Abstract

Only 2.5% of the world's water is fresh, despite the fact that water covers approximately 70% of the planet. This water is used for several recreational purposes and gets polluted by wastewater disposal directly into freshwater bodies. Effluents dispersed into water bodies could be from various sources like industries, households, and agricultural activities. These effluents comprise heavy metals and chemical wastes directly released into water bodies without treatment and could include major contaminants like nitrates, nitrites, ammonia and phosphates. The present study mainly focuses on removal of four significant pollutants from agriculture wastes, i.e., nitrates, nitrites, ammonia, and phosphates. These pollutants are removed using adsorbents via a process known as adsorption. Adsorbents used in the study are fish scales and neem leaves. Several studies have been carried out to measure the efficiency of adsorbents in the removal of contaminants. These studies include equilibrium studies, kinetic studies and isotherm studies. Based on a complete analysis and results obtained, 95% to 99% of contaminants can be removed effectively with an adsorbent dosage of 0.4g (0.2 g of fish scale and 0.2 g of neem leaves powder), optimum pH of 6 and at 303K constant temperature. The dosage variance stems from changing the dosages of two adsorbents in three ways, i.e., by taking both adsorbents in equal dosages, and increasing the dosage of one adsorbent compared to the other and vice versa. The contact time varied from 0 to 140min and the Initial concentration of pollutants has also been varied from 30 to 70 mg/L. In addition to the above variations, thermodynamic studies were also done, and based on the negative values of ΔG and positive value of ΔH and ΔS, it is evident that the reaction of novel adsorbent (combination of fish scales and neem leaves) is spontaneous and endothermic.

HIGHLIGHTS

  • Agricultural wastewater pollutants causing eutrophication is one of the reasons for polluting the river bodies.

  • These pollutants, i.e. nitrates, nitrites, ammonia and phosphates, were treated by integrating two waste materials, fish scales and neem leaves, as single adsorbent.

  • About 95% to 99% of contaminants could be removed from the considered pollutant concentration.

  • Kinetic and isotherm studies were also included in the study.

INTRODUCTION

The available freshwater resources are fast depleting with the daily increase in pollution following varied practices such as disposal of industrial effluents directly into the water without proper treatment and increase of fertilisers in agricultural practices impacting soil fertility (Pimentel et al. 2007). Wastewater that is disposed from agricultural fields contaminates water bodies due to pollutants such as nitrates, nitrites, ammonia and phosphates (Rao 2006). Different methods have been devised to remove pollutants from wastewater, of which adsorption method is considered one of the best methods, wherein low-cost adsorbents are used to remove pollutants (Lito et al. 2012). Excessive amounts of phosphates and nitrates in water can lead to eutrophication, which causes depletion of dissolved oxygen in water and results in pollution of water bodies. As per Indian Standard IS 10500-2012, the acceptable limit of nitrogen in the form of nitrates is 45 ppm as per Central Pollution Control Board (CPCB), the amount of nitrates in wastewater that is disposed is limited to 10 ppm; and according to CPCB, the permissible value for dissolved phosphates (as P) is 5 ppm (mg/L).

Different adsorbents have been taken into consideration for the removal of diverse heavy metals and pollutants from wastewater. Solid waste residue (SWR) from alum and the sulphuric acid factory has been used for the concurrent removal of nitrates and phosphates from wastewater. The results of the study showed that optimum contact time was 90 min and the adsorbent dose was 20 g/L. The R2 values of 0.99 and 1.0 obtained from pseudo-second-order equation showed that this model fitted the adsorption kinetics. The adsorption of phosphate and nitrate was better examined using Freundlich and Langmuir isotherms, with R2 values of 0.99 and 0.98 for phosphate and 0.99 and 0.96 for nitrate, respectively, according to isotherm studies. The SWR exhibited a low inclination towards nitrate adsorption (0.071 mg/g), while SWR's effectiveness in removing phosphate (0.962 mg/g) was decent within optimum contact time. Based on their studies, the SWR could remove phosphates from wastewater compared to nitrates under optimum conditions (Kang & Jeen 2021).

Fly ash is one waste byproduct that can be considered as an adsorbent and used effectively to eliminate anionic surfactants from wastewater. Studies showed that fly ash removed sodium dodecylbenzenesulfonate (SDBS) surfactants effectively at pH 2 at temperature 25 °C; and both physisorption and chemisorption were observed during adsorption of SDBS surfactants on to fly ash. Removal efficiency varied from 62.59% to 84.41% as SDBS concentrations were changed (Siyal et al. 2019).

Kinetic and isotherm studies are the essential studies incorporated to determine the adsorption capacity observed for different pollutants. Langmuir isotherm and second-order kinetic studies are conducted to study the affinity of bone char as adsorbent in Pb(II) removal from aqueous solution. When cellulose-modified bone char was used in place of bone char, uptake capacity of Pb(II) on to bone char increased from 89.9 to 115.7 mg/g (Liao et al. 2021).

Using rice husk ash as adsorbent, oxytetracycline was removed by varying pH, contact time and temperature. Equilibrium for removing of oxytetracycline was reached at 420 min for lower concentration (40 to 80 mg/L). Based on regression analysis, R2 value of Langmuir isotherm was best suited for adsorption study of oxytetracycline on to rice husk ash (Andrade et al. 2020).

Several waste materials such as corn and rice husk biochar can be used as adsorbents for removal of select heavy metals, where removal efficiencies for different heavy metals are Fe (90%), Cr (65%) and Pb (90%) for biochar from rice husk, whereas removal efficiencies for corn husk biochars are Pb (slightly >35%), Cr (only 20%). The contact time for all biochars varies between 20 and 30 min (Sanka et al. 2020).

Fine powder prepared from mature neem leaves was used as an adsorbent to remove metal ions from water. A small amount of 1.6 g dm−3 neem leaves powder used as adsorbent could remove 87% of Cr(VI) at an optimum contact time of 300 min. Suitability of neem powder adsorbent was additionally tested with isotherms and equilibrium kinetic studies. Adsorption coefficients indicated high potentiality of neem leaf powder in removing Cr(VI) from water (Sharma & Bhattacharyya 2005).

In the current study, neem leaves and fish scales have been used for the elimination of different pollutants from wastewater. The main objective is to study the efficiency of fish scales and neem leaves as novel adsorbent to remove agricultural wastewater pollutants such as nitrates, nitrites, ammonia and phosphates. Adsorption capacities are investigated by altering the influence of adsorbent dosage, contact time, and pollutant concentrations (mg/L). Further analysis was carried out by studying the availability of biosorption capacity through kinetic suitability models such as pseudo-first-order and pseudo-second-order kinetics. The intensity of biosorption was studied using different isotherm studies such as Langmuir isotherm, Freundlich isotherm and Temkin isotherm (Nimibofa et al. 2017).

