Bone Meal as a Sustainable Amendment for Zinc Retention in Polluted Soils: Adsorption Mechanisms, Characterization, and Germination Response

Abstract

Soil contamination with heavy metals often resulting from industrial activities and wastewater discharge is a major ecological problem. Bone meal, a by-product of the agri-food industry, is a promising material for remediating soils affected by heavy metal pollution. Bone meal, rich in phosphorus, calcium, and other essential minerals, provides advantages both in immobilizing inorganic pollutants and in improving soil fertility. This study explores the potential of bone meal as an ecological and sustainable solution for the retention of zinc from soils polluted with wastewater. This study analyzes the physicochemical properties of bone meal, the mechanisms of its interaction with metal ions through adsorption processes as revealed by equilibrium and kinetic studies, and its effects on plant germination. The results indicate a maximum adsorption capacity of 2375.33 mg/kg at pH = 6, according to the Langmuir model, while the pseudo-second-order kinetic model showed a coefficient of R² > 0.99, confirming the chemical nature of the adsorption. At pH 12, the retention capacity increased to 2937.53 mg/kg; however, parameter instability suggests interference from precipitation phenomena. At pH 12, zinc retention is dominated by precipitation (Zn(OH)₂ and Zn–phosphates), which invalidates the Langmuir assumptions; accordingly, the Freundlich isotherm provides a more adequate description. Germination tests revealed species-specific responses to Zn contamination and bone meal amendment. In untreated contaminated soil, germination rates were 84% for cress, 42% for wheat, and 50% for mustard. Relative to the soil + bone meal treatment (100% performance), the extent of inhibition reached 19–21% in cress, 24–29% in wheat, and 12% in mustard. Bone meal mitigated Zn-induced inhibition most effectively in wheat (+31% vs. soil; +40% vs. control), followed by cress (+23–27%) and mustard (+14%), highlighting its species-dependent ameliorative potential. Thus, the experimental results confirm bone meal’s capacity to reduce the mobility of zinc ions and improve the quality of the agricultural substrate. By transforming an animal waste product into a material with agronomic value, this study supports the integration of bone meal into modern soil remediation strategies, aligned with the principles of bioeconomy and sustainable development.

1. Introduction

Soil contamination with heavy metals has become a major global environmental issue, with significant implications for ecosystem health and food security. The sources of these pollutants include industrial activities, intensive agriculture, road traffic, and the increasing use of wastewater for irrigation. Heavy metals such as zinc (Zn), copper (Cu), lead (Pb), and cadmium (Cd), once introduced into soils, persist for long periods and exhibit high toxicity, negatively affecting both plant development and the soil’s microbial structure.

In light of these challenges, research efforts have shifted toward identifying effective, eco-friendly, and economically viable remediation methods. Among the alternative materials investigated is bone meal—a by-product of the livestock industry, traditionally used as an organic fertilizer due to its high phosphorus and calcium content. In recent years, however, bone meal has also gained attention as an adsorbent for heavy metals, owing to its chemical composition rich in calcium phosphate (apatite, mainly hydroxyapatite), which can interact with metal ions and reduce their mobility in soil [1,2,3]. However, its performance in real soils, under different contamination scenarios, remains insufficiently explored, warranting further investigation in integrated chemical and biological contexts.

Recent systematic reviews and meta-analyses have synthesized the performance of various soil amendments for heavy metal immobilization. For instance, a 2025 meta-analysis demonstrated that combining biochar and zeolites significantly reduces the availability of cadmium (Cd), copper (Cu), lead (Pb), and zinc (Zn) in soils, through mechanisms such as cation exchange, surface complexation, and precipitation reactions [4]. A comprehensive systematic evaluation indicated that pristine biochars—especially those derived from agricultural residues—can immobilize metals like Pb, Cd, Cu, Ni, and Cr while simultaneously improving soil fertility and microbial diversity [5]. Another meta-analysis focusing on modified biochar for Cd remediation reported average decreases of 65% in soil Cd availability and 71% in plant Cd uptake, with certain modifications (e.g., organic or lignocellulosic feedstocks) achieving reductions of over 96% [6]. Comparatively, hydroxyapatite (HAP)—a primary mineral constituent of bone meal—has consistently been shown to outperform both biochar and organic manure in reducing Cd, Pb, and Zn uptake by plants, while also raising soil pH [7,8,9,10,11]. These findings suggest that, although phosphate-based biochars and aluminosilicate minerals such as zeolites offer rapid immobilization capabilities, bone meal—rich in hydroxyapatite—provides additional benefits such as long-term phosphate supply, liming effect, biodegradability, and alignment with circular economy principles. However, most meta-analytical studies have focused on biochar-based amendments, and less is known about the field performance and comparative efficacy of bone meal under diverse soil and contamination scenarios. This gap in knowledge directly underpins the rationale of the present study, which addresses both chemical and biological performance of bone meal under controlled contamination using cambic soil.

The use of bone meal as a remediation agent is further supported by its economic and environmental advantages. It is an accessible product derived from the valorization of animal waste, contributing to the circular economy and the reduction in organic pollution. Its application also minimizes waste management costs and aligns with sustainable agricultural practices. Compared to other synthetic or commercial materials used for metal retention (such as activated carbon or chemical chelators), bone meal stands out due to its low cost, ease of application, and biodegradability.

Bone meal has a microcrystalline structure with a considerable capacity to retain heavy metals through mechanisms such as ion exchange, complexation, and precipitation. The hydroxyapatite naturally present in animal bones forms insoluble compounds with heavy metals, thereby limiting their bioavailability and reducing the risk of transfer through the food chain. Additionally, the alkaline nature of bone meal contributes to increasing soil pH, which promotes metal immobilization and reduces their toxicity to plants. Therefore, amending soils with bone meal not only acts as a passive remedy for heavy metal pollution but also serves as an active agent in ecological and agricultural restoration [12,13,14].

