlighted the availability of C ≡ C and C ≡ N groups. This peak was more intense in DTCH samples because of unsaturation. Another spectral band near 1,734 cm⁻¹ highlighted the presence of carbonyl stretching vibrations of carboxylic acid (C = O) and esters in hemicellulose (Singh et al. 2020). This spectral peak was less defined in acid and base-treated CH samples because of the removal of hemicellulose after chemical treatment (Singh et al. 2020). A small peak at 1,642 cm⁻¹ represented the (C = O) stretching vibration of the conjugated carbonyl group of lignin (Singh et al. 2020). Finally, a sharp peak at 1,460 cm⁻¹ indicated the stretching vibrations of the C = C group of aromatic skeletal lignin and deformation of the C-H group of lignin and hemicellulose (Kambli et al. 2017; Singh et al. 2020). This peak was more intense in ATCH but less in base-treated and detergent-treated CH samples. Similarly, at 1,423 cm⁻¹, a spectral band corresponding to symmetric bending of CH₂ group (Yeasmin & Mondal 2015; Kambli et al. 2016). However, this peak was much prominent in raw and acid-treated CH samples because of more cellulose content in both.

At 1,364 cm⁻¹, the peak highlighted the in-plane bending of OH groups in cellulose and elongation of aliphatic C-H groups of cellulose and hemicellulose hemicellulose (Yeasmin & Mondal 2015; Singh et al. 2020). The spectral peak located in region 1,158 cm⁻¹ described the asymmetrical stretching of C-O-C bonds in cellulose (Singh et al. 2020). A sharp spectral peak at 1,030 cm⁻¹ corresponded to the C = O symmetrical elongation in alcohols present in lignin (Yeasmin & Mondal 2015; Herlina et al. 2018). The intensity of this peak was less in base-treated, and detergent-treated CH samples due to the removal of lignin. The spectral band existing at at 897 cm⁻¹ highlighted the presence of C-O-C elongation vibrations of β (1–4) glycoside linkage of the cellulose (Yeasmin & Mondal 2015; Kambli et al. 2016).

The PZC value of SD and CH for biosorption of Cr (III) ions was estimated by mass titration method. The PZC of biosorbents were determined to be 3.75 and 4 for SD and CH, respectively. At pH equal to PZC the net charge on the surface of biosorbents is zero and there is no interaction between biosorbent and biosorbate. At lower pH than PZC, the surface of biosorbents is positively charged. While, at higher pH than PZC, the surface of biosorbents is negatively charged (Chand et al. 2009).

The initial pH of the solution is regarded as a controlling factor in the biosorption of metal ions onto biosorbents surface. The main fact behind this is that protons present in solution behave as strong competing biosorbate ions. Moreover, pH also causes ionization of the biosorbents' surface functional groups and chemical speciation of the metallic ions present in the aqueous solution (Božić et al. 2009).

This optimum pH is less than PZC and the surface of biosorbents becomes positively charged. In this regard, the biosorption behavior of HMs onto the biosorbent surface revealed that biosorption of HMs was based on the principle of ions exchange and hydrogen bonding (Rafatullah et al. 2009). At lower pH, the biosorption of HMs is low because of conflict between the metal ions and protons for the attachment on available sites. As the pH rises, the surface of SD and CH becomes less positively charged. So, the attractive electrostatic forces between the HMs and biosorbent surface start increasing and the biosorption capacity also increases (Kapur & Mondal 2014; Gunatilake 2016).

It can be observed from Figure 5 that pH has a strong influence on the biosorption capacity of SD and CH. The biosorption of Cr (III) ion exhibited a similar trend, that is, it increased as the pH increased By observing the results, it is confirmed that biosorption of metal ions obeyed the principle of ion exchange. At lower pH, the biosorption capacity of biosorbents is low because of higher amount of H⁺ ions present in the aqueous solution, which behave as a competitor for the HM ions and cause hindrance in the biosorption of HM ions onto the surface of biosorbents. At pH ≤ 1, the biosorption capacity of biosorbents is zero because of the presence of relatively high concentration of protons, which may lead to the occupation of the active sites and limit the biosorption of HM ions. At higher value of pH, the concentration of H⁺ in the aqueous solution starts decreasing, and the available active binding sites onto the biosorbents surface shifted towards their dissociation condition and adsorb HM ions from the aqueous solution. This behavior is similar to the findings of Schiewer & Volesky (1997).

