Modeling of ammonia removal from wastewater using air ...

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International Journal of Environmental Science and Technology https://doi.org/10.1007/s13762-021-03353-8

ORIGINAL PAPER

Modeling of ammonia removal from wastewater using air stripping/modified clinoptilolite: reusability, optimization, isotherm, kinetic, and equilibrium studies

R. Fathi1 · P. Mohammadi2  · S. A. Hosseini1 · F. Yosefvand3 · H. Norouzi1

Received: 2 December 2020 / Revised: 14 April 2021 / Accepted: 22 April 2021 © Islamic Azad University (IAU) 2021

AbstractExcess chemical and natural fertilizer could create eutrophication of surface waters and then depletion of the quality of water. The present study aimed to survey the removal efficiency of ammonia from aqueous solution using modified clinoptilolite and air stripping process and optimization of variables by response surface methodology. Clinoptilolite was obtained from Semnan (Northeast of Iran) and modified with sodium chloride (to create an adsorbent uniform) and ferric chloride (due to three valent of iron) as an efficient and simple method. The modified clinoptilolite was characterized by scanning electron microscopy, X-ray diffractometer, X-ray fluorescence, and Fourier transform infrared spectroscopy. Employing modified clinoptilolite as an adsorbent for ammonia removal showed that by increasing adsorbent dose, contact time, and pH and decreasing initial ammonia concentration, ammonia removal efficiency has been increased. In the optimum condition, modi-fied clinoptilolite was able to adsorb ammonia as high as 86.04% at an adsorbent dose of 1 g/L, pH of 5, a contact time of 3.7 h, and an initial ammonia concentration of 13.27 mg/L. Also, the sorption capacity of ammonia at the optimum condition of air stripping was 96.14%. This process can properly treat the effluent of stabilization ponds as real wastewater (about 70% for ammonium removal), and the order of reduction effect for cations includes K+ > Ca2+ > Na+ > Mg2+, respectively. The findings showed that ammonia removal followed the Freundlich isotherm and intraparticle diffusion kinetic model. Accord-ing to the obtained results, as an effective and reusable adsorbent, modified clinoptilolite can be appropriately employed for ammonia removal from wastewater.

Keywords Ammonia removal · Eutrophication · Modified clinoptilolite · Optimization · Air stripping · RSM

Introduction

Nitrogen, potassium, and phosphorous are the main required elements for the growth of plants which generates with live-stock as well as agricultural activities and refrigerant. Excess chemical and natural fertilizer could create eutrophication of surface waters and then depletion of the quality of water. Besides, phosphorous and nitrogen compounds could con-taminate the underground waters (De la Torre-Velasco et al. 2013; Montégut et al. 2016; Gholami et al. 2018). Excessive concentration of nitrogen compounds especially ammonia and nitrate makes them toxic compounds. Exposure to the 500 mg/L for 30 min and 3400 mg/L for 60 min could cause irreversible and fatal effects on humans, respectively (Adam et al. 2020).

Ammonia could be harmful to organisms at concentra-tions more than 2 mg/L based on NH3-N which depends on the environmental parameters. Ammonia in the aquatic

Editorial responsibilty: J Aravind.

* P. Mohammadi [email protected]

1 Department of Environmental and Natural Resources, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran

2 Department of Environmental Health Engineering, Research Center for Environmental Determinants of Health, School of Public Health, Kermanshah University of Medical Sciences, Kermanshah, Iran

3 Department of Water Engineering, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran

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environment can be converted to nitrite and nitrate that is significantly influenced by temperature (Al-Sheikh et al. 2021).

Several methods have been taken for nitrogen compound removal from aqueous solutions such as biological treatment (nitrification/denitrification process) (Adam et al. 2020; Mir-zaei et al. 2019), ion exchange (De la Torre-Velasco et al. 2013), chemical treatment, breakpoint chlorination (Al-Sheikh et al. 2021), adsorption, and air stripping (Adam et al. 2020). The removal efficiency of these processes is critically affected by environmental factors such as tempera-ture and pH and process cost because the treatment process is complicated (Adam et al. 2020; Elwakeel et al. 2017; Montalvo et al. 2014).

Because of simplicity, easy operation, and not producing by-products, adsorption has been widely used in the com-parison of other methods (Elwakeel et al. 2021; Elwakeel 2020). Besides, the modified sorbents are versatile and cost-competitive for removing organic and inorganic pollutants from waters, and different industrial applications have been recently reported. Modified adsorbent could improve the adsorption capacity and cause to conversion of the adsor-bent to selective ions (Elwakeel et al. 2012, 2020a, b). Some materials have been used for the adsorption/ion exchange of ammonia from various wastewaters. Some resins such as Purolite and Dowex were found (Al-Sheikh et al. 2021). On the other hand, zeolites like clinoptilolite have many attrac-tive properties for the removal of ammonia from aqueous solution due to high inorganic ions and durability at high temperatures and pH variations. In addition, other aspects of nitrogen removal have been expanded; (i) modifying the zeolite with various methods and (ii) using two processes simultaneously as continuous mode (zeolite and air striping) (Al-Sheikh et al. 2021; Elgarahy et al. 2019).

There are many zeolites synthesized and naturally found in the world. Zeolites could be more attractive for the removal of nitrogen compounds from aqueous environments due to high surface area and cation exchange selectivity and hydrated porous structure. For instance, clinoptilolite presents an alu-minosilicate structure with calcium, potassium, and sodium cations which could be used for the adsorption of ammonium ions and showed high selectivity for ammonium (Dashti et al. 2020; Widiastuti et al. 2011). Clinoptilolite is a harmless, odorless, and flavorless zeolite and can be easily dehydrated/hydrated (Özogul et al. 2016). In addition, clinoptilolite could be employed as a continuous or column mode which might be led to a decrease in the loss of adsorbent (Adam et al. 2020). It was found that chemically modified zeolite was properly employed for the treatment of swine wastewater. The zeolite used for this aim was firstly modified with MgO, and optimum

conditions were an adsorbent dose of 12 g/L, a contact time of 55 min, and a pH of 8.3 (Aghel et al. 2020; Guo et al. 2013). Besides, synthesized and modified zeolite with sur-factant (hexadecyltrimethylammonium (HDTMA)) was used for humic acid removal from water. Zeolite modified showed a large adsorption capacity for humic acid, and maximum adsorption rate was obtained at low (acidic) pH. Based on the study, zeolite modified contains iron oxide which can increase the removal efficiency (Li et al. 2011). Also, it was reported that potassium permanganate could not improve the capac-ity of natural zeolite for the adsorption of ammonium. This phenomenon could be associated with variations of the pore condition on the zeolite surface (Guo et al. 2016). Malovanyy et al. (2013) investigated the synthetic and natural zeolites for ammonium removal using packed-bed columns. The removal efficiency of ammonium was higher than 95% (Malovanyy et al. 2013).