Novelty of this research article

The primary purpose of this research is to utilise a low-cost adsorbent to remove pollutants including nitrates, nitrites, phosphorus, and ammonia from agricultural wastewater. Many authors have employed various adsorbents to remove nitrates and phosphorus, but only a few have used novel adsorbents, which are a fusion of various adsorbents. The primary goal of this study is to determine the efficiency of a composite adsorbent, which is a combination of two individual adsorbents, fish scales and neem leaves powder, in removing four pollutants that are released directly into river bodies from untreated agricultural wastewater. Another critical aspect is the use of fish scales as an adsorbent to remove pollutants, particularly nitrates and phosphates, which cause eutrophication in river bodies if released in excess, which the authors have yet to investigate using fish scales.

MATERIALS AND METHODOLOGY

Preparation of adsorbent

Fish scales

Waste fish scales were collected from the local fish market near Kakinada bus station, Kakinada, Andhra Pradesh, India. Using distilled water, these fish scales were thoroughly washed to remove unwanted particles and subsequently dried at 110 °C using a hot air oven. Dried fish scales were then ground with a mortar grinder, and pulverised scales in powder form were collected by sieving through a 1-mm sieve and retained on an 850 μm particle size sieve (Figure 1).

Neem leaves

Neem leaves were collected locally from Kakinada, Andhra Pradesh, India, and then washed using distilled water to remove unwanted particles. A hot air oven was used to dry the leaves, which were then ground with a mortar grinder. Neem powder was obtained by passing through a 1-mm sieve and retained on an 850 μm particle size (Figure 2).

Preparation of adsorbate

Phosphate solution (stock) was prepared by dissolving a known amount of 0.439 g potassium dihydrogen orthophosphate (KH2PO4) in 1,000 mL distilled water. The desired solution (standard) was obtained by further diluting stock solution using distilled water. In similar manner, nitrate and nitrite stock solution was prepared by dissolving 0.7218 g of sodium nitrite salt (NaNO2) and potassium nitrate salt (KNO3) in 1,000 mL distilled water, respectively. The desired standard solutions of NO3 were obtained by diluting stock solution using distilled water; 0.7218 g ammonium chloride salt (NH4Cl) was dissolved in 1,000 mL distilled water to make an ammonia solution (stock). The desired standard solution was obtained by further diluting stock solution using distilled water.

Equipment used for testing of pollutants

After passing the samples through filter paper, the concentrations of nitrate, nitrite, ammonia, and phosphate for each sample were determined using a HACH DR 3900 Laboratory Spectrophotometer for water analysis and a WENSAR UV Visible spectrophotometer, LMSP UV 1200.

EXPERIMENTAL PROCEDURE

In the first stage, the dosage of adsorbents was fixed as 0.4 g, of which fish scale powder and neem leaf powder were taken equally, i.e., 0.2 g each. The concentration of pollutants in the stock solution was maintained as 50 mg/L. Following the addition of adsorbent to a solution, the flasks were rotated at the rate of 165 rpm; and the uptake of pollutants was tested for different contact periods with 10-minute variation until uptake capacity became constant. The results for different pollutants were recorded accordingly.

In the second stage, the concentration of pollutants was varied from 30 to 70 mg/L, keeping the dosage of adsorbents as 0.4 g with fish scale powder and neem leaf powder taken equally. Flasks containing the solution were rotated at the rate of 165 rpm, and the uptake of pollutants was tested for optimum contact time and results were noted.

In the third stage, the amount of adsorbent was altered by changing the dosages in three ways, i.e., by taking both adsorbents in the same dosage (0.2 g each), by increasing the dosage of one adsorbent (0.3 g) and decreasing the dosage of the other adsorbent (0.1 g) and vice versa, and results obtained were recorded accordingly.

Based on the results obtained, further analysis was carried out using different isotherm studies to determine the effective bond between adsorbents and different pollutants. Different kinetic studies were carried out to determine final optimum conditions to implement in that actual scenario.

Equilibrium studies

The following three isotherm studies were used in order to determine the effective bond between adsorbents and different pollutants.

Langmuir isotherm

The Langmuir isotherm equation is given by
formula
(1)
where Ceq (mg L−1) and qm (mg/g) are the equilibrium molecule concentration and the amount of adsorbed molecules on the adsorbent surface at any given moment, respectively.
The above equation is written as
formula
(2)

By plotting a graph between Ceq/qeq and Ceq, slope (1/qm) and intercept (1/(bqm)) can be determined. Separation factor (RL), which is given by RL = 1/(1 + bCeq), can be used for assessment of adsorbent on different pollutants.

Freundlich isotherm

The Freundlich isotherm can be expressed as (Babu & Gupta 2008)
formula
(3)

Kf represents the biosorption capacity of metal equilibrium concentration and 1/m represents a degree of biosorption with equilibrium concentration. For favourable biosorption, the value of m must be between 1 and 10 (Depci et al. 2012).

Taking logarithms on both sides, we get
formula
(4)

Temkin isotherm

The Temkin isotherm can be expressed as
formula
(5)
The above equation is rewritten as
formula
(6)

Kinetic studies

For kinetic theory, the experiment was conducted in batch studies under optimum conditions. The flasks were placed in an orbital shaker with a constant rotational speed of 165 rpm at constant room temperature and at different time intervals. Once shaking was completed, the conical flasks were filtered in a centrifuge and analysed for pollutant concentration. An extensive number of models have been developed with varying degrees of complexity to achieve pollutant adsorption kinetics. In the present work, pseudo-first-order and pseudo-second-order kinetics have been studied to analyse adsorption kinetics for given nitrate, nitrite, ammonia and phosphate using adsorbents.

Pseudo-first-order kinetic model

The pseudo-first-order kinetic model is given by (Katal et al. 2012)
formula
(7)
  • where qt (mg/g) is biosorption intensity at time t;

  • qeq (mg/g) is biosorption intensity at equilibrium time;

  • k1(min−1) is rate constant of first-order biosorption.

Applying boundary conditions, Integrating equation qt = 0 at t = 0 and q = qt at t = t,

the resultant equation becomes
formula
(8)

A plot of log (qeq − qt) vs t will be straight line with k1 as slope and logqeq as intercept.

