A novel green solution to metal pollution in aquatic environment: Pyracantha coccinea M. J. Roemer

ABSTRACT

Metal pollution today has reached the level of a great threat to humans and their environment. A novel green solution was presented for metal pollution in aquatic environment using Pyracantha coccinea M. J. Roemer in the current study. Due to its widespread industrial use, manganese pollution in water environment has become a serious issue in recent years, and for this reason, it was used as a model metal to determine the treatment potential of P. coccinea M. J. Roemer. The results showed that the pseudo-second-order kinetic model and Freundlich isotherm model agreed well with the experimental data, and the biosorption process had a physical, spontaneous and favourable nature. The maximum metal biosorption capacity was determined to be 59.867 mg g⁻¹. This study showed that P. coccinea M. J. Roemer could present an environmentally friendly, cost-effective, effectual solution for the metal issue in aquatic environment.

KEYWORDS:

• Green removal
• Pyracantha coccinea M. J. Roemer
• metal pollution
• manganese
• aquatic environment

1. Introduction

Metals are inorganic substances that we use widely in almost every aspect of our lives. In addition, some metals such as copper, zinc and manganese are needed in low amounts for vital functions in us and other living things. However, some metals such as mercury, cadmium and lead cause vital problems even in very low amounts [1,2]. In recent years, especially as a result of industrial, agricultural, mining and domestic intense anthropogenic activities, a large amount of metal has been released into aquatic environment [3,4]. This situation causes even more pressure on the limited amount of usable water in the world for vital activities. Metals are non-biodegradable, persistent micropollutants and have bioaccumulation and biomagnification properties. They cause numerous serious vital troubles, including toxicity and carcinogenicity, on humans and other living things [2,5–7]. For this reason, it is vital to reduce the amount of metal in aquatic environment to a level that will not harm living life for the continuity of biological activity in the world ecosystem in an orderly manner.

A variety of techniques such as extraction, accumulation, oxidation, coagulation, membrane separation, reduction, ion exchange and chemical precipitation are usually used to remove metals from aqueous medium [4,8,9]. But most of these methods have troubles such as high energy consumption, secondary pollution formation, usage of noxious chemicals, low efficiency, high cost, generation of harmful by-products and inefficiency at low metal concentration levels [4,5,10]. Biosorption, in which various non-living biomass is used as biosorbent, is currently considered the most suitable alternative metal treatment option. It is a flexible, low-cost, efficient, simple, environmentally friendly and promising sustainable removal technology [3,11–13].

Selection of biosorbent material is key to an efficient biosorption operation [10,14]. Therefore, in recent years, numerous studies have focused on the search for efficient biosorbent for metal removal [10,15,16]. Within this perspective, the current study aimed to present a novel green, efficient, cost-effective and sustainable solution for metal pollution in aquatic environment with Pyracantha coccinea M. J. Roemer. P. coccinea M. J. Roemer is an easy-care, robust shrub-shaped plant species that is widely available in many countries around the world. The plant has widespread use in many fields such as biomonitoring, medicine, food, decoration, erosion prevention and biocontrol [17–19]. In addition to these fields, the use of the plant material in the biosorption process, which is an environmentally friendly cleanup technology, and opportunities such as reuse of the final material in the treatment process after desorption operation or as fertilizer provide an important sustainable contribution to the circular bioeconomy [20–22]. On the other hand, manganese pollution in water environment has become a serious issue in recent years due to its widespread industrial use. Manganese is an essential trace element required for biological activities in human beings and other living things. When this element is found in high amounts in water medium, it causes crucial troubles on living health, as well as many problems on water quality for domestic and industrial applications [23–26]. For this reason, manganese was used as a model metal in the present study to determine the biosorption potential of P. coccinea M. J. Roemer. The micro-morphological structure and active site composition of the green biosorbent were explored by SEM and FTIR studies to characterize the possible interaction of the biosorbent material with the metal ions. The biosorption efficiency of the biosorbent for the removal of the metal from aqueous medium was investigated under different operating conditions. Various biosorption models were applied to the experimental data to understand the nature of treatment process. These studies were of great importance for the practical usage of the biosorbent material for the metal detoxification.