Also, air striping as a simple and low-cost technology could be used in combination with the adsorption process for the removal of ammonia from wastewater. In the air striping, the mass transfer is taken place and nitrogen compounds have transferred to the air as ammonia. The rate of ammonia trans-ferred to the air depends on the temperature, pH, gas pressure, liquid quality, thermodynamic equilibria, etc. Packed tower could be applied as an air striping for accelerating the mass transfer area (Bonmatı́ and Flotats 2003; Quan et al. 2009).

Min-HaoYuan et al. studied ammonia removal using air stripping through a rotating packed-bed reactor. The results showed that high removal efficiency of ammonia was obtained at alkaline pH (Yuan et al. 2016). Shaohua Yin and et al. inves-tigated the ammonia removal efficiency using air stripping and microwave heating. The results of this study represented that combination of air stripping with microwave heating could improve the ammonia stripping at a short time and small size (Yin et al. 2018b).

Optimization of the operational factor through response surface methodology (RSM) for ammonia removal is another aim of this study. The reverse of the conventional optimiza-tion method, RSM as an empirical and mathematical method considers all operational variables as simultaneously (Jahan-giri et al. 2019), investigates the interaction of variables and response (removal efficiency) and sets the minimum runs for ammonium removal (Ghadiri et al. 2020; Khazaei et al. 2016). The present study was aimed to investigate and optimize the hybrid of adsorption and air stripping process for removal of ammonium and then employ them for real wastewater. Besides, the optimization of effective variables, determina-tion of kinetic and isotherm models, and desorption study were surveyed in this study.

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Materials and methods

Characteristics and experiments

To achieve the modification effect on the adsorbent and chemical characteristics, Philips X’Pert X-ray Diffractom-eter with Cu-Kα radiation and Oxford (ED2000) XRF equip-ment were used for the determination of the pattern of the adsorbent X-ray diffraction (XRD) and X-ray fluorescence spectrometry (XRF), respectively. The analysis was carried out at 40 kV and 20 mA, λ = 1.5418 A within 2 theta from 10° to 70°. The morphological characteristics of natural and modified zeolites were surveyed through scanning electron microscopy (SEM) with a scanning electron microscope (Mira 3 Tescan, Czech Republic). Also, the surface func-tions were determined with FTIR analysis (PerkinElmer, USA). The amount of ammonium and sodium was measured with HACH-USA and Flame Photometer (Evans Electrose-lenium LTD, Halstead Essex England). Ammonia concentra-tion was measured using HACH-USA. Also, the total CEC and external CEC (ECEC) of Semnan clinoptilolite rich tuff were determined by Haggerty and Bowman method (Hag-gerty et al. 1994).

Zeolite preparation

Zeolite was obtained from Semnan Province (northeast of Iran) and meshed with standard ASTM Mesh. Then, 500 g of zeolite was repeatedly washed with deionized water and dried at ambient air and oven at 100 °C for 1 h. After that, dried zeolite was soaked at HCl (1 N) for 48 h to achieve a uniform and homogeneous zeolite. Finally, the zeolite was washed with deionized water and dried in the oven for 24 h.

Zeolite modification

Sodium chloride (NaCl) modification

After the initial preparation of the adsorbents, 500 g of pre-prepared zeolites was placed in 1000 mL of NaCl solution (1 M) and was mixed with a shaker for 24 h at 150 rpm. Then, the modified zeolite was dried in an oven at 100 °C for 24 h.

Iron chloride modification (FeCl3)

At this stage, iron chloride (III) was used to improve the adsorbent and increase the adsorption amount and capac-ity and ion exchange capacity due to the high valent of iron chloride (III) and high penetration of the adsorbent. Therefore, 500 g of pre-prepared zeolites was contacted in 1000 mL of iron chloride (0.1 M) and mixed with a shaker

for 24 h at 150 rpm. In the next step, the adsorbents were dried in an oven at 100 °C for 24 h. The prepared zeolite was expected to have good surface properties and be able to adsorb large amounts of cations.

Experiments

This study was conducted at a semi-pilot scale with two processes (adsorption and air stripping). The semi-pilot properties used in this study are shown in Table 1. Also, the schematic of the semi-pilot used for the adsorption and air stripping process is shown in Fig. 1.

Experimental design

Response surface methodology is a statistical and math-ematical method that can be used for the determination of the interaction effects of variables on removal efficiency. Design-Expert® software (version 9) has been employed for experimental design and data analysis. The independent variables for both processes (adsorption and air stripping) of the study as a full factor for experimental design are shown in Table 2. The calculation of coded values for a variable was carried out as the following equation:

Table 1 Pilot properties used in this study

Parameter Characteristics

Adsorption pilot Type Pyrex (glass) Shape Cylinder Height 100 cm Adsorbent height 80 cm Diameter 10.5 cm Total volume 7.85 lit Effective volume 6.28 lit Adsorbent Iranian Clinoptilolite

Air stripping pilot Type Pyrex (glass) Shape Cylinder Height 100 cm Adsorbent height 40–80 cm Diameter 10.5 cm Total volume 7.85 lit Effective volume 6.28 lit Air compressor AC328 (china) Air capacity 150 lit/min Centrifuge pump 100 lit/min

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where the variable coded value represents Xi, X0, and X1 are the variable uncoded value and the variable uncoded value at the center point. It merits to mention that ammo-nium chloride (NH4Cl) was used for stock preparation. In this design, one star block, one cube block and two blocks, total 30 experimental runs were applied.

Regeneration study

Adsorption test: first cycle

In this stage, 25 mL of an aqueous solution with a certain concentration of ammonium ions was made in the clinoptilo-lite dispersion. The adsorbent dose in this stage was about 400 mg/L, the initial concentration (C0) of 60 mg/L, the pH solution of 5, the contact time of 5 h, and the mixing speed of 150 rpm. After the adsorption time, the adsorbent was

Xi =X0− X

1

ΔX

Fig. 1 Schematic of the semi-pilot used in this study

Table 2 Experimental ranges of the independent variables used in this study

Factor Range

Adsorption process Contact time (h) 1–5 pH 5–9 Adsorbent dose (g/L) 1–10 Initial concentration (mg/L) 10–60

Air stripping process Initial concentration (mg/L) 10–60 Aeration time (h) 1–4 pH 7–11 Aeration rate (L/min) 2–4

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separated from the aqueous environment and the residual concentration of ammonia was measured.

