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Application of a heterogeneous physical model for the adsorption of Cd2+, Ni2+, Zn2+ and Cu2+ ions on flamboyant pods functionalized with citric acid
Chemical Engineering Journal xxx (xxxx) xxx
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Application of a heterogeneous physical model for the adsorption of Cd2+, Ni2+, Zn2+ and Cu2+ ions on flamboyant pods functionalized with citric acid b, c ´ ´vez-Gonza ´lez b, Hilda Elizabeth Reynel-Avila Fatma Dhaouadi a, Lotfi Sellaoui a, *, Brenda Cha , ˜ oz b, Didilia Ileana Mendoza-Castillo b, c, Adria ´n Bonilla-Petriciolet b, Liliana Lizbeth Diaz-Mun Eder C. Lima d, Juan Carlos Tapia-Picazo b, Abdelmottaleb Ben Lamine a, * a
Laboratory of Quantum and Statistical Physics, LR18ES18, Monastir University, Faculty of Sciences of Monastir, Tunisia Instituto Tecnol´ ogico de Aguascalientes, Aguascalientes, 20256, Mexico c CONACyT, C´ atedras J´ ovenes Investigadores, Ciudad de M´exico, 03940, Mexico d Institute of Chemistry- Federal University of Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil b
A R T I C L E I N F O
A B S T R A C T
Keywords: Adsorption Biomass Heavy metals Heterogeneous physical model
A heterogeneous physical model with two bindings sites (HPMTBS) was successfully used to explain the adsorption of Cd2+, Ni2+, Zn2+, and Cu2+ ions on flamboyant pods functionalized with citric acid. Experimental results and statistical physics modeling showed that carboxylic and phenolic functionalities of this adsorbent played a relevant role for the adsorption of Cd2+, Ni2+, Zn2+, and Cu2+ ions. Calculations performed with HPMTBS suggested that the removal of these cations was a multi-ionic adsorption process at tested operating conditions. This adsorbent was more effective to remove Cd2+, Ni2+, Zn2+ and Cu2+ ions at high solution temperatures thus indicating an endothermic process with adsorption energies ranging from 20.3 to 29.5 kJ/mol, which were associated to physisorption. The total adsorption capacities varied from 0.10 to 0.32, 0.28 to 0.39, 0.19 to 0.25 and 0.20 to 0.31 mmol/g for Cd2+, Ni2+, Zn2+ and Cu2+, respectively. This difference in adsorption capacities could be attributed to the ionic radius of tested adsorbates. This functionalized biomass can be considered as an alternative adsorbent for facing water pollution by heavy metal ions.
1. Introduction Glass, energy and fuel production, tanneries, mining, paper and metal plating industries are among of the major industrial sectors that generate heavy metal-polluted effluents worldwide [1–2]. Heavy metals are pollutants that can persist in the environment for a long period and represent a threat to the ecosystems because of their toxicological effects on living organisms and humans [3].The toxicity caused by heavy metal ions can generate the inhibition of enzyme activity, poisoning, brain problems and even primary cancer in humans. These toxicological ef fects are associated to a chronic exposure via the water consumption with metal concentrations usually in the order of mmol/L [4]. For these reasons, the removal of heavy metals is of great strategic interest to protect the environment and to reduce health risks for population. In this context, there is a wide variety of techniques and methods to solve the problem of water pollution by heavy metal ions. These
methods include chemical precipitation, electrochemical treatment, ion exchange, membrane separation, ultrafiltration, reverse osmosis, elec trocoagulation, adsorption and biological treatment [5–7]. The adsorption has been used to remove inorganic and organic substances from wastewaters and polluted effluents due to its low energy con sumption, simple design, high treatment efficiency and economic feasibility [8–11]. Its separation performance relies on the selection of an adsorbent with a suitable tradeoff between surface chemistry and textural parameters to minimize effectively the concentrations of target adsorbates in the fluid to be treated. Activated carbon, zeolite, clays, graphene oxide and nanomaterials are examples of adsorbents used to reduce the concentration of heavy metal ions in water [12–16]. How ever, some disadvantages of available adsorbents include its production cost and/or a limited adsorption capacity, which could constraint its application in wastewaters treatment at industrial level [2]. These drawbacks have promoted the research and application of abundant and
* Corresponding authors. E-mail addresses: [email protected] (L. Sellaoui), [email protected] (A.B. Lamine). https://doi.org/10.1016/j.cej.2020.127975 Received 10 November 2020; Received in revised form 26 November 2020; Accepted 30 November 2020 Available online 4 December 2020 1385-8947/© 2020 Elsevier B.V. All rights reserved.
Please cite this article as: Fatma Dhaouadi, Chemical Engineering Journal, https://doi.org/10.1016/j.cej.2020.127975
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Fig. 1. Heavy metal adsorption capacities of flamboyant pods functionalized with citric acid.
low cost materials to prepare alternative adsorbents for heavy metal removal, including the development of surface functionalization methods to improve their physicochemical properties and adsorption performances. Biomasses from different sources are an alternative to implement effective adsorption processes for heavy metal removal from water. Several studies have shown that biomasses contain surface functional groups capable of binding and interacting with metal ions dissolved in aqueous solutions [17]. The removal performance of these materials can be improved via the functionalization of its surfaces thus enhancing the adsorption of heavy metal ions [18,19]. In particular, organic acids can be utilized to incorporate surface functionalities on biomasses thus increasing their adsorption capacities for heavy metals. This biomass functionalization is fundamental to enhance the heavy metal adsorption properties thus reducing the operational cost of water treatment for industrial scale up. On the other hand, flamboyant pods are lignocellu losic wastes abundant in several countries, which have been employed as a renewable adsorbent and low-cost precursor to prepare activated carbon for the removal of dyes and heavy metals [20]. Previous studies have reported the physicochemical characterization of this biomass [20], which has shown a promising potential for its use in water depollution. This paper reports the surface functionalization of flamboyant pods with citric acid to improve the removal of Cd2+, Ni2+, Zn2+ and Cu2+ ions and its theoretical modeling via statistical physics to understand the corresponding adsorption mechanism. To achieve this objective, two statistical physics models (homogenous and heterogeneous) have been applied for the analysis of heavy metal adsorption data. These models can provide physicochemical explanations of the adsorption of Cd2+, Ni2+, Zn2+ and Cu2+ ions on this adsorbent. Note that the statistical physics models can retrieve theoretical information of adsorption phe nomenon, which can not be obtained from the application of traditional adsorption models (i.e., Langmuir, Freundlich, Sips). It is convenient to
highlight that statistical physics models outperform classical adsorption equations for the understanding of adsorption phenomenon. For instance, the statistical physics adsorption models can be used to calculate and analyze steric and energetic parameters linked to the corresponding removal mechanism. Therefore, the results of biomass characterization, experimental adsorption data and its statistical physics modelling were integrated to understand and explain the adsorption of heavy metals on this functionalized biomass. 2. Materials and methods 2.1. Functionalization of flamboyant pods using citric acid for heavy metal adsorption Flamboyant pods were used as adsorbent of heavy metals from aqueous solution. First, this biomass was washed with deionized water, dried, ground and sieved to obtain a mean particle size of 0.45 mm. It was functionalized with citric acid to increase its heavy metal adsorption properties. An experimental design Taguchi L16 was applied to deter mine the best conditions for the functionalization of flamboyant pods for heavy metal removal in aqueous solutions. Table S1 of Supporting In formation illustrates this experimental design where 4 variables with 4 levels were explored for biomass functionalization: temperature of biomass treatment with citric acid (30 – 60 ◦ C), sonication time of the mixture biomass – citric acid solution (0.5 – 4 h), ratio of biomass/citric acid volume (1/10 – 1/25 g/mL) and citric acid concentration (0.5 – 2 M). 16 adsorbents were prepared via this experimental design following the next procedure. Specifically, 1 g of biomass was added to a specific volume of citric acid solution according to the conditions of experi mental L16. The mixture biomass + citric acid was sonicated (with an ultrasonic bath model Branson 8800) for a specific time at a particular temperature. Subsequently, the functionalized biomass was decanted from the acidic solution and, then, it was thermally treated at 150 ◦ C for 2
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Fig. 2. Kinetics of heavy metal adsorption using flamboyant pods functionalized with citric acid. Experimental adsorption conditions: pH 5, 30 ◦ C, 4 g/L of adsorbent/solution dosage.
6 h. The final product was washed with deionized water and dried for its application as adsorbent of heavy metal ions. The best conditions for the biomass functionalization with citric acid were identified via a statistical analysis of the experimental design results using the Signal-to-Noise (S/ N) ratio. The goal of this stage was to improve the heavy metal adsorption capacities of biomass treated with citric acid. Details of the experimental design, its statistical analysis using S/N ratio and the identification of best conditions for biomass functionalization are re ported in Supporting Information. The best functionalized biomass was utilized to quantify the kinetics and isotherms of heavy metal adsorption. Experimental adsorption ki netics for tested heavy metals were done at 30 ◦ C and pH 5 using different initial metal concentrations (0.53 – 2.3 mmol/L) and operating times from 0.16 to 24 h. Adsorption rates were calculated with Pseudo first model via a nonlinear regression. Adsorption isotherms were per formed at 25, 30 and 40 ◦ C and pH 5. Note that pH 5 was identified as the best condition for heavy metal removal based on adsorption exper iments performed at pH 3, 4 and 5. Initial concentration of these metals ranged from 0.2 to 5.1 mmol/L to obtain the corresponding adsorption isotherms. Heavy metal solutions were prepared using nitrate salts of Cd2+, Cu2+, Ni2+ and Zn2+ and deionized water. The pH of these
solutions was adjusted using diluted HNO3 and NaOH. All adsorption experiments were conducted using an adsorbent/volume (m/V) ratio of 0.04 g/L under continuous agitation (120 rpm) at batch conditions. Initial (C0) and final (Ce) concentrations of heavy metals in aqueous solution were quantified using a Thermo Scientific (Ice 3000) atomic absorption spectrophotometer equipped with an air-acetylene burner. The adsorbate mass balance allowed to calculate the adsorption capacity (Qe) Qe =
(Co − Ce )V m
(1)
All adsorption experiments were performed by triplicate showing a reproducibility < 5% and the mean adsorption capacity was reported. Analytical grade reagents were used in all experiments, which were purchased from J.T. Baker. 2.2. Physicochemical characterization of flamboyant pods functionalized with citric acid Functional groups of raw and functionalized flamboyant pods were determined using a Thermo Scientific Nicolet iS10 FTIR spectrometer. 3
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Fig. 3. Effect of solution pH on heavy metal adsorption of flamboyant pods functionalized with citric acid. Experimental adsorption conditions: 4 g/L of adsorbent/ solution dosage and 30 ◦ C.
