**Journal of Water Resource and Protection**

Vol.11 No.06(2019), Article ID:93420,21 pages

10.4236/jwarp.2019.116048

Removing Iron Ions Contaminants from Groundwater Using Modified Nano-Hydroxyapatite by Nano Manganese Oxide

Mohammed Abd-El-Aal Ahmed Ayash^{1*}, Tarek Ahmed Seaf Elnasr^{2,3}, Madiha Hassan Soliman^{4}^{ }

^{1}Sohag Company for Water and Waste Water, Dar El Salam, Sohag, Egypt

^{2}Chemistry Department, Faculty of Science, Al-Azhar University, Assiut, Egypt

^{3}Chemistry Department, Collage of Science, Jouf University, KSA

^{4}Chemistry Department, Faculty of Science, Helwan University, Cairo, Egypt

Copyright © 2019 by author(s) and Scientific Research Publishing Inc.

This work is licensed under the Creative Commons Attribution International License (CC BY 4.0).

http://creativecommons.org/licenses/by/4.0/

Received: May 26, 2019; Accepted: June 27, 2019; Published: June 30, 2019

ABSTRACT

In this article, we study modified nano-hydroxyapatite (HAp) by nano manganese oxide (Mn_{3}O_{4}) as adsorbent material to remove iron ions from groundwater. Different parameters were studied to option optimum conditions of removing such as contact time, pH, initial concentration, a dosage of adsorbent, agitation speed and temperature. Kinetics studies included first order (R^{2} = 0.915), pseudo-first order (R^{2} = 0.936), second order (R^{2} = 0.948), pseudo-second order (R^{2} = 0.995), Elovich equation model (R^{2} = 0.977), intraparticle diffusion (R^{2} = 0.946), Natarajan and Khalaf (R^{2} = 0.915) were carried out, the obtained results revealed that the pseudo-second order is the best to describe the adsorption process because the correlation coefficient is approaching one (R^{2} = 0.995). Adsorption isotherm was calculated by using Freundlich, Langmuir and Temkin constants, adsorption capacity from Langmuir model was 0.606 mg/g. Thermodynamic parameters (ΔG, ΔH = −51 KJ/mol, and ΔS = −142 (KJ/mol)) for the adsorption process were also calculated and discussed.

**Keywords:**

Groundwater, Adsorption, Nano Materials, Hydroxyapatite, Manganese Oxide, Iron Ions, Kinetic, Thermodynamic

1. Introduction

Groundwater is an important resource for the livelihoods and food security of billions of people. It is one of the most difficult problems that pollute the groundwater and the presence of iron. Therefore, in this article, we try to find a solution to the problems of iron in the groundwater [1] [2] .

Among the appropriate solutions to remove or reduce the proportion of iron in the groundwater is Ion exchange [3] , Reverse osmosis [4] , Chemical precipitation [5] , Electrolysis [6] and Adsorption [7] , the choice of which depends upon the type and concentration of both sorptive material and sorbent employed, as well as their costs [8] .

Among these, the adsorption method is more commonly used, adsorption is an effective technology to remove different contaminated from aqueous solutions. In this process, a very high rate of adsorption and excretion occurs. The simple function has caused this method to be one of the best ways to remove iron ions from groundwater such as Polyvinyl alcohol was used for removal of bromothymol blue and methylene blue from [9] . Removal of natural organic matter and its constituents from water by metal oxides and hydroxides based adsorbents were investigated [10] . Fluoride removal capacity from drinking water by Adsorption using nano-sized Alumina and Zirconia modified Alumina was tested [11] . Removal of Cu(II) and Zn(II) by unmodified Lignocellulosic Fibrous Layer of Palm Tree Trunk-Single was studied [12] . Removal of Cu(II) ions from water by rice husk (S.E. Abd Elhafez et al. 2016) [13] , Pb (II), La (III), and Ag (I) ions was removed from aqueous solutions using mediated cellulose nanofibers [14] . Adsorptive of ibuprofen and diclofenac from water using metal-organic framework-derived porous carbon was investigated [15] . Removal of Cr(VI) by a free metal material containing only C, N and O, and having environmental friendliness, was studied [16] . Removal of benzotriazole and benzimidazole from water over a Co-based metal azolate framework MAF-5(Co) was investigated [17] .