Desorption test: first cycle

The adsorbent resulted from the adsorption test (first cycle) was washed with enough deionized water, and then, 25 mL of sodium chloride (0.1 M) was added to the container con-taining the saturated adsorbent from the ammonium ion (adsorbent from the first cycle of adsorption test). The mix-ture was agitated for 5 h at 150 rpm, and then, the solid phase separation was taken place. Finally, the residual concentration of ammonium in the solution (Cdesorbed) was measured.

Adsorption/desorption stages—second to fifth cycle

The adsorbent used in the first cycle was selected and used for the second cycle without any changes. In this stage, 25 mL of the aqueous solution containing ammonium ions (with conditions described at the first adsorption cycle; contact time: 5 h; pH: 5, C0: 60 mg/L and adsorbent dose: 400 mg/L and mixing speed: 150 rpm) was chosen to per-form from the second cycle to fifth steps. Finally, the results were compared with the initial results.

Effluent treatment of adsorbent recovery

To evaluate the effect of air stripping (without adsorption process) at high concentrations of nitrogen compounds resulted from the effluent from zeolite, the effluent of adsor-bent recovery was treated with the air stripping process. It should be noted that the operating conditions were obtained from the optimal parameters.

Evaluation of the adsorption process and air stripping on real wastewater

The ultimate goal of studying any type of research is the application of it in real conditions. Therefore, it was decided to test the optimal conditions of the experiment on real wastewater. For this purpose, the effluent from the waste-water treatment plant (stabilization pond method of Karaj wastewater plant) was employed at optimal conditions. The characteristics of the effluent of the stabilization pond used in this study are shown in Table 3.

Data analysis was also performed using Design-Expert software, and then, parameter optimization was done. It should be noted that all experiments were performed at 25 °C. The amount of ammonia removal was obtained using the following equation:

where R is the efficiency of ammonia removal (%) and Cf and Cp represent the concentration of pollutants (mg/L) in the input and output flows, respectively.

Isotherm and kinetic study

Adsorption isotherm tests were conducted at 25 °C. To deter-mine the isotherm model, 25 mL of solutions with various concentrations of ammonia was used at optimum conditions obtained from the optimization study. The main isotherms (Langmuir and Freundlich models) in the researches were used to evaluate the qualitatively and quantitatively adsorption of ammonia onto modified clinoptilolite.

The importance of reactions that occurred in the process and understanding the adsorbate removal onto the adsorbents was determined through the adsorption kinetics modeling. The most famous kinetic models (pseudo-first, pseudo-second models, Elovich, and intraparticle models) were used for the evaluation of ammonia removal onto clinoptilolite.

R(%) =Cf − Cp

Cf

× 100

Table 3 Characteristics of effluent wastewater from stabilization ponds used in this study

Parameter Unit Value

pH – 7.6 ± 0.3BOD5 mg/L 85 ± 5COD mg/L 187 ± 7.5Ammonia nitrogen mg/L 53.9 ± 3.4Organic nitrogen mg/L 3.45 ± 0.3TKN mg/L 57.4 ± 2.5Ammonia mg/L 0Nitrate mg/L 0Nitrite mg/L 1.25 ± 0.1Fat and grease mg/L 0TSS mg/L 239 ± 8.8Phosphate mg/L 0Sulfate mg/L 178 ± 9.2Calcium mg/L 74 ± 6.7Magnesium mg/L 30.64 ± 2.8Sodium mg/L 0Surfactant mg/L 0TDS mg/L 849 ± 16.7

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Results and discussion

Zeolite modification

At this stage, various chemicals such as sodium chloride and iron chloride were used to modify or improve the natural zeolite. The greatest impact of these materials on the raw zeolite was related to iron chloride, which can be attributed to the unoccupied external orbital (d) and the availability of this orbital in the iron cation. Besides, zeolite modified with iron chloride (III) has a stronger cation bond and therefore can remove various contaminants. The results of this study with the results of PAHs removal have also been confirmed (Faghihian and MOUSA 2007).

Also, the presence of cavities on the surface of zeolites can be the reason for increasing efficiency. In this way, the cations with ferrous salts can move toward the zeolite cavi-ties and conduct the cations into the zeolite to the surface. These surface cations could bond with ammonia ions on the surface of the zeolite. The effectiveness of the phenomenon depends on the KSP of that cation. The higher the ion KSP, the higher the reduction rate. But the solubility of metal salts in water also impacts the removal efficiency. Because the KSP of iron salts is higher than other cations, its adsorption capacity is also higher than other ions. Therefore, according to the obtained results, the zeolite modified with iron chlo-ride was selected and used in the next experiments.

Characteristics

The results of the CEC and ECEC for raw and modified zeolites are presented in Table 4. As can be seen, the amount of CEC and ECEC for different zeolites depends on various factors such as sizes. It can be observed that the modified zeolite with ferric chloride has the highest adsorption sites

and the highest cation exchange ability. Also, the cation exchange capacity of the clinoptilolite zeolite sample used in this study is compared with the zeolite samples reported from other parts of the world. Therefore, it can be concluded that the samples of Iranian zeolites have very good adsorp-tion characteristics and high cation exchange capacity. Also, the modified zeolites used in this study had a very high capacity in cation exchange compared to the natural sam-ples due to having the highest amount of CEC and ECEC.

The results of the XRD images are shown in Fig. 2a and b. Based on the XRD analysis and comparison with zeo-lite standard pattern, the predominant component of zeolite is clinoptilolite mineral and there are minor impurities of feldspar and mordenite. A comparison of the XRD pat-tern of modified zeolite with iron chloride and the standard sample also showed that the modified zeolite is consistent with standard samples. Adsorbents prepared in this study which are calcined at below 700 °C, had regular crystals. Therefore, the optimum temperature for zeolite calcification is 650 °C.

As is clear from the XRF, the chemical formula of zeolite is KNa2Ca2(Si29A17)O72,24H2O which its largest component is silica (67.3%). Other predominant compounds are Al2O3, CaO, and Na2O. This soil has an aluminosilicate structure, which has been modified by iron chloride to adsorb ammo-nia. Table 5 compares the results of the chemical composi-tion of studied clinoptilolite zeolite with other samples of clinoptilolite zeolites reported in different parts of the world. Also, it can be concluded that the zeolite sample used in this study is quite similar to the world-classified sample of clinoptilolite zeolites.

