Abstract
Introduction
The rapid industrialization and urbanization of our cities have resulted in the discharge of high levels of toxic heavy metals such as chromium, lead, mercury, cadmium, and cobalt into the mainstreams of our wastewater systems. These metals tend to possess greater stability and can cause a detrimental impact on our ecosystem as well as our public health once disposed untreated into our environment (Ciopec et al., 2012; Wang and Chen, 2006).
Chromium (Cr) is one of the most naturally abundant water contaminants. The latter exists in a series of oxidation states from −2 to +6 valence electrons; the most important stable states are 0 (element metal), +3 (trivalent), and +6 (hexavalent). Cr3+ and Cr6+ are released into the environment from stationary point sources resulting from human activities. The metal can cause acute and chronic adverse effects in warm-blooded organisms. Most investigators agree that chromium probably exists in biological species in its trivalent state; the main human exposure of Cr(III) comes from diet (Khezami and Capart, 2005; Nabi et al., 2011).
Hexavalent chromium is present in the effluents produced from electroplating, leather tanning, cement, mining, dyeing, fertilizer, and photography industries and can result in severe environmental and public health problems (Demirbas et al., 2004). In general, Cr(VI) concentrations in industrial wastewater range from 0.5 to 270 mg/l; effluents from tannery factories can contain 1300–2500 mg/l of Cr(VI) (Liu et al., 2006) while its tolerance limit in surface wastewater as current recommended by USEPA and the European Union is below 0.05 mg/l. The total concentration of chromium, including Cr(III), Cr(VI) and other forms is usually regulated to values below 2 mg/l (Baral and Engelken, 2002; Park et al., 2008).
There exists many methods in literature which can remove metal ion pollutants from aqueous solutions, and such approaches can be in the form of physical, chemical, and/or biological techniques (Sahinkaya et al., 2012). The traditional physicochemical methods used for (Cr) removal including, but are not limited to chemical precipitation (Monser and Adhoum, 2002), oxidation or reduction (Sedlak and Chan, 1997), ion exchange (Yang et al., 2014), electrochemical treatment (Giri et al., 2012), membrane technology (Hafez et al., 2002), evaporation recovery (Tiravanti et al., 1997), and adsorption onto activated carbon (Deveci and Kar, 2013; Suksabye and Thiravetyan, 2012). Adsorption plays an important role in the improvement of water quality; generally, activated carbon can be used to adsorb metals. The utilization of adsorption methods in this area of research has attracted the attention of many scientists from around the world; however, the process cannot pay much attention but can be both technically and economically challenging in terms of time and costs associated with developing a custom-made methodology for each unique contaminated aqueous solution. The high specific surface area, the microporous character, and the surface chemical nature of activated carbons made them suitable for examination as potential adsorbents for the removal of heavy metals from industrial wastewater (Dobrowolski and Stefaniak, 2000; Kadirvelu and Namasivayam, 2003). In spite of their advantages, they also show many shortcomings such as high preparation cost, reactivation resulting from adsorption saturation, and selectivity challenges. Recently, much attention has been drawn from scientists toward the utilization of biomaterials, which are by-products or wastes derived from large-scale agricultural operations, for the removal of Cr(VI) via synthesis of activated carbon. Among these, less expensive, nonconventional adsorbents, such as apple waste, peanut hull carbon, agricultural wastes, rice husk and straw (Bishnoi et al., 2004; Hsu et al., 2009); hazelnut shell, coconut shell (Babel and Kurniawan, 2004); cornelian cherry, apricot stone, almond shells (Demirbas et al., 2004);
The aim of this research work is to valorize
Experimental
Chemicals
In all experiments, distilled water was used for preparation. Potassium dichromate (K2Cr2O7), hydrochloric acid (HCl), sodium hydroxide (NaOH), and rubidium carbonate (Rb2 CO3) were purchased from Sigma Aldrich. A stock solution containing chromium 1 g/l was prepared by dissolving 2.829 g of potassium dichromate in 1000 ml of bidistilled water. The desired concentrations were obtained by diluting the stock solution with distilled water to obtain concentrations ranging from 50 to 500 mg/l.