In this work, we have used modified nano hydroxyapatite by (Mn_{3}O_{4}) nanoparticles to remove the iron ions from water by adsorption; parameters such as contact time, pH, adsorbent dosage, stirring speed and temperature were investigated. Kinetic, Isotherm Adsorption and Thermodynamic parameters (ΔG, ΔH, and ΔS) for adsorption process were also calculated and discussed.

2. Materials and Methods

2.1. Apparatus

We had all the measurements of pH using Misura Line 1010 pH meter (Romania). All samples are stirred and heated by multiple Heating Magnetic Stirrer (VELP Scientifica) during experimental procedures as well, as micropipette (100 - 1000 μL) is also used. Spectrophotometer Instruments (CECIL3021), Brand (Cambridge, England). Determine the iron ions by Phenanthroline method. The samples were first mixed with KBr and then pressed into pellets. X-ray powder diffraction (XRD) data were collected at room temperature using a Philips 1710 Diffractometer. The patterns were run with Cu target and Ni filter (λ = 1.5418 A˚) at 40 KV and 30 mA in the range of 2θ, with a scanning speed of 06 deg/s. Fourier transform infrared spectroscopy (FTIR) data were collected using a Perkin-Elmer spectrometer model 1430 in the wave number range from 4000 to 400 cm^{−1} Examination on the TEM: Samples were examined by carbon coated grids with a JEOL 1010 Transmission Electron Microscope, made in Japan, at the Regional Center for Mycology and Biotechnology (RCMB), Al-Azhar University.

2.2. Procedures

2.2.1. Synthesis of Hydroxyapatite (HAp)

We have prepared HAp powder using the titration between both H_{3}PO_{4}, adwic 85% in burette and CaCl_{2}∙2H_{2}O, Sigma-Aldrich, 99% - 103% in a beaker until adjustment the pH at a value of 10. Through the addition of NH_{4}OH solution (adwic 30%) during the mixing process using a hotplate for heating the reaction mixture and stirring according to the following equation:

10CaCl_{2}∙2H_{2}O+6H_{3}PO_{4} + 20NH_{4}OH → Ca_{10}(PO_{4})_{6}(OH)_{2} + 20NH_{4}Cl + 38H_{2}O (I)

The mixture was heated in a microwave oven for 10 min until completely dryness and formation the precipitate, and then it was washed with distilled water and filtrated. The precipitate dried by microwave for 4 min [18] .

2.2.2. Synthesis of Manganese Oxide

We can manufacture nano-manganese oxide (Mn_{3}O_{4}) by oxidation of MnCl_{2} solution with a concentrated H_{2}O_{2} solution, followed by the addition of an NH_{3} aq. solution. The suspension thus obtained was treated at 90˚C [19] . With microwave for 7 mint to dryness and formation the precipitate, then it was washed with distilled water and filtrated. The precipitate dried by microwave for 3 min.

2.2.3. Synthesis of Modified Hydroxyapatite Manganese Hydroxide (HApMn)

We have been able to prepare three modifications to test the removal of iron ions first (0.04 HAp:0.06 Mn_{3}O_{4}) second (0.06 HAp:0.04 Mn_{3}O_{4}) and the third (0.08 HAp:0.02 Mn_{3}O_{4}). The percentage of removing iron ions were (R%) = 49%, 47%, and 30% respectively. We chose (0.06 HAp:0.04 Mn_{3}O_{4}) R% = 47% and have found that the best modification is. Three composed of Modification of HAp by Mn_{3}O_{4} were prepared and exam to remove iron ions, to complete this study.