In addition to its efficiency in retaining metals, the application of bone meal in contaminated soils can directly and indirectly influence plant development. In this regard, germination tests are an essential tool for assessing the phytotoxicity of the treated environment. Germination is a critical stage of plant life cycle and is highly sensitive to the presence of soil contaminants. Heavy metals can inhibit seed germination, impede root elongation, and reduce seedling vigor, with negative effects on crop viability. Therefore, germination tests provide valuable insights not only into the efficiency of metal retention but also into the ecological impact of the applied treatment [15,16]. Integrating germination assays with adsorption modeling provides a more holistic understanding of amendment efficacy, beyond chemical endpoints alone.

Addressing the limited understanding of bone meal’s integrated chemical–biological performance in real soils, this study aims to investigate the capacity of bone meal to retain zinc from soils artificially contaminated with wastewater and to assess the effects of this treatment on seed germination. By correlating chemical parameters with the biological response of plants, the research seeks to validate the effectiveness of bone meal as a sustainable solution for improving soils affected by heavy metal pollution, with potential applications in organic farming, horticulture, and the restoration of degraded lands.

This study is novel in its integrated approach, which combines adsorption isotherm and kinetic modeling, morphological and elemental characterization by SEM–EDX, and biological germination tests to evaluate the dual role of bone meal in zinc immobilization and phytotoxicity reduction. Unlike previous studies, which have mainly focused on biochar or plant-derived amendments, this research investigates a soil–bone meal mixture using cambic soil, providing both chemical and biological evidence of its effectiveness. Furthermore, by comparing germination responses and the extent of inhibition in three plant species (cress, wheat, and mustard), this study highlights species-dependent differences that have not been previously reported. From a sustainability perspective, the work demonstrates how a by-product of the agri-food industry can be valorized as a low-cost, environmentally friendly amendment, aligning soil remediation strategies with the principles of circular economy and bioeconomy.

2. Materials and Methods

2.1. Chemical Reagents

The bone meal used in the experiments was a commercial product available on the German market, supplied by GRAU GmbH Spezialtiernahrung, Germany, under the name “BARF Naturreines Knochenmehl.” This is pure bone meal, free of additives, with a high calcium phosphate (hydroxyapatite) content, which makes it a promising adsorbent material for heavy metals. Information regarding its composition and usage can be found on the manufacturer’s official website. ZnSO₄ was purchased from Sigma Aldrich (Merck KGaA, Darmstadt, Germany). Sodium hydroxide (NaOH), hydrochloric acid (HCl), sulfuric acid (H₂SO₄), and ethylenediaminetetraacetic acid disodium salt (EDTA-Na₂) were also purchased from Sigma Aldrich (Merck KGaA, Darmstadt, Germany).

Zinc was determined according to ISO 12739:2006 [17] (Ion-exchange/EDTA titrimetric method), with adaptations. In this study, zinc was quantified in the filtrates obtained after adsorption experiments, omitting the ion-exchange step. The titration was performed with EDTA under adapted conditions. Validation of the adapted method was carried out on a representative subset by ICP-OES (SR EN ISO 11885), and the relative difference between the two methods was ≤10% [17,18].

2.2. Soil Characteristics

The cambic chernozem soil used in this study originates from Teleorman County (Drăgăneşti-Vlaşca), Romania. The area from which the soil was collected is characterized by a deficient and unevenly distributed rainfall regime (multiannual average of 544 mm) and an excessive thermal regime (multiannual average temperature of 10.8 °C). The soil used in the experiments is a cambic chernozem of the vertic subtype, developed on swelling clay as the parent material, with a clay–loam texture within the plow layer depth (

Table 1. Classification of particle size fractions [19].

Granular Fraction Name	Grain Diameter (mm)	Composition (%)
Coarse sand	0.2	0.35
Fine sand	0.02–0.2	17.21
Dusti	0.002–0.02	39.52
Clay	<0.002	42.92

and

Table 2. The physicochemical properties of cambic chernozem soil (Teleorman area).

Property	Value	Analysis Method
pH 1:2.5	5.4	[20]
Humus (%)	2.9	[21]
CaCO3 (%)	0.00	[22]
Ntotal (%)	0.18	[23]
PAL (ppm)	90.00	[24]
Ptotal (%)	0.090	[25]
KAL (ppm)	315	[26]
Zn (ppm)	3.69	[27]
Cu (ppm)	3.01
Fe (ppm)	40.37
Al (ppm)	170
Mn (ppm)	4.5
Alkali saturation level (%)	83.2	[28]
Exchange alkali (me/100 g sol)	28.3	[28]
Hygroscopicity coefficient (%)	6.9	[29]
Volumetric weight (g/cm3)	1.25	[30]

Note: The characterization of this soil was carried out and provided by the National Research and Development Institute for Soil Science, Agrochemistry, and Environmental Protection—ICPA Bucharest.

).

2.3. Characteristics of Bone Meal

Data on the composition, additives, and analysis of bone meal are presented in

Table 3. Composition and major minerals of bone meal. (a) composition (content, % w/w). (b) major minerals.

(a)
Component	Content (% w/w)
Moisture	20.9
Ash	72.8
Protein	0.6
Fat	0.3
Fiber	0.3
Others	5.1
(b)
Mineral	Content (% w/w) *
Calcium (Ca)	22.6
Phosphorus (P)	17.7
Magnesium (Mg)	0.022
Sodium (Na)	0.030

Note: The analysis report is according to the supplier’s label. * Mineral contents refer to the whole product on a mass basis and are largely contained within the ash fraction; therefore, totals across sections (a,b) are not intended to sum to 100%. Data from the supplier’s label.

:

• ▪ Ingredients: bones (100% beef, ground).
• ▪ Additives: the manufacturer guarantees that this product contains no additives.

