Removal of ammonium from fish farms by biochar obtained from rice straw: Isotherm and kinetic studies for ammonium adsorption

Abstract

Ammonium is a water pollutant that harms the environment, particularly fisheries. Rice straw is also an economic waste of rice, with millions of tons produced per year around the world. In this paper, physical and chemical procedures for the modification of rice straw were studied. The kinetic and isothermal adsorption trends were investigated, including the ammonium removal efficiency, the contact time of the adsorbent, the amount of adsorbent, and the initial concentration of NH₄⁺. The effect of temperature and pH on the adsorption process was discussed. The removal efficiency of NH₄⁺ recorded 43, 53.7, and 69.5%, with maximum adsorption values of 2.9, 3.5, and 4.5 mg/g at temperatures of 25 ± 5, 35 ± 5, and 45 ± 5°C, respectively, at pH 7.5. The biochar obtained from rice follows the pseudo-second-order equation for ammonium adsorption kinetics (R² = 0.98). The adsorption isotherm follows Freundlich’s model (R² = 0.99) and Langmuir’s model (R² = 0.98).

Keywords

Biochar ammonium removal adsorption kinetic isotherm physical and chemical modification

Introduction

In many nations, eutrophication is a water contamination issue in lakes, rivers, water repositories, and seas. Our study aims to tackle these issues by investigating the nature and reuse of wastewater, which reduces sewage release and enhances water deficiency conditions. Investigations of sewage medication have also been performed. The effect of ammonium was observed in groundwater, aquaculture, and surface water, on the other hand, causing eutrophication (Huo et al., 2012). The level of ammonium in surface water and groundwater is lower than 3 mg/l. This level is unacceptable in other areas, which require levels lower than 0.05 mg/l (e.g. in aquaculture) (Vu et al., 2017). Current treatment methods of water and wastewater such as coagulation and filtration are not masterful to remove ammonium effectively (Moradi, 2011). Various methods have been used to remove ammonium from wastewater, including precipitation, crystallization, biological removal, adsorption, and ion exchange. The adsorption and ion exchange techniques have a high efficiency to eliminate ammonium. These techniques need a small area for application and have acceptable efficiency in comparison to other methods (Abdehagh et al., 2013; Ma et al., 2012; Namasivayam and Sangeetha, 2006; Vargas et al., 2012; Zhu et al., 2005). Identifying new productive materials that may be used for adsorption and ion exchange is an important research topic (Li et al., 2016; Liu et al., 2010; Taheran et al., 2016).

However, adsorption onto the surface of activated carbon is the most widely used method in water treatment (Liu et al., 2013; Zhu et al., 2012). Activated carbon can remove many of the impurities that occur in water and wastewater (Sarker and Fakhruddin, 2015).

Recently, the use of adsorbents from nature, such as agricultural waste, as alternative resources to replace traditional adsorbents. These resources are economical and environmentally friendly solutions. The majority of previous studies have investigated the adsorption of heavy materials and gases, but few studies emphasized nutrients, such as sawdust for removing phenol (Jadhav and Vanjara, 2004), textile sludge biochars for removing oil (Sohaimi et al., 2017), sewage sludge for removing methylene blue from aqueous solutions (Fan et al., 2017), the removal of cadmium (II) (Guo et al., 2017; Wang et al., 2017; Zama et al., 2017), and atrazine and imidacloprid removal (Mandal et al., 2017). This method has been applied to many natural materials, such as wheat straw (Ma et al., 2011); activated carbon (Björklund and Li, 2017; Gierak and Łazarska, 2017); clinoptilolite (Martins et al., 2017); light-expanded clay aggregate (Sharifnia et al., 2016); wood and rice husks biochar (Cope et al., 2014; Kizito et al., 2015); peanut shells, corn cobs, and cotton stalks (Liu et al., 2016; Vu et al., 2017); six types of wetland plants (i.e. Canna indica, Pennisetum purpureum Schum, Thalia dealbata, Zizania caduciflora, Phragmites australis and Vetiveria zizanioides) (Cui et al., 2016); palladium (II) after recrystallization (Mozaffari et al., 2017; Xue et al., 2017); Al-eggshell for adsorption phosphate (Zhang et al., 2017); and treated ginger waste (Ahmad and Kumar, 2010). Literature reviews exhibit the possibility to reuse and develop agricultural wastes as cheap materials for adsorption. However, the conversion of agricultural waste into charcoal is not simple, as this process depends on several factors to activate the above materials.

Adsorption is a cheap and effective process for removing ammonium. The adsorption of ammonium has been studied through the wastewater treatment process by various adsorbents like activated carbon, biochar, zeolite, and corncob-biochar (Gupta et al., 2015; Ivanova et al., 2010; Lebedynets et al., 2004; Vassileva et al., 2009).

