Immobilization of Heavy Metals Using Biochar and Manganese Dioxide for Preventing Pollution ^†

Abstract

Using biochar/δ-MnO₂ as an adsorbent, heavy metals in soil were immobilized to prevent further pollution. When biochar/δ-MnO₂ was thoroughly mixed with contaminated soil in a ratio of 2:8, the residual fractions of As, Cu, Pb, and Zn increased by 9.78, 39.0, 61.6, and 15.7%. The addition of biochar/δ-MnO₂ significantly immobilized Cu and Pb. Since biochar/δ-MnO₂ fixed As, Cu, Pb, and Zn in the soil, soil contamination was prevented effectively.

1. Introduction

Taiwan’s rapid economic development has indirectly increased soil pollution in farmland with heavy metals such as arsenic (As), copper (Cu), zinc (Zn), and cadmium (Cd). Unlike organic pollutants, heavy metals cannot be easily removed through self-purification from the soil. Instead, they accumulate over time, polluting the soil and infiltrating groundwater. The treatment methods for heavy-metal-contaminated soil include solidification/stabilization, vitrification, phytoremediation, and separation/concentration. The waste generated by these treatment methods affects soil quality. Therefore, adsorbents are used to adsorb heavy metals in the soil as an environmentally friendly approach.

Biochar is a solid material rich in carbon produced by the thermochemical conversion of biomass in a low-oxygen environment [1]. Biochar serves as an adsorbent as it substitutes fuel, catalyst, and soil amendment, which makes biochar available for soil quality improvement. In this study, agricultural waste peanut vines were used as raw material for biochar production. Traditionally, peanut vines are disposed of through burning, causing air pollution. By transforming them into biochar, resource recycling and zero waste can be achieved. δ-type manganese dioxide (MnO₂) is known for its natural oxidizing property. It possesses a unique adsorption-friendly two-dimensional layered structure, large surface area, high porosity, high adsorption activity, small particle size, surface charge, and oxidation capability. Its low production cost and minimal environmental impact allow δ-type MnO₂ to be a useful chemical in the biogeochemical cycles of inorganic and organic compounds. The oxidation mechanism of MnO₂ involves the formation of free radicals through electron transfer. Therefore, manganese dioxide is used for the remediation of polluted groundwater. However, limited research has been conducted for its application in soil pollution control.

2. Materials and Methods

2.1. Preparation of δ-MnO₂/Biochar Composite Material

The raw material for biochar in this study was peanut vines, a common agricultural waste in Yunlin County, a major agricultural county in Taiwan. The peanut vines were crushed into powder, soaked in 0.5 M calcium chloride for 24 h, and then dried in an oven at 105 °C. Subsequently, the dried peanut vine charcoal (biochar) was placed in a high-temperature furnace at 600 °C for 1 h. After cooling, the activated biochar was ground to 100 mesh and treated with 0.1 M hydrochloric acid and acetone to remove surface tars. A solution of tetrahydrate manganese acetate was added to the biochar, and the mixture was stirred with a magnetic stirrer for 10 min and then ultrasonicated for 30 min. The mixture was then placed on a heating plate, and potassium permanganate solution was slowly added while stirring at 80 °C for 1 h. After precipitating solids, the upper liquid was removed with a pipette, and the remaining sample was washed with deionized water. After drying in an oven, the precipitates were ground into powder using an agate mortar to obtain δ-MnO₂-coated biochar (biochar/δ-MnO₂). The specific surface area and pore size analysis (BET), surface imaging analysis (SEM), surface element analysis (EDS), and surface functional group analysis (FTIR) were performed to investigate the properties of biochar/δ-MnO₂.

2.2. Sequential Extraction

Sequential extraction was conducted to obtain different forms of heavy metals in extractants at different pH values. The extraction was performed using the method proposed by Tessier [2]. In the method, heavy metal forms are classified into exchangeable, carbonate, iron-manganese oxide, organic matter-bound, and residual forms. Heavy metals in exchangeable and carbonate forms are more easily released into the environment and absorbed by organisms than in other forms, while organic matter-bound forms are more likely to be released in anaerobic environments.