2.4. Characterization of Bone Meal

The surface morphology of the samples was examined using a Quanta Inspect F50 SEM (scanning electron microscopy) device, operating at an acceleration voltage of 30 kV. The device is equipped with a field emission gun (FEG) having 1.2 nm resolution and coupled with an EDX spectrometer (all from FEI Company, Eindhoven, The Netherlands) having 133 eV resolution at Mn Kα.

2.5. Description of Models for Adsorption Equilibrium Study

2.5.1. The Langmuir Model

The Langmuir model assumes that the surface of the adsorbent contains active sites capable of retaining adsorbate ions through Van der Waals forces or chemisorption. It is based on the hypothesis of physical or chemical bond formation between the surface of the adsorbent and the molecules of the adsorbed component, without interactions between the adsorbed molecules. Adsorption occurs in the form of a monolayer, and the adsorbed molecules do not interact with each other.

The Langmuir isotherm model is described by the following formula:

$${\mathrm{a}}_{\mathrm{e}}={\displaystyle \frac{\mathrm{K}\cdot \mathrm{C}\cdot {\mathrm{a}}_{\mathrm{m}\mathrm{a}\mathrm{x}}}{1+\mathrm{K}\cdot \mathrm{C}}}$$

(1)

which can be linearized as:

$${\displaystyle \frac{1}{{\mathrm{a}}_{\mathrm{e}}}}={\displaystyle \frac{1}{\mathrm{K}\cdot \mathrm{C}\cdot {\mathrm{a}}_{\mathrm{m}\mathrm{a}\mathrm{x}}}}+{\displaystyle \frac{1}{{\mathrm{a}}_{\mathrm{m}\mathrm{a}\mathrm{x}}}}$$

(2)

By performing the variable changes ${\mathrm{y}}_{\mathrm{e}}={\displaystyle \frac{1}{{\mathrm{a}}_{\mathrm{e}}}}$ and $x={\displaystyle \frac{1}{C}}$, the equation of a straight line is obtained, ${\mathrm{y}}_{\mathrm{e}}=\mathrm{A}\cdot \mathrm{x}+\mathrm{B}$. $\mathrm{A}={\displaystyle \frac{1}{\mathrm{K}\cdot {\mathrm{a}}_{\mathrm{m}\mathrm{a}\mathrm{x}}}};\mathrm{B}={\displaystyle \frac{1}{{\mathrm{a}}_{\mathrm{m}\mathrm{a}\mathrm{x}}}}$ where a_e, a_max are the zinc content at equilibrium and the maximum adsorption capacity (at saturation), mg Zn/kg dry adsorbent; C is the concentration of the adsorbate (zinc) solution after adsorption equilibrium is reached, mg/L; K is the adsorption coefficient, L/mg [31,32,33].

2.5.2. The Freundlich Equation

The Freundlich model is based on the hypothesis that chemical equilibrium is reached when there is a dynamic exchange between adsorbed molecules and those remaining in solution. The adsorbent surface is heterogeneous, and the adsorbate species are distributed in multiple layers on the adsorbent surface. This implies that all the adsorption sites have different affinities. The Freundlich isotherm is expressed by the equation:

$${\mathrm{a}}_{\mathrm{e}}=\mathrm{K}\cdot {\mathrm{C}}^{1/\mathrm{n}}$$

(3)

Equation (3) can be linearized by taking the logarithm:

$$\ln {\mathrm{a}}_{\mathrm{e}}=\ln \mathrm{K}+{\displaystyle \frac{1}{\mathrm{n}}}\ln \mathrm{C}$$

(4)

Replacing ${\mathrm{y}}_{\mathrm{e}}=\ln {\mathrm{a}}_{\mathrm{e}}$ and x = ln C, the equation of a straight line is obtained ${\mathrm{y}}_{\mathrm{e}}=\mathrm{A}\cdot \mathrm{x}+\mathrm{B}$; $\mathrm{A}={\displaystyle \frac{1}{\mathrm{n}}};\mathrm{B}=\ln \mathrm{K}$.

2.6. Description of Models for Kinetic Study

(a)

The pseudo-second-order adsorption kinetic model is mathematically described according to Equation (5) [34]:

$${\displaystyle \frac{\mathrm{d}{\mathrm{a}}_{\mathrm{t}}}{\mathrm{d}\mathrm{t}}}=\mathrm{k}″({\mathrm{a}}_{\mathrm{e}}-{\mathrm{a}}_{\mathrm{t}}{)}^2$$

(5)

where k″ is the pseudo-second-order rate constant of the adsorption process (g/min·mg); a_e is the zinc ion loading of the adsorbent at equilibrium (mg/kg); and a_t is the zinc loading of the adsorbent at time t (mg/kg).

By applying the boundary conditions: t = 0, t = t and a_t = 0, a_t = a_t to Equation (5), integrating, and rearranging the terms, we obtain:

$${\int }_0^{{\mathrm{a}}_{\mathrm{t}}}{\displaystyle \frac{\mathrm{d}{\mathrm{a}}_{\mathrm{t}}}{({\mathrm{a}}_{\mathrm{e}}-{\mathrm{a}}_{\mathrm{t}}{)}^2}}=\mathrm{k}″{\int }_0^{\mathrm{t}}\mathrm{d}\mathrm{t}\Rightarrow {\displaystyle \frac{\mathrm{t}}{{\mathrm{a}}_{\mathrm{t}}}}={\displaystyle \frac{1}{\mathrm{k}″{\mathrm{a}}_{\mathrm{e}}^2}}+\left({\displaystyle \frac{1}{{\mathrm{a}}_{\mathrm{e}}}}\right)\mathrm{t}$$

(6)

• (b) The pseudo-first-order adsorption kinetic model is mathematically described according to Equation (7) [34]:

$${\displaystyle \frac{\mathrm{d}{\mathrm{a}}_{\mathrm{t}}}{\mathrm{d}\mathrm{t}}}=\mathrm{k}\prime ({\mathrm{a}}_{\mathrm{e}}-{\mathrm{a}}_{\mathrm{t}})$$

(7)

Applying the boundary conditions: t = 0, t = t and a_t = 0, a_t = a_t, and integrating Equation (7), we obtain: $\ln \left({\mathrm{a}}_{\mathrm{e}}-{\mathrm{a}}_{\mathrm{t}}\right)=\ln {\mathrm{a}}_{\mathrm{e}}-{\mathrm{k}}^{\mathrm{’}}\mathrm{t}$ where k’ and a_e can be determined from the linear regression of experimental data.