Preparation of activated carbon
Charaterization of solid adsorbent
Global chemical analysis
The chemical composition of the biomass
BET surface area and pore distribution
To identify the porous texture of our activated carbon, N2 adsorption–desorption technique was sought using Micrometrics apparatus (ASAP 2010) at −196°C. The surface area of our activated carbon was calculated using Brunauer–Emmett–Teller (BET) equation within the pressure range 0.05–0.35. The micropore volume, area, and external surface area were determined using t-plot method. The total pore volume, calculated from a liquid volume of adsorbate adsorbed at a relative pressure of
Scanning electron microscopy (SEM)
The particle size and morphological feature of activated carbon before and after adsorption of a Cr(VI) were analyzed using SEM QUANTA 250 with an acceleration voltage of 20.00 kV and a working distance of 10.0 mm. The samples were deposited on a disk holder and protected by a carbon tape for it to be fixed; photography was performed using an Everhart–Thornley detector with high vacuum mode and/or circular back scatter detector for contrast. The surface elemental analysis of the activated carbon was carried out using energy dispersed X-ray spectroscopy. The spectra were recorded using EDAX AMATEK equipment.
Fourier transform infrared (FTIR) analysis
The surface chemical characteristics of the biomass and the activated carbon were characterized using Bruker Alpha FTIR spectrometer; the samples were prepared using the KBr pellet technique by mixing a small amount of an activated carbon with 100 mg of dried, spectroscopic grade, KBr which was previously grinded and pressed into a pellet by applying a pressure of 1200 lbf/in2 for about 5 min (the concentration of the sample in KBr should be in the range of 1%); the transparent pellet was dried in an oven at 30°C overnight and then inserted into the instrument; then, the spectra were recorded over the range 4000–400 cm−1 with a spectral resolution of 2 cm−1 and a total number of 64 scans.
Ultraviolet–visible (UV–visible) spectroscopy analysis
The remaining concentration of Cr(VI) ions in solution was measured using UV–visible spectroscopy after reaction with 1.5-diphenylcarbazide; the procedure was performed following a standard method introduced by Gilcreas et al. (1965) using Varian Cary 50 Scan UV–Visible spectrophotometer at wavelength of λ = 540 nm.
pH point of zero charge measurements “pHpzc”
The activated carbon pH point of zero charge (
Thermogravimetric analysis (TGA)
TGA consists of measuring the mass variation of a sample as a function of temperature. It was carried out on an SDT Q600 thermo balance (TA Instruments) under controlled atmosphere (nitrogen) to avoid the combustion of activated carbon. The activated carbon to be analyzed (10–15 mg) is placed in the sample crucible while an empty crucible is placed on the reference arm of the scale. The furnace begins to heat; the temperature rise can be carried out from room temperature to 1500°C at a ramp of 10°C/min.
Batch adsorption study
Kinetic study
In order to study the adsorption of Cr(VI) ions onto activated carbon and the effect of diverse parameters on the adsorption kinetic, an experimental series have been performed on a mechanical shaker equipped with a thermostatic water bath set between 180 and 200 blow per minute (bpm), using a 250 ml conical flask. A series of adsorption experiments were performed.
The first series was to investigate the effect of contact time and initial solution pH, varying from 1 to 6, by adding (0.1 N) of HCl and/or NaOH; the adsorption kinetic of Cr(VI) ions was studied at an initial Cr(VI) concentration equal to 100 mg/l, adsorbent dose of 1 g/l, temperature of 30°C, and a contact time ranging from 5 to 1440 min. The second series of experiments was to study the adsorption kinetic under the effect of temperature ranging between 20, 30, and 40°C and adsorbent dose of 0.5, 1, 2, and 3 g/l at an optimized pH value. The third experimental series was used to study the batch adsorption under optimized conditions (T= 30°C, m = 1 g/l, and pH =2) with varied initial Cr(VI) concentrations in the range of 50–500 mg/l and to identify the effect of initial Cr(VI) concentration.