A previous research approved that the surface chemistry plays a more important role than the Brunauer–Emmett–Teller surface area of adsorbents and the pore structure in adsorbing inorganic compounds from water. The modification strategy is a current method to change the surface chemistry and promote the adsorption efficiency of adsorbents. The oxidation process with H₂O₂, KMnO₄, H₃PO₄, or HNO₃ has been used for modifying the surface characteristics (Abou El-Maaty, 2014; Halim et al., 2013; Moreno-Castilla et al., 2000).

Rice straw (RS) is an environmental burden in many countries. Thus, in this paper, we examine methods of RS activation for work in the adsorption environment. The internal composition of RS is similar to that of wood, which qualifies RS for conversion to good charcoal. We are interested in the adsorption of ammonium by RS for use as a cheap material to recycle water in fish farms with ammonium; it is also worth mentioning that most of these fish farms are near rice farms due to their common necessity of water, as in Egypt. Therefore, the activation of RS for adsorption has been studied using kinetic and isothermal models; on the other hand, the influence of various factors, such as temperature and pH, on the adsorption process was examined to obtain optimum conditions based on laboratory results and mathematical models (e.g. Lineweaver–Burk, Elovich, pseudo-second-order and pseudo-first-order models for kinetic studies and Freundlich and Langmuir models for isothermal studies).

The overall aim of this study was to determine adsorption characteristics of ammonium with a concentration beginning from 2 mg/l (to simulate wastewater of fish farming in Egypt) on biochars obtained from RS in different environmental conditions (including contact time, pH, ammonium concentrations, and adsorbent dose) to determine the kinetics and equilibrium adsorption parameter. These help to achieve insights in the utilization of biochar obtained from RS to adsorb ammonium and improve water quality in fish farms, which operate through water recycling by simple and easy technique.

Methods and materials

Activation of the material (adsorbents)

Biochar synthesis and activation

The biochar was produced from RS that was collected from Kafr El Sheikh city, Egypt and transported to Don State Technical University in Rostov-on-Don city, Russia. The RS material was washed to remove dust by tab water. The sample was dried at a temperature of 105°C until weight stabilization was achieved. The RS was cut to a size range of 1–1.5 cm and then soaked with 1.0 M of NaOH solution at a solid-to-liquid ratio of 1.0 g to 2.5 ml for 2 h. The following procedures were used by Gao et al. (2015) and Liu et al. (2016). The RS after soaking with NaOH was washed four times with tap water, then adjusted pH to 7–8 for the sample by washing with distilled water for three times (Jindo et al., 2014; Körner et al., 2001), and subsequently dried along with storage RSI (chemical activation).

Thermal analysis and thermal activation

Thermal analysis of the rice straw (RSI) has been performed using a NETZSCH-SAT-449 system under the following conditions: raising the temperature of a sample to 600°C with heating rate 30°/min under a static air atmosphere and crucible DSC/TG pan Al₂O₃. Furthermore, thermal activation was applied on the RSI by heating under slow pyrolysis at 500–600°C in the oven for 1 h and obtaining the RSII in 0.16 mm particles.

Adsorbate

Ammonium chloride was obtained from Aquatest company in Rostov-on-Don city, Russia (M= 53.5 g/mol). Five solutions with different concentrations of ammonium (3, 8, 12, 18, and 25 ppm) were prepared by dissolving 0.0446, 0.1188, 0.1783, 0.2673, and 0.371 g of ammonium chloride (NH₄Cl), respectively, in 5 l of distilled water.

Experimental adsorption procedures

Adsorption kinetics

The adsorption kinetics of ammonium on biochar obtained from rice straw (RSII) were investigated by adding different doses of RSII (0.25, 0.5, and 1 g) to 250 ml of an ammonium chloride solution at a rate of 2 g/l (Yao et al., 2012). The initial concentration of ammonium is 12 ppm was added in different flasks, which placed in a shaker at 120 r/min at room temperature (25 ± 0.5°C) for a suitable amount of time to ensure mixing adsorbent with the solution. Samples were removed from the flasks for analysis at 5, 10, 15, 20, 30, 40, 60, 90, and 120 min. The samples were passed through 0.22 µm membrane filters to measure residual ammonium concentrations using an Expert 001 pH meter ionomer. All experimental results were measured in triplicate, by calculating average values. Pseudo-first-order, pseudo-second-order, Elovich, and Lineweaver–Burk models were used to analyze and describe the experimental data related to adsorption kinetics. The equations of kinetic models and their linear forms are given below:

1. Pseudo-first order (Macías-García et al., 2016)

q_{t} = q_{e} (1 - e^{{- k}_{1} t})

(1)

The linearized form is

\ln (q_{e} - q_{t}) = \ln (q_{e}) - K_{1} t

(2)

1. 2. Pseudo-second order

q_{t} = \frac{K_{2} q_{e}^{2} t}{1 + (k_{2} q_{e} t)}

(3)