2.3. Bioaccessibility

Bioaccessibility refers to the ratio of heavy metal concentration ingested into the body of organisms. Therefore, bioaccessibility is used to confirm the release of heavy metals into the human body when contaminated soil is inadvertently ingested. Bioaccessibility is estimated by simulating the dissolution of heavy metals in acidic conditions similar to the stomach and comparing the total amount of heavy metals with the sequentially extracted amount. It is calculated using (1).

$$\mathrm{B}\mathrm{i}\mathrm{o}\mathrm{a}\mathrm{c}\mathrm{c}\mathrm{e}\mathrm{s}\mathrm{s}\mathrm{i}\mathrm{b}\mathrm{i}\mathrm{l}\mathrm{i}\mathrm{t}\mathrm{y}\left(\%,\mathrm{R}\mathrm{B}\mathrm{A}\right)={\displaystyle \frac{\mathrm{C}\mathrm{o}\mathrm{n}\mathrm{c}\mathrm{e}\mathrm{n}\mathrm{t}\mathrm{r}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}\mathrm{o}\mathrm{f}\mathrm{h}\mathrm{e}\mathrm{a}\mathrm{v}\mathrm{y}\mathrm{m}\mathrm{e}\mathrm{t}\mathrm{a}\mathrm{l}\mathrm{s}\mathrm{e}\mathrm{x}\mathrm{t}\mathrm{r}\mathrm{a}\mathrm{c}\mathrm{t}\mathrm{e}\mathrm{d}\mathrm{b}\mathrm{y}\mathrm{s}\mathrm{i}\mathrm{m}\mathrm{u}\mathrm{l}\mathrm{a}\mathrm{t}\mathrm{e}\mathrm{d}\mathrm{g}\mathrm{a}\mathrm{s}\mathrm{t}\mathrm{r}\mathrm{i}\mathrm{c}\mathrm{a}\mathrm{c}\mathrm{i}\mathrm{d}}{\mathrm{T}\mathrm{o}\mathrm{t}\mathrm{a}\mathrm{l}\mathrm{c}\mathrm{o}\mathrm{n}\mathrm{c}\mathrm{e}\mathrm{n}\mathrm{t}\mathrm{r}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}\mathrm{o}\mathrm{f}\mathrm{h}\mathrm{e}\mathrm{a}\mathrm{v}\mathrm{y}\mathrm{m}\mathrm{e}\mathrm{t}\mathrm{a}\mathrm{l}\mathrm{s}}}\times 100\%$$

(1)

2.4. Evaluation of Soil Pollution

2.4.1. Enrichment Factor

The enrichment factor (EF) is a measure used in the assessment of soil pollution. In the natural weathering process. EF values are typically around 1.5. If the EF value exceeds 1.5, the primary source of heavy metals is regarded as anthropogenic. The value is a criterion for assessing the degree of influence [3]. The degree of pollution is classified based on the enrichment level of heavy metals. In the classification, no pollution (EF ≤ 2), slight pollution (2 ≤ EF < 5), moderate pollution (5 ≤ EF < 20), severe pollution (20 ≤ EF < 40), and extremely severe pollution (EF > 40) are defined [4]. The calculation formula of EF is as follows.

$$EF={\displaystyle \frac{\left(\raisebox{1ex}{$C_n$}\!\left/ \!\raisebox{-1ex}{$C_{ref}$}\right.\right)}{\left(\raisebox{1ex}{$B_n$}\!\left/ \!\raisebox{-1ex}{$B_{ref}$}\right.\right)}}$$

(2)

C_n: Concentration of heavy metals in the sample.

C_ref: Reference concentration of heavy metals in the sample.

B_n: Background concentration of heavy metals.

B_ref: Reference background concentration of heavy metals.

2.4.2. Geo-Accumulation Index

The geo-accumulation index (I_geo) is used to assess the impact of heavy metals on soil quality. Due to potential variations in background values related to lithospheric effects, a background correction factor (k = 1.5) is incorporated into the calculation. I_geo is used to categorize pollution levels as no pollution (I_geo < 1), slight pollution (1 < I_geo < 2), moderate pollution (2 < I_geo < 3), moderately severe pollution (3 < I_geo < 4), severe pollution (4 < I_geo < 5), and extremely severe pollution (I_geo > 5) (3) [5].

$$I_{geo}={\log }_2\left({\displaystyle \raisebox{1ex}{$C_n$}\!\left/ \!\raisebox{-1ex}{$k\times B_n$}\right.}\right)$$

(3)

K: Correction factor.