For each experiment, a known volume of solution was collected, centrifuged at 3000 r/min, assayed and analyzed calorimetrically with 1.5-diphenylcarbazide using UV–Visible light spectroscopy in order to measure the remaining concentration of Cr(VI) ions in solution. The metal adsorption efficiency of the adsorbent was determined by adsorption capacity as the amount of metal ions of Cr(VI) adsorbed per gram of adsorbent (mg/g).
Adsorption capacity and removal percentage (
Adsorption kinetic models
Pseudo-first-order and pseudo-second-order kinetic models
Adsorption kinetics was investigated to understand the adsorption dynamic of metal ions onto the adsorbent. Adsorption kinetic is expressed as the solute removal rate that controls the residence time of the adsorbate at the solid–solution interface (Pandey et al., 2010). So, in order to examine the adsorption mechanism process such as mass transfer and chemical reaction, suitable kinetic models were needed to describe our data. In this study, adsorption kinetic data, including all parameters, were modeled using pseudo-first-order and pseudo-second-order kinetic models; this was envisaged in order to investigate the mechanism and the adsorption process of hexavalent chromium ions onto our activated carbon. The nonlinear pseudo-first-order equation (equation (3)), previously determined by Lagergren (1898), is given as follows
The pseudo-second-order equation (equation(4)) (Ho and McKay, 1999) can be formulated as follows
ELOVICH kinetic model
The existence of various chemical groups on the adsorbent has led us to examine the applicability of a model adapted to surfaces such as the Elovich model. Indeed Cr(VI) ions may react on the surface of the adsorbent; this prompts the possibility of a chemical reaction used to control the adsorption mechanism (Tseng and Tseng, 2006). The Elovich kinetic model, represented by equation (5), was applied to each system
where
Adsorption isotherm models
In order to study the mechanism of adsorption and to interpret the relationship between the concentration of the pollutant (adsorbate) and the adsorption capacity of the adsorbent (Naushad, 2014; Wang et al., 2010) at constant temperature, several isotherm models are used to identify the design process (Smith, 1981) and this can provide more information about the capacity of adsorbent. This is usually characterized by the presence of constant values that can affect the nature of the adsorbate–adsorbent surface interaction; we also use this to distinguish the adsorptive capacities of the adsorbent for different pollutants.
In this study, the equilibrium data for the adsorption of Cr(VI) ions onto activated carbon are fitted by seven isotherm models; this is to interpret the equilibrium state for single ion adsorption experiments.
Langmuir
The theoretical basis of Langmuir equation relies on the assumption that there is a finite number of binding sites having a uniform energy and are homogeneously distributed over the adsorbent surface of activated carbon, and there is no interaction between the adsorbed molecules; a saturated layer is formed by the adsorbed molecules and maximum adsorption occurs, so it is assumed that adsorption is of a monolayer type. The mathematical description of the nonlinear equation (equation (6)) is expressed as follows
Freundlich
The Freundlich isotherm was originally empirical in nature, but was interpreted as the adsorption to heterogeneous surfaces or surfaces supporting sites with various affinities. It is assumed that the stronger binding sites are initially occupied. It incorporates two constants:
Temkin
The Temkin model (Temkin, 1941) is based on the assumption that the heat of adsorption, due to interactions with the adsorbate, decreases linearly over time primarily owing to a decrease in adsorbent–adsorbate interactions during gas-phase adsorption. It is an application of the Gibbs relation for adsorbents whose surfaces are considered energetically homogeneous. Several authors proposed using this model in liquid phase; equation (8) is presented as follows
Dubinin–Raduskovich
Another equation used in the analysis of isotherms was proposed by Dubinin and Raduskovich; this model does not assume the presence of homogeneous surfaces or a constant adsorption potential like those in the Langmuir model. The theory of filling the volume of micropores is based on the fact that the adsorption potential is variable and that the free enthalpy of adsorption is connected by the degree of pore filling. The isotherm is expressed by equation (9)
