Optimized removal of hexavalent chromium from water using spent tea leaves treated with ascorbic acid

Spent tea leaves were functionalized with ascorbic acid to obtain treated tea waste (t-TW) to encourage the adsorption of hexavalent chromium from water. The adsorption removal of Cr(VI) was systematically investigated as a function of four experimental factors: pH (2–12), initial Cr(VI) concentration (1–100 mg L−1), t-TW dosage (0–4 g L−1), and temperature (10–50 °C) by following a statistical experimental design. A central composite rotatable experimental design based on a response surface methodology was used to establish an empirical model that assessed the individual and combined effects of factors on adsorptive removal of Cr(VI). The model was experimentally verified and statistically validated then used to predict optimal adsorption removal of Cr(VI) from water. At optimized conditions, ≥ 99% of 1 mg L−1 Cr(VI) can be removed by 4 g L−1 t-TW at a pH of 9. The adsorptive mechanism was assessed by conducting kinetics and equilibrium studies. The adsorption of Cr(VI) by t-TW followed a pseudo-second-order kinetics model (k2 = 0.001 g mg−1 h−1) and could be described by Langmuir and Temkin isotherms, indicating monolayer adsorption and predominantly adsorbate-adsorbent interactions. The t-TW exhibited a competitive Cr(VI) adsorption capacity of 232.2 mg g−1 compared with the other low-cost adsorbents. These results support the utilization of tea waste for the removal of hazardous metal contaminants from aqueous systems.

Optimized removal of hexavalent chromium from water using spent tea leaves treated with ascorbic acid Qammer Zaib & Daeseung Kyung * Spent tea leaves were functionalized with ascorbic acid to obtain treated tea waste (t-TW) to encourage the adsorption of hexavalent chromium from water. The adsorption removal of Cr(VI) was systematically investigated as a function of four experimental factors: pH (2-12), initial Cr(VI) concentration (1-100 mg L −1 ), t-TW dosage (0-4 g L −1 ), and temperature (10-50 °C) by following a statistical experimental design. A central composite rotatable experimental design based on a response surface methodology was used to establish an empirical model that assessed the individual and combined effects of factors on adsorptive removal of Cr(VI). The model was experimentally verified and statistically validated then used to predict optimal adsorption removal of Cr(VI) from water. At optimized conditions, ≥ 99% of 1 mg L −1 Cr(VI) can be removed by 4 g L −1 t-TW at a pH of 9. The adsorptive mechanism was assessed by conducting kinetics and equilibrium studies. The adsorption of Cr(VI) by t-TW followed a pseudo-second-order kinetics model (k 2 = 0.001 g mg −1 h −1 ) and could be described by Langmuir and Temkin isotherms, indicating monolayer adsorption and predominantly adsorbate-adsorbent interactions. The t-TW exhibited a competitive Cr(VI) adsorption capacity of 232.2 mg g −1 compared with the other low-cost adsorbents. These results support the utilization of tea waste for the removal of hazardous metal contaminants from aqueous systems.
Chromium is among the more widespread of heavy metals in aquatic ecosystems, in part due to wastewater released from the chromium plating, leather tannery, textile, and wood preservation industries 1 . In environmental systems, chromium is present primarily in hexavalent and trivalent oxidation states. Cr(III) is generally non-toxic and is an essential agent in animal and human metabolisms 2 . However, Cr(VI) is hazardous to living organisms due to its mutagenicity and carcinogenicity 2 and is among 129 critical pollutants identified by the US EPA 3 . Cr(VI) is known to induce lung cancer, skin irritation, and damage to kidneys, livers, and gastric systems 2,4 . Because wastewater is one of the major environmental sources of this pollutant, the EPA and WHO have limited the maximum permissible levels of chromium to 0.1 and 0.05 mg L −1 , respectively 5,6 . It is therefore highly desirable to bring high concentrations of Cr(VI) in wastewater down to allowable limits before releasing it to the environment.
Concentrations of Cr(VI) and other heavy metals in water can be controlled by ion exchange, solvent extraction, chemical precipitation, membrane-based separation, and adsorption [7][8][9][10] . Among these technologies, adsorption is popular due to its efficiency, convenience, smaller land footprint, and simplicity of operation 8,11 . However, its commercial success is limited by high costs associated with the need for periodic replacement of adsorbent material. The cost-effectiveness of adsorption can be improved by utilizing low-cost adsorbent materials, including waste and biomass 8,12 . Tea waste (TW) in particular has demonstrated an ability to effectively adsorb Cr(VI) from aqueous systems 13,14 .