FTIR spectra were measured with attenuated total reflectance technique and recorded in the region of 4000 – 650 cm− 1 with 32 scans and 4 cm− 1 of resolution. Biomass samples loaded with heavy metals were also analyzed to identify the functional groups involved in adsorption. A protocol based on Boehm methodology [21] was utilized to determine the pH of point of zero charge, acidity and basicity of the raw and functionalized biomasses. Briefly, the pH of point of zero charge was quantified using 0.1 M NaCl solutions where their pH was adjusted from 2 to 8. A mixture of 0.15 g of biomass and 50 mL of NaCl solution with a predefined pH was stirred for 48 h at 25 ◦ C and the final pH was measured. The pH of point of zero charge was identified graphically using the curve of final pH versus initial pH.Total acidic sites were estimated with 0.2 g of biomass and 25 mL of 0.025 M NaOH, which were stirred for 48 h at 25 ◦ C. The adsorbent was separated from solu tion and the remaining solution was titrated with 0.025 MHCl. The total basic sites of biomass were quantified in a similar way but using 0.025 M HCl for the mixture and 0.025 M NaOH was employed for the solution titration.
2.3.1. Homogenous physical model with one binding site (HPMOBS) for metal adsorption This model HPMOBS considers that the functionalized biomass contains one type of functional group that is responsible of the heavy metal adsorption thus generating one surface adsorption energy be tween the metallic ions and biomass surface. Then, it was considered that the functional group can capture ‘n’ ions at tested adsorption temperatures (25, 30 and 40 ◦ C) where one adsorption layer is formed. Therefore, the adsorbed monolayer quantity of HPMOBS is provided by the following expression [22]:
2.3. Homogeneous and heterogeneous physical adsorption models to analyze the heavy metal removal mechanism
2.3.2. Heterogeneous physical model with two bindings sites (HPMTBS) for metal adsorption This model assumes that the functionalized biomass contains two types of surface functionalities that are responsible to adsorb the metallic ions where two surface adsorption energies between ions and biomass are present. These two functional groups can capture ‘n1′ and ‘n2′ ions, respectively, at tested adsorption conditions. Note that the formation of one adsorption layer via each type of binding site also occurs. As a result, the adsorption capacity calculated by this model versus the equilibrium concentration is expressed as [22–24]:
nSm ( )n
Qe = 1+
C1/2 Ce
(2)
The parameters of this model are defined as follows: n is the captured number of Cd2+, Ni2+, Zn2+ and Cu2+ ions per the functional group of functionalized biomass, Sm is the density of functional groups of func tionalized biomass and C1/2 is the concentration at half-saturation.
Experimental adsorption isotherms, i.e. Qe = f (Ce), are the results of interactions between the adsorbates (i.e., heavy metal ions) and adsor bent surface (i.e., biomass functional groups). The analysis and char acterization of isotherms represent a key stage to explain the adsorption mechanism. The integration of physical model calculations and experi mental results (adsorption data and characterization) allows to examine and understand the role of biomass functional groups for the adsorption of Cd2+, Ni2+, Zn2+ and Cu2+ ions. Biomass characterization results indicated that more than one functional group could be participating in the adsorption of these heavy metal ions. For simplicity of the theoret ical interpretation, two physical models were used to analyze the adsorption of Cd2+, Ni2+, Zn2+ and Cu2+ ions on citric-functionalized biomass where it was assumed that the adsorption mechanism involved one or two functional groups. These models are described in the next subsections.
Qe =
n1 Sm1 n2 Sm2 ( )n1 + ( )n2 C1 1 + Ce 1 + CC2e
(3)
Six adjustable parameters are included in HPMTBS expression, which are the number of Cd2+, Ni2+, Zn2+ and Cu2+ ions captured per both functional groups (n1 and n2), the densities of these functional groups (Sm1 and Sm2) and the corresponding half-saturation concentra tions (C1 and C2). 4
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Fig. 4. Isotherms of heavy metal adsorption on flamboyant pods functionalized with citric acid. Experimental adsorption conditions: pH 5 and4 g/L of adsorbent/ solution dosage.
These models HPMOBS and HPMTBS were applied to adjust the experimental adsorption isotherms of Cd2+, Ni2+, Zn2+ and Cu2+ ions obtained at different temperatures. This non-linear regression was car ried out with Origin (version 9) and the selection of best fitted model was based on the determination coefficient R2.
biomass functionalization with citric acid using a ratio of biomass/citric acid of 1/10 g/mL and a citric acid concentration of 2 M. This func tionalized biomass was used in all heavy metal adsorption studies. Adsorption kinetic profiles obtained at different initial heavy metal concentrations with the best functionalized biomass and their modeling with the pseudo first order equation are shown in Fig. 2. Adsorption equilibrium was reached at 24 h and 92% of heavy metal adsorption was obtained after 6 h of contact time thus indicating an important role of functional groups of external biomass surface in the metal removal. Adsorption rate constants (k1) obtained from Pseudo first order model ranged from 0.63 to 2.02 h− 1. On the other hand, the effect of solution pH on heavy metal adsorption is reported in Fig. 3. Solution pH impacted the adsorption of heavy metals where the maximum adsorption capacities were obtained at pH 5 with increments of 119% for Cd2+, 40% for Cu2+, 38% for Ni2+ and 30% for Zn2+, respectively, with respect to the adsorbent perfor mance obtained at pH 3. At low pH, the protons of solution competed with metallic cations by the binding sites of the functionalized biomass thus reducing the heavy metal adsorption capacities. Fig. 4 shows the adsorption isotherms of tested heavy metals at different temperatures using the best functionalized biomass at pH 5. All experiments isotherms can be classed as the L type according to Giles
3. Results and discussion 3.1. Identification of the best conditions for the functionalization of flamboyant pods Fig. 1 shows the adsorption capacities obtained with 16 biomass samples functionalized with citric acid according to the tested experi mental design given in Table S1, see Supporting Information. Metal adsorption capacities of these samples ranged from 0.063 to 0.108 mmol/g for Cd+2, 0.084 to 0.273 mmol/g for Cu+2, 0.126 to 0.261 mmol/g for Ni+2 and 0.098 to 0.223 mmol/g for Zn+2. Overall, all tested conditions for biomass functionalization favored the heavy metal adsorption capacities. Data of Table S1 were utilized to identify the best conditions for the functionalization of flamboyant pods via a statistical analysis of S/N ratio. Results of this statistical analysis are also reported in Supporting Information. These conditions were: 50 ◦ C and 2 h for 5
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functionalized with citric acid at different operating conditions are shown in Table S1 of Supporting Information. Note that pHpzc of raw flamboyant pods was 6.24 and strong electrostatic repulsion forces be tween biomass surface (positively charged) and adsorbates were present at pH < pHpzc, thus reducing the metal adsorption capacities. However, the pHpzc of all biomass samples decreased after their functionalization with citric acid, which favored the uptake of all tested heavy metals. The best adsorbent showed a pHpzc of 2.92 that generated an electrostatic attraction that increased the adsorption capacities due to pH > pHpzc [26].The acidic sites of this biomass, which were responsible of heavy metal adsorption, increased up to 53% after citric acid functionalization. These findings confirmed the importance of these functionalities on heavy metal adsorption and the relevance of surface physicochemical treatment to improve the adsorbent performance [26–28]. It is well known that acidic treatment modifies surface properties of lignocellulosic biomasses and FTIR analysis can be used to confirm the increment of oxygen functionalities on adsorbent surface. Therefore, Fig. 5 shows the FTIR results of raw and functionalized biomasses. Spectrum of raw flamboyant pods contains the typical FTIR bands of lignocellulosic biomasses. The stretching vibration of group OH associ ated to phenols and alcohols was observed in the region of 3400 – 3300 cm− 1[26]. The absorption bands around 2920–2840 cm-1were gener ated from aliphatic chains of C–H [29]. The groups related to C = O of carboxylic, ester or aldehyde vibrations can be observed at 1729 and 1620 cm− 1 [26,30]. The absorption bands at 1250–1023 cm− 1 can be associated with the stretching C–O of phenols, alcohols, carboxylic, ethers and esters [27,31]. The vibrations of C = C, C–C and C–H were identified with bands at 1460, 1415 and 1315/890 cm− 1, respectively, which corresponded to aromatic structures [26,30].Spectrum of func tionalized flamboyant pods showed some displacements and increments in the bands located at 3350, 1729, 1620, 1250–890 cm− 1, which are associated to oxygen functionalities. There was also a reduction and shift in the absorption bands at 2840 and 1465 cm− 1. These structural changes can be an indication of the lignocellulose reaction caused by citric acid with the possible development and/or increment of specific functional groups [28]. FTIR spectra of functionalized flamboyant pods after heavy metal adsorption showed an evident reduction in the in tensity of the absorption bands located at 3340, 1620 and 1250–1023 cm− 1 where the oxygen functionalities can be identified. As stated, the oxygen functional groups play a key role in the heavy metal adsorption via organic-metal interactions like complexation, chemisorption, ligand exchange, among others [26,32–34].