The model used to determine the evolution of the adsorbent loading over time is given by the mass balance Equation (8)

$${\mathrm{a}}_{\mathrm{t}}={\displaystyle \frac{{\mathrm{V}}_{\mathrm{a}\mathrm{q}}({\mathrm{C}}_0-{\mathrm{C}}_{\mathrm{t}})}{{\mathrm{m}}_{\mathrm{s}\mathrm{o}\mathrm{l}}}}+{\mathrm{a}}_0$$

(8)

where ${\mathrm{a}}_{\mathrm{t}}=\mathrm{a}+{\mathrm{a}}_0$, a_t and C_t have the same meaning as in Equation (5), mg/kg, C₀ is the initial concentration of zinc in the aqueous phase, mg/L, V_aq is the volume of the aqueous phase, mL, a₀ is the initial zinc content in the soil, mg/kg, and m_sol is the mass of the solid (soil–bone meal mixture), g.

2.7. Methods

2.7.1. Experimental Methods

To investigate the adsorption process of zinc ions onto a mixture of cambic soil and bone meal, a synthetic Zn²⁺ wastewater solution with a concentration of 600 mg/L was used, representing a model of contaminated effluent. The chosen Zn²⁺ concentration (600 mg/L) corresponds to the upper intervention threshold often referenced for agricultural soils in Romania. According to Romanian legislation (Order MAPPM 765/1997), the maximum admissible level of zinc in soil is 300 mg/kg [35]. Industrial effluents from galvanic processes can exhibit extremely high zinc concentrations. For instance, Thomas et al. (2023) [36] reported up to 1534 mg Zn/L in concentrated galvanic wastewater. Consequently, the selected experimental concentration of 600 mg Zn²⁺/L represents a realistic yet severe contamination scenario, thereby reinforcing the environmental relevance and robustness of the adsorption study.

In the preliminary experiments, 2.5 g of cambic soil (particle size < 2 mm) were mixed with 2.5 g of bone meal (particle size < 0.2 mm). The resulting mixture was placed in a 100 mL Berzelius beaker, and 25 mL of the synthetic Zn²⁺ solution was added, yielding a solid–liquid ratio of 1:5. The pH of the suspension was adjusted in the range of 2–12 using NaOH or HCl solutions to evaluate its influence on retention efficiency.

For the adsorption equilibrium study, the same mixture of 2.5 g cambic soil and 2.5 g bone meal was brought into contact with 25 mL of Zn²⁺ solution (600 mg/L). The mixture was kept static for 24 h to reach adsorption equilibrium. The pH was adjusted using 0.1 M NaOH and 0.1 M HCl, according to the conditions required by the experimental protocol. Afterwards the suspension was filtered on a filter paper with pore size of 0.45 μm.

The concentration of dissolved Zn was determined by complexometric titration with EDTA, using a procedure adapted from ISO 12739:2006 [17]. Validation was performed on a representative subset by ICP-OES (SR EN ISO 11885); the relative difference between EDTA and ICP-OES was ≤10% [18].

For the kinetic study, separate samples were prepared and subjected to magnetic stirring at 200 rpm, for different time intervals: 2, 5, 10, 15, 20, and 30 min. After contact, the suspensions were vacuum filtered, and the resulting aqueous extract was analyzed according to the ISO 12739:2006 standard [17]. To improve the clarity of the methodological description and address the workflow of adsorption experiments, Figure 1, illustrates the initial step of pH adjustment to the target value (using 0.1 M NaOH or HCl) and its maintenance throughout the test. From this common preparation step, the experimental protocol is divided into two distinct branches: the equilibrium branch, where the mixture is kept static for 24 h to reach adsorption equilibrium, and the kinetic branch, where the mixture is subjected to magnetic stirring for predetermined time intervals (2–30 min) to monitor the adsorption rate.

In this study the term retention includes both surface adsorption and precipitation-driven removal. After contact, suspensions were filtered and only the dissolved Zn²⁺ remaining in the filtrate was quantified; therefore, any Zn removed as solid phases (e.g., Zn(OH)₂ or Zn–phosphates nucleated on the solid) is operationally counted as “retained” by the soil–bone meal mixture. This is explicitly considered in the discussion at high pH.

2.7.2. Calculation of the Germination Rate

The germination rate (GR, %) was calculated as the proportion of seeds that germinated within the experimental period relative to the total number of seeds sown for each replicate. The calculation was performed according to the formula [37]:

$$\mathrm{G}\mathrm{R}\left(\mathrm{\%}\right)={\displaystyle \frac{{\mathrm{N}}_{\mathrm{g}}}{{\mathrm{N}}_{\mathrm{t}}}}·100$$

(9)

where N_g is the number of seeds that germinated normally (with visible radicle emergence) and N_t is the total number of seeds sown. Germination was assessed after five days of incubation under the specified experimental conditions. Data are expressed as the means of five replicates ± standard deviation.