C_n: Concentration of heavy metals in the sample.

B_n: Background concentration of heavy metals.

2.4.3. Contamination Factor

The contamination factor (CF) serves as an assessment criterion for the degree of soil pollution caused by a single metal. The calculation formula for the contamination factor is as follows.

$$CF={\displaystyle \frac{C_n}{B_n}}$$

(4)

C_n: heavy metal concentration in sample.

B_n: background heavy metal concentration.

2.4.4. Pollution Load Index

The pollution load index (PLI) serves as an assessment criterion for the overall degree of soil pollution caused by multiple metals. The calculation formula for the pollution load index is as follows.

$$PLI=\sqrt[n]{{CF}_1\times {CF}_2\times \cdots \times {CF}_n}$$

(5)

CF: Contamination Factor.

2.4.5. Single Metal Pollution Factor and Global Metal Pollution Factor

The individual contamination factor (ICF) and the global contamination factor (GCF) are used to represent the potential ecological risk of a single metal in the soil. A higher value indicates a higher ecological pollution risk, and vice versa. GCF represents the overall metal pollution situation. The calculation formulas are as follows.

$$ICF={\sum }_{i=A}^D{\displaystyle \frac{C_{Fi}}{C_{FE}}}GCF={\sum }_{m=1}^n{ICF}_m$$

(6)

C_Fi: sum of non-residual concentrations (mg/kg).

C_FE: residual concentration (mg/kg).

3. Results and Discussion

3.1. Characterization Analysis

3.1.1. Specific Surface Area and Pore Size

The specific surface area and total pore volume of biochar were 94.9 m²/g and 0.09 c.c/g, respectively. For δ-MnO₂, the specific surface area and total pore volume were 245 m²/g and 0.79 c.c/g, respectively. The biochar/δ-MnO₂ composite had a specific surface area and total pore volume of 216 m²/g and 0.45 c.c/g, respectively. Micropores exist on the biochar’s surface, accounting for 79.9% of the total surface area. In δ-MnO₂, the proportions of mesopores and micropores were similar. Mesopores accounted for 57.3% of the total surface area. Biochar/δ-MnO₂ had numerous mesopores, constituting 81.8% of the total surface area. The addition of KMnO₄ in the coating process disrupted the micropore structure, transforming it into mesopores or macropores. After coating, the specific surface area of biochar increased by 2.27 times, with the mesopores being the main contributor as the area of the mesopores increased by 9.26 times. This result was consistent with previous studies [6]. The increase in mesopore volume contributes to the enhancement of the specific surface area, thereby improving the adsorption capacity for pollutants [7]. An increase in specific surface area and pore volume is beneficial for the adsorption capacity of pollutants [8], while excessively small pore sizes result in poor adsorption efficiency [9].

3.1.2. Surface Element Analysis

Figure 1 shows the surface image of biochar/δ-MnO₂, revealing distinct spherical particles adhering to biochar. This result is similar to the findings in Ref. [10]. The pores of the biochar/δ-MnO₂ surface are increased, consistent with the pore size analysis results (

Table 1. Specific surface area and pore size analysis.

Parameters	SBET	SMeso	SMicro	SMeso/SBET	VTotal	VMeso	VMicro	VMeso/VTotal
	—— m2/g ——			— % —	—— cc/g ——			— % —
Biochar	94.9	19.0	75.9	20.1	0.09	0.06	0.03	64.8
δ-MnO2	245	141	105	57.3	0.79	0.75	0.04	95.5
Biochar/δ-MnO2	216	176	40.6	81.2	0.45	0.40	0.05	89.0

Note: (S_BET: specific surface area, S_Meso: mesopore surface area, S_Micro: micropore surface area, V_Total: total pore volume, V_Meso: mesopore volume, V_Micro: micropore volume, S_Meso/S_BET: mesopore area percentage, V_Meso/V_Total: mesopore volume percentage).