Fig. 5. . FTIR spectra of raw (FP) and functionalized (CAFP) flamboyant pods used in heavy metal adsorption.
classification for adsorption in liquid systems [25]. Maximum adsorp tion capacities were obtained at 40 ◦ C with values of 0.14 mmol/g for Cd2+, 0.33 mmol/g for Cu2+, 0.33 mmol/g for Ni2+ and 0.26 mmol/g for Zn2+, respectively. Therefore, the heavy metal adsorption was endo thermic where the adsorption capacities increased up to 30% for Cd2+, 28% for Cu2+, 20% for Ni2+ and 33% for Zn2+ from 25 to 40 ◦ C. This result indicated that thermal agitation facilitated the removal of these heavy metal ions. Note that the adsorption of Ni2+and Cu2+ was higher than those obtained for Zn2+and Cd2+. Surface physicochemical properties of flamboyant pods
3.2. Analysis of heavy metal adsorption mechanism via statistical physics models R2 values obtained from the fitting of experimental adsorption iso therms with two adsorption models are reported in Table 1. HPMTBS showed the highest R2 values for all heavy metals, which varied from 0.988 to 0.999. A simple analysis of HPMTBS parameters as function of temperature indicated that they can be utilized to understand and explain the adsorption mechanism. Therefore, it was concluded that the adsorption of heavy metal ions on functionalized biomass can be better described with this model than a homogeneous model with one binding site. Summarizing, the adjusted parameters of the selected adsorption model are presented in Table 2 and the isotherms adjusted by this model at different adsorption temperatures are represented in the Supporting Information. For a complete analysis of the adsorption mechanism of tested heavy metal ions, all parametersn1, n2, Sm1, Sm2, Qt, C1 and C2 of model HPMTBS were studied as a function of adsorption temperature. Findings and conclusions of this analysis are given in next subsections.
Table 1 Results of isotherm fitting for the adsorption of Cd2+, Ni2+, Zn2+ and Cu2+ on functionalized flamboyant pods at different temperatures. T (◦ C)
HPMOBS
HPMTBS
0.992 0.993 0.996
0.999 0.996 0.996
0.994 0.980 0.993
0.996 0.995 0.998
0.995 0.992 0.994
0.996 0.995 0.999
0.980 0.978 0.984
0.992 0.988 0.998
2+
Cd 25 30 40 Ni2+ 25 30 40 Zn2+ 25 30 40 Cu2+ 25 30 40
3.2.1. Interpretations of the number of captured Cd2+, Ni2+, Zn2+ and Cu2+ ions per functional group(n1 and n2) and their densities (Sm1 and Sm2) Parameters n1 and n2 are related to the two functional groups of 6
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Table 2 Physicochemical parameters obtained from the fitting of experimental adsorption isotherms by the model HPMTBS. T (◦ C)
n1
Sm1(mmol/g)
n2
Sm2(mmol/g)
C1(mmol/L)
C2(mmol/L)
Q1(mmol/g)
Q2(mmol/g)
Qtotal(mmol/g)
6.56 0.66 0.55
0.004 0.08 0.17
2.02 3.39 2.57
0.04 0.02 0.03
0.50 0.40 1.29
0.32 0.39 0.31
0.026 0.05 0.09
0.08 0.07 0.23
0.10 0.12 0.32
4.89 5.42 4.84
0.026 0.02 0.03
1.43 0.68 0.88
0.11 0.40 0.29
0.79 0.83 0.73
1.27 1.62 1.50
0.12 0.10 0.14
0.15 0.27 0.25
0.28 0.37 0.39
5.71 4.92 3.30
0.005 0.008 0.007
1.42 1.54 1.26
0.12 0.12 0.16
1.13 1.08 0.80
0.74 0.39 0.20
0.028 0.039 0.056
0.17 0.18 0.20
0.19 0.22 0.25
4.40 2.87 1.58
0.03 0.06 0.11
3.88 4.39 2.90
0.02 0.03 0.05
0.32 1.13 0.09
1.22 0.16 0.88
0.13 0.17 0.173
0.07 0.13 0.14
0.20 0.30 0.31
2+
Cd 25 30 40 Ni2+ 25 30 40 Zn2+ 25 30 40 Cu2+ 25 30 40
biomass that were involved in the adsorption of Cd2+, Ni2+, Zn2+and Cu2+ ions. Characterization results indicated that carboxylic and phenolic functionalities are those expected to play a relevant role in heavy metal adsorption with flamboyant pods modified with citric acid. Results of HPMTBS indicated that both functional groups contributed in heavy metal adsorption with different degrees depending on the adsorption temperature. For instance, it was observed that: n2 > n1for Cd2+ and n2 > n1 for Cu2+ at 30 and 40 ◦ C, while n1 > n2 for Cd2+ and n1 > n2 for Cu2+ at 25 ◦ C. It was also noted that n1 > n2 for Ni2+ and n1 > n2 for Zn2+ at 25, 30 and 40 ◦ C. This theoretical finding showed that both functionalities contributed to capture Cd2+ and Cu2+ ions, but one surface functionality had a more relevant role for heavy metal adsorp tion. Overall, it can be expected that carboxylic functionalities played the primary role in heavy metal removal using this biomass. Also, these physicochemical parameters can be used to describe the adsorption position of all ions on the functional groups of biomass surface. Note that: a) if n1 and n2 < 0.5, the metallic ions can be captured by two or more functional groups (i.e., there is double or more interactions leading to a multi-interaction adsorption process), b) if 0.5 < n1 and n2 < 1, the ions can be captured by one and two functional groups with two different probabilities (i.e.,simple and double interactions with the adsorption functional group at the same time are feasible), c) if n1 and n2 ≥ 1, the ions can be captured by one functional group (i.e., a multiionic adsorption process) [23,24,35–39]. Overall, the values of n1 and n2 were superior to the unity thus suggesting that these adsorbates were bonded via one adsorbent functional group of tested biomass. The impact of temperature on both parameters is illustrated in Fig. 6. Adsorption temperature has a different impact on the parameters n1 and n2 for tested heavy metals, which could be related to the nature of biomass functional groups and adsorbate physicochemical properties. Thermally speaking, the increment of temperature led to an increment of n1 for Ni2+ and a decrement of n1 for Zn2+, Cu2+ and Cd2+ where this effect was explained in general by the effect of thermal collisions. Both increments and decrements of n with respect to adsorption temperature were observed and these trends could be associated to the change of adsorbates interactions with the biomass functional groups. Sm1 and Sm2 are also two steric parameters that provide information on the number of sites (or functional groups) necessary to adsorb the heavy metal ions at saturation. Fig. 7 reports the trends of these two parameters versus adsorption temperature for all heavy metals. Adsorption temperature showed an opposite impact to that observed for the numbers of ions captured per both functional groups n1 and n2. Indeed, the increment of the ions captured per functional group led to minimize the adsorption space available on the biomass surface. Note that a decrease of ni (i = 1,2) generated an increment in the number of anchorages, then an increment in the density of Smi is expected. The
increase of the density of functional groups with temperature can be justified by the appearance of additional functional groups that can contribute in the adsorption of these heavy metal ions [40]. 3.2.2. Interpretation of the monolayer adsorption quantity at saturation (Q1, Q2 and Qt) Parameters n and Sm can be used to estimate the adsorbed quantities (Q) at saturation that are associated to the biomass functional groups. At high equilibrium concentration (i.e., at saturation), they are given by: Q1 = n1 *Sm1
(4)
Q2 = n2 *Sm2
(5)
So, the total adsorbed quantity is given by: Qt = Q1 + Q2
(6)
Results indicated that the adsorbed quantity Q2, which was related to the second type of functional group, was greater than that of the first functional group at different temperatures for the adsorption of Cd2+, Ni2+ and Zn2+. On the other hand, the first functional group played a more relevant role in the adsorption of Cu2+ ions at different adsorption temperatures (i.e., Q1 > Q2). This physical adsorption model provided the degree of contribution of these two types of functional groups. For instance, it was noted that: Sm2 > Sm1 and ΔE2 > ΔE1 for Cd2+ adsorption at 25 ◦ C. This result indicated that the adsorption capacity (Q2) was mainly favored by the adsorption energy and the density of second functional group. The adsorbed quantity of this metal for the second functional group was controlled by the number of ions captured per site and the adsorption energy since n2 > n1 andΔE2 > ΔE1 at 30 ◦ C. Fig. 8 shows that thermal agitation led to an improvement in the total adsorbed quantity (Qt) thus indicating the endothermic nature of this adsorption process for all tested ions. Comparatively, the adsorbed quantities of these heavy metals followed the next trend: Qt (Ni2+) > Qt (Cu2+) > Qt (Zn2+) > Qt (Cd2+). The adsorption preference of func tionalized biomass for the Ni2+ removal may be due to their small ionic radius in comparison with other cations. For illustration, the ionic radius ◦ of Ni2+, Cu2+, Zn2+ and Cd2+ were 0.69, 0.72, 0.74 and 0.97 A , respectively. This trend shows that as the cation radius increases, there is a reduction in the adsorption capacities. Other researchers have found similar trends in heavy metal adsorption. For instance, Jumina et al. [41] showed that the adsorption of heavy metal ions on C-phenylcalix [4] pyrogallolarene material followed the trend: Ni2+~Cu2+ > Cr3+ > Pb2+ [41]. This adsorption trend was inversely proportional to the ionic radius of adsorbates. Ma et al. [42] also found that the affinity of Ca/ Namontmorillonite for Cu2+ was higher than for Pb2+. The hydrated cationic radius of metal ion could be associated to this finding where 7
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Fig. 6. Effect of temperature on the number of Cd2+, Ni2+, Zn2+ and Cu2+ ions captured by the surface functional groups n1 and n2 of functionalized flam boyant pods.