2.3. Analytical Methods

Amount of adsorbent of iron on happening at any time (q_{t}) was calculated as follows [8] [9] :

${q}_{t}=\left({C}_{o}-{C}_{t}\right)V/m$ (1)

where, C_{o} and C_{t} are the concentrations of iron ions at initial and equilibrium time, respectively (mg/L), V is the solution volume (L) and m is the mass of dry adsorbent used (g). At equilibrium, q_{e} = q_{t} and C_{t} = C_{e}; therefore, the amount of sorbed metal ion (q_{e}) was calculated according to Equation (2)

${q}_{e}=\text{}\left({C}_{o}-{C}_{e}\right)V/m$ (2)

The removal efficiency (RE%) is calculated according to the following equation [12] :

$\text{RE}\left(\%\right)=\left(\left({C}_{o}-{C}_{e}\right)/{C}_{o}\right)\times 100$ (3)

3. Results and Discussion

3.1. Characterizations

Figure 1(a) shows the FTIR (Fourier transform infrared spectroscopy) of HAp. The broad bands in the regions 1600 - 1700 cm^{−1} and 3200 - 3600 cm^{−1} correspond to H-O-H bands of lattice water. The bands characteristics of the phosphate and hydrogen phosphate groups in apatite environment are observed at 565, 632, 603, 962, and 1000 - 1100 cm^{−1} for
${\text{PO}}_{4}^{3-}$ and at 875 cm^{−1} for
${\text{HPO}}_{4}^{2-}$ [18] .

FTIR of the Manganese Oxide sample is shown in Figure 1(b). Several absorption bands can be observed at 500 - 1000 cm^{−1} for (Mn-O), 3000 - 3500 cm^{−1} stretching, the 1636. While the 606, 564, 510.2 and 417 cm^{−1} bands should be ascribed to the Mn–O vibrations in MnO_{6} octahedral [19] .

FTIR results indicate the presence of some bounded water to HApMn.

Figure 2(a) and Figure 2(b) shows XRD (X-ray Diffraction) patterns of the

(a)(b)

Figure 1. FTIR spectra for (a) HAp and (b) HApMn.

(a)(b)

Figure 2. (a) XRD profiles for prepared HAp; (b) XRD profiles for Mn_{3}O_{4}.

HAp and Mn_{3}O_{4} samples, respectively. The intensive diffraction peaks appeared at 25.9, 28.9, 31, 32.3, 33, 33.9, 36.9, 39.2, 44.3, 46.4, 47.8, 49.5, 51.22, 53.4, 58.4, 60.2, 64.5, 74.4, 76.7 and 55.9 are assigned to the characteristic peaks for Mn-O, and the peaks occurred at respectively, should be ascribed to the characteristic peaks for Mn-O [19] . Hence, the sample appears to be composed of a majority of HApMn. Scherer equation can be written as [7] [20] :

$D=K\lambda /\beta \mathrm{cos}\theta $ (4)

where D is the crystal size (nm), λ is the wavelength of X-ray light, β is the full width of the half maximum of the diffraction peak, and θ is the diffraction angle. Shape factor of K is usually taken as 0.9. It was found that the particle sizes were 4.2 nm and 3.6 nm for HAp and Mn_{3}O_{4}, respectively. The result is tabulated in Table 1.

Figure 3(a) and Figure 3(b) show TEM (Transmission electron microscopy) of HAp profiles and Mn_{3}O_{4} profiles respectively.

3.2. Study of Adsorption Factors

We have used a Patch method for all adsorption work, 100 ml of sample (2- 10) ppm, temperature (25 - 75)˚C, pH (3 - 8), contact time (5 - 90) min, the speed of agitation (100 - 8000) rpm, iron ions concentration was measured before placing

Table 1. Size of HAp and Mn_{3}O_{4} calculate by XRD (Scherer equation) and measured by TEM.

(a)(b)

Figure 3. (a) TEM profiles for prepared of HAp; (b) TEM profiles for prepared Mn_{3}O_{4}.

the adsorbent and after putting them for different samples obtained from different wells as shown in Table 2. Various adsorption parameters for the effective removal of iron ions using modified hydroxyapatite as an adsorbent from aqueous solution were studied and optimized.

3.2.1. Effect of Contact Time

We have studied the effect of contact time in different time periods ranging from 5 to 90 min with the initial metal concentration of 2 ppm iron ions in presence 0.1 g of HApMn with continuous stirring at 400 rpm and at pH 6 [21] . Remove iron ions over time, where it was about 25% in 5 minutes and reached 60% in 90 minutes see Figure 4.