The plot of
Redlich–Peterson
This is a three-parameter mono-solute model widely used and cited in literature because of its application for a range of concentrations. It is an empirical model combining the parameters of the Langmuir and Freundlich equations. It has been widely applied to gas-phase adsorption, and by analogy, its expression in liquid phase is given by equation (11)
Under certain conditions, in particular for high solute concentrations in the liquid phase, Redlich–Peterson expression becomes comparable to that of Freundlich
Tóth
Tóth (2000) modified the Langmuir equation to reduce the experimental error; it is also a model very often cited and used. It was established for gas-phase adsorption (1962) from the Langmuir isotherm, but also considers that the surface of the adsorbent is not energetically homogeneous; it is therefore of particular interest. The application of the latter is better suited to BET isothermal multilayer adsorption, which is a specific type of Langmuir isotherm and has a very restrictive validity (Khan et al., 1997) in liquid phases; it is generally used as an application of the Langmuir model, close to the empirical model of Redlich–Peterson. The Tóth model is represented by equation (12)
The Tóth model is reduced to the Langmuir model when the parameter
Sips
This three-parameter model is known as the identifier of the main problems associated with the continuous increase in the adsorbent amount with increasing concentrations in the Freundlich equation; Sips (1948) proposed an equation similar to the equation of Freundlich. However, the model has limitations in cases where the concentration is sufficiently high. This isotherm is given by equation (13)
Results and discussion
Characterization of the “ZRC-AC”
Global chemical analysis
Results of the biochemical analysis and the elemental analysis of the biomass were obtained and are summarized in Table 1; we note that the extracts represent 7.7% of the jujube cores; the carbon content is almost the same as that of oxygen in the raw material; this is due to the significant presence of holocellulose (hemicelluloses and cellulose), on the one hand, and lignin, on the other hand; the nitrogen content in the jujube cores is low; the data also show that the composition of these cores approximates that of wood. These results are confirmed by the visual aspects of jujube cores. Thus, it can be concluded that this material is a lignocellulosic biomass (Benturki, 2008).
Approximation of the main constituents of ZRC-AC.
ZRC-AC: Z
XRF analysis of the material, summarized in Table 1, revealed that the components of the biomass are minerals in the form of oxides; for activated carbon synthesized from this lignocellulosic material, the principal inorganic compounds are oxides of silicon, magnesium, calcium, iron, aluminum, and sodium. This is confirmed by the rate of ash, found between 1 and 5%, i.e. 4.83% for the biomass and 4.79% for the activated carbon. The high content of silicon and calcium present in the biomass is owing to assimilation from the ground.
Rubidium carbonate was used for the activation of the raw biomass; one of the advantages associated with the utilization of the latter reagent is its ability to remove inorganic impurities present in the biomass by dissolution as well as its stability and nonhazardous characteristics; it is clear from Table 1 that the concentration of impurities in the precursor material such as Si and Mg decreased after treatment with rubidium carbonate.
N2 adsorption–desorption
Figure 1 presents the nitrogen adsorption–desorption isotherm of activated carbon at 77 K; adsorption data were obtained with a relative pressure

Adsorption/desorption isotherm of N2 at 77 K on ZRC-AC.

Pore size distribution of ZRC-AC.
Textural characteristics of the prepared
SEM
SEM is a very useful tool to examine the surface structure and morphological feature of biomass and activated carbon. Figure 3 displays SEM images of the surface structure and morphology of our materials, so the effect of activation and carbonization on the pore distribution and morphology of activated carbon was clearly demonstrated while significant differences in surface morphologies of our samples were also observed.

SEM micrographs of ZRC-AC.