). The oxidative action of KMnO₄ disrupts the micropore structure in the coating process, transforming it into mesopores. Thus, the specific surface area of biochar increased by 2.27 times after coating [6]. In the coating process, KMnO₄ reacts with Mn(CH₃COO)₂·4H₂O to deposit δ-MnO₂ on the surface of biochar, forming a layered and flocculent structure, which provides a larger specific surface area and highly reactive void structure [11]. Before coating, the elements of the biochar surface included C, O, Cl, and Ca with C and O being the major elements. After thermal decomposition, peanut vines became carbon-rich solid materials, similar to the characteristics of biochar [12]. The presence of Cl and Ca is attributed to the use of CaCl₂ as an activator in the thermal decomposition process of peanut vines. Surface elements of biochar/δ-MnO₂ included C, O, Ca, Mn, and K, with C, O, and Ca having the same origins. Mn and K in biochar/δ-MnO₂ originated from the precipitation reaction in coating using KMnO₄ and Mn(CH₃COO)₂·4H₂O [11].

3.1.3. Functional Group Analysis (Figure 2)

The absorption by biochar/δ-MnO₂ was observed at 1635 cm⁻¹ due to the internal pores in the δ-MnO₂ structure and the bending vibration of -OH and H₂O [13]. This indicates that the Mn identified in the surface element analysis originated from δ-MnO₂. In the range of 1725–1680 cm⁻¹, absorption is related to carboxyl groups (C=O) that stretch vibrations at the wavelengths. Absorption at 1699, 1716, and 1733 cm⁻¹ indicates the presence of C=O in biochar/δ-MnO₂ [14]. Conjugated C=O structures dissociate H⁺, which increases the alkalinity of the soil by combining with metal oxides, hydroxides, and carbonate dissolved substances in the soil. With H⁺ dissociation, C=O transforms from -COOH to -COO and binds heavy metal ions, which causes heavy metal adsorption. In the range of 3800–2200 cm⁻¹, stretched vibrations of water molecules and hydroxyl groups are observed [15]. Absorption occurs at 3565, 3627, and 3647 cm⁻¹, indicating the presence of -OH. These -OH groups are protonated during the adsorption process and bind heavy metal ions to immobilize them.

Figure 2. Surface functional group analysis of biochar/δ-MnO₂.

Figure 2. Surface functional group analysis of biochar/δ-MnO₂.

3.1.4. Bioavailability

Table 2. Bioavailability of metals with the addition of different concentrations of biochar/δ-MnO₂.

Biochar/δ-MnO2 (%)	As	Cu	Pb	Zn
0	8.34	7.79	3.18	5.19
1	7.31	6.15	2.00	4.34
5	6.41	5.69	2.00	3.86
10	5.98	5.48	1.98	3.76
20	7.13	6.61	2.35	4.47

presents the bioavailability of different concentrations of biochar/δ-MnO₂ for heavy metals in soil. The bioavailability of As, Cu, Pb, and Zn in polluted soil decreased with the addition of biochar/δ-MnO₂ [8], indicating that the addition of biochar/δ-MnO₂ to polluted soil reduced the bioavailability of heavy metals. The reduction was more pronounced for As and Pb, suggesting that biochar/δ-MnO₂ is more effective in inhibiting the absorption of As and Pb by the human body.

3.2. Heavy Metal Forms in Soil

Sequential extraction results of As, Cu, Pb, and Zn revealed that the addition of biochar/δ-MnO₂ had a pronounced effect on the fixation of Cu and Pb (Figure 3). Upon the addition of biochar/δ-MnO₂ to the soil, soil organic matter (SOM) and MnO₂ increased. SOM exhibited a higher selectivity for divalent metal ions, with varying bond strengths for different metals. The bond strength follows the order Cu > Pb > Zn. With prolonged mixing time, Cu and Pb transformed into more stable compounds, resulting in stable forms. Therefore, the residual form increased, achieving an enhancement in fixation.

Zn showed less change in the concentration in the organic matter-bound form, while the iron-manganese oxide form showed significant change. The strong adsorption capability of iron-manganese oxides/hydroxides for Zn caused biochar/δ-MnO₂ to initially adsorb exchangeable Zn ions on the surface, which later transformed into internal spherical complexes. This makes it less susceptible to release, thus enhancing its fixation ability.

Heavy metals in the residual form predominantly existed in polluted soil, exhibiting higher stability. The adsorption capacity of As(V) on δ-MnO₂ surfaces is weaker than Cu, Pb, and Zn. Consequently, the changes in forms were less significant for As than Cu, Pb, and Zn, resulting in a less pronounced fixation of biochar/δ-MnO₂ on As.