3.2.2. Effect of pH

PH is an important factor in the adsorption process. The pH of 3 - 8 is determined

Table 2. Iron ion concentrations of well samples before and after treatment.

Figure 4. Effect of contact time on iron ions removal using HApMn.

by using 30% ammonia solution or 37% hydrochloric acid solution and the same conditions as above. Note that the increase in pH increases the removal iron ions (see Figure 5). It may be due to precipitation of iron ions as Fe^{+3} hydroxide brown precipitate [22] .

3.2.3. Effect of Agitation Speed

The effect of the stirring speed on the removal of iron ions under the same experimental conditions is studied by agitation Speed (100 - 800) rpm. The efficiency of the removal was found to increase with increased agitation speed (see Figure 6). Iron ions increase the speed of stirring [23] .

3.2.4. Effect of Initial Concentration of Iron Ions

By studying the effect of iron ion concentration per 100 ml, we found that the removal efficiency was reduced by increasing the concentration of iron per 100 ml see Figure 7 [24] .

3.2.5. Effect of Temperature

Under the same experimental conditions the effect of temperature on iron ions removal was studied by varying the temperature from 25˚C to 75˚C. As we see from Figure 8, as the temperature increases the removal percentage increase [25] .

3.2.6. Applications of the Method

Around 100 ml of sample (well water) at pH about 7.4, the temperature at 30˚C, stirring at 400 rpm, stirring time 30 min was used to measure iron ions concentrations.

Figure 5. Effect of pH on iron ions removal using HApMn.

Figure 6. Effect of agitation speed on iron ions removal using HApMn.

Figure 7. Effect of initial concentration on iron ions removal using HApMn.

Figure 8. Effect of temperature on iron ions removal using HApMn.

3.3. Kinetics Modeling

We have done a study the kinetic of adsorption and adsorption rate controls; we found a metal ion uptake rate with a residence time of adsorbate uptake at solid interface solution. We have studied seven equations models, the first-order rate equation, pseudo-first order rate equation, second-order rate equation, pseudo-second order rate equation, intra-particle diffusion, and Elovich equations. See Table 3 for the parameter values.

3.3.1. First Order Kinetic Equation

The equation of a straight line is applicable [12] [26] :

$-\mathrm{ln}\left({C}_{t}/{C}_{o}\right)={K}_{1}t$ (5)

where, C_{t} (mg/L) is the concentration at a given time t and C_{o} (mg/L) is initial concentration of iron ions in solution. K_{1} (min^{−1}) is the first order rate constant. The regression R^{2} obtained by the linear plot of –ln(C_{t}/C_{o}) against t (Figure 9), is shown in Table 3, R^{2} was greater than 0.9, which indicates a good fit to the experimental data.

3.3.2. Second Order Kinetic Equation

The linear version is given by this relationship [12] [26] :

$\left(1/{C}_{t}\right)-\left(1/{C}_{o}\right)={K}_{2}t$ . (6)

where, k_{2} [L/mg/min] is the second order rate constant for the adsorption process, determined from the linear plot of (1/C_{t} – 1/C_{o}) against t, shown in (Figure 10) for iron ions. See Table 3, for the value of the constants. The

Table 3. Summary of kinetic modeling parameters.

Figure 9. First Order Kinetic Equation plot for the adsorption of iron ions on HApMn.

Figure 10. Second order rate equation plot for the adsorption of iron ions on HApMn.

regression value (R^{2}) is greater than 0.9 for iron ions. Indicating that the equation can be applied to experimental data for iron ions.

3.3.3. Pseudo First Order Kinetic Equation

The mathematical relationship to describe the pseudo-motif model proposed by Lagergren is shown in equation [12] [27] :

$\mathrm{ln}\left({q}_{e}-{q}_{t}\right)=\mathrm{ln}{q}_{e}-{K}_{1}{p}_{t}$ (7)

where K_{1} is the rate constant of pseudo-first order adsorption (L/min). q_{e} and q_{t} are adsorption capacity (mg/g) at equilibrium and at any time t, respectively. The value of the constants q_{e}, k_{1} and R^{2} obtained from the linear plot of ln(q_{e} − q_{t}) vs t (Figure 11) are shown in Table 3. The regression rate R^{2} > 0.9 For iron ions.