Pseudo-second-order kinetics

The pseudo-second-order kinetic model (Kaparapu & Krishna Prasad 2018) is given by
formula
(9)
where k2 is rate constant for pseudo-second-order system
Applying boundary conditions qt = 0 at t = 0 and q = qt at t = t;
formula
(10)

Thermodynamic study

The thermodynamic study is given by
formula
(11)
where R is the molar gas constant (8.314 J mol−1 K−1), T is the absolute temperature in Kelvin, ΔG° (KJ/mol) is the Gibbs free energy change, enthalpy change ΔH° (KJ/mol), change in entropy ΔS° (KJmol−1 K−1), and KL (L/mg) is the constant.
Values of ΔH and ΔS are determined from the slope and intercept of a plot of lnKL against 1/T (Mudzielwana et al. 2019). Similarly, KL is given by
formula
(12)
where

RESULTS AND DISCUSSION

Effect of contact time

The effect of contact time was analysed by shaking 0.4 g of given adsorbents, i.e., mixture of powders of 0.2 g fish scales and 0.2 g neem leaves, in 200 mL of nitrate, nitrite, ammonia and phosphate solution concentration 50 mg/L. This operation was carried out for different time intervals, like 10, 20, 30, 40, up to 140 min, at a speed of 165 rpm (Zhang et al. 2009). Following every time interval, the sample was analysed to calculate the amount of nitrate, nitrite, ammonia and phosphate. Figure 3 shows % biosorption capacities at different time intervals. As the time interval increased, the adsorption capacities for the different pollutants also increased, and Table 1 shows the % biosorption capacities at optimum contact time. It can also be observed that % biosorption for nitrites is greater, followed by ammonia, nitrate and phosphate. It can be concluded that the removal affinity of adsorbents is greater for nitrites, ammonia, nitrate and phosphate. Similar results were also observed, i.e. the increase of adsorption capacity of Cr(VI) in the removal of Cr(VI) from an aqueous solution, where the contact time is varied from 10 to 70 min (Panda et al. 2017).

Figure 1

(a) Fish scales and (b) fish scale powder.

Figure 1

(a) Fish scales and (b) fish scale powder.

Figure 2

(a) Neem leaves and (b) neem leaves powder.

Figure 2

(a) Neem leaves and (b) neem leaves powder.

Figure 3

Pollutant biosorption values at various time intervals. (Initial concentration = 50 ppm, adsorbent dose = 0.2 g/200 mL pollutant solution, temperature = 30 °C, pH = 6, Orbital shaking speed = 165 rpm).

Figure 3

Pollutant biosorption values at various time intervals. (Initial concentration = 50 ppm, adsorbent dose = 0.2 g/200 mL pollutant solution, temperature = 30 °C, pH = 6, Orbital shaking speed = 165 rpm).

Table 1

% Biosorption for different pollutants at optimum contact time

PollutantContact time in min% of biosorption
Nitrate 140 96.24 
Nitrite 100 99.5 
Phosphate 140 95.92 
Ammonia 110 98.42 
PollutantContact time in min% of biosorption
Nitrate 140 96.24 
Nitrite 100 99.5 
Phosphate 140 95.92 
Ammonia 110 98.42 

Effect of adsorbent dose

50 m/L nitrate, nitrite, ammonia and phosphate solutions, each of 200 mL, with an equal amount of adsorbent dosage of 0.4 g, while dosage variance came from changing dosages of two adsorbents in three ways, i.e., by taking both adsorbents in equal dosage and by taking one adsorbent in greater dosage and the other adsorbent in lesser dosage and vice versa, and agitated with constant agitation speed at 165 rpm for equilibrium time at constant temperature (Wei et al. 2008). The concentration of nitrate, nitrite, ammonia and phosphate for each individual sample was determined. From Figure 4 and Table 2, it can be concluded that when the dosage of adsorbent of fish scales is 0.3 g and that of neem leaves is 0.1 g, the capacity for removal of pollutants gets increased as compared to the remaining two cases, and the order of % removal is nitrites, followed by ammonia, phosphates and nitrates. Previous research has shown that the increase in the adsorbent dose can increase the % biosorption capacity. For example, lead(II) removal using Polypyrrole-Based Activated Carbon has obtained similar results in that an increase in the adsorbent dosage improved the adsorption capacity (Alghamdi et al. 2019). However, in this study the adsorbent dosage is the same (0.4 g), but variations of the two adsorbents are made as shown in Table 2, which showed that the dosage of fish scales has more effect than that of neem leaves on the % removal of pollutants is more. From this it is evident that the efficiency of fish scales is more than that of neem leaves in removing pollutants. However, the combination of both showed better results.

Figure 4

Effect of dosage variance on % removal of different contaminants. (Initial concentration = 50 ppm, temperature = 30 °C, pH = 6, orbital shaking speed = 165 rpm.) Error bars represent the standard deviation of the mean.

Figure 4

Effect of dosage variance on % removal of different contaminants. (Initial concentration = 50 ppm, temperature = 30 °C, pH = 6, orbital shaking speed = 165 rpm.) Error bars represent the standard deviation of the mean.

Table 2

Effect of dosage variance on % biosorption of different pollutants

Dosage of fish scale powder (g)Dosage of neem powder (g)Total dosage of both fish scale and neem leaf powder (g)AmmoniaNitratesNitritesPhosphatesStandard error
0.3 0.1 0.4 98.68 97.46 99.64 96.92 0.6 
0.2 0.2 0.4 98.38 96.22 99.48 95.90 0.9 
0.1 0.3 0.4 96.58 94.58 99.24 93.76 1.2 
Dosage of fish scale powder (g)Dosage of neem powder (g)Total dosage of both fish scale and neem leaf powder (g)AmmoniaNitratesNitritesPhosphatesStandard error
0.3 0.1 0.4 98.68 97.46 99.64 96.92 0.6 
0.2 0.2 0.4 98.38 96.22 99.48 95.90 0.9 
0.1 0.3 0.4 96.58 94.58 99.24 93.76 1.2 

Effect of initial pollutant concentration (Co)

Different pollutant concentrations of 30, 40, 50, 60 and 70 mg/L (Ahmed et al. 2010), 200 mL of each, were transferred to 250 mL conical flasks. Subsequently, 0.4 g of fish scale powder and neem leaf powder in equal dosages (0.2 g/L) was added to each of those beakers. The beakers were kept under rotation at 165 rpm for optimum contact time at room temperature. Collected samples were passed through filter paper and tested for concentrations of nitrate, nitrite, ammonia and phosphate present in aqueous solution. From Figure 5 and Table 3, it can be deduced that when the initial concentration of pollutants was varied from 30 to 70 ppm, the adsorbent's efficiency decreased for a constant adsorbent dosage of 0.4 g. The decrease of the adsorption capacity with an increase in the pollution concentration can be validated by Katal et al. (2012). As the pollutant concentration rises from 50 to 300 mg/L, the adsorption capacity decreases from 94.5% to 46.3%.

Figure 5

Effect of varying concentrations of different pollutants. (Adsorbent dose = 0.2 g/200 mL pollutants solution, temperature = 30 °C, pH = 6, Orbital shaking speed = 165 rpm). Error bars represent the standard deviation of the mean.