Tea waste is an intriguing adsorbent due to the prevalence of functional groups on its surface 13,15 . These functional groups can be fine-tuned using chemical treatments according to the intended use, including the adsorptive removal of Cr(VI). Tea is one of the most consumed beverages worldwide. With a 4.9% annual growth rate, tea production is estimated to reach 8.52 million tonnes by the year 2025 16 . Black tea in particular constitutes approximately 87% of all the tea consumed in the US and between 75 and 80% of worldwide consumption 16 , leading to the production of large volumes of TW. This issue can be mitigated by utilizing black TW as an adsorbent material. The utilization of TW as an adsorbent not only contributes to circular economies and low environmental    www.nature.com/scientificreports/ using an Ultraviolet-Visible light spectrophotometer (Genesys 10S Vis by Thermo Scientific) and the following equation: where C i and C f are the initial and final concentrations of Cr(VI), respectively. The experimentally obtained equilibrium data were fitted to adsorption isotherms such as Langmuir, Freundlich, Temkin, and Dubinin-Radushkevich (D-R) models. The kinetics data were evaluated through pseudofirst-order (PFO), pseudo-second-order (PSO), and intraparticle diffusion models. Nonlinear regression analyses were applied for adsorption isotherm models 23 and adsorption kinetics models 24 . Linear regression, while convenient, introduces error propagation and inaccurately estimates model parameters 23 . The model parameters were therefore calculated by nonlinear solving methods using Microsoft Excel Solver. The fittings of the regression models were evaluated to gauge the model fitting accuracy.

Results and discussion
Characterization. The morphology of TW and t-TW was characterized using an SEM, which generates a beam of electrons that interact with the surface of a sample to provide information about the topography and composition of a sample 25,26 . Figure 1a,b depicts SEM images of the surface characteristics of TW and t-TW, respectively. Both images represent a largely smooth surface at the same (× 3000) magnification. There were no observable differences before and after treatment with ascorbic acid, other than a slight increase in surface roughness in the t-TW. However, EDX analysis revealed a slight decrease in oxygen content from 27.7 in TW to 25.5% in t-TW. This may be due to reduction of some oxygen-rich functional groups 27 . As previous studies have suggested the biosorption of heavy metals by carboxyl and amine groups present on similar materials 13,28 , FTIR analysis was performed, as shown in Fig. 1c.
The TW and t-TW comprise numerous functional groups that can adsorb Cr(VI) 13,25,[28][29][30] . It has been reported that the absorbance at certain wavelengths varied by magnitude and/or shifted following ascorbic acid  25,29,30 . The antioxidant activity of black tea was enhanced by ascorbic acid 31 . This can be attributed to the lessening of carbonyl, epoxy, aromatic ethers, carboxyl, and hydroxyl functional groups due to partial reduction of t-TW by ascorbic acid as reported previously 20,32 . These variabilities in functional groups lead to the comparatively enhanced adsorption of Cr(VI) from water by t-TW, as shown in Fig. 2. The experimentally observed equilibrium adsorption capacity of t-TW was up to 20 percent greater than that of TW at identical shaking speeds, temperatures, pH values and water quality. The observed maximum experimental adsorption capacities of TW and t-TW were 193.45 mg g −1 and 231.95 mg g −1 , respectively. These values are comparable to those reported for mixed tea waste 13 and tea-waste biochar 14 . These results warranted further investigation into modeling and optimization of Cr(VI) adsorption by t-TW.