Figure 3 illustrates the presence of a large number of pores on the surface of our materials; the latter products tend to possess porous, rough surfaces, with distinct walls resulting from subjecting the material to chemical and thermal activation processes. The creation of micro and mesopores was the result of the volatilization of some materials such as lignin and other organic compounds present in
FTIR spectroscopy
Surface chemistry is the main parameter for determining the adsorption capacity of activated carbon; the prepared activated carbon had a high content of carbon and a low content of oxygen. Functional groups on the activated carbon are determined by the pH of the activated carbon (

FTIR spectra of ZRC-AC (a) and the Cr(VI)-loaded ZRC-AC, Cr(VI) (b).

FTIR spectra of “ZRC-AC” (a) before adsorption and (b) after adsorption of hexavalent chromium.
TGA
The protocol of TGA is detailed as above. These measurements were made under nitrogen atmosphere to avoid combustion of the activated carbon. The corresponding thermograms are shown in Figure 6.

Thermogravimetric and derived thermogravimetric spectra TG/DTG of ZRC-AC.
A first loss of mass is observed at about 100°C, which must correspond to the loss of moisture content of the activated carbon (53.89%); this quantity of water or small adsorbed molecules is surely related to their higher surface area. From this temperature, the mass slope becomes relatively high; the mass loss at moderate temperatures corresponds to the decomposition of carboxylic groups (150–400°C) and lactones (350–600°C). This coincides with the presence of cellulose at 300°C as shown in the figure (deriv. weight (%/°C)); however, the increased mass loss starting at 600°C, as well as the presence of curves of the derived weight as a function of temperature at 650 and 900°C, correspond well to the presence of phenols, carbonyls, and basic groups. So, it can be observed that the mass slope is very high which can be associated with the decomposition of weak acids to CO and CO2 gas (Driel et al., 1983; Zielke et al., 1996).
Effect of batch adsorption parameters
Effect of contact time and initial pH of solution
pH is one of the most important environmental factor used to determine the adsorption of heavy metal ions; the value strongly influences the properties of both adsorbates and adsorbents such as the ionic state of functional groups present on the adsorbent as well as the chemical properties of the studied metal in solution (Mohanty et al., 2006); for this reason, the pH affects not only the degree of ionization and specifications of the adsorbate, but also the surface charge of the adsorbent during reaction (Babel and Kurniawan, 2004), so the effect of pH directly impacts the electrostatic interactions between the adsorbate and adsorbent’s surface. In order to study the effect of pH on adsorption of Cr(VI) ions by “ZRC-AC,” a series of kinetic experiments for each value of pH (1–6) were studied at constant Cr(VI) concentration (100 mg/l) and “ZRC-AC” (1 g/l). The experiments were performed in a conical flask (250 ml) and placed in a mechanical shaker equipped with a thermostatic water bath set between 180 and 200 bpm at 30°C. The results are illustrated in Figure 7.

Effect of (a) contact time and initial solution pH, (b) of adsorbent dose, (c) temperature on Cr(VI) removal percent by ZRC-AC (Cr(VI) concentration= 100 mg/l, adsorbent dose = 1 g/l, agitation rate, 200 bpm and T = 30°C for (a) and (b)).
Figure 7(a) shows the effect of solution pH on the removal percentage of Cr(VI) following kinetic adsorption; the amount of adsorbed chromium (
We can observe from Figure 8 that decreasing the pH from 6 to 2 leads to an increase in adsorption from 27.2 to 62.08 mg/g, so we can conclude that pH = 2 is the best optimum pH value for the highest removal efficiency or adsorption of chromium ions on activated carbon; although previous works by other scientists such as those of Garg et al. (2007), Kiran et al. (2007), and Malkoç et al. (2006) used different adsorbents, they also found that pH =2 was an optimum pH value for the maximum adsorption of Cr(VI) ions; this process is well observed in acidic media. Similar results were observed by El-Shafey (2005) who suggested the use of modified rice husk as adsorbent for the removal of chromium ions from wastewater. Our results are also in agreement with previous studies by Liu et al. (2014) and Karthikeyan et al. (2005); the former study affirmed that the adsorption phenomenon, as a function of pH, is dependent on (i) Cr(VI) species, (ii) their solubility in solution, and (iii) the overall surface charge of the activated carbon (Gueye et al., 2014).