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Fig. 7. Impact of temperature on the two densities of biomass-receiving functional groups Sm1 and Sm2 at pH 5.
Pb2+ (0.2655 nm) > Cu2+ (0.2065 nm) [42]. Finally, Zou et al. [43] reported that Pb2+showed stronger electrostatic interactions with microplastics than Cu2+ and Cd2+ since this metal has the minimum hydrated ionic radius.
tested adsorption conditions. According to the magnitude of all estimated energies, the adsorption of Cd2+, Ni2+, Zn2+ and Cu2+ ions occurred via mainly physical forces and was endothermic. Table 3 indicates that the adsorption energies followed this trend: ΔE2 > ΔE1 for Cd2+, ΔE1 > ΔE2 for Ni2+ and ΔE2 > ΔE1 for Zn2+ at tested adsorption temperatures. Adsorption energies of Cu2+ were: ΔE1 > ΔE2 at 25 and 40 ◦ C, while ΔE2 > ΔE1 at 30 ◦ C. These calculations confirmed that both functional groups were involved in the adsorption of these metal ions on the functionalized biomass surface but with different degrees. Finally, the proposed functionalization of flamboyant pods with citric acid can be easily implemented for industrial applications to obtain an adsorbent with tailored properties for heavy metal adsorption. It could be expected that the industrial implementation of this approach can generate a reduction in water treatment costs based on the fact that a waste biomass is used as adsorbent.
3.2.3. Adsorption energies ΔE1 and ΔE2 The values of C1 and C2 were used to calculate the adsorption en ergies and to characterize the interactions between the adsorbed ions (Cd2+, Ni2+, Zn2+ and Cu2+) and biomass surface. These two parameters are related to the adsorption energy via the following expression [35]: ( ) Cs ΔE1,2 = RTln (7) C1,2 where R = 8.314 J/mol.K is the ideal gas constant and Cs is the solubility of the adsorbate. Table 3 reports the calculated adsorption energies at 9
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capacities of all heavy metals increased up to 33% with temperature where the adsorption of these metal ions was inversely proportional to the ionic radius. Physisorption was associated to the removal of these adsorbates with adsorption energies lower than 30 kJ/mol. This func tionalized biomass can be an alternative adsorbent for the low cost removal of heavy metals from water. Finally, the model HPMTBS can be used to characterize and understand the adsorption mechanism of relevant water pollutants using a variety of adsorbents. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi. org/10.1016/j.cej.2020.127975. References [1] P. Indhumathi, S. Sathiyaraj, J.P. Koelmel, S.U. Shoba, C. Jayabalakrishnan, M. Saravanabhavan, The efficient removal of heavy metal ions from industry effluents using waste biomass as low-cost adsorbent: thermodynamic and kinetic models, Z. Phys. Chem. 232 (4) (2018) 527–543. [2] A. Agarwal, U. Upadhyay, I. Sreedhar, S.A. Singh, C.M. Patel, A review on valorization of biomass in heavy metal removal from wastewater, J. Water Process. Eng. 38 (2020), 101602. [3] S. Morais, F.G. Costa, M.D.L. Pereir, Heavy metals and human health, Environ. Health - Emerging Issues Pract. 10 (2012) 227–246. [4] S. Sarode, P. Upadhyay, M.A. Khosa, T. Mak, A. Shakir, S. Song, A. Ullah, Overview of wastewater treatment methods with special focus on biopolymer chitin-chitosan, Int. J. Biol. Macromol. 121 (2019) 1086–1100, https://doi.org/10.1016/j. ijbiomac.2018.10.089. [5] B. Volesky, Detoxification of metal-bearing effluents: biosorption for the next century, Hydrometallurgy 59 (2-3) (2001) 203–216, https://doi.org/10.1016/ S0304-386X(00)00160-2. [6] J. Wang, C. Chen, Biosorbents for heavy metals removal and their future, Biotechnol. Adv. 27 (2) (2009) 195–226, https://doi.org/10.1016/j. biotechadv.2008.11.002. [7] R. Chakraborty, A. Asthana, A.K. Singh, B. Jain, A.B.H. Susan, Adsorption of heavymetal ions by various low-cost adsorbents: a review, Int. J. Environ. Anal. Chem. 1–38 (2020). [8] P.P. Prabhu, B. Prabhu, A review on removal of heavy metal ions from waste waterusing natural / modified bentonite, MATEC Web Conf. 02021 (2018) 1–13. [9] J. Iqra, M. Faryal, R. Uzaira, T. Noshaba, Preparation of zeolite from incinerator ash and its application for the remediation of selected inorganic pollutants: A greener approach, Mater. Sci. Eng. 60 (2014), 012060. [10] R. Chakraborty, R. Verma, A. Asthana, S.S. Vidya, A.K. Singh, Adsorption of hazardous chromium (VI) ions from aqueous solutions using modified sawdust: kinetics, isotherm and thermodynamic modeling, Int. J. Environ. Anal. Chem. 1–18 (2019). [11] M. Visa, Synthesis and characterization of new zeolite materials obtained from fly ash for heavy metals removal in advanced wastewater treatment, Powder. Technol. 294 (2016) 338–347. [12] R. Shahrokhi-Shahraki, C. Benally, M.G. El-Din, J. Park, High Efficiency Removal of Heavy Metals Using Tire-Derived Activated Carbon vs Commercial Activated Carbon: Insights into the Adsorption Mechanisms, Chemosphere 264 (2020), 128455. [13] T.P. Belova, Adsorption of heavy metal ions (Cu2+, Ni2+, Co2+ and Fe2+) from aqueous solutions by natural zeolite, Heliyon. 5 (9) (2019), e02320. [14] H. Es-sahbany, M. Berradi, S. Nkhili, R. Hsissou, M. Allaoui, M. Loutfi, D. Bassir, M. Belfaquir, M.S. El Youbi, Removal of heavy metals (nickel) contained in wastewater-models by the adsorption technique on natural clay, Mater. Today: Proceedings. 13 (2019) 866–875. [15] M.H. Sadeghi, M.A. Tofighy, T. Mohammadi, One-dimensional graphene for efficient aqueous heavy metal adsorption: Rapid removal of arsenic and mercury ions by graphene oxide nanoribbons (GONRs), Chemosphere 253 (2020), 126647. [16] K. Tohdee, L. Kaewsichan, Enhancement of adsorption efficiency of heavy metal Cu (II) and Zn (II) onto cationic surfactant modified bentonite, J. Environ. Chem. Eng. 6 (2) (2018) 2821–2828. [17] S. Doyurum, A. Celik, Pb(II) and Cd(II) removal from aqueous solutions by olive cake, Hazard. Mater. 138 (2006) 22–28. [18] W. Zhang, H. Duo, S. Li, Y. An, Z. Chen, Z. Liu, Y. Ren, S. Wang, X. Zhang, X. Wang, An overview of the recent advances in functionalization biomass adsorbents for toxic metals removal, Colloids Interface Sci. Commun. 38 (2020), 100308. ´ Villabona-Ortíz, C. Tejada-Tovar, A. ´ [19] A. Herrera-Barros, N. Bitar-Castro, A. D. Gonz´ alez-Delgado, Nickel adsorption from aqueous solution using lemon peel
Fig. 8. Total adsorbed quantity of Cd2+, Ni2+, Zn2+ and Cu2+on functionalized flamboyant pods as a function of adsorption temperature.