Model development, validation, and diagnostic analysis. The measured Cr(VI) removal (%) at different pH, initial Cr(VI) concentration, t-TW dosage, and temperature settings are listed in Table 2. The Cr(VI) removal (%) was in the range of 0-93.3%-corresponding to experimental runs 1 and 22, respectively ( Table 2). These two experiments were performed at the same temperature (30 °C) and initial Cr(VI) concentration (50.5 mg/L) but used different adsorbent dosages (0 and 2 t-TW g L −1 ) and pH values (7 and 2). From the experimental results, an empirical model representing the relationship between the operating factors and Cr(VI) removal (%) response was developed: The coefficients in the equation represent the linear, quadratic, and cubic terms of the factors. A negative sign indicates an antagonistic effect, whereas a positive term denotes a synergistic effect of a certain factor (or combination of factors) on Cr(VI) removal (%) 21,33 . The adequacy of the model (Eq. (2)) to represent the experimental data was tested by plotting the experimental values against values predicted by the RSM model. The RSM model exhibited satisfactory approximation of the actual Cr(VI) adsorption removal (%), as demonstrated by the high correlation coefficient (R 2 ) of 0.99 (Fig. 3), implying that 99% of the variations in the results can be attributed to the studied factors 34,35 . In addition, the adjusted correlation coefficient (adj. R 2 = 0.97) was close to the R 2 . An adj. R 2 is usually preferred over R 2 because, unlike R 2 , an adjusted value only increases upon the addition of statistically significant model term(s) 21 . The difference between the adj. R 2 and predicted R 2 was 0.23, which was slightly higher than the desirable range (≤ 0.2) 36 . This may be due to the complexity of the cubic model and suggests that the model should be used with caution when predicting above or below experimentally validated ranges.
Analysis of variance (ANOVA) was performed to statistically validate the model, as shown in Table 3. The model and all its terms (except "D") were statistically significant at a > 95% confidence level, indicated by p values below 0.05. The linear term D, representing the effect of temperature on Cr(VI) reduction, was significant only at an 85% confidence level. Despite its statistically low significance, it was retained to maintain the model's www.nature.com/scientificreports/ hierarchy due to its interaction with the statistically significant terms (AD and A 2 D) 37 . The adequate precision (signal-to-noise ratio) was 36.56, which is well above the required threshold value of 4. This indicates adequate response signals and the suitability of the model for use in the experimental design space 21,38 . The regression analysis and ANOVA therefore validate the model as an appropriate tool to study the effect of factors on Cr(VI) adsorption removal.

Effects of variables on Cr(VI) adsorption.
To investigate the linear effects of changing the levels of a single factor on the response, one-factor effects plots were generated (Fig. 4). Cr(VI) removal was effected by pH, initial Cr(VI) concentration, adsorbent (t-TW) dosage, or temperature. The red circles represent experimental design points, black lines represent modeled prediction, and turquoise lines represent the least-significantdifference at a 95% confidence level. Figure 4a shows that Cr(VI) removal decreased with an increase in pH from 4.5 to 9.5 (level ± 1 from Table 1). At a pH of 4.5, approximately 40% Cr(VI) removal was observed, and this decreased to 10 ± 2% as the pH approached neutrality. The trend continued at basic pH conditions until no removal was observed at pH 8.5. The decrease in Cr(VI) adsorption with an increase in pH has been reported in activated carbons 39 , nanocomposites 40 , and organic adsorbents 41 such as ours. The pH of the solution affects the Experimental conditions are provided in Table 2. ) ions. Because the free energy of adsorption of divalent ions is higher than that of monovalent ions, the divalent ions adsorbed less frequently on t-TW 40 . The surface of the t-TW was also deprotonated with an increase in the pH of the surrounding aqueous solution, leading to decreased positive surface charges. Consequently, the negatively charged chromate ions experienced electrostatic repulsion at a higher pH, which resulted in decreased adsorption of chromate ions. Figure 4b depicts the decline in Cr(VI) removal (%) as the initial Cr(VI) concentration increases from 25.5 to 50.5 (mg L −1 ). The trend is similar to that of pH, but less pronounced (a less steep slope) when compared with pH. The decrease in adsorption removal-upon increasing initial Cr(VI) concentrations-can be attributed to the unavailability of sufficient adsorption sites (on t-TW) at higher