Figure 5

Effect of varying concentrations of different pollutants. (Adsorbent dose = 0.2 g/200 mL pollutants solution, temperature = 30 °C, pH = 6, Orbital shaking speed = 165 rpm). Error bars represent the standard deviation of the mean.

Table 3

Effect of adsorbent on different pollutants with variations in initial pollution concentration

Initial pollutant concentration% removal of nitrates% removal of nitrites% removal of ammonia% removal of phosphatesStandard error
30 97.17 99.63 98.70 96.73 0.2 
40 96.70 99.55 98.68 96.38 0.2 
50 96.22 99.48 98.38 95.90 0.3 
60 95.40 99.28 97.42 94.65 0.3 
70 94.87 99.10 96.26 93.51 0.4 
Initial pollutant concentration% removal of nitrates% removal of nitrites% removal of ammonia% removal of phosphatesStandard error
30 97.17 99.63 98.70 96.73 0.2 
40 96.70 99.55 98.68 96.38 0.2 
50 96.22 99.48 98.38 95.90 0.3 
60 95.40 99.28 97.42 94.65 0.3 
70 94.87 99.10 96.26 93.51 0.4 

Effect of pH

The surface charge of the biosorbent material and the degree of ionisation of the pollutant are affected by an aqueous solution's pH, a vital monitoring parameter in biosorption. In this research the removal efficiencies of nitrates, nitrites, phosphates and ammonia biosorption data were determined and obtained in the pH range of 2 to 9 (Abdus-Salam & Adekola 2005) with C0 = 50 mg/L, along with 0.4 g of integrated biosorbent (0.2 g of each, i.e. fish scales and neem leaves powder). Figure 6 and Table 4 depict the influence of aqueous solution pH on the % biosorption of several contaminants along with the error bars. The % biosorption of the nitrates, nitrites and ammonia has shown a significant increase when pH value is varied between 2 and 6, and it is also seen that there is a decrease in the % biosorption after pH 6 in reference to Figure 8 and Table 4. This result is comparable to adsorptive nitrate removal using red mud at pH 7, and beyond that pH value the % biosorption decreased (Cengeloglu et al. 2006), and on the contrary, as shown in Figure 8, the maximum % biosorption capacity for both the phosphates and nitrates is observed in the pH range from 5 to 7, and the pH value less than 4 and pH value greater than 7 did not show maximum % biosorption removal.

Figure 6

Effect of pH on different pollutants. (Adsorbent dose = 0.2 g/200 mL pollutants solution, initial concentration = 50 ppm, temperature = 30 °C, orbital shaking speed = 165 rpm). Error bars represent the standard deviation of the mean.

Figure 6

Effect of pH on different pollutants. (Adsorbent dose = 0.2 g/200 mL pollutants solution, initial concentration = 50 ppm, temperature = 30 °C, orbital shaking speed = 165 rpm). Error bars represent the standard deviation of the mean.

Figure 7

Effect of Temperature on different pollutants. (Adsorbent dose = 0.2 g/200 mL pollutants solution, initial concentration = 50 ppm, pH = 6, orbital shaking speed = 165 rpm). Error bars represent the standard deviation of the mean.

Figure 7

Effect of Temperature on different pollutants. (Adsorbent dose = 0.2 g/200 mL pollutants solution, initial concentration = 50 ppm, pH = 6, orbital shaking speed = 165 rpm). Error bars represent the standard deviation of the mean.

Figure 8

(a)–(d): Plot between ln(KL) vs 1/T for two different adsorbents. (Adsorbent dose = 0.4 g/200 mL pollutants solution, initial concentration = 50 ppm, pH = 6, orbital shaking speed = 165 rpm).

Figure 8

(a)–(d): Plot between ln(KL) vs 1/T for two different adsorbents. (Adsorbent dose = 0.4 g/200 mL pollutants solution, initial concentration = 50 ppm, pH = 6, orbital shaking speed = 165 rpm).

Table 4

Effect of pH on % removal of different pollutants

pH% removal of nitrates% removal of nitrites% removal of phosphates% removal of ammoniaStandard error
93.76 97.70 93.76 97.04 1.1 
94.24 98.16 94.30 97.36 1.0 
95.08 98.44 95.38 97.62 0.8 
95.78 98.98 95.92 98.12 0.8 
96.22 99.48 95.92 98.38 0.9 
95.84 99.32 95.9 98.22 0.9 
95.1 99.04 94.92 97.82 1.0 
94.22 98.66 94.16 97.44 1.1 
pH% removal of nitrates% removal of nitrites% removal of phosphates% removal of ammoniaStandard error
93.76 97.70 93.76 97.04 1.1 
94.24 98.16 94.30 97.36 1.0 
95.08 98.44 95.38 97.62 0.8 
95.78 98.98 95.92 98.12 0.8 
96.22 99.48 95.92 98.38 0.9 
95.84 99.32 95.9 98.22 0.9 
95.1 99.04 94.92 97.82 1.0 
94.22 98.66 94.16 97.44 1.1 

Effect of temperature

The effects of changes in the temperature on different pollutant uptake are shown in Figure 7, which along with Table 5 represents the biosorption of nitrates, nitrites, phosphates and ammonia by the combination of fish scales and neem leaves powder as a novel adsorbent. From the research it is evident that when the temperature was raised, the biosorption capacity increased. The temperature was investigated in batch experiments carried out at five constant temperatures: 298, 303, 308, 313 and 318 K (Jiang et al. 2018). With an increase in temperature, the % removal was increased from 95.04% to 97.36% for nitrates, 99.16% to 99.82% for nitrites, 97.96% to 99.34% for ammonia and 94.76% to 97.04% for phosphates for initial pollutants concentration of 50 mg/L. Because of the chemical interaction between biosorbates and biosorbents, and the increased rate of intra-particle diffusion, we can conclude that the biosorption reaction is endothermic (Gouamid et al. 2013).