Table 3 Calculated adsorption energies ΔE1 and ΔE2 for the adsorption of heavy metals on functionalized flamboyant pods. T(◦ C) Cd2+ 25 30 40 Ni2+ 25 30 40 Zn2+ 25 30 40 Cu2+ 25 30 40
C1(mmol/L)
C2(mmol/L)
ΔE 1 (kJ/mol)
ΔE 2 (kJ/mol)
0.50 0.40 1.29
0.32 0.39 0.31
24.10 25.05 22.93
25.23 25.12 26.65
0.79 0.83 0.73
1.27 1.62 1.50
21.73 22.11 23.10
20.64 20.29 21.20
1.13 1.08 0.80
0.74 0.39 0.20
22.54 23.04 24.66
23.61 25.54 28.66
0.32 1.13 0.09
1.22 0.16 0.88
24.93 22.18 29.54
21.71 27.96 23.73
4. Conclusions This paper has applied a heterogeneous physical model (HPMTBS) to characterize and explain the physicochemical parameters involved in the adsorption of Cd2+, Ni2+, Zn2+ and Cu2+ ions on flamboyant pods functionalized with citric acid. Functionalization of this biomass with citric acid was optimized via a Taguchi experimental design and sta tistical analysis based on the Signal-to-Noise ratio calculated for the heavy metal adsorption capacities. The best conditions for biomass surface functionalization were identified where the final adsorbent increased its metal adsorption capacities up to 53% at tested operating conditions. Modeling results based on a statistical physics adsorption model demonstrated that the removal of these cations was multi-ionic at different adsorption temperatures where two functional groups of this biomass participated in the adsorption with different degrees. Biomass characterization results suggested that these functionalities corre sponded to carboxylic and phenolic functional groups. The adsorption 10
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Application of a heterogeneous physical model for the adsorption of Cd2+, Ni2+, Zn2+ and Cu2+ ions on flamboyant pods functionalized with citric acid b, c ´ ´vez-Gonza ´lez b, Hilda Elizabeth Reynel-Avila Fatma Dhaouadi a, Lotfi Sellaoui a, *, Brenda Cha , ˜ oz b, Didilia Ileana Mendoza-Castillo b, c, Adria ´n Bonilla-Petriciolet b, Liliana Lizbeth Diaz-Mun Eder C. Lima d, Juan Carlos Tapia-Picazo b, Abdelmottaleb Ben Lamine a, * a
Laboratory of Quantum and Statistical Physics, LR18ES18, Monastir University, Faculty of Sciences of Monastir, Tunisia Instituto Tecnol´ ogico de Aguascalientes, Aguascalientes, 20256, Mexico c CONACyT, C´ atedras J´ ovenes Investigadores, Ciudad de M´exico, 03940, Mexico d Institute of Chemistry- Federal University of Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil b
A R T I C L E I N F O
A B S T R A C T
Keywords: Adsorption Biomass Heavy metals Heterogeneous physical model
A heterogeneous physical model with two bindings sites (HPMTBS) was successfully used to explain the adsorption of Cd2+, Ni2+, Zn2+, and Cu2+ ions on flamboyant pods functionalized with citric acid. Experimental results and statistical physics modeling showed that carboxylic and phenolic functionalities of this adsorbent played a relevant role for the adsorption of Cd2+, Ni2+, Zn2+, and Cu2+ ions. Calculations performed with HPMTBS suggested that the removal of these cations was a multi-ionic adsorption process at tested operating conditions. This adsorbent was more effective to remove Cd2+, Ni2+, Zn2+ and Cu2+ ions at high solution temperatures thus indicating an endothermic process with adsorption energies ranging from 20.3 to 29.5 kJ/mol, which were associated to physisorption. The total adsorption capacities varied from 0.10 to 0.32, 0.28 to 0.39, 0.19 to 0.25 and 0.20 to 0.31 mmol/g for Cd2+, Ni2+, Zn2+ and Cu2+, respectively. This difference in adsorption capacities could be attributed to the ionic radius of tested adsorbates. This functionalized biomass can be considered as an alternative adsorbent for facing water pollution by heavy metal ions.
1. Introduction Glass, energy and fuel production, tanneries, mining, paper and metal plating industries are among of the major industrial sectors that generate heavy metal-polluted effluents worldwide [1–2]. Heavy metals are pollutants that can persist in the environment for a long period and represent a threat to the ecosystems because of their toxicological effects on living organisms and humans [3].The toxicity caused by heavy metal ions can generate the inhibition of enzyme activity, poisoning, brain problems and even primary cancer in humans. These toxicological ef fects are associated to a chronic exposure via the water consumption with metal concentrations usually in the order of mmol/L [4]. For these reasons, the removal of heavy metals is of great strategic interest to protect the environment and to reduce health risks for population. In this context, there is a wide variety of techniques and methods to solve the problem of water pollution by heavy metal ions. These
methods include chemical precipitation, electrochemical treatment, ion exchange, membrane separation, ultrafiltration, reverse osmosis, elec trocoagulation, adsorption and biological treatment [5–7]. The adsorption has been used to remove inorganic and organic substances from wastewaters and polluted effluents due to its low energy con sumption, simple design, high treatment efficiency and economic feasibility [8–11]. Its separation performance relies on the selection of an adsorbent with a suitable tradeoff between surface chemistry and textural parameters to minimize effectively the concentrations of target adsorbates in the fluid to be treated. Activated carbon, zeolite, clays, graphene oxide and nanomaterials are examples of adsorbents used to reduce the concentration of heavy metal ions in water [12–16]. How ever, some disadvantages of available adsorbents include its production cost and/or a limited adsorption capacity, which could constraint its application in wastewaters treatment at industrial level [2]. These drawbacks have promoted the research and application of abundant and
* Corresponding authors. E-mail addresses: [email protected] (L. Sellaoui), [email protected] (A.B. Lamine). https://doi.org/10.1016/j.cej.2020.127975 Received 10 November 2020; Received in revised form 26 November 2020; Accepted 30 November 2020 Available online 4 December 2020 1385-8947/© 2020 Elsevier B.V. All rights reserved.
Please cite this article as: Fatma Dhaouadi, Chemical Engineering Journal, https://doi.org/10.1016/j.cej.2020.127975
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Fig. 1. Heavy metal adsorption capacities of flamboyant pods functionalized with citric acid.
low cost materials to prepare alternative adsorbents for heavy metal removal, including the development of surface functionalization methods to improve their physicochemical properties and adsorption performances. Biomasses from different sources are an alternative to implement effective adsorption processes for heavy metal removal from water. Several studies have shown that biomasses contain surface functional groups capable of binding and interacting with metal ions dissolved in aqueous solutions [17]. The removal performance of these materials can be improved via the functionalization of its surfaces thus enhancing the adsorption of heavy metal ions [18,19]. In particular, organic acids can be utilized to incorporate surface functionalities on biomasses thus increasing their adsorption capacities for heavy metals. This biomass functionalization is fundamental to enhance the heavy metal adsorption properties thus reducing the operational cost of water treatment for industrial scale up. On the other hand, flamboyant pods are lignocellu losic wastes abundant in several countries, which have been employed as a renewable adsorbent and low-cost precursor to prepare activated carbon for the removal of dyes and heavy metals [20]. Previous studies have reported the physicochemical characterization of this biomass [20], which has shown a promising potential for its use in water depollution. This paper reports the surface functionalization of flamboyant pods with citric acid to improve the removal of Cd2+, Ni2+, Zn2+ and Cu2+ ions and its theoretical modeling via statistical physics to understand the corresponding adsorption mechanism. To achieve this objective, two statistical physics models (homogenous and heterogeneous) have been applied for the analysis of heavy metal adsorption data. These models can provide physicochemical explanations of the adsorption of Cd2+, Ni2+, Zn2+ and Cu2+ ions on this adsorbent. Note that the statistical physics models can retrieve theoretical information of adsorption phe nomenon, which can not be obtained from the application of traditional adsorption models (i.e., Langmuir, Freundlich, Sips). It is convenient to
highlight that statistical physics models outperform classical adsorption equations for the understanding of adsorption phenomenon. For instance, the statistical physics adsorption models can be used to calculate and analyze steric and energetic parameters linked to the corresponding removal mechanism. Therefore, the results of biomass characterization, experimental adsorption data and its statistical physics modelling were integrated to understand and explain the adsorption of heavy metals on this functionalized biomass. 2. Materials and methods 2.1. Functionalization of flamboyant pods using citric acid for heavy metal adsorption Flamboyant pods were used as adsorbent of heavy metals from aqueous solution. First, this biomass was washed with deionized water, dried, ground and sieved to obtain a mean particle size of 0.45 mm. It was functionalized with citric acid to increase its heavy metal adsorption properties. An experimental design Taguchi L16 was applied to deter mine the best conditions for the functionalization of flamboyant pods for heavy metal removal in aqueous solutions. Table S1 of Supporting In formation illustrates this experimental design where 4 variables with 4 levels were explored for biomass functionalization: temperature of biomass treatment with citric acid (30 – 60 ◦ C), sonication time of the mixture biomass – citric acid solution (0.5 – 4 h), ratio of biomass/citric acid volume (1/10 – 1/25 g/mL) and citric acid concentration (0.5 – 2 M). 16 adsorbents were prepared via this experimental design following the next procedure. Specifically, 1 g of biomass was added to a specific volume of citric acid solution according to the conditions of experi mental L16. The mixture biomass + citric acid was sonicated (with an ultrasonic bath model Branson 8800) for a specific time at a particular temperature. Subsequently, the functionalized biomass was decanted from the acidic solution and, then, it was thermally treated at 150 ◦ C for 2
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Fig. 2. Kinetics of heavy metal adsorption using flamboyant pods functionalized with citric acid. Experimental adsorption conditions: pH 5, 30 ◦ C, 4 g/L of adsorbent/solution dosage.
6 h. The final product was washed with deionized water and dried for its application as adsorbent of heavy metal ions. The best conditions for the biomass functionalization with citric acid were identified via a statistical analysis of the experimental design results using the Signal-to-Noise (S/ N) ratio. The goal of this stage was to improve the heavy metal adsorption capacities of biomass treated with citric acid. Details of the experimental design, its statistical analysis using S/N ratio and the identification of best conditions for biomass functionalization are re ported in Supporting Information. The best functionalized biomass was utilized to quantify the kinetics and isotherms of heavy metal adsorption. Experimental adsorption ki netics for tested heavy metals were done at 30 ◦ C and pH 5 using different initial metal concentrations (0.53 – 2.3 mmol/L) and operating times from 0.16 to 24 h. Adsorption rates were calculated with Pseudo first model via a nonlinear regression. Adsorption isotherms were per formed at 25, 30 and 40 ◦ C and pH 5. Note that pH 5 was identified as the best condition for heavy metal removal based on adsorption exper iments performed at pH 3, 4 and 5. Initial concentration of these metals ranged from 0.2 to 5.1 mmol/L to obtain the corresponding adsorption isotherms. Heavy metal solutions were prepared using nitrate salts of Cd2+, Cu2+, Ni2+ and Zn2+ and deionized water. The pH of these
solutions was adjusted using diluted HNO3 and NaOH. All adsorption experiments were conducted using an adsorbent/volume (m/V) ratio of 0.04 g/L under continuous agitation (120 rpm) at batch conditions. Initial (C0) and final (Ce) concentrations of heavy metals in aqueous solution were quantified using a Thermo Scientific (Ice 3000) atomic absorption spectrophotometer equipped with an air-acetylene burner. The adsorbate mass balance allowed to calculate the adsorption capacity (Qe) Qe =
(Co − Ce )V m
(1)
All adsorption experiments were performed by triplicate showing a reproducibility < 5% and the mean adsorption capacity was reported. Analytical grade reagents were used in all experiments, which were purchased from J.T. Baker. 2.2. Physicochemical characterization of flamboyant pods functionalized with citric acid Functional groups of raw and functionalized flamboyant pods were determined using a Thermo Scientific Nicolet iS10 FTIR spectrometer. 3
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Fig. 3. Effect of solution pH on heavy metal adsorption of flamboyant pods functionalized with citric acid. Experimental adsorption conditions: 4 g/L of adsorbent/ solution dosage and 30 ◦ C.