2. Materials and methods

2.1. Preparation of green biosorbent

P. coccinea M. J. Roemer fruit biomass was collected from a local park in Sinop, Turkey. The plant biomass was thoroughly cleaned from dust and dirt by washing with tap water and distilled water. The material was oven-dried at a temperature of 80°C for about 24 h. It was crushed into powder with the help of a grinder and sieved with a 0.5 mm mesh sieve. The powdered plant material was then mixed with dilute sodium hydroxide solution (0.3 mol L⁻¹) using a magnetic shaker at room temperature for about 24 h. After the pretreatment, the biomass was thoroughly washed with distilled water to remove the remaining chemical and achieve neutral pH. Finally, the treated biomass was dried again and stored in an airtight bottle for the metal biosorption experiment.

2.2. Preparation of metal solution

Manganese (Manganese (II) chloride dihydrate, purity: ≥99.0%, CAS No: 20603-88-7, Merck) used as model metal in this study was provided by a local chemical supplier in Samsun, Turkey. A stock solution of manganese (1000 mg L⁻¹) was made by dissolving the required amount of the metal in distilled water. The stock solution was then diluted to the required metal concentrations (10–30 mg L⁻¹) using distilled water to get the desired metal-laden solution grades. Dilute hydrochloric acid (0.1 mol L⁻¹) and sodium hydroxide (0.1 mol L⁻¹) solutions were used to adjust the pH levels of the prepared metal-loaded solution samples. The chemicals of analytical purity were used in the metal biosorption study.

2.3. Biosorption operation

The metal biosorption study was performed using batch experiment technique at room temperature on an orbital shaker. A certain amount of the biosorbent material and a certain concentration of the metal solution were added to a conical flask with a working volume of 100 mL and mixed at 150 rpm for a predetermined time. After the experiment period was completed, approximately 1.5 mL of solution sample was taken from the mixture and then the biosorbent material was separated from the solution phase. The metal concentration in the sample was quantified using a manganese test set (Merck Spectroquant 114770) by measuring the absorbance at 445 nm with the aid of a UV-Visible spectrophotometer device (Thermo Genesys 10 S). The following equations were used to determine the efficiency of the biosorbent material to remove the metal from the solution phase at a specified time (t) and equilibrium (e), respectively. (1) $\begin{array}{rl}& q_{\text{t}}=\frac{(C_{\text{0}}-C_{\text{t}})V}{m}.\end{array}$(1) (2) $\begin{array}{rl}& q_{\text{e}}=\frac{(C_{\text{0}}-C_{\text{e}})V}{m}.\end{array}$(2) where q_t (mg g⁻¹), q_e (mg g⁻¹), C₀ (mg L⁻¹), C_t (mg L⁻¹), C_e (mg L⁻¹), V (L) and m (g) are the efficiency of the biosorbent at a specified time, the efficiency of the biosorbent at equilibrium, the metal concentration at start time, the metal concentration at a specified time, the metal concentration at equilibrium, the solution volume and the biosorbent mass, respectively.

2.4. Characterization

The micro-morphological structure and active site composition of the biosorbent material were investigated by SEM and FTIR studies to characterize the possible interaction of the biosorbent material with the metal ions using SEM (Zeiss Evo Ls 10) and FTIR (PerkinElmer Spectrum 400) instruments.

2.5. Study of operating conditions

The biosorption efficiency of the biosorbent material for the removal of the metal from aqueous medium was investigated using the single-factor experiment approach under different operating conditions, including the metal concentration (C₀: 10–30 mg L⁻¹, t: 120 mins, pH: 6, m: 10 mg), pH (pH: 2–6, t: 120 mins, C₀: 15 mg L⁻¹, m: 10 mg), amount of biosorbent (m: 10–30 mg, t: 120 mins, C₀: 25 mg L⁻¹, pH: 6) and operation time (t: 0–120 mins, C₀: 30 mg L⁻¹, pH: 6, m: 10 mg).