The linearized form is

\frac{t}{q_{t}} = \frac{1}{K_{2} q_{e}^{2}} + \frac{1}{q_{e}} t

(4)

1. 3. Elovich (Thilagan et al., 2013)

q_{t} = \frac{1}{β} \ln (α β t + 1)

(5)

The linearized form is

q_{t} = α + β \ln (t)

(6)

1. 4. Lineweaver–Burk (Compostela, 1988)

V = \frac{V_{m a x} [s]}{k_{m} + [s]}

(7)

The linearized form is

\frac{1}{V} = \frac{k_{m}}{V_{m a x} [s]} + \frac{1}{v_{m a x}}

(8)

The ammonium removal efficiency (η) was calculated with the following equation

η = \frac{C_{0} - C_{t}}{C_{0}} \times 100

(9)

where q_t and [s] are the amount of ammonium removed at one time t (mg of adsorbed per g of adsorbent) was calculated with the following equation (Wassie and Srivastava, 2016)

q_{t} = \frac{(C_{0} - C_{t}) V}{m}

(10)

where q_e is the adsorption capacity in balance (mg/g); k₁, k₂, and k_m are the pseudo-first-order, pseudo-second-order, and Michaelis–Menten for Lineweaver–Burk constants, respectively; α is the initial adsorption rate (mg/g); β is the desorption constant (g/mg); V_max is the maximum reaction velocity (mg/g); t is time (min); C₀ is the ammonium concentration at the start of the experiment (mg/l); C_t is the ammonium concentration at t (mg/l); v is the solution volume (l); and m is the mass of adsorbent (g).

Adsorption isotherm

The same sampling, mixing, filtration, and analysis procedures described for adsorption kinetics were used to identify the adsorption isotherms of ammonium in the RSII. Instead of different time periods, 0.5 g of sorbents was mixed with 250 ml of ammonium solutions with varying initial concentrations: 3.15, 8, 12.1, 18, and 25 mg/l. The Langmuir and Freundlich models were used to analyze the experimental data for the adsorption isotherm (Langmuir, 1918; Yao et al., 2011). The supposition of the Langmuir isotherm is based on sorption occurring at specific homogeneous sites of adsorbent heat (as adsorption for all sites is constant); however, the Freundlich isotherm is assumed to be a heterogeneous surface (multilayer adsorption) with a nonequal distribution of adsorption heat over the surface (Novak et al., 2010; Wu et al., 2017; Yusof et al., 2010). The Langmuir and Freundlich equations can be written as shown below:

1. Langmuir model

q_{e} \equiv \frac{q_{m} k_{1} C_{e}}{1 + k_{1} C_{e}}

(11)

The linearized form is

\frac{C_{e}}{q_{e}} = \frac{1}{q_{m} k_{1}} + \frac{1}{q_{m}} C_{e}

(12)

2. Freundlich model

q_{e} = k_{f} C_{e}^{\frac{1}{n}}

(13)

The linearized form is

\ln q_{e} = \ln k_{f} + \frac{1}{n} \ln C_{e}

(14)

where q_e is the adsorption capacity at equilibrium on the adsorbent (mg/g) and C_e is the equilibrium concentration (mg/l); the other parameters are constants of different isotherms, which were determined based on the experimental data.

During the experiments, the pH was monitored at all steps to create optimal conditions for ammonium absorption, which depends directly on the pH. The pH in all experiments was 7.5 ± 0.5, for the reasons mentioned in section effect of pH.

Results and discussion

Raw material characterization

Physicochemical properties of RS waste

The chemical configuration of RS depends on the planting time, climate, type of rice, source of water, and geographical conditions (Agbagla-Dohnani et al., 2003). The quality parameters and main characteristics of the initial RS are presented in Table 1.

Table 1.

Chemical analysis of the raw material.

	The internal components of rice straw
Oxides	SiO₂	Fe₂O₃	CaO	MgO	SO₃	P₂O₅	Na₂O	TiO₂	K₂O	MnO
Content (%)	74.67	0.8	3.1	5.2	1.3	1.0	1.2	0.03	12.3	0.03
Characteristics	Wa (%)	Ab (%)	S_tc (%)	V_Σd (cm³/g)
The result	14.8	0.96	0.19	1.3

^aW is ash content for dry weight.

^bA is moisture.

^cSt is total sulfur.

^dV_Σ is total pores.

RS has a high concentration of silica and can be categorized as attractive material that contains silica. In addition, in the thermal analysis (based on temperature), silica is responsible for the type of ash that is formed (Elwan et al., 2006), with amorphous ash exhibiting reduced adsorption. Sodium hydroxide was selected to dilute the silica in the raw material, which uses the first step in the modification of RS. The reaction of sodium hydroxide and silicon oxide can be written by the following chemical equation

2 N a O H + S i O_{2} \to N a_{2} S i O_{3} + H_{2} O

(15)

Results of the TG–DTG analysis of RS

Four temperature zones were obtained from the thermogravimetric analysis curve (TG–DTG) of raw RS (from room temperature to 120°C, from 120 to 370°C, from 370 to 500°C, and from 500 to 600°C), based on weight loss, as illustrated in Figure 1.