FTIR spectra were measured with attenuated total reflectance technique and recorded in the region of 4000 – 650 cm− 1 with 32 scans and 4 cm− 1 of resolution. Biomass samples loaded with heavy metals were also analyzed to identify the functional groups involved in adsorption. A protocol based on Boehm methodology [21] was utilized to determine the pH of point of zero charge, acidity and basicity of the raw and functionalized biomasses. Briefly, the pH of point of zero charge was quantified using 0.1 M NaCl solutions where their pH was adjusted from 2 to 8. A mixture of 0.15 g of biomass and 50 mL of NaCl solution with a predefined pH was stirred for 48 h at 25 ◦ C and the final pH was measured. The pH of point of zero charge was identified graphically using the curve of final pH versus initial pH.Total acidic sites were estimated with 0.2 g of biomass and 25 mL of 0.025 M NaOH, which were stirred for 48 h at 25 ◦ C. The adsorbent was separated from solu tion and the remaining solution was titrated with 0.025 MHCl. The total basic sites of biomass were quantified in a similar way but using 0.025 M HCl for the mixture and 0.025 M NaOH was employed for the solution titration.
2.3.1. Homogenous physical model with one binding site (HPMOBS) for metal adsorption This model HPMOBS considers that the functionalized biomass contains one type of functional group that is responsible of the heavy metal adsorption thus generating one surface adsorption energy be tween the metallic ions and biomass surface. Then, it was considered that the functional group can capture ‘n’ ions at tested adsorption temperatures (25, 30 and 40 ◦ C) where one adsorption layer is formed. Therefore, the adsorbed monolayer quantity of HPMOBS is provided by the following expression [22]:
2.3. Homogeneous and heterogeneous physical adsorption models to analyze the heavy metal removal mechanism
2.3.2. Heterogeneous physical model with two bindings sites (HPMTBS) for metal adsorption This model assumes that the functionalized biomass contains two types of surface functionalities that are responsible to adsorb the metallic ions where two surface adsorption energies between ions and biomass are present. These two functional groups can capture ‘n1′ and ‘n2′ ions, respectively, at tested adsorption conditions. Note that the formation of one adsorption layer via each type of binding site also occurs. As a result, the adsorption capacity calculated by this model versus the equilibrium concentration is expressed as [22–24]:
nSm ( )n
Qe = 1+
C1/2 Ce
(2)
The parameters of this model are defined as follows: n is the captured number of Cd2+, Ni2+, Zn2+ and Cu2+ ions per the functional group of functionalized biomass, Sm is the density of functional groups of func tionalized biomass and C1/2 is the concentration at half-saturation.
Experimental adsorption isotherms, i.e. Qe = f (Ce), are the results of interactions between the adsorbates (i.e., heavy metal ions) and adsor bent surface (i.e., biomass functional groups). The analysis and char acterization of isotherms represent a key stage to explain the adsorption mechanism. The integration of physical model calculations and experi mental results (adsorption data and characterization) allows to examine and understand the role of biomass functional groups for the adsorption of Cd2+, Ni2+, Zn2+ and Cu2+ ions. Biomass characterization results indicated that more than one functional group could be participating in the adsorption of these heavy metal ions. For simplicity of the theoret ical interpretation, two physical models were used to analyze the adsorption of Cd2+, Ni2+, Zn2+ and Cu2+ ions on citric-functionalized biomass where it was assumed that the adsorption mechanism involved one or two functional groups. These models are described in the next subsections.
Qe =
n1 Sm1 n2 Sm2 ( )n1 + ( )n2 C1 1 + Ce 1 + CC2e
(3)
Six adjustable parameters are included in HPMTBS expression, which are the number of Cd2+, Ni2+, Zn2+ and Cu2+ ions captured per both functional groups (n1 and n2), the densities of these functional groups (Sm1 and Sm2) and the corresponding half-saturation concentra tions (C1 and C2). 4
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Fig. 4. Isotherms of heavy metal adsorption on flamboyant pods functionalized with citric acid. Experimental adsorption conditions: pH 5 and4 g/L of adsorbent/ solution dosage.
These models HPMOBS and HPMTBS were applied to adjust the experimental adsorption isotherms of Cd2+, Ni2+, Zn2+ and Cu2+ ions obtained at different temperatures. This non-linear regression was car ried out with Origin (version 9) and the selection of best fitted model was based on the determination coefficient R2.
biomass functionalization with citric acid using a ratio of biomass/citric acid of 1/10 g/mL and a citric acid concentration of 2 M. This func tionalized biomass was used in all heavy metal adsorption studies. Adsorption kinetic profiles obtained at different initial heavy metal concentrations with the best functionalized biomass and their modeling with the pseudo first order equation are shown in Fig. 2. Adsorption equilibrium was reached at 24 h and 92% of heavy metal adsorption was obtained after 6 h of contact time thus indicating an important role of functional groups of external biomass surface in the metal removal. Adsorption rate constants (k1) obtained from Pseudo first order model ranged from 0.63 to 2.02 h− 1. On the other hand, the effect of solution pH on heavy metal adsorption is reported in Fig. 3. Solution pH impacted the adsorption of heavy metals where the maximum adsorption capacities were obtained at pH 5 with increments of 119% for Cd2+, 40% for Cu2+, 38% for Ni2+ and 30% for Zn2+, respectively, with respect to the adsorbent perfor mance obtained at pH 3. At low pH, the protons of solution competed with metallic cations by the binding sites of the functionalized biomass thus reducing the heavy metal adsorption capacities. Fig. 4 shows the adsorption isotherms of tested heavy metals at different temperatures using the best functionalized biomass at pH 5. All experiments isotherms can be classed as the L type according to Giles
3. Results and discussion 3.1. Identification of the best conditions for the functionalization of flamboyant pods Fig. 1 shows the adsorption capacities obtained with 16 biomass samples functionalized with citric acid according to the tested experi mental design given in Table S1, see Supporting Information. Metal adsorption capacities of these samples ranged from 0.063 to 0.108 mmol/g for Cd+2, 0.084 to 0.273 mmol/g for Cu+2, 0.126 to 0.261 mmol/g for Ni+2 and 0.098 to 0.223 mmol/g for Zn+2. Overall, all tested conditions for biomass functionalization favored the heavy metal adsorption capacities. Data of Table S1 were utilized to identify the best conditions for the functionalization of flamboyant pods via a statistical analysis of S/N ratio. Results of this statistical analysis are also reported in Supporting Information. These conditions were: 50 ◦ C and 2 h for 5
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functionalized with citric acid at different operating conditions are shown in Table S1 of Supporting Information. Note that pHpzc of raw flamboyant pods was 6.24 and strong electrostatic repulsion forces be tween biomass surface (positively charged) and adsorbates were present at pH < pHpzc, thus reducing the metal adsorption capacities. However, the pHpzc of all biomass samples decreased after their functionalization with citric acid, which favored the uptake of all tested heavy metals. The best adsorbent showed a pHpzc of 2.92 that generated an electrostatic attraction that increased the adsorption capacities due to pH > pHpzc [26].The acidic sites of this biomass, which were responsible of heavy metal adsorption, increased up to 53% after citric acid functionalization. These findings confirmed the importance of these functionalities on heavy metal adsorption and the relevance of surface physicochemical treatment to improve the adsorbent performance [26–28]. It is well known that acidic treatment modifies surface properties of lignocellulosic biomasses and FTIR analysis can be used to confirm the increment of oxygen functionalities on adsorbent surface. Therefore, Fig. 5 shows the FTIR results of raw and functionalized biomasses. Spectrum of raw flamboyant pods contains the typical FTIR bands of lignocellulosic biomasses. The stretching vibration of group OH associ ated to phenols and alcohols was observed in the region of 3400 – 3300 cm− 1[26]. The absorption bands around 2920–2840 cm-1were gener ated from aliphatic chains of C–H [29]. The groups related to C = O of carboxylic, ester or aldehyde vibrations can be observed at 1729 and 1620 cm− 1 [26,30]. The absorption bands at 1250–1023 cm− 1 can be associated with the stretching C–O of phenols, alcohols, carboxylic, ethers and esters [27,31]. The vibrations of C = C, C–C and C–H were identified with bands at 1460, 1415 and 1315/890 cm− 1, respectively, which corresponded to aromatic structures [26,30].Spectrum of func tionalized flamboyant pods showed some displacements and increments in the bands located at 3350, 1729, 1620, 1250–890 cm− 1, which are associated to oxygen functionalities. There was also a reduction and shift in the absorption bands at 2840 and 1465 cm− 1. These structural changes can be an indication of the lignocellulose reaction caused by citric acid with the possible development and/or increment of specific functional groups [28]. FTIR spectra of functionalized flamboyant pods after heavy metal adsorption showed an evident reduction in the in tensity of the absorption bands located at 3340, 1620 and 1250–1023 cm− 1 where the oxygen functionalities can be identified. As stated, the oxygen functional groups play a key role in the heavy metal adsorption via organic-metal interactions like complexation, chemisorption, ligand exchange, among others [26,32–34].