2.6. Modelling of metal biosorption process

Various biosorption kinetics, thermodynamics and isotherm models were applied to the experimental data to understand the nature of the metal treatment process. The kinetics modelling study was done using the pseudo-first-order, pseudo-second-order and intra-particle diffusion models [9,27–29]. The standard Gibbs free energy change thermodynamics modelling parameter was used to determine the feasibility and spontaneity of the metal biosorption operation [8]. The isotherm modelling study was made using Freundlich, Langmuir and Dubinin-Radushkevich models [30–33].

2.7. Data evaluation procedure

The mathematical evaluation of the metal biosorption operation was carried out using the experimental data averages with the help of SigmaPlot 12.0 software. The compatibility of the experimental data with the mathematical equations was determined by the nonlinear regression approach. R², adjusted R² (adjR²) and RMSE parameters were used to evaluate the fit quality of the mathematical equations.

3. Results and discussion

3.1. Characterization study

The micro-morphological structure and active site composition of the biosorbent were studied by SEM and FTIR instruments to characterize the possible interaction of the biosorbent with the metal ions. Figure 1 exhibits the micrograph of SEM for the biosorbent (a) and the metal-loaded biosorbent (b). SEM surface investigation indicated that the biosorbent had an irregular and rough surface composition. These surface properties are very valuable for the biosorption of the metal ions to the biosorbent surface [3,4,34]. The change in the surface morphology of the biosorbent after the metal biosorption resulted from the binding of the metal ions to the biosorbent surface. On the other hand, Figure 2 shows the spectrum of FTIR for the biosorbent (a) and the metal-loaded biosorbent (b). The main FTIR spectrum bands of the biosorbent material were at the positions of 3331.88, 2921.24, 2851.21, 2380.09, 2348.25, 2313.24, 1727.52, 1600.19, 1415.56, 1320.06, 1250.03, 1024.02, 890.32, 645.21 and 594.28 cm⁻¹. These FTIR spectral bands indicated the presence of functional groups such as O-H, C–C, N-H, C–H, C = O, C–N, C = C, C–O and C–O–C, which were in the structure of bio-macromolecules in the biosorbent [3,6,11,35]. FTIR analysis showed that the biosorbent material had a wide variety of functional groups. Various changes such as the shape differences, position shifts, intensity differences, appearance and disappearance of FTIR spectral bands of the biosorbent after the biosorption of the metal ions showed that this plentiful functional group framework played a major role in the metal biosorption process.

Figure 1. SEM micrograph for biosorbent (a) and metal-loaded biosorbent (b).

Figure 2. FTIR spectrum for biosorbent (a) and metal-loaded biosorbent (b).

3.2. Operating conditions analysis

The biosorption efficiency of the biosorbent for the metal removal from aqueous medium was investigated under main operating conditions, including the concentration of the metal, pH, the biosorbent amount and operation time.

The effect of the metal concentration on the biosorption operation is indicated in Figure 3(a). The biosorption capacity of the biosorbent increased from 37.864 mg g⁻¹ to 52.427 mg g⁻¹ as the concentration of the metal increased from 10 mg L⁻¹ to 30 mg L⁻¹. The high concentration of the metal in the solution reduced the mass transfer resistance and increased the chance of effective collision between the biosorbent particles and the metal ions, resulting in increased biosorption performance of the biosorbent. However, when the biosorption capacity of the biosorbent was calculated as a percentage, it was noticed that its biosorption yield decreased with the increase of the metal concentration (data not presented). At the low metal concentration, the ratio of the active sites on the biosorbent material to the total metal ions was high, which increased the biosorption efficiency by increasing the probability of interaction between the biosorbent particles and the metal ions [13,23].

Figure 3. Effect of metal concentration (a), pH (b), biosorbent amount (c), operation time (d).

The effect of pH on metal biosorption process is shown in Figure 3(b). The biosorption capacity of the biosorbent increased from 10.680 mg g⁻¹ to 38.835 mg g⁻¹ with the increase of pH level from 2 to 6. At the low pH level, the surface of the biosorbent became positively charged by the protonation of the active sites on the biosorbent, which reduced the biosorption efficiency of the biosorbent as it created an electrostatic repulsion effect against the positively charged metal ions. At the high pH level, the positively charged active sites on the biosorbent were deprotonated and became negatively charged. These negatively charged active sites enhanced the biosorption capacity of the biosorbent by retaining the positively charged metal ions well due to the force of electrostatic attraction [3,5,33].