Figure 1.

TG–DTG curve for RS. DTG: Differential thermogravimetry; TG: Thermogravimetry.

These zones were explained according to a previous study (Mall et al., 2006). The second zone recorded a high percentage of weight loss in comparison to the other zones. The weight loss was approximately 6.46% during the heating of RS up to 120°C, due to the loss of moisture in the RS. A significant weight loss of approximately 50.12% was recorded in the second zone from 120 to 370°C, which was due to the degradation of the cellulose-related component that forms carbon. Lignin was decomposed in the third zone (370–500°C), with a mass loss of 13.8%, indicating better stability than cellulose and hemicellulose. The last zone was from 500 to 600°C, with a slight loss of mass that stopped at 600°C. The final mass was approximately 29% of the initial weight, indicating that all organic compounds had been completely converted. Finally, the appropriate temperature to activate RS to RSII is 500–600°C.

Effect of pH

The ammonium adsorption of RSII was investigated by creating three pH groups. The first group used RSII without adjusting the pH, which was physically and chemically activated (burn RSI after soaking with NaOH, and without washing to produce RSII⁻¹), while pH ranges were recorded in these groups from 9 to 10.2. The second group is pH 7, which was obtained by washing RS after soaking it with a solution of NaOH prior to a burning process. This pH range was achieved after washing RS with tap water and distilled water for three times. The third group was achieved by adding HCl to generate a pH from 2 to 6. In Figure 2, with a low pH from 2 to 5.5, the percentage of removed ammonium was low, while the process achieved the highest percentage of ammonium removal at 12%. We noted that when the pH increases from 5.5 to 8 the removal efficiency of NH₄⁺ reaches to 57%, but when the pH increases from 9 to 10.2 the removal efficiency of NH₄⁺ reaches to 15%.

Figure 2.

Effect of pH on ammonium ion removal efficiency (initial concentration of NH₄⁺ (C₀) =12 ppm, temperature =25 ± 2°C).

Decreased adsorption at different pH values is caused by ammonium ion effects with free hydrogen ions (H⁺) in the solution. The low efficiency of the adsorption process at a lower pH could relate to high protonation of functional groups (C = O, COO⁻) (HA + B ↔ A⁻ + HB⁺) on the biochar surfaces, which impart a partial positive charge that repels the polar attraction of NH₄⁺ ions in aqueous solutions. In the solution, there is competition between H⁺ and NH₄⁺ ions adsorbed on the surface of an adsorbent. This competition is in favor of H ions when decreasing the pH in the solution.

Here, the ammonium adsorption in water followed the ion exchange mechanism. High pH values > 10 lead to the conversion of most ammonium ions into ammonia, which cannot be adsorbed. Therefore, all steps of adsorption processes were carried out with pH values of 7–8 (Huang et al., 2010; Jindo et al., 2014; Novak et al., 2010).

Adsorption studies: Kinetics and isotherm

Adsorption kinetics of RSII

The relationship between the rate of adsorption and the contact time shows the kinetics of adsorption. The process of NH₄⁺ adsorption by RSII with different contact times and different concentrations is shown in Figure 3. Adsorption kinetics of RSII occurs in three main stages: fast, slow, and equilibrium. The first stage is the fastest stage (up to 15 min), the adsorption rate increased quickly, where half of the adsorption capacity is obtained. The NH₄⁺ adsorption began to slow down in the second stage, which occurred from 15 min to the equilibrium stage of adsorption at 60 min. We also noticed that the adsorption rate increased with an increasing initial concentration of the solution at all stages of the study.

Figure 3.

Adsorption kinetics of NH₄⁺ onto RSII (temperature = 25 ± 2°C, pH = 7.5, C₀ = 3, 8, 12, 18, and 25 ppm).

The speed of the reaction can be explained for RSII, where some anionic groups with negative charges are located on the surface of the adsorbent such as –COO⁻. These groups rapidly interact with ammonium ions. At the end of this reaction with the anionic groups, the NH₄⁺ goes into a slow process, which represents adsorption on the internal skeleton of the RSII. So, the NH₄⁺ adsorption on RSII consisted of two reaction processes. Also increasing the concentration of ammonium leads to congestion of cations in the solution, which increases the chances of adsorption as well as its speed.