SEM images provide information on surface properties, shape, size, and how particles are placed at the surface of zeolites. The morphology of the zeolite surface is observed by SEM in Fig. 2c and d, and the nested and porous structure

Table 4 The results of CEC and ECEC for various zeolites

Zeolites CEC (meq/g) ECEC (meq/g) References

Turkish Clinoptilolite 1.6–1.8 – Alpat et al. (2008)Brazilian Mordenite 2.29 – Wang and Peng (2010)Italian Philisit + Chabazite 2.12 – Passaglia et al. (1990)Turkish Clinoptilolite 1.84 – Karadag et al. (2006)Chinese clinoptilolite 1.03 – Du et al. (2005)Chili Clinoptilolite and mordenite 2.05 – Englert and Rubio (2005)Iranian Clinoptilolite and mordenite 2.61 – Malekian et al. (2011)Croatia Clinoptilolite 1.45 – Farkas et al. (2005)Ukraine Clinoptilolite 1.64 – Sprynskyy et al. (2005)Australian Clinoptilolite 2.20 – Wang and Zhu (2006)Clinoptilolite 2.09 0.03 This studyClinoptilolite modified with NaCl 2.68 0.15 This studyClinoptilolite modified with FeCl3 6.55 1.74 This study

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of the zeolite shows the unique structure of this adsorbent and its high ability of it for the adsorption of ammonia. The position of the peaks seen in Fig. 3c and d which include

SiO2 compounds, indicates the structural foundations of zeolite.

The results of the FTIR analysis are shown in Fig. 2e. As can be seen, the modification of zeolite has led to

Fig. 2 XRD analysis for a natural and b modified zeolites with FeCl3; c and d SEM images for modified clinoptilolite; and e FTIR analysis for raw clinoptilolite (CP-original), modified with NaCl (CP-Na), and FeCl3 (CP-Fe)

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changes in the peaks obtained by FTIR. In the FTIR spec-trum, a sample of natural zeolite is observed at a peak of 1079 cm which is related to asymmetric tensile vibrations (Si–O).

Experimental design and modeling

Central composite design (CCD) is one of the most widely used methods of response surface methodology (RSM) that determines the interactions between variables and the appro-priate process response. The number and order of experi-ments were designed and proposed according to the CCD. Table 6 shows the results of the experimental design for the adsorption of ammonia onto the modified clinoptilolite. As observed in this table, the highest and lowest removal effi-ciency of ammonia was 100 and 5.66%.

Table 7 shows a one-way ANOVA model for operating parameters of ammonia removal onto modified clinop-tilolite. The confidence interval (CI) in this study was considered to be 95%. Therefore, P values is significance by the value of less than 0.05. The value of lack of fit (LOF) was 0.07 which is not in the significant range. The significant P values and the insignificant values of LOF for model represent that employing designed model could be used to interpret the adsorption of ammonium into

modified zeolite. All variables studied in this study were significant in the model. The value of R2 in the model was 0.96. The small difference between the adjusted R2 and R2 predicted by the model indicated that the model is appro-priate. If the size of sample has been small and various terms include in the model, the adjusted correlation coef-ficient could show the values significantly smaller than the multiple correlation coefficients. In this study, the value of adjusted correlation coefficient is considerably support the high significance of the model. The values of Prob > F lower than 0.05 referring to all the model terms are individually significant. The larger values of the F values in companion with the smaller P values present the more significant of the corresponding coefficients. Therefore, based on the P and t value, time initial con-centrations of ammonium can be selected as the main effective variables on the removal of ammonium.

In addition, the results of the design performed to remove ammonia using air stripping are shown in Table 8. Based on the results, as the contact time and pH increase, the removal efficiency of ammonia increases, which showed the effect of these two important factors on the efficiency of ammonia removal through air stripping.

In addition, the results of modeling the air stripping process to remove ammonia based on the quadric model

Table 5 Comparison of chemical composition (%) of clinoptilolite zeolites reported in other studies with clinoptilolite samples in this study

* Loss of ignition

Zeolite Chemical composition (%) References

SiO2 Al2O3 CaO K2O Na2O Fe2O3 MgO TiO2 LoI*

Turkish Clinoptilolite 70.90 12.4 2.54 4.46 0.28 1.21 0.83 0.089 – Alpat et al. (2008)Iranian Clinoptilolite 70 10.46 0.2 4.92 2.86 0.46 – 0.02 – Ashrafizadeh et al. (2008)Cuban Clinoptilolite 62.36 13.14 2.72 1.2 3.99 1.63 1.22 – – Cabrera et al. (2005)Turkish Clinoptilolite 69.72 11.74 2.3 4.14 0.76 1.21 0.31 – – Favvas et al. (2016)Chinese Clinoptilolite 65.52 9.89 3.17 0.88 2.31 1.04 0.61 0.21 – Mirahsani et al. (2019)Clinoptilolite + mordenite 67 13 3.2 0.45 2.6 2 1.69 0.2 – Zieliński et al. (2016)Turkish Clinoptilolite 69.31 13.11 2.07 2.83 0.52 1.31 1.13 – – Azogh et al. (2019)Croatian Clinoptilolite 46.93 13.39 2 1.3 2.4 2.07 1.08 – – Mazeikiene et al. (2016)Clinoptilolite + mordenite 66.5 11.81 3.11 3.12 2.01 1.3 0.72 0.21 – Shaban et al. (2017)Turkish Clinoptilolite 64.99 9.99 3.51 1.95 0.18 3.99 1.01 – – Atallah et al. (2019)Chinese Clinoptilolite 68.27 7.48 2.61 1.69 0.68 1.95 1.87 – – Ji et al. (2007)Turkish Clinoptilolite 70 14 2.5 2.3 0.2 0.75 1.15 0.05 – Karadag et al. (2007)Chinese Clinoptilolite 69.5 11.05 2.95 1.13 2.95 0.08 0.13 0.14 – Wang et al. (2006)Ukrainian Clinoptilolite 67.29 12.32 3.01 2.76 0.66 1.26 0.29 0.26 – Korkuna et al. (2006)Slovakian Clinoptilolite 67.1 12.3 2.91 2.28 0.66 2.3 1.1 0.17 – Pilchowski and Chmielewská (2003)Croatian Clinoptilolite 55.8 13.32 5.75 2.35 3.9 1.3 0.7 – –- Sharma and Katoch (2019)Ukrainian Clinoptilolite 66.7 12.3 2.1 2.96 2.06 1.05 1.07 – – Sukor et al. (2017)Australian Clinoptilolite 68.26 12.99 2.09 4.11 0.64 1.37 0.83 0.23 – Wang and Peng (2010)Ave 65.9 11.93 2.71 2.49 1.65 1.46 0.93 0.16 – –*Raw clinoptilolite 67.35 10.90 1.24 4.39 3.71 0.88 1.21 0.33 9.99 This study**Modified Clinoptilolite with FeCl3 46.35 14.14 0.19 0.09 9.65 9.65 4.03 1.08 14.82 This study

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are shown in Table 9. Based on the results, most of the variables were significant and time and concentration vari-ables were more important (minimum p value). But the interactions of the variables were not significant except for time and concentration. The value of the lack of fit vari-able in this model was not significant (p value: 0.08) which indicates that the model is suitable for predicting results. Also, the regression coefficient of R2 predicted was close to the adjusted R2 which is another reason for the suitable model for predicting results.