The effect of the biosorbent amount on the metal biosorption capacity of the biosorbent material is indicated in Figure 3(c). The biosorption performance of the biosorbent decreased from 55.340 mg g⁻¹ to 41.748 mg g⁻¹ as the amount of the biosorbent increased from 10 mg to 30 mg. At the high biosorbent amount, the overlapping of the biosorbent particles and the fact that a large number of the active binding sites remained empty caused a decrease in the metal biosorption capacity of the biosorbent. However, when the metal biosorption performance of the biosorbent was examined as a percentage, it was observed that the biosorption capacity of the biosorbent increased as the biosorbent amount increased (data not shown). This increase in the biosorption efficiency of the biosorbent was due to the availability of larger surface area and higher numbers of the active binding sites with rising the biosorbent amount [6,36].

The effect of operation time on the metal biosorption process is shown in Figure 3(d). At first, the biosorption process was rapid and most of the metal biosorption occurred in this stage. The biosorbent material had a large number of available active binding sites and an empty surface at this stage, resulting in rapid and intense metal biosorption. Later on, the biosorption performance of the biosorbent increased to a certain extent, but its biosorption rate gradually decreased. At this stage, most of the binding sites of the biosorbent were occupied by the metal ions as the biosorption process progressed, resulting in a reduction in the speed of the biosorption. Eventually, the biosorption activity hardly increased and the biosorption process reached the equilibrium state as the available binding sites of the biosorbent were almost completely filled by the metal ions [3,33]. Hereby, the biosorbent material achieved the maximum biosorption performance at a metal concentration of 30 mg L⁻¹, a pH of 6 and a biosorbent amount of 10 mg in a 120-minute operation period.

3.3. Metal biosorption modelling study

Various biosorption kinetics, thermodynamics and isotherm models were applied to the experimental data to understand the nature of the metal biosorption process. The kinetics modelling study was performed using the following models. (3) $\begin{array}{rl}& \text{Pseudo - first - order:}{q}_{\text{t}}=q_{\text{e}}(1-{\text{e}}^{-k_{1}t}).\end{array}$(3) (4) $\begin{array}{rl}& \text{Pseudo - second - order:}{q}_{\text{t}}=\frac{k_{\text{2}}{q_{\text{e}}}^{\text{2}}t}{1+k_{\text{2}}{q}_{\text{e}}t}.\end{array}$(4) (5) $\begin{array}{rl}& \text{Intra - particle diffusion:}{q}_{\text{t}}=C+k_{\text{p}}\sqrt{t}.\end{array}$(5) where k₁ (min⁻¹), k₂ (g mg⁻¹ min⁻¹), C (mg g⁻¹) and k_p (mg g⁻¹ min^−1/2) are the pseudo-first-order rate constant, the pseudo-second-order rate constant, a parameter about the boundary layer thickness and the intra-particle diffusion rate constant, respectively. The results of kinetics modelling study for the metal biosorption are listed in Table 1. The biosorption kinetics for the metal removal from aqueous medium followed the pseudo-second-order model. This showed that the electrostatic mechanism, which included the electron exchanging or sharing between the active sites on the biosorbent and the metal ions, dominated the metal biosorption process [6,37–39]. On the other hand, the effect of the intra-particle diffusion on the metal biosorption is shown in Figure 4. The mass transfer (movement) of the metal ions from aquatic environment onto the biosorbent consisted of multiple steps. The first stage was the external (film) diffusion, in which the metal ions were transported from the solution bulk phase to the outer surface of the biosorbent. The next stage was intra-particle diffusion, in which the metal ions were transported from the external surface of the biosorbent into its pores. The final stage referred to the biosorption (surface reaction), in which the metal ions were retained by the biosorbent [13,40]. Furthermore, the curve of the metal biosorption capacity (q_t) against √t was non-linear and did not pass through the point of origin [16]. These results revealed that there were multiple stages (mechanisms) controlling the metal ions biosorption operation.