The kinetic NH₄⁺ adsorption data were fitted with four kinetic models. Table 2 shows the model parameters with R² and experimental values for five initial concentrations of the NH₄Cl solution. As shown in Table 2, the results showed that the Elovich, pseudo-first-order, and pseudo-second-order models are suitable for describing the adsorption kinetics, with all R² values being larger than 0.87. However, the pseudo-second-order model had the best fit, based on R² values and decreases of k₂ (g/mg min), with an increased concentration of ammonium in solution and the convergence of equation values with actual values; moreover, this model has a better chance to calculate the q_e value, which worked with the experimental result. Therefore, the pseudo-second-order model can be used to predict the kinetic process for NH₄⁺ adsorption. The pseudo-second-order model obtained high reliability and stability in another mass of RSII, with an R² value of 0.99 and an average q_e of 2.6 mg/g, as shown in Figure 4. The above results indicate that this model is the best choice to represent NH₄⁺ absorption on RSII. For that, the parameters of the pseudo-second-order model, with an initial concentration of NH₄⁺ = 12 ppm at different concentrations of adsorbent RSII were presented in Table 3 with mean absolute percentage error (MAPE). The MAPE was calculated by an equation which is defined below (Mozaffari et al., 2017)

MAPE = \frac{100}{λ} (\sum_{i = 1}^{λ} |\frac{q_{e x p} - q_{m o d e l}}{q_{e x p}}|)

(16)

where λ is the number of data points in each set and q_exp and q_model are the experimental and model results for the adsorption capacity at the equilibrium.

Table 2.

Coefficient of determination (R²) for the Lineweaver–Burk, Elovich, pseudo-first-order, and pseudo-second-order kinetic models and model parameters.

Model		Pseudo-first order			Pseudo-second order			Elovich			Lineweaver–Burk
C^a(mg/l)	q_expb(mg/g)	k₁ (min⁻¹)	q_e (mg/g)	R²	k₂ (g/mg min)	q_e (mg/g)	R²	β (g/mg)	α (mg/g)	R²	k_m	R²
3.15	1	0.07	1.1	0.97	0.036	1.42	0.99	0.410	0.164	0.97	59.4	0.87
8	2	0.14	4.25	0.97	0.016	3.04	0.98	0.683	0.305	0.99	−9.51	0.77
12	2.6	0.03	1.8	0.95	0.027	2.87	0.99	0.589	0.004	0.98	−10.7	0.89
18	3.55	0.04	2.67	0.98	0.021	3.9	0.98	0.648	1.354	0.93	−15.5	0.96
25	4.5	0.04	4.1	0.87	0.012	5.22	0.98	1.053	0.720	0.92	−25.5	0.85

^aInitial concentration of ammonium in aqueous solution.

^bExperimental results for the adsorption capacity at the equilibrium.

Figure 4.

Pseudo-second-order plot (C₀ =12 ppm, temperature = 25 ± 2°C, pH = 7.5).

Table 3.

Parameters of the pseudo-second-order model, with an initial concentration of NH₄⁺ = 12 ppm at different concentrations of adsorbent RSII.

Concentration of adsorbent (mg/50 ml)		Pseudo-second-order parameters
Concentration of adsorbent (mg/50 ml)	q_exp (mg/l)	k₂ (g/mg min)	q_e (mg/g)	R²	MAPE (%)
0.05	2.1	0.036	2.4	0.993	6.41
0.1	2.6	0.026	2.8	0.996	3.45
0.2	2.8	0.076	2.6	0.991	1.15

MAPE: mean absolute percentage error.

Adsorption isotherm of RSII

The experimental data for isotherm adsorption were placed in the Langmuir and Freundlich models and R² values were extracted for both models. The adsorption isotherm of RSII for NH₄⁺ is described in Figure 5 using the Langmuir and Freundlich models. The parameters of these models with correlation coefficient R² were presented in Table 4. The results show that the Freundlich and Langmuir models accurately describe the adsorption of NH₄⁺, with R² values larger than 0.98 for all models, but the Freundlich model coincides with the experimental data better than the Langmuir model, with R² = 0.99. In addition, the n constant for the Freundlich isotherm measures exchange intensity or surface heterogeneity and also indicates the ease of adsorption when n > 1. In this study, the value of n was larger than 1, which suggested that the adsorption conditions fit with the Freundlich model.

Figure 5.

Ammonium adsorption equilibrium prediction on RSII from the Langmuir and Freundlich models (contact time = 120 min, temperature = 25 ± 2°C, and pH = 7.5).

Table 4.

Isothermal parameters for the Langmuir and Freundlich models of adsorbent NH₄⁺ on RSII.