However, the increase in pH increases the biosorption capacity but up to certain pH, above that pH, the increase in pH causes a decrease in biosorption capacity. This is due to formation of metal hydroxides precipitates into the aqueous solution, which settles down and biosorption capacity of HMs decreases. So, in case of Cr (III), the chromium hydroxide precipitates formed at pH greater than 4. Therefore, the optimum pH is less than pH at which precipitates of metal hydroxides formed (Rafatullah et al. 2009).

The modifications of SD and CH by sulfuric acid, sodium hydroxide, and detergent powder can either increase or decrease % RE of Cr (III) ions compared with biosorption of raw biosorbents. The obtained results showed that the biosorption of Cr (III) ions was increased by using chemically modified SD and CH in comparison with untreated sawdust and corn husk. However, the H₂SO₄ treatment resulted in low adsorption capacity as compared to NaOH and detergent powder activation but high in comparison with raw biosorbents.

The acidic modification of biosorbents enhanced the acidic properties and hydrophilic character of biosorbents (Rehman et al. 2019; Abegunde et al. 2020). Gao et al. (2017) concluded that acid modification affects the lipophilic and hydrophobic character, the charge on the surface, porosity, and the oxygen-containing functional groups, which resulted in alternation in adsorption potential of biosorbents than raw biosorbents. Similarly, the treatment with an alkali or base involved the removal of the surface impurities such as waxes or natural fat. These surface impurities hide the adhesion ability of the biosorbents. The roughness on the surface also increases after removal of impurities by NaOH treatment which thus, exposes more surface –OH and other functional groups on the surface, which increases the adhesion properties (Wong et al. 2003; Ndazi et al. 2007; Abegunde et al. 2020).

Therefore, the % RE of acid treatment is less than that of base and detergent treatment because of the increase in positive charge on biosorbent surface and the excessive concentration of H+ ions in the solution, which cause hindrance in the biosorption of metal ions. Similarly, the base treatment has high % RE than acid treatment because of exposure of excessive active sites for metal binding but less than detergent treatment. The detergent treatment enhanced the adsorption capacity of biosorbents than acid and base treatment, due to the increase in surface porosity and exposure of more functional groups for the attachment of metal ions. Thus, the overall percentage removal efficiency of the biosorbents are: RSD and RCH < ATSD and ATCH < BTSD and BTCH < DTSD and DTCH.

The association between the amount of a specific adsorbate and its adsorption potential onto the exterior of a biosorbent can be evaluated by using adsorption isotherms (Rafatullah et al. 2009). The biosorption of HMs onto the biosorbent can be described by isotherms. These isotherms specify the scattering of HMs between two phases: liquid phase and solid phase (Desta 2013). To identify the biosorption potential of SD and CH for the biosorption of Cr (III) ions present in an aqueous sample, the Langmuir isotherm model and the Freundlich isotherm model were used. The Langmuir model specified the homogeneity of the surface of the biosorbents, while the Freundlich isotherm model specified the heterogeneity of the surface of the biosorbents.

This model considered that one molecular layer of adsorbate was developed onto the adsorbent surface, and it remained constant even the concentration of adsorbate was high (Gunatilake 2016). The Langmuir isotherm model assumed that a single biosorption film of moleculeswas formed on the exterior of the biosorbent and restricted active sites were present for biosorption (Desta 2013). Further, the biosorbent's surface was homogenous and had the same affinity for all the metal ions (Kapur & Mondal 2014). Therefore, the adsorption of metal ions at a site did not affect the adjacent site, and once a site was filled with metal ions, no further metal ion can attach to that site. In this way, a saturation point was reached where maximum adsorption of metal ions was achieved (Desta 2013).

The linear expression of the Langmuir equation was presented in Equation (3). In this equation, q_max is the single layer adsorption potential of the adsorbent. q_max is the maximum concentration of adsorbate which is absorbed on the exterior of the biosorbent. K_L is the Langmuir constant linked with the adsorption energy. C_e is the equilibrium amount of HM ions in the aqueous sample and q_e is the equilibrium amount of HM ions on the biosorbent (Gunatilake 2016).