Determination of
Different forms of hexavalent chromium Cr(VI) exist in aqueous solutions, for example, CrO42−, HCrO4−, and Cr2O72−; the stability of Cr(VI) ions is dependent on pH of solution. In pH ranging from 2 to 6, the predominant form of Cr(VI) ions is those mentioned earlier. It is well known that the dominant form of Cr(VI) at pH =2 is HCrO4−, so,
When the pH of solution is less than At pH = 1, although the medium is acidic, a small rate of elimination has been noticed; at such pH, more protons are available which can promote the reduction of Cr(VI) to Cr(III). The cationic ions interact with the protonated surface of activated carbon via an electrostatic repulsion phenomenon as a result of competition between protons, Cr(III) species, and the adsorption surface active sites (Liu et al., 2014). At pH = 2, the dominant form of chromium is HCrO4−, so, at lower pH values, a large number of H+ ions exists in the solution medium; as a result, the surface protonation of activated carbon leads to the formation of positively charged sites. These protons interact with chromium atoms by an electrostatic attraction phenomenon so that HCrO4− is adsorbed on carbon thus causing an increase in chromium adsorption. At 2>pH>6, the gradual decrease in the rate of adsorption is due to the coexistence of Cr2O72− and CrO42− with HCrO4− in the solution medium; thus, causing competition on the adsorption sites. Furthermore, similar results have also been reported by other investigators (Rao et al., 2002; Ucum et al., 2002).
The decrease in chromium adsorption resulting from the increase in pH of solution can be explained by the abundance of OH− ions in solution which in turn can compete with the chromate and hydrogen chromate ions for adsorption; as a result, an electrostatic repulsion phenomenon takes place. The electrostatic interactions can give rise to chemisorptions as explained by equations (14) to (16) (Liu et al., 2014). The theoretical distribution of the predominant chemical species of Cr(VI) is presented in Figure 9(a) (Barrera-Diaz et al., 2012)

Pourbaix diagram for Cr chemical species in aqueous solution ([CrO42−] = 2.00 mM, I= 0.005 M, and T= 25°C).
Effect of contact time and adsorbent dose of activated carbon on the adsorption of hexavalent chromium
The effect of adsorbent dosage on Cr(VI) adsorption was investigated by varying the amount of activated carbon from 0.5 to 3 g/l. Figure 7(b) illustrates the variation of removal percentage of Cr(VI) at different adsorbent doses; generally, experimental data showed that the removal percentage of Cr(VI) increased from 31.6 to 64% at an initial Cr(VI) concentration of 100 mg/l, while the adsorbent mass increased from 0.5 to 3 g/l. This may be due to an increase in the availability of active sites when there is more amount of adsorbent dose. However, since there were no large differences observed between the adsorption percentage of Cr(VI) at adsorbent concentration of 3 and 1 g/l, we decided to take into account the most economical approach where it was considered that the adsorbent dose of 1 g/l is an optimum dose for our studies.
Effect of temperature on adsorption of Cr(VI) onto Z. jujube rubidium carbonate activated carbon
Figure 7(c) illustrates that the increase in diffusion rate of Cr(VI) ions during the process of external mass transport with respect to temperature (Meena et al., 2008) favors an increase in removal percentage from 46 to 74.4%. This phenomenon could be explained by the dispersion of Cr(VI) ions and the increase in the number of adsorption sites resulting from the rupture of the internal bonds near the surface sites; however, the decrease in removal percentage at low temperature can be attributed to the low kinetic energy of Cr(VI) ions heading toward the active sites of the adsorbent, consequently, this leads to ion agglomeration and thereby minimizing the interaction between the adsorbate and the active sites. This is primarily due to the microporous nature of the activated carbon.