The normal plot of residual data for both processes (adsorption and air stripping) is shown in Fig. 3a and b. According to the results, residual data had a negligible distribution, changed in close to the linear line, and rep-resented an S shape. Therefore, data had a normal distri-bution and could use a systematic test for interpretation of them. Also, the results obtained from the model were

plotted against the results of the experiment to observe the conformity of the obtained results (Fig. 3b and c). The results indicated that the results obtained are close to each other and it can be assured that the model has been able to properly predict the data and the results of the model can be trusted.

Investigation of the experimental parameters

The effect of contact time

Investigation of the effect of contact time on ammonia removal showed that efficiency increases with increasing contact time. It should be noted that the equilibrium time for ammonia removal was obtained to be 3.7 h. Besides, the results showed that the adsorption rate increases significantly at the initial contact time. This high initial removal rate can

Fig. 3 Normal plot of residuals for a adsorption process, b air stripping and plot of experimental values versus predicted model values for c adsorption process, d air stripping

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be attributed to the gradient of the concentration created between the ammonia molecules and the availability of the adsorption sites on the modified zeolites with iron chloride. The maximum removal efficiency for modified clinoptilolite with sodium chloride was 79.36%. This amount for modi-fied zeolite with iron chloride was greater than modified zeolite with NaCl (94.40%). The results of this study were consistent with studies on the uptake of various pollutants by clinoptilolite. It was found that the equilibrium time for the removal of MTBE using various modified clinoptilolites was 4 h (Ghadiri et al. 2012).

The effect of pH on adsorption rate

The efficiency of ammonia removal was investigated with modified zeolites at different pH. Based on the results, the maximum adsorption of ammonia was obtained at high pH. It could be because the weak positive charge of non-polar

compounds is maximum at low pH and this low surface charge decreases rapidly with increasing pH (Wang and Peng 2010). Also, zeolites are stable at different pH ranges with high and low ionic strengths, and desorption phenom-enon has rarely been reported in these circumstances (Ji et al. 2007). It is, therefore, possible that surface factors attach the surface of the zeolites at high pH and this issue can cause a sudden increase in the concentration of ammo-nia on the zeolite. However, in this study, the adsorption of ammonia increases with increasing pH and reaches its maximum at pH equal to 11. Also, hydrogen ions (H+) can act as a competing ion for the adsorption of ammonium and can occupy some zeolite sites at acidic pH. The high efficiency of the clinoptilolite at high pH has also caused the pollutant particles to bond at the specified adsorbent sites (Susanne and Colin 2018). The results of the interac-tion effect of efficient variables using the adsorption study are shown in Fig. 4.

Table 6 Details of experiments obtained central composite design (CCD) for adsorption pilot

Run Factor 1 Factor 2 Factor 3 Factor 4 Response 1 Response 2A: D (gr/L) B: pH C: T (h) D:C (mg/L) NH3 OUT (mg/L) NH3 removal (%)

1 5. 5 7 3 60 32. 58 45. 682 10 9 1 60 49. 53 17. 453 5. 5 7 3 10 2. 34 76. 534 1 5 5 60 16. 14 73. 095 1 9 5 60 21. 83 63. 616 10 5 1 60 43. 56 27. 387 5. 5 7 3 35 9. 21 73. 668 5. 5 7 3 35 10. 08 71. 189 10 7 3 35 8. 42 75. 9210 1 9 1 10 7. 47 25. 2511 5. 5 7 3 35 8. 62 75. 3612 1 7 3 35 12. 26 64. 9413 5. 5 7 1 35 23. 65 32. 4114 5. 5 9 3 35 13. 09 62. 5915 1 9 1 60 56. 60 5. 6616 10 9 1 10 6. 35 36. 4817 10 5 5 60 9. 99 83. 3418 5. 5 7 3 35 9. 86 71. 8219 5. 5 5 3 35 8. 75 74. 9920 5. 5 7 5 35 3. 94 88. 7221 1 5 1 10 5. 80 41. 9722 10 5 5 10 0 10023 1 5 5 10 0. 43 95. 6024 5. 5 7 3 35 8. 23 76. 4725 1 5 1 60 52. 60 12. 3226 10 9 5 10 0. 09 99. 0127 10 5 1 10 5. 03 49. 6828 10 9 5 60 17. 39 71. 0029 1 9 5 10 1. 12 88. 7530 5. 5 7 3 35 8. 77 74. 93

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Effect of initial concentrations of adsorbate on ammonia removal

The study of the effect of different initial concentrations in various conditions designed by the software was analyzed. Based on the findings, the removal capacity increases with increasing the initial concentration of ammonia, which can be due to the higher available adsorption-free sites and ion exchange bands at low ammonia concentrations. The results showed that the adsorption with clinoptilolite modi-fied with ferric chloride reached equilibrium after 180 min. Besides, various studies showed that the maximum adsorp-tion rate occurs at the first 30 min for natural or synthetic zeolites (Aharia et al. 2019; Zhang 2018).

The results indicated that the removal of ammonia is highly dependent on the initial concentration and decreases with an increasing initial concentration of ammonia and the highest removal efficiency was obtained at lower initial concentrations. The availability of sufficiently adsorption sites at low concentrations was the main reason for the high adsorption efficiency in these conditions, and the acces-sibility of adsorption sites overcomes the concentration of ammonia molecules. In the reverse condition, ammonia molecules have a higher driving force at high concentra-tions and overcome the force of mass transfer resistance between the solid phase and the solution. Therefore, as can be seen, the adsorption capacity of ammonia increases with increasing initial concentration. These results are

consistent with studies conducted on the removal of vari-ous types of pollutants by the natural adsorbent clinoptilo-lite (Dong and Lin 2016; Zhang et al. 2016).

Effect of adsorbent concentration on ammonia removal

Based on the results of experiments, it is observed that with increasing the adsorbent concentration, the removal efficiency of ammonium increases, but adsorption capacity decreases. These results indicated the removal efficiency of ammonia depends on the adsorbent value due to an increase in the adsorbent concentration resulted in the formation of many adsorption sites on the adsorbents which ultimately increases the removal efficiency. On the other hand, increas-ing the adsorption sites reduces the driving force related to the ammonia concentration and then reduces the adsorption capacity. The results of this study were also confirmed by Chang et al. in 2007 and Krishnan and Haridas in 2008 (LIU et al. 2007).