	Langmuir			Freundlich
	K_l (l/mg)	q_max (mg/g)	R²	K_f (l/mg)	n	R²
RSII	0.260	4.251	0.98	0.822	1.623	0.99

Effect of temperature on ammonium removal efficiency

The influence of three different temperatures on the adsorption of ammonium on RSII was investigated. In the experimental study, the concentration of adsorbent of RSII was 0.1 g/50 ml with the initial concentration of ammonium (C₀) = 12 mg/l; a pH value was 7.5 ± 5; and the same conditions of shaking, extraction, and measurement as previously mentioned for calculating the adsorption isotherm and kinetics. The first temperature is room temperature, which was 25 ± 2°C. The second and third temperatures were applied by heating the samples in electric furnaces with the following temperatures 35 ± 5 and 45 ± 5°C. The removal of ammonium was high at high temperatures, with values of 43, 53.7, and 69.5% at temperatures of 25 ± 2, 35 ± 5, and 45 ± 5°C, respectively. In Figure 6 based on the pseudo-second-order equation, the reason for the increased removal efficiency of ammonium is the fact that the ammonium ion acquires greater kinetic energy at high temperatures, allowing rapid adsorption on the surface, with complete adsorption including adsorption into the internal pores of RSII. The adsorption capacity at equilibrium (q_e) is 2.858, 3.457, and 4.478 mg/g at these temperatures, respectively.

Figure 6.

The pseudo-second-order equation model at different temperatures (C₀ =12 ppm and pH = 7.5).

Conclusions

This study examined the potential use of biochar obtained from RS for NH₄⁺ adsorption from aqueous solution. We investigated the factors that influence the process of adsorption: physical and chemical methods of modifying RS, contact time, adsorbent dose, initial concentration of adsorbate, and pH solution. The rice straw RSII achieved a removal efficiency of 43% of ammonium at room temperature (25°C), with an initial concentration of NH₄Cl of 12 mg/l and a pH of 7.5 ± 0.5. The adsorption equilibrium of NH₄⁺ was achieved after a contact time 90 min, with the best range of pH 7–8 yielding an improved adsorption performance. The kinetic data for the adsorption of NH₄⁺ fit with the pseudo-second-order kinetic model. The isothermal data coincided with Freundlich’s model, which achieved R² = 0.99 and Langmuir’s model (R² = 0.98).

Overall, these results suggest that biochar obtained from rice straw (RSII) can be used effectively for ammonium removal from aqueous solutions.

Footnotes

Acknowledgements

Authors are thankful to Kafrelsheikh University and Don State Technical University for supporting our work.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

References

Abdehagh

Tezel

and Thibault

(2013) Adsorbent screening for biobutanol separation by adsorption: Kinetics, isotherms and competitive effect of other compounds. Adsorption 19: 1263–1272.

Agbagla-Dohnani

Nozire

Gaillard-Martinie

et al . (2003) Effect of silica content on rice straw ruminal degradation. The Journal of Agricultural Science 140(2): 183–192.

Ahmad

and Kumar

(2010) Adsorption studies of hazardous malachite green onto treated ginger waste. Journal of Environmental Management 91(4): 1032–1038.

Björklund

and Li

(2017) Adsorption of organic stormwater pollutants onto activated carbon from sewage sludge. Journal of Environmental Management 197: 490–497.

Compostela

(1988) Kinetics of acid phosphatase activity various soils of Galicia (NW Spain). Soil Biology and Biochemistry 20(3): 275–280.

Cope

Webster

and Sabatini

(2014) Arsenate adsorption onto iron oxide amended rice husk char. Science of the Total Environment 488–489(1): 554–561.

Cui

, Hao

, Zhang

, He

and Yang

(2016) Capacity and mechanisms of ammonium and cadmium sorption on different wetland-plant derived biochars. Science of The Total Environment 539: 566–575. DOI: 10.1016/j.scitotenv.2015.09.022.

Elwan

Attriss

Mahmoud

et al . (2006) Characterization of rice straw/ash and using in clay bricks. In: Proceeding of first scientific environmental conference, Zagazig University, pp.79–92.

El-Wakil

Abou El-Maaty

and Awad

(2014) Removal of lead from aqueous solution on activated carbon and modified activated carbon prepared from dried water hyacinth plant. Journal of Analytical & Bioanalytical Techniques 5: 187. DOI: 10.4172/2155-9872.1000187.

10.

Fan

Wang

et al . (2017) Removal of methylene blue from aqueous solution by sewage sludge-derived biochar: Adsorption kinetics, equilibrium, thermodynamics and mechanism. Journal of Environmental Chemical Engineering 5(1): 601–611.

11.

Gao

Xue

Deng

et al . (2015) Removal of aqueous ammonium by biochars derived from agricultural residuals at different pyrolysis temperatures. Chemical Speciation and Bioavailability 27(2): 92–97.

12.

Gierak A and Łazarska I (2017) Adsorption of nitrate, nitrite, and ammonium ions on carbon adsorbents. Adsorption Science & Technology 35: 721–727.

13.

Guo

Tang

Song

et al . (2017) Adsorptive removal of Ni²⁺ and Cd²⁺ from wastewater using a green longan hull adsorbent. Adsorption Science & Technology 36(1-2): 762–773. DOI: 10.1177/0263617417722254.

14.