initial Cr(VI) concentrations 43 . This hypothesis was supported by the increase in Cr(VI) removal with an increase in t-TW dosage, as shown in Fig. 4c, with a nearly linear increase in Cr(VI) adsorption occurring as the t-TW dosage increased. Figure 4d shows an insignificant increase in Cr(VI) removal with an increase in temperature from 20 to 50 °C. A small (0.7%) increase in Cr(VI) removal was observed upon increasing the temperature from 20 to 30 °C, which is difficult to attribute to an increase in mass transfer rate with an increase of temperature 45 . In addition, the term is significant only at an 85% confidence level (Table 3), and such a minor change can be considered inconsequential. To summarize, one-factor-at-a-time plots suggest (i) the greatest impact on Cr(VI) removal was pH followed by initial Cr(VI) Further analysis of the model parameters was performed using three-dimensional response surface plots. An RSM allows for the investigation of the combined effects of factors on response with the aid of surface plots. Surface plots can be generated by varying two variables at a time and observing their effect on the response, while keeping the others constant at a certain level (usually mid-range) 33,46 . Table 3 lists the significant interactions of the terms AB, AC, AD, and BD, and response surfaces were generated to study these interactions. Figure 5 shows the combined effects of pH and initial chromium concentration (AB), pH and adsorbent dosage (AC), pH and temperature (AD), and initial chromium concentration and adsorbent dosage (BC). A decrease in Cr(VI) adsorption removal can be seen with an increase in pH in combination with the initial Cr(VI) concentration (Fig. 5a), t-TW (Fig. 5b), and temperature (Fig. 5c). The pH-dominated effects, such as the one-factor effect of pH (Fig. 4a), can be explained by the prevalence of fewer affinitive chromate ions (at high pH), leading to less-frequent electrostatic interactions with the adsorbent surface, resulting in reduced adsorptive removal of Cr(VI) 39,40 . Figure 5d shows the decrease in adsorptive removal with a decrease in adsorbent dosage and increase in initial Cr(VI) concentrations. This may be due to the unavailability of adsorption sites for Cr(VI) adsorption at lower t-TW dosages, as discussed earlier 39 . To conclude, one-factor plots and response surface graphs establish the most pronounced effect of pH on Cr(VI) removal, which is consistent with earlier similar studies 43,47 . These observations require the optimization of parameters to effectively remove Cr(VI) from water using t-TW in a pH range suitable for drinking water.
Process optimization. The adsorption removal of Cr(VI) was optimized in drinking water pH range (6.5-9.5) using t-TW as an adsorbent. The initial Cr(VI) concentration was fixed at 1 mg L −1 and complete removal was targeted as shown in ramp plots (Fig. 6a). The model predicted 99% removal, thereby limiting the residual concentration of Cr(VI) to 0.01 mg L −1 . The targeted residual Cr(VI) concentration-at optimized conditionswas well below the allowable concentrations recommended by the US EPA (0.1 mg L −1 ) and WHO (0.05 mg L −1 ) 5,6 . Experiments were conducted at prescribed settings and no residual Cr(VI) was detected. A ≥ 99% adsorp- where C e (mg L −1 ) is the equilibrium concentration, q m (mg g −1 ) is the Langmuir maximum adsorption capacity, K L (L mg −1 ) is the Langmuir adsorption constant, K f ([mg g −1 ] [L mg −1 ] 1/n ) is the Freundlich constant, n is the Freundlich exponent, A T (L.mg −1 ) is the Temkin isotherm equilibrium binding constant, b T (J mol −1 ) is the Temkin isotherm constant, q DR (mg g −1 ) is the D-R maximum sorption capacity, K DR (mol 2 kJ −2 ) is the D-R constant related to sorption energy, and ε (= RT ln [1/1 + C e ] ) is the Polanyi potential. Figure 7 shows Cr(VI) adsorption isotherms and the corresponding equilibrium parameters reported in Table 4. The adsorption equilibrium was best described by Temkin > Langmuir > Freundlich > D-R models, based on regression coefficients. The Temkin model assumes uniform distribution of binding energy sites on t-TW surface and a linear decrease in the heat of adsorption of Cr(VI) species as the adsorption progressed 23,48 . Similarly, the Langmuir model also suggests monolayer adsorption 23,49 . The calculated separation factor suggests Langmuir adsorption of Cr(VI) on t-TW was favorable 48 . Nevertheless, Freundlich and D-R fittings were also significant which indicates multilayer adsorption and pore filling due to heterogeneous surfaces 23,48 . Therefore, it is assumed that the adsorption of Cr(VI) on t-TW was largely monolayer, but occasionally multilayer, in nature due to a mixture of uniform and non-uniform surfaces, as shown in SEM micrographs (Fig. 1).