The effect of aeration volume on ammonia removal efficiency

Increasing the amount of aeration increases the efficiency of ammonia removal. The phenomenon of the aeration vol-ume effect is probably associated with the effect of airflow between gas–liquid phases. The overall resistance of the mass transfer for ammonia removal is mainly related to

Table 7 Results of ANOVA test for response surface quadratic model for ammonia adsorption onto modified clinoptilolite

Source Sum of squares df Mean square F value p valueProb > F

Model 19,815. 16 14 1415. 37 109. 04 < 0. 0001 SignificantA–D 440. 75 1 440. 75 33. 96 < 0. 0001B-pH 435. 84 1 435. 84 33. 58 < 0. 0001C–T 14,707. 24 1 14,707. 24 1133. 08 < 0. 0001D–C 2537. 89 1 2537. 89 195. 53 < 0. 0001AB 0. 66 1 0. 66 0. 051 0. 8250AC 11. 40 1 11. 40 0. 88 0. 3635AD 7. 42 1 7. 42 0. 57 0. 4614BC 17. 79 1 17. 79 1. 37 0. 2600BD 0. 028 1 0. 028 2. 149E-003 0. 9636CD 0. 19 1 0. 19 0. 015 0. 9057A2 3. 46 1 3. 46 0. 27 0. 6134B2 0. 61 1 0. 61 0. 047 0. 8313C2 196. 65 1 196. 65 15. 15 0. 0014D2 173. 09 1 173. 09 13. 34 0. 0024Residual 194. 70 15 12. 98Lack of fit 173. 12 10 17. 31 4. 01 0. 0692 not significantPure error 21. 58 5 4. 32Cor total 20,009. 86 29

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Table 8 Details of the experiments designed with CCD for ammonia removal using air stripping

Run Factor 1 Factor 2 Factor 3 Factor 4 Response 1 Response 2A: Air (L/min) B: pH C: T (h) D: C (mg/L) N R (%) N out (mg/L)

1 4 11 4 10 96. 35 0. 362 4 7 1 10 29. 19 7. 083 2 7 1 60 4. 53 57. 284 2 11 4 10 86. 91 1. 305 4 11 1 60 21. 91 46. 856 4 9 2.5 35 56. 24 15. 317 3 9 2.5 10 56. 69 4. 338 2 11 1 10 33. 58 6. 649 3 9 2.5 35 54. 57 15. 9010 3 9 2.5 60 33. 84 39. 6911 4 7 4 10 90. 01 0. 9912 3 9 2.5 35 60. 34 13. 8813 2 11 1 60 53. 98 27. 6114 3 9 2.5 35 58. 16 14. 6415 2 7 4 10 80. 69 1. 93116 3 9 2.5 35 52. 83 16. 5017 3 11 2.5 35 55. 55 15. 5518 4 7 1 60 13. 96 51. 6219 2 11 4 60 66. 45 20. 1320 3 9 1 35 25. 93 25. 9221 3 9 4 35 80. 66 6. 76922 4 11 4 60 75. 77 14. 5323 3 7 2.5 35 46. 37 18. 7724 2 9 2.5 35 48. 11 18. 1625 2 7 1 10 20. 2 7. 9826 3 9 2.5 35 50. 79 17. 2227 3 9 2.5 35 54. 82 15. 8128 2 7 4 60 57. 83 25. 3029 4 7 4 60 64. 55 21. 2730 4 11 1 10 39. 75 6. 025

Table 9 The results of the one-way ANOVA test for modeling the air stripping system for ammonia removal

Source Sum of squares df Mean square F value p valueProb > F

Model 14,376. 96 10 1437. 70 37. 77 < 0. 0001 significantA-Air 69. 82 1 69. 82 1. 83 0. 1915B-pH 839. 41 1 839. 41 22. 05 0. 0002C–T 11,561. 63 1 11,561. 63 303. 73 < 0. 0001D–C 1097. 46 1 1097. 46 28. 83 < 0. 0001AB 108. 16 1 108. 16 2. 84 0. 1082AC 111. 72 1 111. 72 2. 94 0. 1029AD 102. 62 1 102. 62 2. 70 0. 1171BC 149. 70 1 149. 70 3. 93 0. 0620BD 103. 73 1 103. 73 2. 73 0. 1152CD 232. 72 1 232. 72 6. 11 0. 0230Residual 723. 25 19 38. 07Lack of fit 662. 47 14 47. 32 3. 89 0. 0708 not significantPure error 60. 77 5 12. 15Cor total 15,100. 21 29

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the gas at the liquid–gas level. The resistance of the mass transfer via the gas phase can be reduced by increasing the velocity of the airflow. When the airflow velocity was fluc-tuated in the low range, increasing the airflow had almost no effect on the mass transfer coefficient due to the lower shear stress on the surface of the water droplets. The high velocity of the gas flow causes larger shear stress at the droplet surface; thus, this phenomenon could reduce the gas resistance and then greatly increase the mass transfer coefficient. On the other hand, high gas flow velocities can create more shear stress, which is applied to the surface of water droplets along the surface of the porous tube to break water droplets into smaller size or even to form a mist and therefore a significant increase in the level of mass transfer occurs. Thus, an observable increase in the surface transfer coefficient (KLa) during the high airflow rate may be due to the combined effect of the two reasons mentioned above. So, it can lead to an increase in mass transfer between liquid and gas phases due to an increase in air circulation (Quan et al. 2009).

In fact, in terms of the continuous and dispersed phases, the mass transfer process of liquid gas is amplified using two streams of opposite impinging. These opposite imping-ing streams can quickly cause a drop in pressure before the injection site; then, the velocity of mass transfer decreases. However, likely, the rapid increase in the mass transfer coef-ficient after the critical point may also be due to the conver-sion of flow patterns occurring at this point, but this needs further investigation (Bonmatı́ and Flotats 2003; Quan et al. 2009). The results of the interaction effect of the air strip-ping process on the ammonia removal are shown in Fig. 5.

Regeneration and reusability study of modified clinoptilolite

This section discusses the results of the study of regeneration and reusability of the modified clinoptilolite which was used in laboratory experiments to remove ammonium. A regenera-tion study was performed in 5 consecutive cycles. Figure 6 shows the adsorption/desorption rate of ammonium ions dur-ing repeated washings with 0.1 mM sodium chloride salt. It should be noted that the results obtained in laboratory experi-ments were repeated three times. According to the results, the adsorption capacity decreased from 85 to 67% and the desorp-tion capacity decreased from 84 to 76% after 5 washing steps.