2.7.3. Calculation of the Extent of Inhibition

The extent of inhibition was determined relative to the soil + bone meal treatment, which exhibited the highest germination rate for each plant species and was therefore considered the reference (100% performance). For each treatment (control and Soil), the extent of inhibition (%) was calculated as [38]:

$$\mathrm{E}\mathrm{x}\mathrm{t}\mathrm{e}\mathrm{n}\mathrm{t} \mathrm{o}\mathrm{f} \mathrm{i}\mathrm{n}\mathrm{h}\mathrm{i}\mathrm{b}\mathrm{i}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}\left(\mathrm{\%}\right)={\displaystyle \frac{{\mathrm{R}}_{\mathrm{r}\mathrm{e}\mathrm{f}}-{\mathrm{R}}_{\mathrm{t}\mathrm{r}\mathrm{e}\mathrm{a}\mathrm{t}}}{{\mathrm{R}}_{\mathrm{r}\mathrm{e}\mathrm{f}}}}·100$$

(10)

where R_ref is the germination rate in the reference treatment and R_treat is the germination rate in the treatment of interest. This approach was adopted because the control did not always yield the highest germination, and using the best-performing treatment as the reference allows for a more meaningful quantification of the relative inhibitory effects. Data is expressed as the mean of five replicates.

3. Results and Discussion

3.1. Characterization of Bone Meal: SEM-EDX

The images obtained by scanning electron microscopy (SEM) provided essential information on the morphological changes in the bone meal-based adsorbent surface, before and after contact with the Zn²⁺ solution at different pH values.

In the control images (Figure 2a,d,g), corresponding to untreated bone meal, a porous structure is observed, with irregularly agglomerated particles of varying sizes, characteristic of materials rich in hydroxyapatite. The surfaces display a well-developed topography, with high adsorption potential due to the presence of functional groups capable of interacting with metal ions.

After adding the Zn²⁺ solution at pH = 6 (Figure 2b,e,h), the surface of the adsorbent shows granular coverage and compact agglomerations, indicating efficient zinc retention. The structure remains stable, confirming that favorable chemical adsorption occurs at this pH, through mechanisms such as phosphate complexation, electrostatic interactions, and possible co-precipitation reactions. This behavior is supported by the high values of adsorption capacity and initial rate observed in the kinetic and adsorption equilibrium studies [3,12,13,14,15].

In contrast, at pH = 2 (Figure 2c,f,i), the mineral structure of the bone meal appears significantly affected. The surfaces are visibly altered, with amorphous aggregates and a smooth morphology, indicating partial dissolution of hydroxyapatite in the acidic environment. These visual observations support the conclusion that under acidic conditions, the adsorption efficiency decreases significantly due to the loss of the physicochemical properties of the adsorbent. Under these conditions, zinc retention is limited, as confirmed by the EDX analysis, which shows a weak presence of Zn²⁺ on the sample surface.

In conclusion, SEM analysis confirms the crucial role of pH in the zinc retention process. At neutral pH 6, bone meal retains its structure and adsorption capacity, whereas acidic conditions destabilize it, reducing efficiency. SEM observations combined with EDX analysis confirmed pH-dependent changes in surface composition, clarifying the mechanisms of zinc adsorption.

In the case of untreated bone meal (Figure 3), the EDX spectrum highlights the presence of these elements characteristic of its mineral composition: carbon (C), oxygen (O), phosphorus (P), potassium (K), and calcium (Ca). These reflect the basic structure of hydroxyapatite [Ca₁₀(PO₄)₆(OH)₂], the active component responsible for the heavy metal retention capacity.

For the sample treated with Zn solution at pH = 2 (Figure 4), the EDX spectrum reveals a more complex composition, including a wide range of elements: silicon (Si), aluminum (Al), iron (Fe), manganese (Mn), chromium (Cr), and zinc (Zn), in addition to the previously present elements (C, O, K, Ca, P). This chemical profile confirms the influence of the soil added to the mixture, as well as the interaction between zinc and the mineral-organic components of the samples [9,10,11]. However, the lower intensity of the Zn signal compared to pH 6 suggests limited adsorption, likely due to the solubilization of hydroxyapatite in the acidic environment (Figure 5). The distribution maps (Figure 6) show a relatively uniform dispersion of zinc on the sample surface, but at low density, indicating weak and superficial binding.

At pH = 6 (Figure 5), the EDX spectrum confirms the presence of zinc in a significantly more pronounced form, along with elements such as C, O, Fe, Al, Si, P, K, and Ca. This distribution reflects effective Zn²⁺ retention, favored by the structural stability of the bone meal in a neutral environment and its enhanced capacity to interact with metal ions. Elemental mapping (Figure 7) reveals a homogeneous and intense distribution of zinc on the sample surface, alongside phosphorus and calcium, likely indicating the formation of insoluble compounds (such as Zn₃(PO₄)₂ or Zn–Ca phosphates), which supports the chemical adsorption mechanism [7,39,40,41,42].

The EDX analysis confirms the major influence of pH on zinc adsorption efficiency. At pH = 6, superior fixation is achieved, uniformly distributed across the surface of the biochar, whereas at pH = 2, the interaction is significantly reduced. These observations support the hypothesis that zinc adsorption occurs through complexation and precipitation mechanisms, facilitated by active functional groups and the structural stability of bone meal.

3.2. Adsorption Equilibrium Study

Adsorption is most commonly described using isotherms. For a comprehensive description of the process, the Langmuir and Freundlich models were applied.

The adsorption isotherm, which represents the relationship between the amount of zinc adsorbed and the equilibrium concentration of the solutions (Langmuir and Freundlich equations), allows for the calculation of the maximum adsorption capacity (a_max) and the constant (K) related to adsorption energy parameters necessary for comparing different adsorbents in terms of their adsorption properties for zinc ions.

The adsorption equilibrium study was conducted to evaluate the ability of the system composed of cambic soil and bone meal to adsorb zinc ions (Zn²⁺) under equilibrium conditions, maintaining contact for 24 h. Thermodynamic parameters were determined by fitting the experimental data to the classical Langmuir and Freundlich adsorption models, in order to identify the predominant mechanism and the efficiency of the process as a function of pH.