Table 5

Effect of temperature variations on % removal of different pollutants

Temperature (K)% removal of nitrates% removal of nitrites% removal of phosphates% removal of ammoniaStandard error
298 95.04 99.16 94.76 97.96 1.09 
303 96.22 99.48 95.90 98.38 0.86 
308 96.64 99.64 96.22 98.68 0.82 
313 96.88 99.76 96.72 99.08 0.77 
318 97.36 99.82 97.04 99.34 0.70 
Temperature (K)% removal of nitrates% removal of nitrites% removal of phosphates% removal of ammoniaStandard error
298 95.04 99.16 94.76 97.96 1.09 
303 96.22 99.48 95.90 98.38 0.86 
308 96.64 99.64 96.22 98.68 0.82 
313 96.88 99.76 96.72 99.08 0.77 
318 97.36 99.82 97.04 99.34 0.70 

Thermodynamic studies

To determine the applicability of fish scales and neem leaves as a novel adsorbent for the removal of nitrates, nitrites, ammonia and phosphates, the thermodynamic parameters such as Gibbs free energy (ΔG), enthalpy change (ΔH), and entropy change (ΔS) are used to investigate the adsorption thermodynamics. These parameters ΔG, ΔH, and ΔS can be calculated using Equations (11) and (13), and the values of ΔH and ΔS are calculated using the slope and intercept of a plot of lnKL against 1/T. Table 6 provides the values of ΔG at different temperatures for different pollutants with fish scales and neem leaves powder as a novel adsorbent, and Figure 8(a)–8(d) exhibits the graphs of lnKL against 1/T. The negative value (ΔG) for all the four pollutants denotes that nitrates, nitrites, ammonia and phosphates adsorption on to the fish scales and neem leaves powder as a novel adsorbent is spontaneous and favourable (Rincón-Silva et al. 2016). Enthalpy change (ΔH) is positive, indicating that the adsorption of nitrates, nitrites, ammonia and phosphates was endothermic (Doke & Khan 2013). The entropy change (ΔS) value is also positive, suggesting that the ions of nitrates, nitrites, ammonia, and phosphates are dispersed randomly over the adsorbent surface (Manoj Kumar Reddy et al. 2013).

Table 6

Thermodynamic parameters of nitrates, nitrites, ammonia and phosphates

PollutantTemp (K)KLΔG (KJ mol−1)ΔH (KJ mol−1)ΔS (JK−1 mol−1)R2
Nitrates 298 9.581 −5.599 23.830 99.233 0.9559 
303 12.728 −6.408 
308 14.381 −6.827 
313 15.526 −7.137 
318 18.439 −7.705 
Nitrites 298 59.024 −10.103 61.06 239.143 0.9958 
303 95.654 −11.489 
308 138.389 −12.624 
313 207.833 −13.888 
318 277.278 −14.872 
Ammonia 298 24.010 −7.875 44.93 176.747 0.9822 
303 30.364 −8.598 
308 37.379 −9.273 
313 53.848 −10.373 
318 75.258 −11.424 
Phosphates 298 9.042 −5.455 22.45 94.056 0.9692 
303 11.695 −6.195 
308 12.728 −6.514 
313 14.744 −7.002 
318 16.392 −7.394 
PollutantTemp (K)KLΔG (KJ mol−1)ΔH (KJ mol−1)ΔS (JK−1 mol−1)R2
Nitrates 298 9.581 −5.599 23.830 99.233 0.9559 
303 12.728 −6.408 
308 14.381 −6.827 
313 15.526 −7.137 
318 18.439 −7.705 
Nitrites 298 59.024 −10.103 61.06 239.143 0.9958 
303 95.654 −11.489 
308 138.389 −12.624 
313 207.833 −13.888 
318 277.278 −14.872 
Ammonia 298 24.010 −7.875 44.93 176.747 0.9822 
303 30.364 −8.598 
308 37.379 −9.273 
313 53.848 −10.373 
318 75.258 −11.424 
Phosphates 298 9.042 −5.455 22.45 94.056 0.9692 
303 11.695 −6.195 
308 12.728 −6.514 
313 14.744 −7.002 
318 16.392 −7.394 

Adsorption isotherms

Langmuir isotherm

The Langmuir isotherm is explained in Figure 9(a)–9(d), where the graph was produced between Ceq and Ceq/Qeq. It can be concluded that there is an effective link between adsorbent and various contaminants based on the Langmuir constant (b) values of nitrates, nitrites, ammonia, and phosphates. Constant b values declined in the following order: nitrites, ammonia, phosphates, and nitrates, as shown in Table 7. Table 7 also shows that the maximum adsorption capabilities ranged from 41.84 to 54.34 mg/g. It can be extrapolated from this that when the value of b increased, the percentage of pollutants eliminated increased.

Figure 9

(a)–(d) Langmuir isotherm graph for % biosorption of nitrates, nitrites, phosphates and ammonia.

Figure 9

(a)–(d) Langmuir isotherm graph for % biosorption of nitrates, nitrites, phosphates and ammonia.

Table 7

Langmuir isotherm parameters

PollutantEquationQmax (mg/g)b, L/mgR2
Nitrate (Ceq/Qeq) = 0.0184 Ceq + 0.0437 54.34 0.421 0.9954 
Nitrite (Ceq/Qeq) = 0.0209 Ceq + 0.0052 47.84 4.019 0.998 
Phosphate (Ceq/Qeq) = 0.0204 Ceq + 0.046 49.01 0.443 0.997 
Ammonia (Ceq/Qeq) = 0.0239 Ceq + 0.0152 41.84 1.572 0.9961 
PollutantEquationQmax (mg/g)b, L/mgR2
Nitrate (Ceq/Qeq) = 0.0184 Ceq + 0.0437 54.34 0.421 0.9954 
Nitrite (Ceq/Qeq) = 0.0209 Ceq + 0.0052 47.84 4.019 0.998 
Phosphate (Ceq/Qeq) = 0.0204 Ceq + 0.046 49.01 0.443 0.997 
Ammonia (Ceq/Qeq) = 0.0239 Ceq + 0.0152 41.84 1.572 0.9961 

Freundlich isotherm

It can be shown that values of the Freundlich constant (Kf), which represent biosorption capacities of different pollutants, reduced in the following order: nitrites, ammonia, phosphates, and nitrates, as shown in Table 8. From this, it can be determined that as the Kf value increased, so did the percentage of contaminants. The Freundlich constant M values in Table 8 range from 1.77 to 2.48, indicating that adsorption is favourable in these conditions. The value of M must be between 1 and 10 for good biosorption.

Table 8

Freundlich isotherm parameters

PollutantEquationKf (mg/g)MR2
Nitrate log Qeq = 0.5651 log Ceq + 1.2124 16.30 1.77 0.996 
Nitrite log Qeq = 0.4784 log Ceq + 1.6499 44.64 2.09 0.9861 
Phosphate log Qeq = 0.5206 log Ceq + 1.1894 15.466 1.92 0.9778 
Ammonia log Qeq = 0.4034 log Ceq + 1.3835 24.18 2.48 0.9318 
PollutantEquationKf (mg/g)MR2
Nitrate log Qeq = 0.5651 log Ceq + 1.2124 16.30 1.77 0.996 
Nitrite log Qeq = 0.4784 log Ceq + 1.6499 44.64 2.09 0.9861 
Phosphate log Qeq = 0.5206 log Ceq + 1.1894 15.466 1.92 0.9778 
Ammonia log Qeq = 0.4034 log Ceq + 1.3835 24.18 2.48 0.9318 

Temkin isotherm

The Temkin isotherm parameters for different pollutants, i.e., nitrates, nitrites, ammonia and phosphates, and their relation are shown in Figure 11(a)–11(d), and Table 9 shows the Temkin constants AT and BT values. Based on isotherm studies and from values of linear regression coefficients (R2), it can be concluded that the Langmuir model is best suited for biosorption studies for the various pollution concentrations.