As seen in Fig. 6, the decrease in the adsorption capacity of clinoptilolite after 5 washes reaches about 18%, which does not show a sharp decrease in adsorption efficiency. On the other hand, the reusability study showed that the low desorption rate was about 8%. The adsorption capacity loss can be due to the effect of the sodium chloride salt on the ligand bond on the adsorbent. On the other hand, the bond

formed on the surface of the clinoptilolite occupied a part of the adsorption capacity; therefore, these sites were not available during the recovery of the adsorbent.

Investigate the removal of nitrogen compounds from the effluent from the stabilization pond

Real municipal and industrial wastewater contains various pollutants such as cations like K+, Na+, Ca2+, and Ma2+ and many other cations in aquatic environments that com-pete with ammonium ions. The effect of these cations on the removal of ammonium onto modified zeolite was inves-tigated. The experiments were performed at 25 °C. The pH of the solutions was adjusted to be 5, and adsorbent doses were 10 g/L (according to the optimum condition). Based on the results (Fig. 7), the presence of individual metal ions significantly reduced the efficiency of ammonium removal. As the initial concentration of cation increased, the removal efficiency of ammonium decreased. The order of reduc-tion effect for cations includes K+ > Ca2+ > Na + > Mg2+, respectively. This suggests that the selection of ammonium for adsorption on the modified zeolite is a priority over other cations. Various results were obtained in previous studies to select natural and synthesized zeolites for the adsorption of various cations. The order of the cation adsorption priority was obtained as Na+ > K+ > Ca2+ > Mg2+ based on the study of Zhang et al. (2016) and Shaban et al. (2017).

Wastewater treatment resulting from zeolite regeneration using air stripping

Air stripping is a very efficient process for removing nitro-gen compounds, especially ammonia. The performance of wastewater treatment depends on the various environmental factors such as temperature, pH, ammonia concentration, as well as the presence of other compounds in the wastewa-ter. According to the results (Fig. 8), the higher the pH, the higher the removal rate. However, high pH and temperature helped to remove high levels of nitrogen compounds. It can also be attributed to factors such as the air permeability coef-ficient between the two gas and liquid phases.

Nonlinear modeling of adsorption system and optimization

According to the p values obtained by the models, the sig-nificance of the model variables and finally the model was developed. The p value model obtained for all responses was significant (less than 0.0001). This indicated the sig-nificance of the model variables and ultimately the model. The difference between the adjusted R2 and the predicted R2 for all responses was less than 0.2 which presents a good

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model in this study. The accuracy of the model was meas-ured by the noise-to-signal ratio, which was greater than 4 for all responses. This ratio also represented that the pro-posed models can be used for process responses. The model developed for removing ammonia and statistical analysis od difference between experimental data and predicted data are shown in Tables 10 and 11, respectively.

System optimization can be achieved based on the response level method. For this purpose, optimization was performed with the help of the model developed by this method. Based on the conditions and modeling, optimized variables are shown in Table 12. Also, the results of this study and other researches are shown in Table 13. According to the results, the adsorp-tion capacity of zeolite used in this study was moderate and presented a prosperous application.

Isotherm study

Determination of the adsorption isotherm model and data from adsorption isotherm studies are essential for the full-scale design of adsorption process units. For this purpose, the data obtained from ammonia adsorption were analyzed with the important isotherm models (Freundlich and Langmuir models). The results of the isotherm of ammonia adsorption onto modified clinoptilolite are shown in Fig. 9. The results of adsorption isotherms showed that the adsorption of ammonia onto clinoptilolite followed the Freundlich isotherm model with a correlation coefficient of 0.994. Adsorption of ammo-nia was also strongly correlated with the Langmuir isotherm model (0.995 > R2 > 0.825). The maximum adsorption capac-ity (qm) parameter is a good criterion for comparing different adsorbents which indicated a relatively high amount in this study.

On the other hand, the tendency of ammonia for adsorbing onto modified zeolites can be assessed using the equilibrium factor (RL) derived from the Langmuir equation. This dimen-sionless factor was calculated using the following equation:

where Ci is the initial concentration of ammonia (mg/L) and constant KL is Langmuir instants (L/mg) according to the adsorption energy. RL values can be interpreted based on Table 14 (Hilal et al. 2012). This parameter was equal to 0.025–0.001 for the adsorption of clinoptilolite. These results showed that the adsorption of ammonia onto modi-fied clinoptilolite was favorable.

Kinetic study

First-order, second-order, Elovich kinetic, and intraparticle diffusion equations were used to model the adsorption of ammonia onto modified clinoptilolite. The intraparticle dif-fusion model was well-matched with laboratory data, and its correlation coefficient was very high (R2 < 0.98). The details of the kinetic study of ammonia adsorption onto modified clinoptilolite are shown in Table 15. In other words, the results of this study showed that the particle dif-fusion model is the best model for determining the reac-tion rate. It was clear that the adsorption kinetic constant increases with increasing the initial concentration of ammo-nium. Thus, there is a direct relationship between the rate of adsorption and the initial concentration of ammonium. The adsorption of ammonium on modified clinoptilolite at higher initial concentrations of ammonium is faster than the low initial concentration of adsorbate. According to the obtained results, it can be concluded that the adsorption of ammonium on the clinoptilolite is taken place at high speed which is very desirable and important from an engineering and economic point of view.

Conclusion

Clinoptilolite was obtained from Semnan (Northeast of Iran) and modified with sodium chloride and ferric chloride as an efficient and simple method. According to the results of the characteristics of zeolite, it was determined that the chemical formula of zeolite was KNa2Ca2(Si29A17)O72,24H2O and its largest component was silica. Also, the experimental design (RSM and CCD) as a mathematical and statistical method was used for the study of ammonia removal with adsorp-tion and air stripping. The results of the adsorption process showed that by increasing adsorbent dose, contact time, and pH and decreasing ammonia concentration ammonia

RL =1

1 + (KLCi)

Fig. 4 The interaction effect of variables on the adsorption of ammo-nia onto modified clinoptilolite a pH and contact time at an adsor-bent dose of 5.5 g/L and ammonia concentration of 35 mg/L, b adsor-bent dose and contact time at pH of 7 and ammonia concentration of 35 mg/L, c ammonia concentration and contact time at pH of 7 and adsorbent dose of 5 g/L, d pH and adsorbent dose at a contact time of 3 h and ammonia concentration of 35 mg/L, e pH and ammonia con-centration at the contact time of 3 h and the adsorbent dose of 5 g/L, and f adsorbent dose and ammonia concentration at the adsorbent dose of 3 g/L and pH of 3