Variation amount of metal adsorbed per unit mass and removal percentage of Cr(VI) as a function of adsorbent dose at different temperatures (20, 30, and 40°C) (Cr(VI) concentration= 100 mg/l and agitation rate of 200 bpm).
Modeling of batch adsorption kinetic data
All kinetic experimental data were fitted by pseudo-first-order, pseudo-second-order, and Elovich models according to the equations cited above; all plots are shown in Figures 11 and 12. The results and kinetic parameters including first-order rate constant

Adsorption of chromium as a function of time (a) at varied solutions pH, (b) at varied adsorbent dose, and (c) at varied temperatures for the kinetic pseudo-first-order model and (d), (e), (f) for the kinetic pseudo-second-order model (chromium concentration = 100 mg/l, stirring speed = 200 r/min).

Adsorption of chromium as a function of time (a) at varied solutions pH, (b) at varied adsorbent dose, and (c) at varied temperatures for the kinetic Elovich model (chromium concentration = 100 mg/l, stirring speed = 200 r/min) Pseudo-first-order, pseudo-second-order, and Elovich models rate constants for pH values and adsorbent doses.
Pseudo-first-order, pseudo-second-order, and Elovich parameters.
For the Elovich kinetic model, constants
Modeling of batch adsorption isotherm data
The aim of this work is to find several models that can be used to describe the experimental data obtained from the adsorption process; for this reason, the equilibrium data were modeled with two-parameter equations by applying the concept of four models (Langmuir, Freundlich, Temkin, and Dubinin–Raduskovich), and three-parameter equations, by applying the concept of three models (Redlich–Peterson, Tóth, and Sips). These calculations are performed in order to find the model that can best describe, with precision, the experimental results of our adsorption process, also to compare the theoretical adsorption isotherms with the experimental ones; these protocols shall also provide us with more insights regarding the behavior of chromium in solution. In order to compare models, several parameters were taken into account, including the correlation coefficient (
where
Two-parameter models
Langmuir isotherm
The fitting results and the Langmuir constant
Values showing the constants of the two- and the three-parameter models and correlation coefficients.
APE: average percentage error.
The second information that can be extracted from this model was the favorable adsorption nature of our adsorbate material; this was previously described by Hall et al. (1966) whereby
Temkin isotherm
The adsorption data of Cr(VI) onto activated carbon were analyzed using Temkin isotherm model. The value of surface coverage θ for all three temperatures was calculated using the theoretical maximum adsorption capacity (theoretical
The parameters of Temkin model are regrouped in Table 4; the value of θ is higher than 0.68 for all three temperatures; however, the lower correlation coefficient obtained, in conjunction with the presence of a higher APE, makes the Temkin isotherm not fit to adequately describe the adsorption isotherm of Cr(VI) onto activated carbon; the mean values of the APE at 20, 30, and 40°C are 4.57, 9.68, and 6.55%, respectively.
Dubinin–Raduskovich isotherm
The high value of correlation coefficient (
Three-parameter models
The three-parameter equations of Redlich–Peterson, Sips, and Tóth models were tested in our study for the purpose of modeling the equilibrium adsorption data. The values of parameters obtained using nonlinear fitting analyses are regrouped in Table 4.
The Tóth model fits well with the adsorption isotherm of hexavalent chromium at different temperatures; the correlation coefficient is also good (
The experimental results of our adsorption isotherm were also fitted using the Redlich–Peterson model; the results are summarized in Table 4. The correlation coefficient and APE (3.65%) provide a satisfactory result in terms of data fitting.