Adsorption kinetics

Pseudo-first-order kinetic model

Based on values of rate constant K1 from Table 10 and linear regression coefficient R2 values from Figure 12(a)–12(d), it can be concluded that first-order kinetics is not best suited for the study of suitability for removal of different pollutants using adsorbents when compared with values of second-order kinetics.

Figure 10

(a)–(d) Freundlich isotherm graph for % biosorption of nitrates, nitrites, phosphates and ammonia.

Figure 10

(a)–(d) Freundlich isotherm graph for % biosorption of nitrates, nitrites, phosphates and ammonia.

Figure 11

(a)–(d) Temkin isotherm graph for % biosorption of nitrates, nitrites, phosphates and ammonia.

Figure 11

(a)–(d) Temkin isotherm graph for % biosorption of nitrates, nitrites, phosphates and ammonia.

Figure 12

(a)–(d) First-order adsorption kinetics of nitrates, nitrites, phosphates and ammonia.

Figure 12

(a)–(d) First-order adsorption kinetics of nitrates, nitrites, phosphates and ammonia.

Table 9

Temkin isotherm parameters

PollutantEquationAT, L/mgbT, J/mgR2
Nitrate Qeq = 0.389 lnCeq − 1.2551 0.939 32,371.91 R2 = 0.9944 
Nitrite Qeq = 0.4418 lnCeq − 3.510 0.975 28,497.08 R2 = 0.9978 
Phosphate Qeq = 04235 lnCeq − 1.264 0.935 29,741.94 R2 = 0.9978 
Ammonia Qeq = 0.5151 lnCeq − 2.5921 0.961 24,457.69 R2 = 0.9785 
PollutantEquationAT, L/mgbT, J/mgR2
Nitrate Qeq = 0.389 lnCeq − 1.2551 0.939 32,371.91 R2 = 0.9944 
Nitrite Qeq = 0.4418 lnCeq − 3.510 0.975 28,497.08 R2 = 0.9978 
Phosphate Qeq = 04235 lnCeq − 1.264 0.935 29,741.94 R2 = 0.9978 
Ammonia Qeq = 0.5151 lnCeq − 2.5921 0.961 24,457.69 R2 = 0.9785 
Table 10

First-order equation and coefficients

KineticsPollutantModel equationR2Rate constant, K1
First-order Nitrate log(Qeq − Qt) = −0.0251 t–1.4886 0.7402 0.0578 min−1 
First-order Nitrite log(Qeq − Qt) = −0.0354 t–1.2572 0.8225 0.0851 min−1 
First-order Phosphate log(Qeq − Qt) = −0.025 t–1.5375 0.7163 0.0575 min−1 
First-order Ammonia log(Qeq − Qt) = −0.0307 t–1.4067 0.7862 0.0707 min−1 
KineticsPollutantModel equationR2Rate constant, K1
First-order Nitrate log(Qeq − Qt) = −0.0251 t–1.4886 0.7402 0.0578 min−1 
First-order Nitrite log(Qeq − Qt) = −0.0354 t–1.2572 0.8225 0.0851 min−1 
First-order Phosphate log(Qeq − Qt) = −0.025 t–1.5375 0.7163 0.0575 min−1 
First-order Ammonia log(Qeq − Qt) = −0.0307 t–1.4067 0.7862 0.0707 min−1 

Pseudo-second-order kinetic model

Based on tabulated values from Table 11 of rate constant (K2), it can be observed that values of constant K2 increased in the following order, i.e., nitrites, ammonia, phosphates and nitrates. From this, it can be deduced that as the K2 value grew, the percentage of contaminants removed increased. From the R2 values from Figure 13(a)–13(d), it may be stated that second-order kinetics is the best fit for describing the kinetic investigations of four different contaminants using novel adsorbents (combination of fish scales and neem leaves).

Figure 13

(a)–(d) Second-order adsorption kinetics of nitrates, nitrites, phosphates and ammonia.

Figure 13

(a)–(d) Second-order adsorption kinetics of nitrates, nitrites, phosphates and ammonia.

Table 11

Second-order equation and coefficients

KineticsPollutantModel equationR2Rate constant, K2
Pseudo-second-order Nitrate t/Qt = 0.04 t + 0.2567 0.9976 0.0062 g.(mg.min)−1 
Pseudo-second-order Nitrite t/Qt = 0.0985 t + 0.1968 0.9999 0.0197 g.(mg.min)−1 
Pseudo-second-order Phosphate t/Qt = 0.1001 t + 0.7262 0.9967 0.0055 g.(mg.min)−1 
Pseudo-second-order Ammonia t/Qt = 0.0983 t + 0.4199 0.9990 0.0092 g.(mg.min)−1 
KineticsPollutantModel equationR2Rate constant, K2
Pseudo-second-order Nitrate t/Qt = 0.04 t + 0.2567 0.9976 0.0062 g.(mg.min)−1 
Pseudo-second-order Nitrite t/Qt = 0.0985 t + 0.1968 0.9999 0.0197 g.(mg.min)−1 
Pseudo-second-order Phosphate t/Qt = 0.1001 t + 0.7262 0.9967 0.0055 g.(mg.min)−1 
Pseudo-second-order Ammonia t/Qt = 0.0983 t + 0.4199 0.9990 0.0092 g.(mg.min)−1 

COMPARISON WITH OTHER ADSORBENTS

The adsorption capacity of various adsorbents that have already been used for the removal of nitrates and phosphates has been compared. According to Table 12, none of the researchers used the composite adsorbent to remove nitrates and phosphates. In comparison to the adsorbents listed in Table 12, the removal efficiency of fish scale and neem leaves as novel adsorbents in the removal of nitrates and phosphates is significant.