Data analysis was carried out at three pH values (2, 6, and 12) to highlight the influence of pH on the adsorption process. The parameters obtained using the Langmuir and Freundlich models are listed in

Table 4. Parameters of the Langmuir and Freundlich models for cambic soil.

pH	Langmuir			Freundlich
	K (mg−1·L)	amax (mg·kg−1)	R2	K	n–1	R2
2	0.0139	101.88	0.5016	1.4559	0.8180	0.7572
6	0.0389	2375.33	0.8717	115.39	0.6966	0.9071
12	−0.0562	−3692.79	0.9961	186.44	1.2976	0.9944

, and the Langmuir and Freundlich isotherms are presented in Figure 8, Figure 9 and Figure 10.

The results obtained indicate a significant influence of pH on adsorption behavior. At pH 2, the values of the Langmuir equilibrium constant (K = 0.0139 mg⁻¹·L) and the maximum adsorption capacity (a_max = 101.88 mg/kg) were low, and the correlation coefficient R² (0.5016) indicated a poor fit of the data to the model. Similarly, the Freundlich model showed a modest constant value (K = 1.4559) and an insufficient fit (R² = 0.7572). These results suggest that under acidic conditions, adsorption mechanisms are strongly limited, most likely due to the dissolution of hydroxyapatite from the bone meal and the destabilization of the adsorbent structure.

At pH 6, the situation changes dramatically. The Langmuir model indicates a very high maximum adsorption capacity (a_max = 2375.33 mg/kg) and a greatly improved correlation coefficient (R² = 0.8717), highlighting efficient retention of zinc ions under slightly neutral conditions. In parallel, the Freundlich model provided a good fit (R² = 0.9071), with an exponent 1/n < 1 (0.6966), which indicates a favorable adsorption process on a heterogeneous surface, characteristic of the soil–bone meal mixture. The associated graph (Figure 10) shows a good overlap between experimental data and the modelled isotherms, supporting the applicability of both models, with a slight advantage for Freundlich, considering the heterogeneous nature of the adsorbent surface.

At pH 12, zinc removal is strongly affected by precipitation processes. The Langmuir fit yields non-physical parameters (negative K and a_max= −3692.79 mg/kg; R² = 0.9961), which indicates that the assumptions of monolayer adsorption on a homogeneous surface are not in agreement with experimental data. In highly alkaline media, the ionic product of Zn²⁺ and OH ^{– -} exceeds the solubility of Zn(OH)₂(s), and heterogeneous nucleation on bone-meal surfaces is favored; concomitantly, phosphate released from hydroxyapatite can drive formation of sparingly soluble Zn–phosphates (e.g., Zn₃(PO₄)₂). Consistent with this, the Freundlich model better captures the data at pH 12: K = 186.4350K, 1/n > 1 (1.2976), R² = 0.9944, reflecting heterogeneous surfaces and multilayer interactions typical of precipitation–adsorption coupling. We therefore retain the negative Langmuir value in Table 4 to explicitly signal model limitation at high pH.

Overall, the Freundlich model describes better the adsorption behavior of the system at extreme pH of 12, where the surface of the adsorbent is likely significantly altered and involves a heterogeneous distribution of active sites. At pH 6, both models are valid, with a slight preference for Freundlich, confirming the complex and variable nature of the bone meal-derived adsorbent surface.

The maximum adsorption capacity values determined for the soil–bone meal mixture range between 0.1 and 2.4 mg/g, depending on pH. These values are comparable to those reported in the literature for similar materials. Azeem et al. (2022) [3] reported values of 0.8–2.5 mg/g for bone-derived biochar used for Zn(II) immobilization in contaminated soils, while Majewska and Hanaka (2025) [6] reported capacities exceeding 2 mg/g for phosphate-based biochar under alkaline pH conditions. Therefore, the results obtained in this study are consistent with existing data, confirming the effectiveness of bone meal as a natural adsorbent for zinc immobilization in soils.

These parameters support the idea that bone meal incorporated into soil is an effective and eco-friendly adsorbent material, with real potential for application in the remediation of heavy metal-contaminated soils.

3.3. Kinetic Study

To understand the adsorption mechanism of zinc ions (Zn²⁺) on the soil–bone meal based adsorbent, a kinetic study was conducted based on the pseudo-first-order and pseudo-second-order models, analyzing efficiency as a function of pH. The experiments were carried out at a constant solution concentration (600 mg/L) over a time interval of 30 min, with successive sampling at six time points. The kinetic parameters calculated by bilinear regression, according to the mathematical models used, are presented in

Table 5. Kinetic parameters for pseudo-first-order and pseudo-second-order kinetic models.

pH	C (mg·L−1)	Pseudo First Order		Pseudo Second Order
		k′ (min−1)	R2	K″ (kg·mg−1·min−1)	v0 (mg·g−1·min−1)	ae (mg·kg−1)	R2
2	600	0.1801	0.7304	0.0009	3610.18	2010.91	0.9974
6	600	0.1079	0.8514	0.0003	1382.52	2116.10	0.9931
12	600	0.1670	0.7590	0.0160	138,250.19	2937.53	1

.

The kinetic study of the zinc ion adsorption process on the soil–bone meal mixture highlighted the significant influence of pH on metal retention efficiency. For this analysis, pseudo-first-order and pseudo-second-order kinetic models were used, with their parameter values calculated by bilinear regression.

The pseudo-first-order model, which assumes that adsorption is governed by physical mechanisms, provided only a modest fit to the experimental data, with correlation coefficient (R²) values below 0.85, indicating that this model does not accurately describe the adsorption mechanism. In contrast, the pseudo-second-order model, which involves the formation of chemical bonds between metal ions and the adsorbent surface, showed excellent agreement with the experimental data. The R² values obtained for this model were very close to 1, confirming that zinc adsorption on the soil–bone meal mixture is a chemically driven process.