Fig. 5. . FTIR spectra of raw (FP) and functionalized (CAFP) flamboyant pods used in heavy metal adsorption.
classification for adsorption in liquid systems [25]. Maximum adsorp tion capacities were obtained at 40 ◦ C with values of 0.14 mmol/g for Cd2+, 0.33 mmol/g for Cu2+, 0.33 mmol/g for Ni2+ and 0.26 mmol/g for Zn2+, respectively. Therefore, the heavy metal adsorption was endo thermic where the adsorption capacities increased up to 30% for Cd2+, 28% for Cu2+, 20% for Ni2+ and 33% for Zn2+ from 25 to 40 ◦ C. This result indicated that thermal agitation facilitated the removal of these heavy metal ions. Note that the adsorption of Ni2+and Cu2+ was higher than those obtained for Zn2+and Cd2+. Surface physicochemical properties of flamboyant pods
3.2. Analysis of heavy metal adsorption mechanism via statistical physics models R2 values obtained from the fitting of experimental adsorption iso therms with two adsorption models are reported in Table 1. HPMTBS showed the highest R2 values for all heavy metals, which varied from 0.988 to 0.999. A simple analysis of HPMTBS parameters as function of temperature indicated that they can be utilized to understand and explain the adsorption mechanism. Therefore, it was concluded that the adsorption of heavy metal ions on functionalized biomass can be better described with this model than a homogeneous model with one binding site. Summarizing, the adjusted parameters of the selected adsorption model are presented in Table 2 and the isotherms adjusted by this model at different adsorption temperatures are represented in the Supporting Information. For a complete analysis of the adsorption mechanism of tested heavy metal ions, all parametersn1, n2, Sm1, Sm2, Qt, C1 and C2 of model HPMTBS were studied as a function of adsorption temperature. Findings and conclusions of this analysis are given in next subsections.
Table 1 Results of isotherm fitting for the adsorption of Cd2+, Ni2+, Zn2+ and Cu2+ on functionalized flamboyant pods at different temperatures. T (◦ C)
HPMOBS
HPMTBS
0.992 0.993 0.996
0.999 0.996 0.996
0.994 0.980 0.993
0.996 0.995 0.998
0.995 0.992 0.994
0.996 0.995 0.999
0.980 0.978 0.984
0.992 0.988 0.998
2+
Cd 25 30 40 Ni2+ 25 30 40 Zn2+ 25 30 40 Cu2+ 25 30 40
3.2.1. Interpretations of the number of captured Cd2+, Ni2+, Zn2+ and Cu2+ ions per functional group(n1 and n2) and their densities (Sm1 and Sm2) Parameters n1 and n2 are related to the two functional groups of 6
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Table 2 Physicochemical parameters obtained from the fitting of experimental adsorption isotherms by the model HPMTBS. T (◦ C)
n1
Sm1(mmol/g)
n2
Sm2(mmol/g)
C1(mmol/L)
C2(mmol/L)
Q1(mmol/g)
Q2(mmol/g)
Qtotal(mmol/g)
6.56 0.66 0.55
0.004 0.08 0.17
2.02 3.39 2.57
0.04 0.02 0.03
0.50 0.40 1.29
0.32 0.39 0.31
0.026 0.05 0.09
0.08 0.07 0.23
0.10 0.12 0.32
4.89 5.42 4.84
0.026 0.02 0.03
1.43 0.68 0.88
0.11 0.40 0.29
0.79 0.83 0.73
1.27 1.62 1.50
0.12 0.10 0.14
0.15 0.27 0.25
0.28 0.37 0.39
5.71 4.92 3.30
0.005 0.008 0.007
1.42 1.54 1.26
0.12 0.12 0.16
1.13 1.08 0.80
0.74 0.39 0.20
0.028 0.039 0.056
0.17 0.18 0.20
0.19 0.22 0.25
4.40 2.87 1.58
0.03 0.06 0.11
3.88 4.39 2.90
0.02 0.03 0.05
0.32 1.13 0.09
1.22 0.16 0.88
0.13 0.17 0.173
0.07 0.13 0.14
0.20 0.30 0.31
2+
Cd 25 30 40 Ni2+ 25 30 40 Zn2+ 25 30 40 Cu2+ 25 30 40
biomass that were involved in the adsorption of Cd2+, Ni2+, Zn2+and Cu2+ ions. Characterization results indicated that carboxylic and phenolic functionalities are those expected to play a relevant role in heavy metal adsorption with flamboyant pods modified with citric acid. Results of HPMTBS indicated that both functional groups contributed in heavy metal adsorption with different degrees depending on the adsorption temperature. For instance, it was observed that: n2 > n1for Cd2+ and n2 > n1 for Cu2+ at 30 and 40 ◦ C, while n1 > n2 for Cd2+ and n1 > n2 for Cu2+ at 25 ◦ C. It was also noted that n1 > n2 for Ni2+ and n1 > n2 for Zn2+ at 25, 30 and 40 ◦ C. This theoretical finding showed that both functionalities contributed to capture Cd2+ and Cu2+ ions, but one surface functionality had a more relevant role for heavy metal adsorp tion. Overall, it can be expected that carboxylic functionalities played the primary role in heavy metal removal using this biomass. Also, these physicochemical parameters can be used to describe the adsorption position of all ions on the functional groups of biomass surface. Note that: a) if n1 and n2 < 0.5, the metallic ions can be captured by two or more functional groups (i.e., there is double or more interactions leading to a multi-interaction adsorption process), b) if 0.5 < n1 and n2 < 1, the ions can be captured by one and two functional groups with two different probabilities (i.e.,simple and double interactions with the adsorption functional group at the same time are feasible), c) if n1 and n2 ≥ 1, the ions can be captured by one functional group (i.e., a multiionic adsorption process) [23,24,35–39]. Overall, the values of n1 and n2 were superior to the unity thus suggesting that these adsorbates were bonded via one adsorbent functional group of tested biomass. The impact of temperature on both parameters is illustrated in Fig. 6. Adsorption temperature has a different impact on the parameters n1 and n2 for tested heavy metals, which could be related to the nature of biomass functional groups and adsorbate physicochemical properties. Thermally speaking, the increment of temperature led to an increment of n1 for Ni2+ and a decrement of n1 for Zn2+, Cu2+ and Cd2+ where this effect was explained in general by the effect of thermal collisions. Both increments and decrements of n with respect to adsorption temperature were observed and these trends could be associated to the change of adsorbates interactions with the biomass functional groups. Sm1 and Sm2 are also two steric parameters that provide information on the number of sites (or functional groups) necessary to adsorb the heavy metal ions at saturation. Fig. 7 reports the trends of these two parameters versus adsorption temperature for all heavy metals. Adsorption temperature showed an opposite impact to that observed for the numbers of ions captured per both functional groups n1 and n2. Indeed, the increment of the ions captured per functional group led to minimize the adsorption space available on the biomass surface. Note that a decrease of ni (i = 1,2) generated an increment in the number of anchorages, then an increment in the density of Smi is expected. The
increase of the density of functional groups with temperature can be justified by the appearance of additional functional groups that can contribute in the adsorption of these heavy metal ions [40]. 3.2.2. Interpretation of the monolayer adsorption quantity at saturation (Q1, Q2 and Qt) Parameters n and Sm can be used to estimate the adsorbed quantities (Q) at saturation that are associated to the biomass functional groups. At high equilibrium concentration (i.e., at saturation), they are given by: Q1 = n1 *Sm1
(4)
Q2 = n2 *Sm2
(5)
So, the total adsorbed quantity is given by: Qt = Q1 + Q2
(6)
Results indicated that the adsorbed quantity Q2, which was related to the second type of functional group, was greater than that of the first functional group at different temperatures for the adsorption of Cd2+, Ni2+ and Zn2+. On the other hand, the first functional group played a more relevant role in the adsorption of Cu2+ ions at different adsorption temperatures (i.e., Q1 > Q2). This physical adsorption model provided the degree of contribution of these two types of functional groups. For instance, it was noted that: Sm2 > Sm1 and ΔE2 > ΔE1 for Cd2+ adsorption at 25 ◦ C. This result indicated that the adsorption capacity (Q2) was mainly favored by the adsorption energy and the density of second functional group. The adsorbed quantity of this metal for the second functional group was controlled by the number of ions captured per site and the adsorption energy since n2 > n1 andΔE2 > ΔE1 at 30 ◦ C. Fig. 8 shows that thermal agitation led to an improvement in the total adsorbed quantity (Qt) thus indicating the endothermic nature of this adsorption process for all tested ions. Comparatively, the adsorbed quantities of these heavy metals followed the next trend: Qt (Ni2+) > Qt (Cu2+) > Qt (Zn2+) > Qt (Cd2+). The adsorption preference of func tionalized biomass for the Ni2+ removal may be due to their small ionic radius in comparison with other cations. For illustration, the ionic radius ◦ of Ni2+, Cu2+, Zn2+ and Cd2+ were 0.69, 0.72, 0.74 and 0.97 A , respectively. This trend shows that as the cation radius increases, there is a reduction in the adsorption capacities. Other researchers have found similar trends in heavy metal adsorption. For instance, Jumina et al. [41] showed that the adsorption of heavy metal ions on C-phenylcalix [4] pyrogallolarene material followed the trend: Ni2+~Cu2+ > Cr3+ > Pb2+ [41]. This adsorption trend was inversely proportional to the ionic radius of adsorbates. Ma et al. [42] also found that the affinity of Ca/ Namontmorillonite for Cu2+ was higher than for Pb2+. The hydrated cationic radius of metal ion could be associated to this finding where 7
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Fig. 6. Effect of temperature on the number of Cd2+, Ni2+, Zn2+ and Cu2+ ions captured by the surface functional groups n1 and n2 of functionalized flam boyant pods.