The sequential extraction results of heavy metals confirmed that the addition of biochar/δ-MnO₂ significantly enhanced the fixation of Cu and Pb, while the effect on Zn and As was less significant. Exchangeable and carbonate forms pose ecological risks and iron-manganese oxide forms are indicative of potential ecological risks. Therefore, the changes in the proportion in the residual form can be used for assessing heavy metal properties. When adding biochar/δ-MnO₂ to the soil in a ratio of 2:8, the best effect was observed with an increase in the residual form proportions by 9.78, 39.0, 61.6, and 15.7% for As, Cu, Pb, and Zn, respectively. This substantiates the significant effectiveness of biochar/δ-MnO₂ in enhancing the fixation of Cu and Pb.

3.3. Soil Pollution Assessment

3.3.1. EF

Table 3. Enrichment factor of heavy metals in soil.

Ratio of Biochar/δ-MnO2 in Soil (%)	As	Cu	Pb	Zn
0	8.34	7.79	3.18	5.19
1	7.31	6.15	2.00	4.34
5	6.41	5.69	2.00	3.86
10	5.98	5.48	1.98	3.76
20	7.13	6.61	2.35	4.47

Note: No pollution (EF < 2), slight pollution (2 ≤ EF < 5), moderate pollution (5 ≤ EF < 20), severe pollution (20 ≤ EF < 40), severe pollution (EF > 40).

presents the soil exhibiting moderate contamination for As, Cu, Zn, and mild contamination for Pb. After the addition of biochar/δ-MnO₂, the contamination levels decreased. The optimal proportion was 10% to transform Pb from mild to non-contamination and Cu and Zn from moderate to mild contamination. As maintained a moderate contamination level. Biochar/δ-MnO₂ alleviated contamination with a better effect observed for Pb, Cu, and Zn, indicating its potential effectiveness in remediating Pb, Cu, and Zn pollution.

3.3.2. I_geo

Table 4. Geo-accumulation index (I_geo).

Ratio of Biochar/δ-MnO2 in Soil (%)	As	Cu	Pb	Zn
0	2.62	2.52	1.23	1.94
1	2.68	2.43	0.81	1.93
5	2.49	2.32	0.81	1.76
10	2.36	2.24	0.77	1.69
20	2.28	2.17	0.68	1.61

Note: When I_geo < 1, it means no pollution. When 1 < I_geo < 2, it means slight pollution. When 2 < I_geo < 3, it means light pollution. When 3 < I_geo < 4, it means moderate pollution. When 4 < I_geo < 5, it means high pollution. When I_geo > 5, it means high pollution [16].

shows that As and Cu exhibited higher pollution levels. With biochar/δ-MnO₂, a significant decrease in I_geo was observed. The decrease was significant for Pb, transitioning from mild to non-contamination. As and Cu maintained a moderate contamination level, while Zn remained similar. The changes in As forms were less pronounced with biochar/δ-MnO₂, as As was associated with the iron-manganese oxide and organic matter-bound forms. δ-MnO₂ increased As in the iron-manganese oxide form over time. In acidic environments, As is usually present as As(V), and biochar/δ-MnO₂ exhibits weaker adsorption capacity for As(V). Consequently, As is less adsorbed. Pb and Cu showed more adsorption to organic matter, forming stable organic compounds. Zn exhibited more adsorption on iron-manganese oxides/hydroxides.

3.3.3. CF and PLI

CF reveals the potential risk of individual heavy metals in the soil. Before adding biochar/δ-MnO₂, the concentrations of As, Cu, and Zn were high, while that of Pb was moderate. After the addition of biochar/δ-MnO₂, CF decreased for all heavy metals. Although As maintained a high CF, the CF of Pb remained low, and the CFs of Cu and Zn were still high. The CF values of As, Cu, and Zn were reduced by 20%, while that of Pb was reduced by 30%. Biochar/δ-MnO₂ reduced the CFs of those heavy metals considerably. PLI is used to estimate the impact of heavy metals on pollution. When PLI > 1, it indicates pollution, with a higher value indicating severe pollution. After adding biochar/δ-MnO₂, PLI values decreased, indicating a reduction in pollution levels (

Table 5. Contamination factor (CF) and pollution load index (PLI).