Gupta

Sadegh

Yari

et al . (2015) Removal of ammonium ions from wastewater: A short review in development of efficient methods. Global Journal of Environmental Science and Management 1(2): 149–158.

15.

Halim

Latif

and Ithnin

(2013) Ammonia removal from aqueous solution using organic acid modified activated carbon. World Applied Sciences Journal 24(1): 1–6.

16.

Huang

Xiao

Yan

et al . (2010) Ammonium removal from aqueous solutions by using natural Chinese (Chende) zeolite as adsorbent. Journal of Hazardous Materials 175(1–3): 247–252.

17.

Huo

Lin

Dong

et al . (2012) Ammonia-nitrogen and phosphates sorption from simulated reclaimed waters by modified clinoptilolite. Journal of Hazardous Materials 229–230: 292–297.

18.

Ivanova

Karsheva

and Koumanova

(2010) Adsorption of ammonium ions onto natural zeolite. Journal of the University of Chemical Technology and Metallurgy 45(3): 295–302.

19.

Jadhav

and Vanjara

(2004) Removal of phenol from wastewater using sawdust, polymerized sawdust and sawdust carbon. Indian Journal of Chemical Technology 11(1): 35–41.

20.

Jindo

Mizumoto

Sawada

et al . (2014) Physical and chemical characterization of biochars derived from different agricultural residues. Biogeosciences 11(23): 6613–6621.

21.

Kizito

Kipkemoi Kirui

et al . (2015) Evaluation of slow pyrolyzed wood and rice husks biochar for adsorption of ammonium nitrogen from piggery manure anaerobic digestate slurry. Science of the Total Environment 505: 102–112.

22.

Körner

Das

Veenstra

et al . (2001) The effect of pH variation at the ammonium/ammonia equilibrium in wastewater and its toxicity to Lemna gibba. Aquatic Botany 71(1): 71–78.

23.

Langmuir

(1918) The adsorption of gases on plane surfaces of glass, mica and platinum. Journal of the American Chemical Society 40(9): 1361–1403.

24.

Lebedynets

Sprynskyy

Sakhnyuk

et al . (2004) Adsorption of ammonium ions onto a natural zeolite: Transcarpathian clinoptilolite. Adsorption Science & Technology 22(9): 731–741.

25.

Wang

Zhou

et al . (2016) Enhancing phosphate adsorption by Mg/Al layered double hydroxide functionalized biochar with different Mg/Al ratios. Science of the Total Environment 559: 121–129.

26.

Liu

Dong

Liu

et al . (2010) Screening of novel low-cost adsorbents from agricultural residues to remove ammonia nitrogen from aqueous solution. Journal of Hazardous Materials 178(1–3): 1132–1136.

27.

Liu

Sun

et al . (2013) Adsorption characteristics of ammonium nitrogen by biochar from diverse origins in water. Advanced Materials Research 664: 305–312.

28.

Liu

Xue

Gao

et al . (2016) Removal of ammonium from aqueous solutions using alkali-modified biochars. Chemical Speciation and Bioavailability 28(1–4): 26–32.

29.

et al . (2012) CO₂ adsorption on zeolite X/activated carbon composites. Adsorption 18: 503–510.

30.

Yue

et al . (2011) Adsorption removal of ammonium and phosphate from water by fertilizer controlled release agent prepared from wheat straw. Chemical Engineering Journal 171(3): 1209–1217.

31.

Macías-García

Gómez Corzo

Alfaro Domínguez

et al . (2016) Study of the adsorption and electroadsorption process of Cu (II) ions within thermally and chemically modified activated carbon. Journal of Hazardous Materials 328: 46–55. DOI: 10.1016/j.jhazmat.2016.11.036.

32.

Mall

Srivastava

and Agarwal

(2006) Removal of Orange-G and methyl violet dyes by adsorption onto bagasse fly ash – Kinetic study and equilibrium isotherm analyses. Dyes and Pigments 69(3): 210–223.

33.

Mandal

Singh

and Purakayastha

(2017) Characterization of pesticide sorption behaviour of slow pyrolysis biochars as low cost adsorbent for atrazine and imidacloprid removal. Science of the Total Environment 577: 376–385.

34.

Martins

Souza

TSO

and Foresti

(2017) Ammonium removal from landfill leachate by clinoptilolite adsorption followed by bioregeneration. Journal of Environmental Chemical Engineering 5(1): 63–68.

35.

Moradi

(2011) The removal of ions by functionalized carbon nanotube: Equilibrium, isotherms and thermodynamic studies. Chemical and Biochemical Engineering Quarterly 25(2): 229–240.

36.

Moreno-Castilla

López-Ramón

Carrasco-Marı́n

et al . (2000) Changes in surface chemistry of activated carbons by wet oxidation. Carbon 38(14): 1995–2001.

37.