◂

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Fig. 6 Regeneration test for ammonia removal onto modified clinop-tilolite (contact time: 5  h; pH:5, C 0: 60  mg/L and adsorbent dose: 400 mg/L and mixing speed: 150 rpm)

Fig. 7 Real wastewater treatment using modified clinoptilolite/air stripping process (pH: 5, adsorbent dose: 10 g/L, ammonia nitrogen: 53.9 mg/L)

Fig. 8 Investigation of air stripping removal efficiency for ammonia removal from the effluent of the regeneration test (pH: 11.6; air: 4 L/min)

Fig. 5 The interaction effect of variables on the removal of ammonia using air stripping a aeration rate and pH at the time of 2.5  h and ammonia concentration of 35 mg/L, b time and aeration rate at pH of 9 and ammonia concentration of 35 mg/L, c aeration rate and ammo-nia concentration at pH of 9 and time of 2.5 h, d pH and time at aera-tion rate of 3 L/min and ammonia concentration of 35 mg/L, e time and ammonia concentration at an aeration rate of 3 L/min and pH of 9, and f pH and ammonia concentration at the aeration rate of 3 L/min and time of 2.5 h

◂

Table 10 Model developed to remove ammonia by the method used in the study

Adsorption process

NH3 R = NH3 R =

+ 22. 25,977 + 71. 59+ 0. 38,418* D + 4. 95* A− 1. 64,710* pH − 4. 92* B+ 26. 10,695* T + 28. 58* C+ 0. 41,955* C − 11. 87* D+ 0. 022,521* D * pH + 0. 20* AB− 0. 093,785* D * T − 0. 84* AC+ 6. 05167E-003* D * C + 0. 68* AD+ 0. 26,359* pH * T + 1. 05* BC− 8. 35000E-004* pH * C − 0. 042* BD− 2. 17000E-003* T * C − 0. 11* CD+ 0. 057,033* D2 + 1. 15* A2

− 0. 12,133* pH2 − 0. 49* B2

− 2. 17,802* T2 − 8. 71* C2

− 0. 013,078* C2 − 8. 17* D2

Air stripping process

NR = NR =

− 63. 91,648 + 52. 35+ 12. 81,078* Air + 1. 97* A+ 8. 08,103* pH + 6. 83* B+ 24. 34,668* T + 25. 34* C− 0. 21,251* C − 7. 81* D− 1. 30,000* Air * pH − 2. 60* AB+ 1. 76,167* Air * T + 2. 64* AC− 0. 10,130* Air * C − 2. 53* AD− 1. 01,958* pH * T − 3. 06* BC+ 0. 050,925* pH * C + 2. 55* BD− 0. 10,170* T * C − 3. 81* CD

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Table 11 Statistical analysis for the difference of experimental and predicted data

Paired T test

Paired differences t df Sig. (2-tailed)

Mean Std. deviation Std. error mean 95% confidence interval of the difference

Lower Upper

Adsorption process 0.09100 2.53739 0.46326 − 0.85648 1.03848 0.196 29 0.846Air stripping 0.00267 4.99424 0.91182 − 1.86221 1.86755 0.003 29 0.998

Table 12 The results of process optimization in the present study

Adsorption process

Number D pH T C NH3 R Desirability

1 1. 000 5. 000 3. 700 13. 275 86. 037 0. 852

Air stripping process

Number Air pH T C NH3 R Desirability

2 4. 000 11. 649 3. 995 10. 309 96. 418 1. 000

Table 13 Comparison of the results of this study and other researches

Adsorbent Pollutant Adsorption capacity (mg/g)

Reference

H-form zeolite Ammonium 21.23 Zhao et al. (2004)Na-form zeolite 41.15Zeolite modified by potassium permanganate Ammonium 5.84 Guo et al. (2016)Calcium form clinoptilolite Ammonium 7.67 Ji et al. (2007)Ball-milled bamboo biochar Ammonium 22.9 Qin et al. (2020)Biochar obtained from rice straw Ammonium 4.5 Khalil et al. (2018)Mg–Al-modified biochar Ammonium 0.7 Yin et al. (2018a)

Nitrate 40.63Phosphate 74.47

Modified Clinoptilolite with FeCl3 Ammonium 7.05 This study

Fig. 9 Isotherm study of ammonia removal onto modified clinoptilolite a Langmuir, b Freundlich models (pH: 5, time: 3, 7 h, adsorbent dose: 1 g/L)

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removal has been increased. Nonlinear modeling of the adsorption and optimization system showed that the p value of the model for all responses was less than 0.0001. This indicated the significance of the model variables. Also, the correlation coefficient (R2) indicated that the model can be used to predict the required results and optimization of the variables. The optimal conditions for the adsorption system were an adsorbent dose of 1, pH: 5, a contact time of 3.7 h, and an initial concentration of 13.3 mg/L that removal effi-ciency equal to be 86.4%. Nonlinear modeling of the air stripping system and determination of optimal points were performed, which the p value model of that was less than 0.0001 for all responses. Besides, this process can properly treat the effluent of stabilization ponds as real wastewater (about 70% for ammonium removal) and the order of reduc-tion effect for cations includes K + > Ca2 + > Na + > Mg2+,

respectively. Based on the results and employing the combi-nation of adsorption and air stripping for ammonia removal from real wastewater, it could be concluded that the hybrid of adsorption/air stripping is a good option for purifying pond stabilization effluent.

Acknowledgements The authors would like to express their special thanks to the Islamic Azad University, Kermanshah branch, for their kind cooperation in this study.

Author contributions RF and PM have taken part in design and con-duct of the study and manuscript preparation. SAH, FY, and FK got involved in the intellectual helping in different stages of the study. RF have done technical analysis and manuscript preparation. All authors read and approved the final manuscript.

Declarations

Conflicts of interest The authors declare that there is no conflict of interests/competing interests.

Ethical statement The authors declare that they have no compliance with ethical standards.

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Table 14 The equilibrium factor (RL) for isotherm study

The value of RL Isotherm process

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Table 15 Results of kinetic study of ammonia removal onto modified clinoptilolite (pH: 5, adsorbent dose: 1 g/L)

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20 40 50

Pseudo-first order k1 13.32 21.34 30.51qe cal 0.41 0.38 0.59R2 0.96 0.99 0.90

Pseudo-second order k2 0.29 0.11 0.001qe cal 3.78 5.29 59.47R2 0.87 0.37 0.51

Elovich � 0.24 0.14 0.12� 0.24 6.58 14.90R2 0.91 0.92 0.92

Intraparticle diffusion Kdif 6.39 10.70 12.73C 18.66 11.65 12.73R2 0.98 0.99 0.98

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