Table 12

Comparison of absorption capacities of different adsorbents with the present studied adsorbents

AdsorbentNitrate (mg/g)Phosphate (mg/g)References
Solid waste residue (SWR) from aluminium sulphate factory 0.065 13.15 Berkessa et al. (2019)  
Clinoptilolite-Supported Iron Hydroxide Nanoparticle 10.1 9.71 Mikhak et al. (2017)  
Amine crosslinked magnetic banana bract activated carbon 75.81 91.78 Karthikeyan et al. (2020)  
Modified commercial activated carbon 21.51 – Mazarji et al. (2017)  
Fish scales and neem leaves as novel adsorbent 24.06 23.98 This study 
AdsorbentNitrate (mg/g)Phosphate (mg/g)References
Solid waste residue (SWR) from aluminium sulphate factory 0.065 13.15 Berkessa et al. (2019)  
Clinoptilolite-Supported Iron Hydroxide Nanoparticle 10.1 9.71 Mikhak et al. (2017)  
Amine crosslinked magnetic banana bract activated carbon 75.81 91.78 Karthikeyan et al. (2020)  
Modified commercial activated carbon 21.51 – Mazarji et al. (2017)  
Fish scales and neem leaves as novel adsorbent 24.06 23.98 This study 

CONCLUSIONS

This study was carried out to effectively remove four major pollutants, namely nitrates, nitrites, ammonia and phosphates, using waste materials such as fish scales and neem leaves as adsorbents. About 95% to 99% of contaminants could be removed from the considered pollutant concentration range using a combination of fish scales and neem leaves as adsorbents. The percentage removal efficiency for nitrates with the combination of fish scales and neem leaves as novel adsorbent for optimum contact time of 140 min was 96.24%. In contrast, for nitrites, for optimum contact time of 100 min, the value was 99.48%. Similarly, percentage removal efficiency for phosphates and ammonia with the integration of fish scales and neem leaves as novel adsorbent for optimum contact times of 140 and 110 min was 95.92% and 98.38%, respectively, by maintaining the adsorbent dosage as 0.4 g (0.2 g fish scales and 0.2 g neem leaves powder), pH values constant at 6 and temperature value as 303 K. It is evident that when the temperature was varied from 298 to 318 K, the biosorption capacities for the nitrates, nitrites, ammonia and phosphates increased. As a result, thermodynamic studies were done from, which the values of ΔG, ΔH and ΔS were calculated. The negative value of ΔG for all the four pollutants denotes that the adsorption of nitrates, nitrites, ammonia and phosphates on to the fish scales and neem leaves powder as a novel adsorbent is spontaneous and favourable. Based on the enthalpy change (ΔH), which is positive, it can be deduced that the biosorption reaction is endothermic. The Langmuir model is a good fit for the sorption data in the concentration range tested, based on the above investigations and the results of linear regression coefficient (R2) values. Because the second-order constant K2 value is much lower than that of the first-order constant K1, pseudo-second-order kinetics is the ideal model for kinetic data assessments. Furthermore, the values of constant K2 are observed to rise in the following order: nitrites, ammonia, nitrates, and phosphates, implying that the percentage of pollutants removed increases as the K2 value increases. Finally, the novel adsorbents, a combination of fish scales and neem leaves, have the potential and success of removing the four significant pollutants, nitrates, nitrites, ammonia, and phosphates, from synthetic aqueous solutions.

DATA AVAILABILITY STATEMENT

All relevant data are included in the paper or its Supplementary Information.