Ratio of Biochar/δ-MnO2 in Soil (%)	As	Cu	Pb	Zn	PLI
0	9.23	8.62	3.52	5.75	6.34
1	9.62	8.08	2.62	5.71	5.84
5	8.43	7.49	2.62	5.08	5.38
10	7.70	7.07	2.56	4.84	5.09
20	7.30	6.77	2.40	4.58	4.83

Note: CF < 1 indicates low pollution; 1 ≤ CF < 3 indicates moderate pollution; 3 ≤ CF < 6 indicates severe pollution; CF ≤ 6 indicates severe pollution.

).

3.3.4. Mobility, ICF, and GCF

Table 6. Mobility of each metal.

Ratio of Biochar/δ-MnO2 in Soil (%)	As	Cu	Pb	Zn
0	6.01	33.3	21.7	65.3
1	2.44	22.4	5.29	55.3
5	2.75	16.3	0.75	44.6
10	1.86	13.0	0.61	39.5
20	1.52	7.61	0.63	31.3

presents the mobility of heavy metals in the soil: Zn > Pb > Cu > As. After adding biochar/δ-MnO₂, the order of the mobility was Zn > Cu > As > Pb. Mobility presents the degree of the potential for heavy metal pollution. The results aligned with EF, I_geo, CF, and PLI. ICF and GCF are standards for assessing potential ecological risks. In the polluted soil, Zn and Pb had higher ICF, indicating higher potential mobility and bioavailability. After adding biochar/δ-MnO₂, all ICF values decreased. The ICF of As, Cu, and Pb decreased to the level of no contamination, and that of Zn decreased to moderate contamination. In GCF, pollution levels decreased from heavy to low contamination.

Table 7. Mobility, individual contamination factor (ICF), and global contamination factor (GCF).

Ratio of Biochar/δ-MnO2 in Soil (%)	ICF				GCF
	As	Cu	Pb	Zn
0	0.56	4.79	4.10	5.83	11.3
1	0.46	3.28	2.61	3.71	10.1
5	0.57	2.87	2.50	2.93	8.87
10	0.58	1.84	1.90	2.59	6.90
20	0.35	0.59	0.30	1.82	3.07

Note: ICF < 1 low pollution, 1 ≤ ICF < 3 moderate pollution, 3 ≤ ICF < 6 severe pollution, 6 < ICF severe pollution, GCF < 6 low pollution, 6 < GCF < 12 moderate pollution, 12 < GCF < 24 severe pollution, 24 < GCF severe pollution.

presents the ICF and GCF and the potential ecological risk. Residual forms, composed of primary and secondary minerals, are less affected by external factors and pose no potential risk to the environment. Exchangeable and carbonate forms present ecological risks, while iron-manganese oxide and organic matter-bound forms present potential ecological risks. Therefore, exchangeable, carbonate, iron-manganese oxide, and organic matter-bound forms affect ICF and GCF.

4. Conclusions

After coating with δ-MnO₂, the biochar’s specific surface area increased by 2.27 times, and functional groups such as OH, C-O, C=O, and C=C contributed to the adsorption of heavy metal ions. Biochar/δ-MnO₂ increased pH and SOM. The pH increase was induced by the precipitation of metals and enhanced soil’s negative charge, thereby increasing its adsorption capacity for heavy metal elements. Meanwhile, SOM, with functional groups, binds heavy metal ions, altering their bonding forms to organic matter-bound forms. The optimal effect was observed for As, Cu, Pb, and Zn when adding biochar/δ-MnO₂ to the soil in a ratio of 2:8. The residual fraction for As, Cu, Pb, and Zn increased by 9.78, 39.0, 61.6, and 15.7%, respectively, confirming the significant effectiveness of biochar/δ-MnO₂ in enhancing the fixation of Cu and Pb. Biochar/δ-MnO₂ reduced the bioavailability of As, Cu, Pb, and Zn, with a pronounced decrease in As and Pb bioavailability from 68.5 to 21.4 and from 2.92 to 2.58%, respectively. Biochar/δ-MnO₂ is beneficial for mitigating soil pollution, with the most notable effect for Pb, Cu, and Zn.