The Langmuir isotherm modelwas tested by plotting a graph between C_e/q_e vs C_e. The value of q_max and K_L were obtained from the slope of the graph and the intercept, respectively. The value of R², the Langmuir constant, and q_max were summarized in Table 2 for Cr (III) ions biosorption. The R² value for Cr (III) ions biosorption on raw and chemically modified SD and CH ranged from 0.9999 to 1 (Table 2), which depicted that both adsorbents had the efficient potential for Cr (III) ions biosorption. The literature had more or less similar R² values. The value of correlation coefficient R² indicated that both raw and chemically modified SD and CH had good adsorption potential for Cr (III) and the Langmuir model was best fitted for both adsorbents.

This model was applicable for non-ideal biosorption of metal ions onto the heterogeneous exterior of the biosorbent and multilayer biosorption (Rafatullah et al. 2009). The Freundlich isotherm model was an empirical expression incorporating the heterogeneous exterior of the biosorbent (Desta 2013) and also described the adsorption potential of the biosorbent for biosorbate (Gunatilake 2016).

The linear expression of the Freundlich isotherm model was presented by Equation (4). In this equation, K_F was the Freundlich constant, which described the biosorption potential of biosorbent and 1/n is biosorption intensity. The value of 1/n and K_F were dependent on the interaction of adsorbent and adsorbate and were calculated from the slope and the intercept of the graph. q_e specified the concentration of adsorbate, which was absorbed in equilibrium per amount of biosorbent. C_e highlighted the equilibrium amount of HM ions present in an aqueous sample.

The Freundlich isotherm model was described by plotting a graph between log C_e vs log q_e. The value of 1/n, K_F, and linear regression coefficient (R²) were summarized in Table 2 for Cr (III) ions adsorption. The n specifies the degree of linearity between aqueous sample concentration and biosorption (Desta 2013; Muhaisen 2017). If n = 1, then the process of biosorption was linear. If n < 1, then the phenomena of biosorption were chemical. If n > 1, then the phenomena of biosorption were physical (Desta 2013; Gunatilake 2016). The value of n, which was obtained from the Freundlich equation for Cr (III) ions adsorption, ranges from 0.0177 to 3.2673 for raw and chemically treated sawdust and from 0.0086 to 1.8887 for raw and chemically treated corn husk (Table 2). The value of n was less than 1 for ATSD, BTSD, DTSD, ATCH, BTCH, and DTCH, which indicated that the phenomenon of adsorption was chemical. Only the value of n for biosorption of Cr (III) ions by using RSD and RCH was greater than 1 (Table 2), which showed that the phenomenon of adsorption was physical.

The value of correlation coefficients (R²) for biosorption of Cr (III) ranged from 0.9978 to 1 (Table 2), which highlighted that both biosorbents were suitable for Cr (III) biosorption. Therefore, for the value of R², it is estimated that the Freundlich isotherm model was also suited for biosorption of Cr (III) by using raw and chemically modified SD and CH. Nearly literature had been reported with similar results. Therefore, both SD and CH had a good potential for biosorption of HM ions from aqueous samples.

The adsorption kinetics models were studied to investigate the change in metal adsorption with time and time required to reach the equilibrium. To present the kinetics equation highlighting the biosorption of Cr (III) on raw and chemically modified SD and CH, PFO and PSO models were used.

The Lagergren-first-order kinetics equation was firstly given by Lagergren in 1898 (Rafatullah et al. 2009) and presented in Equation (5). When it was applied for boundary conditions qt = 0 at t = 0 and qt = qt at t = t and then it rearranged into linearized expression as shown in Equation (6). In this equation, q_e described the amount of metal ions adsorbed per unit mass of biosorbent (mg/g), q describes the amount of metal ions adsorbed at any time (mg/g), and k₁ is the rate constant of PFO kinetics model. The values of the adsorption kinetic parameters were obtained from the slope and intercept of the graph (Kapur & Mondal 2014).

The PFO kinetics model was described by plotting a graph between log (q_e–q_t) vs t. The value of q_e, k₁ and R² were summarized in Table 3 for the biosorption of Cr (III) ions by using raw and chemically treated SD and CH. In case of Cr (III) biosorption, the value of R² lies between 0.7162 and 0.9983, and it depicted that PFO models have deficient or poor correlation coefficient for the data to best fit. Therefore, it can be summarized that PFO model had no satisfactory values and was not suitable for biosorption of Cr (III) ions using raw and chemically treated SD and CH.