Adsorption kinetics. Adsorption kinetics describe the rate and mechanism of the adsorption process. Figure 8 shows the saturation of t-TW surface with Cr(VI) over time. Adsorption kinetics were rapid for the first 8 h, likely due to the abundance of available adsorption sites for the initial adsorption. Afterward, adsorption of Cr(VI) progressed at a relatively slower rate from 8 to 24 h and reached equilibrium after 2 days. The experimental kinetic data were fitted to the PFO, PSO, and intraparticle models 24 : www.nature.com/scientificreports/ where q t is the adsorption capacity at time t, k 1 (1 h −1 ) is the PFO rate constant, k 2 (g mg −1 h −1 ) is the PSO rate constant, K ip (mg g −1 h −0.5 ) is the intraparticle diffusion rate constant, and C (mg g −1 ) is the intercept of intraparticle diffusion plot. Figure 8 shows PFO, PSO, and intraparticle diffusion kinetic models fitted to experimental data. Their corresponding kinetic parameters are tabulated in Table 4. The PSO kinetic model appears to fit the data reasonably well as evident from a high regression coefficient value of 0.98 25 . Because the PSO model closely predicted the experimental equilibrium adsorption capacity, it was assumed that Cr(VI) adsorption by t-TW was a physisorption phenomenon in which the adsorption rate was proportional to the availability of adsorption sites 24,25 . The intraparticle diffusion model employs an empirical relationship that relates the amount of adsorbate to the square root of time (t 0.5 ), as shown in Eq. (9) 25 . The adsorption of Cr(VI) by t-TW generated two-step multilinear intraparticle diffusion plots (Fig. 8b): step 1 from 0 to 8 h and step 2 from 8 to 120 h. Nearly 60% of Cr(VI) was adsorbed by the t-TW during step 1. Also, the slope of step 1 is steeper than that of step 2, indicating rapid transport of Cr(VI) ions from the bulk to the external surface of t-TW 24,25 . Corresponding parameters of the intraparticle diffusion plots are provided in Table 4. The intraparticle model fits the experimental data reasonably well as evident by high regression coefficients. The intraparticle diffusion model postulates that intraparticle diffusion would be the sole rate-limiting step if the plot of qt versus t 0.5 crosses the origin 24 . The intercept of the second step did not pass from the origin, suggesting that several mechanisms are involved and intraparticle diffusion is not the sole rate-limiting step 25 .
Comparison with other adsorbents. The adsorption capacity of t-TW compared with other adsorbent materials reported in the literature is presented in Table 5. The adsorption capacity of t-TW is 232 mg g −1 , which is significantly higher than several low-cost and some advanced adsorbents. Moreover, ascorbic acid treatment to synthesize t-TW is a simple process that requires no pre-treatment of the adsorbent surface. The pre-treatment step is often an energy-intensive process that requires the use of hazardous and corrosive chemicals, such  www.nature.com/scientificreports/ as persulfates, mineral acids, peroxides, and alkalis 14,50 . Ascorbic acid-mediated t-TW synthesis can therefore be classified as a green route toward material functionalization.

Conclusions
The utilization of tea waste (TW) as an adsorbent material can help reduce solid waste disposal problems, thereby contributing to sustainable consumption and production objective. In this study, treated tea waste (t-TW) was prepared from spent black TW by modifying it with ascorbic acid; an environmentally friendly, non-toxic, and inexpensive functionalizing agent. The experimental adsorption capacity of t-TW was close to 232 mg g −1 , one of the highest among agricultural waste-based adsorbents. The synthesized t-TW was investigated for toxic Cr(VI) removal from aqueous systems using a statistical experimental design and an RSM. The empirical model was developed and statistically validated to describe the effect of pH (2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12), initial Cr(VI) concentration (1-100 mg L −1 ), adsorbent dosage (0-4 g L −1 ), and temperature (10-50 °C) on adsorption removal of Cr(VI) from aqueous systems. The adsorption removal of Cr(VI) was chiefly regulated by the pH of the solution. The RSM model  www.nature.com/scientificreports/ was used to predict (and later experimentally verify) ≥ 99% removal of Cr(VI) from water at optimized conditions; pH = 9; initial Cr(VI) concentration = 1 mg L −1 ; adsorbent dosage = 4 g L −1 ; and temperature = 40 °C. The residual Cr(VI) concentrations after treatment, at optimized conditions, comply with US EPA and WHO regulatory requirements. The adsorption equilibrium data were best fitted to Temkin and Langmuir isotherms, indicating monolayer adsorption on heterogeneous surface. The kinetics were adequately described by PSO and intraparticle diffusion models. The adsorption of Cr(VI) was controlled by intraparticle diffusion on the t-TW surface. The results indicate that t-TW is a promising candidate for the adsorptive removal of heavy metals from aqueous systems.

Data availability
The datasets used and/or analyzed during the current study available from the corresponding author on reasonable request.