3.3.4. Pseudo-Second Order Kinetic Equation

The linear relationship of pseudo-second order kinetic model is given by [12] [23] [24] [25] [27] [28] :

$t/{q}_{t}=1/{K}_{2}{q}_{e}^{2}+t/{q}_{e}$ (8)

where K_{2} (g/mg/min) is the rate constant of pseudo-second order adsorption rate constant. The values of k_{2}, R^{2} and q_{e} were calculated from the plots of t/q_{t} on the vertical axis, and t (min) on the horizontal axis (Figure 12) as shown in Table 3. The regression R^{2} > 0.9, for iron meaning that this model provided the best fit for the adsorption data.

Figure 11. Pseudo first-order kinetic plot for the adsorption of iron ions on HApMn.

Figure 12. Pseudo second order rate plot for the adsorption of iron ions on HApMn.

3.3.5. Elovich Equation

The Elovich equation used to describe the kinetics of chemisorption of gas on solids, The linear relationship is given by [12] [23] [24] [25] [27] [28] :

${q}_{t}=\left(1/\beta \right)\mathrm{ln}\left(\alpha \beta \right)+\left(1/\beta \right)\mathrm{ln}t$ (9)

where, the constants α and β were obtained from the slope and intercept of the linear plot of q_{t} (mg/g) against ln(t, min) as shown in (Figure 13), for the adsorption of iron ions on HApMn.

3.3.6. Intra-Particle Diffusion Rate Equation

The intra-particle diffusion equation [12] [28] [29] [30] is given as Equation (10) shown in Figure 14.

${q}_{t}=k{p}_{t}^{1/2}+C$ (10)

where, K_{p} (mg/g∙min^{1/2}) is the intraparticle diffusion rate constant and C is the intercept. by drawing q_{t} on the Y-axis against t (min) on X-axis we can find the slope, intercept and correlation coefficient as seen in Table 3, it was observed that the intraparticle diffusion rate constant increased with an increase in initial concentrations.

3.3.7. Natarajan and Khalaf

Natarajan and Khalaf equation [31] developed a relationship between the initial concentration and concentration at any time. The linear form is expressed as:

$\mathrm{ln}\left({C}_{o}/{C}_{t}\right)={K}_{n}\cdot t$ (11)

Figure 13. Elovich plot for the adsorption of iron ions on HApMn.

Figure 14. Intraparticle diffusion equation plot for the adsorption of iron ions on HApMn.

where, C_{t} is the concentration of iron (mg/L) at time t. The plot of ln(C_{o}/C_{t}) against t will give a straight line and the value of k_{n} can be obtained from the slope of the graph (Figure 15). The values of k_{n} and R^{2} are shown in Table 3. The correlation coefficient R2 for the pseudo second order kinetic model is greater than 0.99.

3.4. Adsorption Isotherms

Adsorption data are generally described by adsorption isotherms, such as Freundlich, Langmuir, and Temkin isotherm models.

3.4.1. Freundlich Isotherm

This model proposes monolayer sorption with a heterogeneous energy distribution of active sites, accompanied by interactions between adsorbed molecules. The general form of this model is presented in the following equation [12] [32] :

${q}_{e}={K}_{F}{C}_{e}1/n$ (12)

The linear form of the Equation (12) is [12] [33] :

$\mathrm{ln}{q}_{e}=\mathrm{ln}{K}_{F}+1/n\mathrm{ln}{C}_{e}$ (12a)

This isotherm relates the amount of solute adsorbed at equilibrium per weight

Figure 15. Natarajan and Khalaf plot for the adsorption of iron ions on HApMn.

of adsorbent where q_{e} (mol/g) to the adsorbate concentration at equilibrium C_{e} (mol/dm^{3}), is the most widely non-linear sorption models used. K_{F} (mg/g) stands for adsorption capacity and 1/n stands for adsorption intensity.