The time evolutions of the concentration, loading, and reaction rate as a function of pH are presented in Figure 11, Figure 12 and Figure 13.

The analysis of kinetic parameters showed that at pH 12, the initial adsorption rate (v₀) was extremely high (1382.5 mg/g·min), and the equilibrium adsorption capacity (a_e) reached a maximum of 2937.5 mg/kg. These results indicate high reactivity and superior efficiency of the mixture under alkaline conditions. At pH 6, a similarly high retention capacity was observed (2116.1 mg/kg), with slightly slower kinetics than at pH 12, but with very good overall efficiency. In contrast, at pH 2, both the adsorption rate and the amount of zinc retained were significantly lower, indicating that the acidic environment promotes hydroxyapatite dissolution and reduces the adsorbent’s capacity to retain metal ions.

The graph (Figure 11), showing the evolution of Zn²⁺ concentration over time, confirms these trends: at pH 12, the concentration drops sharply within the first few minutes, whereas at pH 2, the process is slower and remains incomplete. The evolution of adsorbent loading follows the same pattern, with the highest values obtained under alkaline conditions. Additionally, the analysis of the adsorption rate highlights a clear difference between pH levels, with a much higher rate observed at pH 12 in the initial moments of adsorbent–adsorbate contact.

The experimentally obtained values for the maximum adsorption capacity of zinc ions on the soil–bone meal mixture—up to 2937.5 mg/kg at pH = 12—fall within the range reported in the literature for similar materials. For instance, Cheung et al. (2000) [43] reported values of maximum 3465 mg/kg for Zn(II) adsorption onto bone char, depending on thermal treatment and environmental conditions, confirming similar complexation and co-precipitation mechanisms. Azeem et al. (2021) [3] demonstrated the efficiency of bone-derived biochar in retaining zinc and reducing its bioavailability in contaminated soils, supporting its use as a natural amendment. Likewise, Majewska and Hanaka (2025) [6] reported comparable adsorption capacities (over 2000 mg/kg) for phosphate-based biochars under alkaline conditions, similar to those tested in this study.

These results confirm the chemical nature of the adsorption process, the favorable properties of the adsorbent surface, and the validity of the pseudo-second-order kinetic models, as already demonstrated by the high correlation coefficients (R² > 0.99). Therefore, the data support the integration of bone meal into eco-friendly strategies for the remediation of heavy metal-contaminated soils.

The kinetic data confirm that the adsorption of zinc ions onto the soil–bone meal adsorbent is a chemical process, accurately described by the pseudo-second-order model. Maximum efficiency is achieved in slightly alkaline environments, supporting the use of this material for the remediation of heavy metal-contaminated soils, especially when pH conditions can be controlled or adjusted.

From the perspective of adsorption performance, bone meal exhibits a natural affinity for phosphate ions due to its high calcium content; however, its capacity varies considerably depending on pretreatment and experimental conditions. In the literature, reported values for untreated bone meal are often in the range of 0.1–3 mg P/g [44], similar to those obtained in this study (0.1–2.5 mg P/g). Thermal or chemical treatment, or reduction in particle size, can increase the capacity to 50–90 mg P/g [45], although these values involve additional processing steps. In comparison, activated carbon shows capacities of approximately 15 mg P/g, while activated carbon modified with iron oxide can reach 98.4 mg P/g. Raw biochars generally present capacities <5 mg P/g, whereas Mg- or Al-modified biochars can exceed 150 mg P/g [46,47]. Thus, the results obtained for untreated bone meal fall within the performance range of other non-activated materials, with the advantages of low cost and the valorization of a by-product.

3.4. Effects of Zinc and Bone Meal on Plant Germination and Growth in Treated Soil

To evaluate the influence of zinc on germination and the capacity of bone meal to reduce the toxic effects of zinc ions, an experiment was conducted using seeds from three plant species: mustard (Brassica alba), garden cress (Lepidium sativum), and wheat (Triticum aestivum).

Ten seeds from each species were selected and tested under identical conditions to ensure comparability of results. The seeds were placed in Petri dishes—one for each substrate and species combination—resulting in a total of nine experimental dishes (three for each plant type). The substrate varied according to treatment, with the following variants: control: moist cotton wool, with no soil or additional materials; contaminated soil: 30 g of dry soil treated with a zinc solution; soil–bone meal: a mixture consisting of 25 g of soil and 5 g of bone meal, used to evaluate the remedial effect of this adsorbent material (Figure 14).

All Petri dishes were treated with 15 mL of a zinc sulfate (ZnSO₄) solution at a concentration of 600 mg/L (without control samples), applied evenly across the substrate surface. This high concentration was chosen to simulate a severe contamination scenario, typical of soils affected by industrial wastewater irrigation [48,49].

After treatment, the dishes were kept under controlled temperature, light, and humidity conditions for one week, during which the germination process was monitored.

Germination tests were performed in five biological replicates for each treatment. Results are reported as the mean ± standard deviation, and error bars in the graphs represent the standard deviation of the replicates. Statistical significance between treatments was determined using one-way ANOVA test (

Table 6. One-way analysis of variance (ANOVA) test results for cress.

Source of Variation	Sum of Squares	Degrees of Freedom	Mean Squares	F Value	p Value
Between Groups	9.733	2	4.867	11.231	0.002
Within Groups	5.200	12	0.433
Total	14.933	14

Note: η² = 0.652 for cress.

,

Table 7. One-way analysis of variance (ANOVA) test results for wheat.

Source of Variation	Sum of Squares	Degrees of Freedom	Mean Squares	F Value	p Value
Between Groups	4.133	2	2.067	3.263	0.074
Within Groups	7.600	12	0.633
Total	11.733	14

Note: η² = 0.352 for wheat.

and

Table 8. One-way analysis of variance (ANOVA) test results for mustard.