Figure 4. Effect of intra-particle diffusion on metal biosorption.

Table 1. Biosorption kinetics modelling results.

Model	Parameter
Pseudo-first-order
	qe	k1	R^2	AdjR^2	RMSE
	mg g^−1	min^−1	-	-	-
	49.318	0.064	0.947	0.939	3.968
Pseudo-second-order
	qe	k2	R^2	AdjR^2	RMSE
	mg g^−1	g mg^−1 min^−1	-	-	-
	57.163	0.00141	0.980	0.977	2.451
Intra-particle diffusion
	C	kp	R^2	AdjR^2	RMSE
	mg g^−1	mg g^−1 min^−1/2	–	–	–
	8.222	4.793	0.916	0.904	4.995

The standard Gibbs free energy change thermodynamics modelling parameter was used to determine the feasibility and spontaneity of the metal biosorption process. The following equations were used to calculate this thermodynamics parameter. (6) $\begin{array}{rl}& \text{Gibbs free energy:}\mathrm{\Delta }{G}^{\circ }=-R\text{Tln}{K}_{\text{D}}.\end{array}$(6) (7) $\begin{array}{rl}& \text{Distribution coefficient:}{K}_{\text{D}}=\frac{C_{\text{eb}}}{C_{\text{e}}}.\end{array}$(7) where ΔG° (kJ mol⁻¹), R (J mol⁻¹ K⁻¹), T (K), K_D and C_eb (mg L⁻¹) are the standard Gibbs free energy change parameter, the gas constant, the temperature, the distribution coefficient and the metal concentration on the biosorbent at equilibrium, respectively. The standard Gibbs free energy change parameter for the metal biosorption operation was obtained in the range of −4.375 and −1.840 kJ mol⁻¹. The negative standard Gibbs free energy change shows that the biosorption process is of a feasible and spontaneous nature. Again, the negative standard Gibbs free energy change parameter between −400 and −80 kJ mol⁻¹ refers a chemisorption process, and between −20 and 0 kJ mol⁻¹ refers a physisorption process [4,33]. Thus, the standard Gibbs free energy change values obtained for the current study indicated that the biosorption process had a physical, spontaneous and favourable nature.

The isotherm modelling study was carried out using the following equations. (8) $\begin{array}{rl}& \text{Freundlich:}{q}_{\text{e}}=K_{\text{F}}{C_{\text{e}}}^{\frac{1}{n_{\text{F}}}}.\end{array}$(8) (9) $\begin{array}{rl}& \text{Langmuir:}{q}_{\text{e}}=\frac{q_{\text{m}}{K}_{\text{L}}{C}_{\text{e}}}{\text{1 + }{K}_{\text{L}}{C}_{\text{e }}}.\end{array}$(9) (10) $\begin{array}{rl}& \text{Equilibrium factor:}{R}_{\text{L}}=\frac{1}{1+K_{\text{L}}{C}_0}.\end{array}$(10) (11) $\begin{array}{rl}& \text{Dubinin - Radushkevich:}{q}_{\text{e}}=q_{\text{m}}{\text{e}}^{-B{\epsilon }^{\text{2}}}.\end{array}$(11) (12) $\begin{array}{rl}& \text{Polanyi potential:}\mathcal{E}=R\text{Tln}\left(1+\frac{1}{C_{\text{e}}}\right).\end{array}$(12) (13) $\begin{array}{rl}& \text{Mean free energy:}E=\frac{1}{\sqrt{2B}}.\end{array}$(13) where K_F (mg g⁻¹ (L mg⁻¹)^1/n_F), n_F, q_m (mg g⁻¹), K_L (L mg⁻¹), R_L, B (mol² kJ⁻²), ε and E (kJ mol⁻¹) are a parameter about the metal biosorption capacity of the biosorbent material, a parameter about the biosorption intensity, the maximum metal biosorption efficiency, a parameter about the biosorption energy, the equilibrium (separation) factor, a parameter about the energy of biosorption, the Polanyi potential and the mean free energy, respectively. The results of isotherm modelling study for the metal biosorption operation are shown in Table 2. The experimental metal biosorption data agreed well with Freundlich isotherm model. This showed that a multi-layer biosorption mechanism operated between the metal ions and the active binding sites on the heterogeneous surface of the biosorbent [1,41]. On the other hand, n_F, R_L and E parameters were estimated as 4.163, 0.113–0.277 and 0.440 kJ mol⁻¹, respectively. n_F parameter between 0 and 10 refers a favourable biosorption process. Again, R_L parameter between 0 and 1 also shows a favourable biosorption operation. E parameter between 0 and 8 kJ mol⁻¹ indicates a physisorption process, and between 8 and 16 kJ mol⁻¹ indicates a chemisorption process [10,13,16,35,40]. Thence, n_F, R_L and E parameters values obtained for the present study showed that the metal biosorption operation had a favourable and physical nature.