Mozaffari

Thompson

et al . (2017) Colloidal nanoparticle size control: Experimental and kinetic modeling investigation of the ligand-metal binding role in controlling the nucleation and growth kinetics. Nanoscale 9: 3772–13785.

38.

Namasivayam

and Sangeetha

(2006) Removal and recovery of vanadium (V) by adsorption onto ZnCl₂ activated carbon: Kinetics and isotherms. Adsorption 12: 103–117.

39.

Novak

Busscher

Watts

et al . (2010) Short-term CO₂ mineralization after additions of biochar and switchgrass to a Typic Kandiudult. Geoderma 154(3–4): 281–288.

40.

Sarker

and Fakhruddin

ANM

(2015) Removal of phenol from aqueous solution using rice straw as adsorbent. Applied Water Science 7(3); 1459–1465. Springer Berlin Heidelberg. DOI: 10.1007/s13201-015-0324-9.

41.

Sharifnia

Khadivi

Shojaeimehr

et al . (2016) Characterization, isotherm and kinetic studies for ammonium ion adsorption by light expanded clay aggregate (LECA). Journal of Saudi Chemical Society 20: S342–S351.

42.

Sohaimi

KSA

Ngadi

Mat

et al . (2017) Synthesis, characterization and application of textile sludge biochars for oil removal. Journal of Environmental Chemical Engineering 5(2): 1415–1422. DOI: 10.1016/j.jece.2017.02.002.

43.

Taheran

Naghdi

Brar

et al . (2016) Adsorption study of environmentally relevant concentrations of chlortetracycline on pinewood biochar. Science of the Total Environment 571: 772–777.

44.

Thilagan

Gopalakrishnan

and Kannadasan

(2013) Adsorption of copper(II) ions in aqueous solution by chitosan immobilised on red soil: Isotherms, kinetics and mechanism. International Journal of Pharmaceutical and Chemical Sciences 2(2): 1055–1066.

45.

Vargas

Giraldo

and Moreno-Piraján

(2012) Study of CO₂ adsorption in functionalized carbon. Adsorption 19(2–4): 323–329.

46.

Vassileva

Tzvetkova

and Nickolov

(2009) Removal of ammonium ions from aqueous solutions with coal-based activated carbons modified by oxidation. Fuel 88(2): 387–390.

47.

Trinh

Doan

et al . (2017) Removing ammonium from water using modified corncob-biochar. Science of the Total Environment 579: 612–619.

48.

Wang

et al . (2017) Removal of cadmium (II) from aqueous solution: A comparative study of raw attapulgite clay and a reusable waste–struvite/attapulgite obtained from nutrient-rich wastewater. Journal of Hazardous Materials 329(2): 66–76.

49.

Wassie

and Srivastava

(2016) Teff straw characterization and utilization for chromium removal from wastewater: Kinetics, isotherm and thermodynamic modelling. Journal of Environmental Chemical Engineering 4(1): 1117–1125.

50.

Lan

et al . (2017) Unraveling sorption of lead in aqueous solutions by chemically modified biochar derived from coconut fiber: A microscopic and spectroscopic investigation. Science of the Total Environment 576: 766–774.

51.

Xue

and Liu

(2017) Adsorption of aquatic Cd²⁺ using a combination of bacteria and modified carbon fiber. Adsorption Science & Technology (August 21, 2017): 1–15. DOI: 10.1177/0263617417724946.

52.

Yao

Gao

Inyang

et al . (2011) Removal of phosphate from aqueous solution by biochar derived from anaerobically digested sugar beet tailings. Journal of Hazardous Materials 190(1–3): 501–507.

53.

Yao

Gao

Zhang

et al . (2012) Effect of biochar amendment on sorption and leaching of nitrate, ammonium, and phosphate in a sandy soil. Chemosphere 89(11): 1467–1471.

54.

Yusof

Keat

Ibrahim

et al . (2010) Kinetic and equilibrium studies of the removal of ammonium ions from aqueous solution by rice husk ash-synthesized zeolite Y and powdered and granulated forms of mordenite. Journal of Hazardous Materials 174(1–3): 380–385.

55.

Zama

Zhu

Y-G

Reid

et al . (2017) The role of biochar properties in influencing the sorption and desorption of Pb(II), Cd(II) and As(III) in aqueous solution. Journal of Cleaner Production 148(2): 127–136.

56.

Zhang

et al . (2017) Statistical optimization and batch studies on adsorption of phosphate using. Adsorption Science & Technology (November 13, 2017): 1–19. DOI: 10.1177/0263617417740790.

57.

Zhu

Zhang

et al . (2012) Studies on removal of NH₄⁺-N from aqueous solution by using the activated carbons derived from rice husk. Biomass and Bioenergy 43: 18–25.

58.

Zhu

Kapteijn

Groen

et al . (2005) Adsorption on Kureha activated carbon: Isotherms and kinetics. Adsorption 11: 637–641.