By plotting of lnq_{e} on Y-axis versus lnC on X-axis we can determine K_{F} and 1/n from a slope and intercept respectively (Figure 16).

3.4.2. Langmuir Isotherm

The Langmuir model [8] [26] [29] [32] describes adsorption as a monolayer surface corresponding to solids with identical homogeneous sites. This is according to the following linear relationship:

${C}_{e}/{q}_{e}=1/\left({q}_{\mathrm{max}}b\right)+\left(1/{q}_{\mathrm{max}}\right)C$ (13)

where q_{e} is the amount adsorbed (mg/g), C_{e} is the equilibrium concentration of the adsorbate ions (mg/L), q_{max} and b are Langmuir constants. Where, q_{max} (mg/g) is Langmuir constant related to maximum adsorption capacity (monolayer capacity) andb (L/mg) is the energy of adsorption.

By plotting of C_{e}/q_{e} versus C_{e} should indicate a straight line of slope 1/q_{max} and an intercept of 1/q_{max} b.

Figure 17: shows Langmuir isotherm for iron ions adsorption at various initial iron ions concentrations using HApMn at adsorbent dosage of 0.1 g, agitation speed of 400 rpm, solution pH 6 and temperature of 30˚C. Based on the correlation coefficient (R^{2}) shown in Table 4 the adsorption isotherm can be better described by Langmuir equation. Also, the Langmuir equation yields a better fit of the experimental data than the Freundlich equation. Further, the essential characteristics of Langmuir isotherm can be described by a separation factor R_{L}, which indicates the shape of the isotherm and nature of the adsorption process. this is expressed by the following equation [8] [29] [30] [34] .

${R}_{L}=\left[1/\left(1+b{C}_{o}\right)\right]$ (14)

where C_{o} is the initial concentration of iron ions (mg/L). The separation factor When R_{L} is greater than 1, the process is unfavourable, R_{L} = 1, Linear, 0 < R_{L} < 1, favorable and R_{L} = 0 irreversible. In this study, the Calculated values for R_{L} are

Table 4. Adsorption isotherms constants.

Figure 16. Freundlich isotherm for iron ions sorption on HApMn.

Figure 17. Langmuir isotherm for iron ions adsorption on HApMn.

found to be a fraction in the range of 0 - 1 (0.442), an indication that the adsorption process is favorable [35] .

3.4.3. Temkin Isotherm

The linear form of the Temkin equation is given by [8] [29] [30] [36] :

${q}_{e}=\beta \mathrm{ln}KT+\beta \mathrm{ln}{C}_{e}$ (15)

where, β which is related to the heat of adsorption, and KT (L/mg) is the equilibrium binding constant corresponding to the maximum binding energy. By plotting q_{e} on Y-axis versus on X-axis we can be calculated β and KT calculated from the slope and the intercept. Figure 18: shows Temkin model isotherm for iron ions adsorption at various initial iron ions concentrations using HApMn at adsorbent dosage of 0.1 g, agitation speed of 400 rpm, solution pH 6 and temperature of 25˚C.

3.5. Thermodynamic Parameters

Thermodynamic parameters [37] such as and entropy (ΔS), enthalpy (ΔH) and free energy (ΔG) were determined using Equations (16)-(19):

Figure 18. Temkin model plot for Adsorption of iron on HApMn.

${K}_{c}={q}_{e}/{C}_{e}$ (16)

$\Delta G=-\text{}RT\mathrm{ln}{K}_{c}$ (17)

$\text{Ln}{K}_{c}=\left(-\Delta H/R\right)\left(1/T\right)+\Delta S/R$ (18)

where q_{e} is the amount of solute adsorbed on the adsorbent cubic decimeter of the solution at equilibrium, K_{c} is the equilibrium constant, and C_{e} (mol/dm^{3}) is the equilibrium concentration of the solute in solution, T is temperature in Kelvin and R (8.314 J/K/mol) is the gas constant. By plotting of on Y-axis against 1/T on X-axis we found ΔH and ΔS were obtained from the slope and intercept of Vant Hoff isotherm (Figure 19). Table 5 shows the calculated values of the thermodynamic parameters.