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Fig. 7. Impact of temperature on the two densities of biomass-receiving functional groups Sm1 and Sm2 at pH 5.
Pb2+ (0.2655 nm) > Cu2+ (0.2065 nm) [42]. Finally, Zou et al. [43] reported that Pb2+showed stronger electrostatic interactions with microplastics than Cu2+ and Cd2+ since this metal has the minimum hydrated ionic radius.
tested adsorption conditions. According to the magnitude of all estimated energies, the adsorption of Cd2+, Ni2+, Zn2+ and Cu2+ ions occurred via mainly physical forces and was endothermic. Table 3 indicates that the adsorption energies followed this trend: ΔE2 > ΔE1 for Cd2+, ΔE1 > ΔE2 for Ni2+ and ΔE2 > ΔE1 for Zn2+ at tested adsorption temperatures. Adsorption energies of Cu2+ were: ΔE1 > ΔE2 at 25 and 40 ◦ C, while ΔE2 > ΔE1 at 30 ◦ C. These calculations confirmed that both functional groups were involved in the adsorption of these metal ions on the functionalized biomass surface but with different degrees. Finally, the proposed functionalization of flamboyant pods with citric acid can be easily implemented for industrial applications to obtain an adsorbent with tailored properties for heavy metal adsorption. It could be expected that the industrial implementation of this approach can generate a reduction in water treatment costs based on the fact that a waste biomass is used as adsorbent.
3.2.3. Adsorption energies ΔE1 and ΔE2 The values of C1 and C2 were used to calculate the adsorption en ergies and to characterize the interactions between the adsorbed ions (Cd2+, Ni2+, Zn2+ and Cu2+) and biomass surface. These two parameters are related to the adsorption energy via the following expression [35]: ( ) Cs ΔE1,2 = RTln (7) C1,2 where R = 8.314 J/mol.K is the ideal gas constant and Cs is the solubility of the adsorbate. Table 3 reports the calculated adsorption energies at 9
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capacities of all heavy metals increased up to 33% with temperature where the adsorption of these metal ions was inversely proportional to the ionic radius. Physisorption was associated to the removal of these adsorbates with adsorption energies lower than 30 kJ/mol. This func tionalized biomass can be an alternative adsorbent for the low cost removal of heavy metals from water. Finally, the model HPMTBS can be used to characterize and understand the adsorption mechanism of relevant water pollutants using a variety of adsorbents. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi. org/10.1016/j.cej.2020.127975. References [1] P. Indhumathi, S. Sathiyaraj, J.P. Koelmel, S.U. Shoba, C. Jayabalakrishnan, M. Saravanabhavan, The efficient removal of heavy metal ions from industry effluents using waste biomass as low-cost adsorbent: thermodynamic and kinetic models, Z. Phys. Chem. 232 (4) (2018) 527–543. [2] A. Agarwal, U. Upadhyay, I. Sreedhar, S.A. Singh, C.M. Patel, A review on valorization of biomass in heavy metal removal from wastewater, J. Water Process. Eng. 38 (2020), 101602. [3] S. Morais, F.G. Costa, M.D.L. Pereir, Heavy metals and human health, Environ. Health - Emerging Issues Pract. 10 (2012) 227–246. [4] S. Sarode, P. Upadhyay, M.A. Khosa, T. Mak, A. Shakir, S. Song, A. Ullah, Overview of wastewater treatment methods with special focus on biopolymer chitin-chitosan, Int. J. Biol. Macromol. 121 (2019) 1086–1100, https://doi.org/10.1016/j. ijbiomac.2018.10.089. [5] B. Volesky, Detoxification of metal-bearing effluents: biosorption for the next century, Hydrometallurgy 59 (2-3) (2001) 203–216, https://doi.org/10.1016/ S0304-386X(00)00160-2. [6] J. Wang, C. Chen, Biosorbents for heavy metals removal and their future, Biotechnol. Adv. 27 (2) (2009) 195–226, https://doi.org/10.1016/j. biotechadv.2008.11.002. [7] R. Chakraborty, A. Asthana, A.K. Singh, B. Jain, A.B.H. Susan, Adsorption of heavymetal ions by various low-cost adsorbents: a review, Int. J. Environ. Anal. Chem. 1–38 (2020). [8] P.P. Prabhu, B. Prabhu, A review on removal of heavy metal ions from waste waterusing natural / modified bentonite, MATEC Web Conf. 02021 (2018) 1–13. [9] J. Iqra, M. Faryal, R. Uzaira, T. Noshaba, Preparation of zeolite from incinerator ash and its application for the remediation of selected inorganic pollutants: A greener approach, Mater. Sci. Eng. 60 (2014), 012060. [10] R. Chakraborty, R. Verma, A. Asthana, S.S. Vidya, A.K. Singh, Adsorption of hazardous chromium (VI) ions from aqueous solutions using modified sawdust: kinetics, isotherm and thermodynamic modeling, Int. J. Environ. Anal. Chem. 1–18 (2019). [11] M. Visa, Synthesis and characterization of new zeolite materials obtained from fly ash for heavy metals removal in advanced wastewater treatment, Powder. Technol. 294 (2016) 338–347. [12] R. Shahrokhi-Shahraki, C. Benally, M.G. El-Din, J. Park, High Efficiency Removal of Heavy Metals Using Tire-Derived Activated Carbon vs Commercial Activated Carbon: Insights into the Adsorption Mechanisms, Chemosphere 264 (2020), 128455. [13] T.P. Belova, Adsorption of heavy metal ions (Cu2+, Ni2+, Co2+ and Fe2+) from aqueous solutions by natural zeolite, Heliyon. 5 (9) (2019), e02320. [14] H. Es-sahbany, M. Berradi, S. Nkhili, R. Hsissou, M. Allaoui, M. Loutfi, D. Bassir, M. Belfaquir, M.S. El Youbi, Removal of heavy metals (nickel) contained in wastewater-models by the adsorption technique on natural clay, Mater. Today: Proceedings. 13 (2019) 866–875. [15] M.H. Sadeghi, M.A. Tofighy, T. Mohammadi, One-dimensional graphene for efficient aqueous heavy metal adsorption: Rapid removal of arsenic and mercury ions by graphene oxide nanoribbons (GONRs), Chemosphere 253 (2020), 126647. [16] K. Tohdee, L. Kaewsichan, Enhancement of adsorption efficiency of heavy metal Cu (II) and Zn (II) onto cationic surfactant modified bentonite, J. Environ. Chem. Eng. 6 (2) (2018) 2821–2828. [17] S. Doyurum, A. Celik, Pb(II) and Cd(II) removal from aqueous solutions by olive cake, Hazard. Mater. 138 (2006) 22–28. [18] W. Zhang, H. Duo, S. Li, Y. An, Z. Chen, Z. Liu, Y. Ren, S. Wang, X. Zhang, X. Wang, An overview of the recent advances in functionalization biomass adsorbents for toxic metals removal, Colloids Interface Sci. Commun. 38 (2020), 100308. ´ Villabona-Ortíz, C. Tejada-Tovar, A. ´ [19] A. Herrera-Barros, N. Bitar-Castro, A. D. Gonz´ alez-Delgado, Nickel adsorption from aqueous solution using lemon peel
Fig. 8. Total adsorbed quantity of Cd2+, Ni2+, Zn2+ and Cu2+on functionalized flamboyant pods as a function of adsorption temperature.
Table 3 Calculated adsorption energies ΔE1 and ΔE2 for the adsorption of heavy metals on functionalized flamboyant pods. T(◦ C) Cd2+ 25 30 40 Ni2+ 25 30 40 Zn2+ 25 30 40 Cu2+ 25 30 40
C1(mmol/L)
C2(mmol/L)
ΔE 1 (kJ/mol)
ΔE 2 (kJ/mol)
0.50 0.40 1.29
0.32 0.39 0.31
24.10 25.05 22.93
25.23 25.12 26.65
0.79 0.83 0.73
1.27 1.62 1.50
21.73 22.11 23.10
20.64 20.29 21.20
1.13 1.08 0.80
0.74 0.39 0.20
22.54 23.04 24.66
23.61 25.54 28.66
0.32 1.13 0.09
1.22 0.16 0.88
24.93 22.18 29.54
21.71 27.96 23.73
4. Conclusions This paper has applied a heterogeneous physical model (HPMTBS) to characterize and explain the physicochemical parameters involved in the adsorption of Cd2+, Ni2+, Zn2+ and Cu2+ ions on flamboyant pods functionalized with citric acid. Functionalization of this biomass with citric acid was optimized via a Taguchi experimental design and sta tistical analysis based on the Signal-to-Noise ratio calculated for the heavy metal adsorption capacities. The best conditions for biomass surface functionalization were identified where the final adsorbent increased its metal adsorption capacities up to 53% at tested operating conditions. Modeling results based on a statistical physics adsorption model demonstrated that the removal of these cations was multi-ionic at different adsorption temperatures where two functional groups of this biomass participated in the adsorption with different degrees. Biomass characterization results suggested that these functionalities corre sponded to carboxylic and phenolic functional groups. The adsorption 10
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