REFERENCES

Abdus-Salam
N.
&
Adekola
F.
2005
The influence of pH and adsorbent concentration on adsorption of lead and zinc on a natural goethite
.
African Journal of Science and Technology
6
(
2
).
https://doi.org/10.4314/ajst.v6i2.55175
.
Ahmed
Y. M.
,
Mamun
A. A.
,
Muyibi
S. A.
,
Al-Khatib
M. F. R.
,
Jameel
A. T.
&
AlSaadi
M. A.
2010
Effect of Adsorbate Initial Concentration on the Removal of Pb from Aqueous Solutions by Carbon Nanofibers
. In:
24th Symposium of Malaysian Chemical Engineers (SOMChE 2010) and 1st International Conference on Process Engineering and Advanced Materials 2010 (ICPEAM2010)
, pp.
15
17
.
Alghamdi
A. A.
,
Al-Odayni
A. B.
,
Saeed
W. S.
,
Al-Kahtani
A.
,
Alharthi
F. A.
&
Aouak
T.
2019
Efficient adsorption of lead (II) from aqueous phase solutions using polypyrrole-based activated carbon
.
Materials
12
(
12
).
https://doi.org/10.3390/ma12122020
.
Andrade
C. A.
,
Zambrano-Intriago
L. A.
,
Oliveira
N. S.
,
Vieira
J. S.
,
Quiroz-Fernández
L. S.
&
Rodríguez-Díaz
J. M.
2020
Adsorption behavior and mechanism of oxytetracycline on rice husk ash: kinetics, equilibrium, and thermodynamics of the process
.
Water, Air, and Soil Pollution
231
(
3
).
https://doi.org/10.1007/s11270-020-04473-6
.
Babu
B. V.
&
Gupta
S.
2008
Adsorption of Cr(VI) using activated neem leaves: kinetic studies
.
Adsorption
14
(
1
).
https://doi.org/10.1007/s10450-007-9057-x
.
Berkessa
Y. W.
,
Mereta
S. T.
&
Feyisa
F. F.
2019
Simultaneous removal of nitrate and phosphate from wastewater using solid waste from factory
.
Applied Water Science
9
(
2
).
https://doi.org/10.1007/s13201-019-0906-z
.
Cengeloglu
Y.
,
Tor
A.
,
Ersoz
M.
&
Arslan
G.
2006
Removal of nitrate from aqueous solution by using red mud
.
Separation and Purification Technology
51
(
3
),
374
378
.
https://doi.org/10.1016/j.seppur.2006.02.020
.
Depci
T.
,
Kul
A. R.
&
Önal
Y.
2012
Competitive adsorption of lead and zinc from aqueous solution on activated carbon prepared from Van apple pulp: study in single- and multi-solute systems
.
Chemical Engineering Journal
,
200–202
,
224
236
.
https://doi.org/10.1016/j.cej.2012.06.077
.
Doke
K. M.
&
Khan
E. M.
2013
Adsorption thermodynamics to clean up wastewater; critical review
.
Reviews in Environmental Science and Biotechnology
12
(
1
),
25
44
.
https://doi.org/10.1007/s11157-012-9273-z
.
Gouamid
M.
,
Ouahrani
M. R.
&
Bensaci
M. B.
2013
Adsorption equilibrium, kinetics and thermodynamics of methylene blue from aqueous solutions using Date palm Leaves
.
Energy Procedia
36
,
898
907
.
https://doi.org/10.1016/j.egypro.2013.07.103
.
Jiang
L. L.
,
Yu
H. T.
,
Pei
L. F.
&
Hou
X. G.
2018
The effect of temperatures on the synergistic effect between a magnetic field and functionalized graphene oxide-carbon nanotube composite for Pb2+ and phenol adsorption
.
Journal of Nanomaterials
2018
.
https://doi.org/10.1155/2018/9167938
.
Kang
J.
&
Jeen
S. W.
2021
Simultaneous removal of nitrate and phosphate in groundwater using Ca-citrate complex
.
Environmental Science and Pollution Research
28
,
35738
35750
.
https://doi.org/10.1007/s11356-021-13312-y
.
Kaparapu
J.
&
Krishna Prasad
M.
2018
Equilibrium, kinetics and thermodynamic studies of cadmium(II) biosorption on Nannochloropsis oculata
.
Applied Water Science
8
(
6
).
https://doi.org/10.1007/s13201-018-0810-y
.
Karthikeyan
P.
,
Vigneshwaran
S.
&
Meenakshi
S.
2020
Removal of phosphate and nitrate ions from water by amine crosslinked magnetic banana bract activated carbon and its physicochemical performance
.
Environmental Nanotechnology, Monitoring and Management
13
,
100294
.
https://doi.org/10.1016/j.enmm.2020.100294
.
Katal
R.
,
Baei
M. S.
,
Rahmati
H. T.
&
Esfandian
H.
2012
Kinetic, isotherm and thermodynamic study of nitrate adsorption from aqueous solution using modified rice husk
.
Journal of Industrial and Engineering Chemistry
18
(
1
),
295
302
.
https://doi.org/10.1016/j.jiec.2011.11.035
.
Liao
J.
,
Zhang
Y.
,
He
X.
,
Zhang
L.
&
He
Z.
2021
The synthesis of a novel titanium oxide aerogel with highly enhanced removal of uranium and evaluation of the adsorption mechanism
.
Dalton Transactions
50
(
10
).
https://doi.org/10.1039/d0dt04320f
.
Lito
P. F.
,
Aniceto
J. P. S.
&
Silva
C. M.
2012
Removal of anionic pollutants from waters and wastewaters and materials perspective for their selective sorption
.
Water, Air, and Soil Pollution
223
,
6133
6155
.
https://doi.org/10.1007/s11270-012-1346-7
.
Manoj Kumar Reddy
P.
,
Mahammadunnisa
S.
,
Ramaraju
B.
,
Sreedhar
B.
&
Subrahmanyam
C.
2013
Low-cost adsorbents from bio-waste for the removal of dyes from aqueous solution
.
Environmental Science and Pollution Research
20
(
6
),
4111
4124
.
https://doi.org/10.1007/s11356-012-1360-8
.
Mazarji
M.
,
Aminzadeh
B.
,
Baghdadi
M.
&
Bhatnagar
A.
2017
Removal of nitrate from aqueous solution using modified granular activated carbon
.
Journal of Molecular Liquids
233
,
139
148
.
https://doi.org/10.1016/j.molliq.2017.03.004
.
Mikhak
A.
,
Sohrabi
A.
,
Kassaee
M. Z.
,
Feizian
M.
&
Najafi Disfani
M.
2017
Removal of nitrate and phosphate from water by clinoptilolite-supported iron hydroxide nanoparticle
.
Arabian Journal for Science and Engineering
42
(
6
),
2433
2439
.
https://doi.org/10.1007/s13369-017-2432-3
.
Mudzielwana
R.
,
Gitari
W. M.
&
Ndungu
P.
2019
Removal of As(III) from synthetic groundwater using Fe-Mn bimetal modified kaolin clay: adsorption kinetics, isotherm and thermodynamics studies
.
Environmental Processes
6
(
4
),
1005
1018
.
https://doi.org/10.1007/s40710-019-00397-4
.
Mutavdžić Pavlović
D.
,
Ćurković
L.
,
Grčić
I.
,
Šimić
I.
&
Župan
J.
2017
Isotherm, kinetic, and thermodynamic study of ciprofloxacin sorption on sediments
.
Environmental Science and Pollution Research
24
(
11
),
10091
10106
.
https://doi.org/10.1007/s11356-017-8461-3
.
Nimibofa
A.
,
Ebelegi
A. N.
&
Wankasi
D.
2017
Modelling and interpretation of adsorption isotherms
.
Journal of Chemistry
.
https://doi.org/10.1155/2017/3039817
.
Panda
H.
,
Tiadi
N.
,
Mohanty
M.
&
Mohanty
C. R.
2017
Studies on adsorption behavior of an industrial waste for removal of chromium from aqueous solution
.
South African Journal of Chemical Engineering
23
,
132
138
.
https://doi.org/10.1016/j.sajce.2017.05.002
.
Pimentel
D.
,
Petrova
T.
,
Riley
M.
,
Jacquet
J.
,
Ng
V.
,
Honigman
J.
&
Valero
E.
2007
Water resources: agricultural and environmental issues
. In:
Food, Energy, and Society, Third Edition
.
https://doi.org/10.1201/9781420046687
.
Rao
N. S.
2006
Nitrate pollution and its distribution in the groundwater of Srikakulam district, Andhra Pradesh, India
.
Environmental Geology
51
(
4
),
631
645
.
https://doi.org/10.1007/s00254-006-0358-2
.
Rincón-Silva
N. G.
,
Moreno-Piraján
J. C.
&
Giraldo
L.
2016
Equilibrium, kinetics and thermodynamics study of phenols adsorption onto activated carbon obtained from lignocellulosic material (Eucalyptus Globulus labill seed)
.
Adsorption
22
(
1
),
33
48
.
https://doi.org/10.1007/s10450-015-9724-2
.
Sanka
P. M.
,
Rwiza
M. J.
&
Mtei
K. M.
2020
Removal of selected heavy metal ions from industrial wastewater using rice and corn husk biochar
.
Water, Air, and Soil Pollution
231
(
5
).
https://doi.org/10.1007/s11270-020-04624-9
.
Sharma
A.
&
Bhattacharyya
K. G.
2005
Azadirachta indica (Neem) leaf powder as a biosorbent for removal of Cd(II) from aqueous medium
.
Journal of Hazardous Materials
125
(
1–3
),
102
112
.
https://doi.org/10.1016/j.jhazmat.2005.05.012
.
Siyal
A. A.
,
Shamsuddin
M. R.
,
Rabat
N. E.
,
Zulfiqar
M.
,
Man
Z.
&
Low
A.
2019
Fly ash based geopolymer for the adsorption of anionic surfactant from aqueous solution
.
Journal of Cleaner Production
229
,
232
243
.
https://doi.org/10.1016/j.jclepro.2019.04.384
.
Wei
X.
,
Viadero
R. C.
&
Bhojappa
S.
2008
Phosphorus removal by acid mine drainage sludge from secondary effluents of municipal wastewater treatment plants
.
Water Research
42
(
13
),
3275
3284
.
https://doi.org/10.1016/j.watres.2008.04.005
.
Zhang
G.
,
Liu
H.
,
Liu
R.
&
Qu
J.
2009
Removal of phosphate from water by a Fe-Mn binary oxide adsorbent
.
Journal of Colloid and Interface Science
335
(
2
),
168
174
.
https://doi.org/10.1016/j.jcis.2009.03.019
.
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