When comparing two-parameter models with three-parameter models, the Tóth model stands out; this is due to the lower APE value (4%). The two-parameter models, i.e. Dubinin–Raduskovich, Langmuir, and Freundlich, are better than the Sips model; therefore, the following trend can be used to summarize the best models used to describe the adsorption equilibrium isotherm of Cr(VI) onto activated carbon
Tóth > Dubinin–Raduskovich > Redlich–Peterson > Langmuir > Sips > Temkin> Freundlich
In summary, the importance of our work is to study and compare as many isotherms as possible in order to get as much information about the nature of the adsorption process of Cr(VI) onto our activated carbon. It is also apparent that the three-parameter models are better used to explain the adsorption process when compared to two-parameter models; this observation has been previously described by Hamdaoui and Naffrechoux (2007). Moreover, three-parameter models were developed to address deficiencies associated with the two-parameter models (Khan et al., 1997; Mullah and Robinson, 1996; Ozkaya, 2006; Vijayaraghavan et al., 2006)
A comparison between the maximum adsorption capacity of Cr(VI) ions onto “ZRC-AC” and other adsorbents has been performed and the results are regrouped in Table 5.
Comparison between the adsorption capacities of various activated carbons and our “ZRC-AC” for Cr(VI) removal.
ZRC-AC: Z
Thermodynamic parameters
Thermodynamic parameters such as enthalpy (Δ

Plot of
The thermodynamic values (Δ
Thermodynamic parameters for the adsorption of Cr(VI) ions onto “ZRC-AC” at different temperatures.
ZRC-AC: Z
The importance of temperature in the adsorption of Cr(VI) ions onto activated carbon has been clearly illustrated; hydrogen bonds formed between the solute and solvent at low temperatures can modify the shape and size of the molecules, thus hindering the adsorbate from accessing the micropores of the adsorbent. Such phenomenon was previously observed by Fontecha-Camara et al. (2006), whereby an increase in temperature can result in weakening of hydrogen bonds formed between water molecules as well as between water molecules and the solute and/or adsorbent (Terzyk, 2004) which as a result increases the pore diffusion (Costa et al., 1988; García Araya et al., 2003).
This interpretation can be further strengthened by obtaining detailed information about the kind of functional groups present on the surface; those information were obtained following FTIR analyses of our freshly prepared activated carbon (Figure 4(a) and (b)). Figure 5 shows the FTIR spectrum of freshly activated carbon (Figure 4(a)) superimposed on Cr(VI) adsorbed activated carbon (Figure 4(b)). By comparing both spectra, many changes in absorption bands can be mentioned: (i) The decrease in intensity of O–H and/or N–H stretching vibrations (3446–3438 cm−1) suggests the formation of new interactions between Cr(VI) ions and either the surface O–H and/or NH2 groups. (ii) The change in intensity as well as the shift in C–H bands (2922–2918 cm−1) suggests that the adsorption of Cr(VI) ions onto activated carbon has taken effect. (iii) The decrease in C = C absorption intensity between 1624 and 1593 cm−1 reflects the presence of interactions between the latter group and Cr(VI) ions. (iv) The drop in intensity of C–O stretching vibrations (1122–1042 cm−1) implies the participation of C–O groups in the adsorption phenomenon (Hlihor et al., 2015). From these interpretations, we may be able to conclude that O–H, C–O, and C–H groups constitute the main binding sites for Cr(VI) adsorption. Therefore, increasing temperature leads to an increase in the adsorption capacity of Cr(VI); thus, indicating the endothermic nature of the overall adsorption process (positive Δ
Conclusion
In this study, “ZRC-AC,” prepared from “ZRC-AC” has a medium surface area, basic The adsorption of Cr(VI) by “ZRC-AC” was found to be favorable at pH=2, while the removal efficiency has a proportional relationship with “ZRC-AC” dose; this is unlike other adsorbents whereby the adsorption capacity decreases with an increase in the adsorbent dose. The modeling of kinetic data showed that our adsorption experimental data were in good agreement with a pseudo-second-order model. The better fit obtained with Langmuir isotherm model suggests that the adsorption of Cr(VI) ions onto activated carbon is homogeneous and of monolayer nature; this model appears to provide the best correlation of experimental data for the adsorption of Cr(VI) than the Freundlich isotherm. The highest monolayer adsorption capacity obtained was 196.38 mg/g. The thermodynamic parameters Δ