The Lagergren-first-order equation was modified by Ho and McKay (Rafatullah et al. 2009) and the proposed form of represented in Equation (7). After specific integration by administering the conditions q_t = 0 at t = 0 and q_t = q_t at t = t, the linearized expression of this equation was showed in Equation (8). In this equation, the value of q_t represented time of adsorption (min)(mg/g), k₂ represented the second-order rate constant (g/mg/min), q_e represented the adsorption amount at equilibrium (mg/g). The values of kinetic parameters can be calculated by plotting a graph between t/q and t. the values of k₂ and q_e can be obtained from the slope and intercept of the plotted graph. The values of q_e, k₂, and R² are summarized in Table 3 for the biosorption of Cr (III) by using raw and chemically treated SD and CH (Li et al. 2007; Rafatullah et al. 2009). The values of correlation coefficient R² for PSO model was very high. The minimum value of R² was 0.9793 and maximum was 1 which was ideal values for a perfect model. Therefore, PSO was the best-fitted kinetic model, and the biosorption of Cr (III) onto the surface of SD and CH perfectly obeyed PSO kinetic model.

The values of thermodynamic parameters for the biosorption of Cr (III) by using raw and chemically treated SD and CH were calculated by Equations (9)–(11) and summarized in Table 4. The value of Gibb's free energy (ΔG°) was negative which was an indication of the feasibility and spontaneity of the biosorption process. The positive value of ΔH° is indication of the endothermic nature of reaction. While the positive value of entropy (ΔS°) indicated the increased randomness at the solid-solution interface during the biosorption of metal ions onto the active sites present onto the surface of biosorbents. It also showed that both biosorbents had high biosorption potential for Cr (III) ions (Ajmal et al. 1998; Rafatullah et al. 2009).

SD and CH are useful biosorbents for the removal of HMs as they effectively remove Cr (III) ions from aqueous samples up to 99%. The process of biosorbtion by SD and CH is reliable, feasible and easy to process. So it will be helpful in designing a wastewater treatment plant on small and large scale for treatment of heavy metals for treatment of industrial and municipal wastewater. The chemical modifications of biosorbents are a successful approach and it increases the biosorption potential for HMs removal. This study also provides an efficient approach to industrialist, government, and private organizations to treat industrial and municipal wastewater with higher removal efficiency by using a variety of biosorbents with chemical modifications and also encourage the practical applications of biosorption techniques over other conventional methods. Furthermore, there is a need for continue research work in order to better understand the mechanism of biosorption, effects of different operating parameters, % RE and adsorption capacity of different biosorbents after modifications by a variety of chemicals. Extensive research work is required in regeneration of biosorbents and utilization of composites and mixtures of different biosorbents and estimation of their adsorption potential. Government and private organizations should abandon the conventional modes of treatments techniques and should encourage such approaches like biosorption in which country's own agricultural waste is utilized for the treatment of other waste, which in terms save many resources and investments, and benefit for the economy of the country.

SD and CH were used as biosorbents to eliminate Cr (III) from the aqueous sample. These biosorbents were chemically treated with H₂SO₄ (ATSD and ATCH), sodium hydroxide (BTSD and BTCH), and detergent powder (DTSD and DTCH). These raw and chemically treated adsorbents were employed to eliminate chromium (III). The results showed that among all biosorbents, detergents-treated biosorbents (DTSD and DTCH) have efficient removal efficiency up to 99%. The SEM examination of the surface revealed that the surface porosity has increased after chemical treatment. The FTIR analysis highlighted the presence of functional groups and showed that hydroxyl (OH-) and carbonyl groups were highly active functional groups present on the surface of adsorbents which had increased the efficiency for Cr (III) removal. The adsorption isotherm data expresses that the Langmuir and Freundlich isotherm models were best suited to Cr (III) ions biosorption by using raw and chemically modified SD and CH. The biosorption obeyed pseudo-second-order kinetic models and thermodynamic parameters indicated the spontaneity and feasibility of the process. The biosorption process is endothermic and both biosorbents had a greater affinity for biosorption of Cr (III) ions. The order of removal efficiency of raw and chemically modified SD and CH was DTSD and DTCH > BTSD and BTCH > ATSD and ATCH > RSD and RCH. Thus, DTSD and DTCH have a greater potential for the adsorption of HMs. It has dual benefits by removing the HMs from the aqueous solution in a reliable, affordable, and eco-friendly way. Further, the biosorption process utilized agricultural waste products, so it reduced the handling and disposal issues of solid waste management and achieve sustainability.

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

The authors declare there is no conflict.