Table 2. Biosorption isotherm modelling results.

Model	Parameter
Freundlich
	KF	nF	R^2	AdjR^2	RMSE
	mg g^−1 (L mg^−1)^1/nF	–	–	–	–
	24.294	4.163	0.999	0.998	0.342
Langmuir
	qm	RL	R^2	AdjR^2	RMSE
	mg g^−1	–	–	–	–
	59.867	0.113-0.277	0.989	0.978	1.090
Dubinin-Radushkevich
	qm	E	R^2	AdjR^2	RMSE
	mg g^−1	kJ mol^−1	–	–	–
	52.040	0.440	0.936	0.872	2.620

3.4. Comparison study for metal biosorption capacity

The maximum metal biosorption capacity of P. coccinea M. J. Roemer was determined to be 59.867 mg g⁻¹. A literature review comparing the capacity of various biosorbent materials for the metal biosorption from aqueous environment is shown in Table 3. As could be seen from the table, the biosorbent was quite successful in removing the metal from aqueous medium. This indicated that P. coccinea M. J. Roemer could be a cost-effective and effective material for an environmentally friendly solution to the metal issue in aquatic environment.

Table 3. Biosorption capacity comparison table.

Biosorbent	Biosorption capacity (mg g^−1)	References
Pyracantha coccinea M. J. Roemer	59.867	Current study
Rhodococcus opacus	6.91	[26]
Arthrospira (Spirulina) platensis	44.3	[42]
Parthenium hysteroporous bud and leaf powder	14.863	[43]
Sargassum carpophyllum residue	21.19	[44]
Carboxylated Sargassum carpophyllum residue	31.65	[44]
Caulerpa lentillifera residue	17.73	[44]
Carboxylated Caulerpa lentillifera residue	52.63	[44]
Papiliotrema huenov biomass	35.02	[45]
Aspergillus versicolor	22.9	[25]
Eucheuma spinosum	4.13	[46]
Sewage sludge loaded calcium alginate	31.04	[47]
Herpetocypris brevicaudata carapace loaded AXAD-4 resin	35.3	[48]
Alfalfa	13.62	[49]
Chopped grass pellets	15.22	[49]
Chopped grass	33.47	[49]
Bacillus cereus loaded magnetic ɣ-Fe2O3 nanoparticle	30.3	[50]

4. Conclusions

A novel green solution for metal pollution in aquatic environment was presented using P. coccinea M. J. Roemer in this study. Manganese was used as a model metal to determine its biosorption potential. Characterization study showed that the material had an irregular and rough surface and a wide variety of functional groups, which played an important role in metal biosorption. The biosorbent achieved the maximum metal treatment capacity at a metal concentration of 30 mg L⁻¹, a pH of 6 and a biosorbent amount of 10 mg in a 120-minute treatment period. Freundlich and the pseudo-second-order models agreed well with the biosorption data. The thermodynamics analysis indicated that the biosorption process had a physical, spontaneous and favourable nature. The maximum metal biosorption capacity of the biosorbent was determined to be 59.867 mg g⁻¹. The current study showed that P. coccinea M. J. Roemer could be a promising material for green solution to the metal pollution in aquatic medium.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability

All data generated or analysed during the study are included in the article.