In order to understand this process better, we must calculate the entropies and enthalpies of temperature periods using the previous equations [32] [38] :

$\Delta G\u02da=\Delta H\u02da-T\Delta S\u02da$ (19)

where, K_{c}_{1} is the equilibrium constant at temperature T_{1} and K_{c}_{2} are the equilibrium constant at temperature T_{2}.

Increasing the value of ΔG˚ with increasing temperature leads to the process of adsorption of iron ions on HApMn become preferred in low temperatures. The negative value of ΔH˚ proves that the adsorption process was exothermic reaction and a certain amount of heat developed during the iron ions that adsorbed on the surface of the adsorbents. The more negative value of ΔS˚, the more degree of randomization in the solid/liquid interface during the absorption process where entropy expresses the amount of randomness or disorder in the system.We used entropy (ΔS˚) to determine the degree of disorder or randomness in the system. We know that the higher the negative values of ΔS˚, the lower the degree of randomization in the solid/liquid interface during the adsorption process [39] . The values of ΔH˚ and ΔS˚ calculated from the plot of lnK versus 1/T.

The value of ΔH˚ was negative, indicating that the adsorption reaction was exothermic (high heat of adsorption). Another equation that has been used to determine the possible adsorption mechanism is the Dubinin-Radushkevick

Table 5. Thermodynamic parameters for adsorption of iron ions on HApMn.

Figure 19. Thermodynamic model plot for Adsorption of iron ions on HApMn.

Figure 20. Dubinin-Radushkevick equation plot.

[40] equation, which assumes a constant sorption potential. The linear presentation of this equation is expressed by

$\mathrm{ln}{q}_{e}=\mathrm{ln}{q}_{m}-{K}_{E}{\epsilon}^{2}$ (20)

$\epsilon =RT\mathrm{ln}\left(1+1/{C}_{e}\right)$ (21)

where ε is the Polanyi potential, q_{t} is the monolayer capacity (mol/g), C_{e} is the equilibrium concentration (mol/dm^{3}), and K_{E} is the constant related to sorption energy (mol^{2}/KJ^{2}) The parameters q_{t} and K_{E} can be obtained from the intercept and slope of the plot as shown in Figure 20. The free energy of sorption (E) is calculated by

$E=1/{\left(-2{K}_{E}\right)}^{1/2}$ (22)

Adsorption type could be estimated by evaluating of E value. If this value is < 8, 8 - 16 or >16 kJ/mol, the adsorption type can be explained by physical adsorption, ion-exchange, or chemical adsorption, respectively [41] . In this case, the adsorption is chemical adsorption at all temperatures because E value was 50 kJ/mol.

4. Conclusion

In this article, we use Modified HApMn for removing iron ions from groundwater. Adsorption of iron on HApMn follows pseudo-second order kinetic model, Langmuir adsorption isotherm, Adsorption capacity from the Langmuir model is 0.604 mg/g, the adsorption process is chemical type because adsorption energy value is 50 kJ/mol, and adsorption is favorable at low temperatures, the negative value of ΔH˚ confirms that the sorption process is exothermic in nature and a given amount of heat is evolved during the binding iron ions on the surface of adsorbents.

Acknowlegements

It is my pleasure to express my deepest thanks to Chemistry Department, Faculty of Science, Helwan University, my thanks to Chemistry Department, Faculty of Science, Al-Azhar University, Assiut Branch, for his support and I thank Sohag Company for Water and Waste Water, Dar El Salam, Sohag, Egypt.

Conflicts of Interest

The authors declare no conflicts of interest regarding the publication of this paper.

Cite this paper

Abd-El-Aal Ahmed Ayash, M., Elnasr, T.A.S. and Soliman, M.H. (2019) Removing Iron Ions Contaminants from Groundwater Using Modified Nano-Hydroxyapatite by Nano Manganese Oxide. Journal of Water Resource and Protection, 11, 789-809. https://doi.org/10.4236/jwarp.2019.116048

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