Source of Variation	Sum of Squares	Degrees of Freedom	Mean Squares	F Value	p Value
Between Groups	1.200	2	0.600	1.125	0.357
Within Groups	6.400	12	0.533
Total	7.600	14

Note: η² = 0.158 for mustard.

).

Parameters observed included germination percentage, time to emergence of the first seedlings, and the length of embryonic roots, with the goal of identifying potential toxic effects of zinc and how bone meal may mitigate these effects. This method allows for a clear and comparative evaluation of the influence of heavy metals on plant germination and the effectiveness of bone meal as a remediation agent, through a simple yet relevant experimental model applicable to contaminated environments.

This section evaluated the impact of zinc ions (Zn²⁺), in the presence and absence of bone meal, on the germination and early development of three plant species: wheat, mustard, and cress. Zinc, at a high concentration (600 mg/L), exhibited a clear phytotoxic effect, significantly reducing the germination rate and embryonic development of the plants. Soils contaminated solely with zinc ions showed a marked inhibitory effect, manifested by a low number of sprouts, thin stems, and pale coloration of plant tissues—signs of pronounced physiological stress.

In contrast, when bone meal was introduced as a soil amendment in the contaminated substrate, clear beneficial effects on germination capacity were observed. Bone meal played an essential role in reducing zinc bioavailability, acting as an efficient adsorbent for metal ions. As a result, plant germination in soil treated with bone meal was visibly improved, especially in the case of cress, which showed the highest tolerance to contamination.

The applied zinc concentration exceeded the maximum tolerable level for plants, leading to reduced or even absent germination in some cases. While the substrate type had a minor influence on the germination rate, the major impact was caused by the presence of zinc in the applied solution.

Among the three analyzed species, cress proved to be the most tolerant to zinc-induced stress, achieving a germination rate of 80% (8 out of 10 seeds). This suggests a higher biological capacity of cress to manage heavy metal toxicity, either through physiological exclusion mechanisms or by accumulating zinc without immediate lethal effects. In contrast, mustard and wheat showed significantly lower germination rates, reflecting greater sensitivity to zinc toxicity.

The data were statistically analyzed with one-way analysis of variance (one-way ANOVA) at a significance level of p < 0.05 by using OriginPro 8 software (Table 6, Table 7 and Table 8), analyzed separately for each species (n = 5 replicates per group). Effect size was reported as eta-squared, η² = SS_between/SS_total, where SS denotes sums of squares (with SS_between the between-groups sum of squares and SS_total the total sum of squares). In one-way ANOVA, η² equals partial eta-squared.

The one-way ANOVA on germination counts across treatments (control, Zn-contaminated soil, soil + bone meal; n = 5 per group) showed a significant effect only for cress (Lepidium sativum), F(2, 12) = 11.23, p = 0.0018, η² = 0.652, indicating higher germination in the bone-meal variant than in the other groups. For wheat (Triticum aestivum), F(2, 12) = 3.26, p = 0.074, η² = 0.352, and for mustard (Brassica alba), F(2, 12) = 1.13, p = 0.357, η² = 0.158, differences were not statistically significant. These results indicate that the mitigation of Zn phytotoxicity by bone meal is species dependent—clear for cress, and the differences were not significant for mustard and wheat under the present experimental conditions.

The germination rate of the three species varied significantly depending on the treatment and their intrinsic tolerance to zinc contamination (Figure 15). Cress (Lepidium sativum) showed the highest values, with 66% in the control variant and 68% in Zn-contaminated soil, indicating a high tolerance to the metal. Amendment with bone meal increased germination to 84%, highlighting both the ability of cress to perform under stress conditions and the beneficial effect of the adsorbent in reducing metal bioavailability. Wheat (Triticum aestivum) recorded the lowest germination rates, with 30% in the control and 32% in contaminated soil, suggesting marked sensitivity to the experimental conditions. The application of bone meal improved germination to 42%, indicating a moderate ameliorative effect. Mustard (Brassica alba) exhibited intermediate tolerance, with 44% germination in both the control and contaminated soil, and a modest increase to 50% following bone meal amendment. Overall, the results confirm that the positive effect of bone meal is species dependent, being greatest in cress, followed by wheat, and minimal in mustard.

Bone meal amendment resulted in the highest absolute germination in cress (84%), followed by mustard (50%) and wheat (42%) (Figure 15). However, when expressed as the extent of inhibition relative to the soil + bone meal treatment (Figure 16), the most pronounced reduction in Zn-induced effects was observed in wheat (+31% vs. soil; +40% vs. control), while cress showed a +23–27% improvement and mustard a modest +14%. These findings indicate that the ameliorative effect of bone meal is species dependent—largest in relative terms for wheat, yet leading to the highest final germination in cress.

These results highlight differences in tolerance to heavy metal contamination, an important factor for selecting species used in agriculture or phytoremediation [50,51]. Thus, zinc at high concentrations has a significant negative effect on seed germination, and among the tested species, cress proved to be the most tolerant, making it a promising candidate for future studies on heavy metal tolerance.

3.5. Mechanism of Zinc Retention in Soil–Bone Meal Mixture

Bone meal used as a soil amendment is obtained through the pyrolysis of waste from the meat industry (such as cow femur, poultry, pork, or sheep bones) and has a predominantly mineral composition, mainly consisting of calcium phosphate—especially in the form of hydroxyapatite [Ca₁₀(PO₄)₆(OH)₂]. This composition gives the material a high adsorption capacity for toxic metal ions such as zinc (Zn²⁺), lead (Pb²⁺), cadmium (Cd²⁺), and copper (Cu²⁺). The mechanisms involved include ion exchange, complexation, electrostatic interactions, and dissolution–precipitation reactions [14,16,43].

The retention of zinc (Zn²⁺) in soil amended with bone meal is governed by a combination of physicochemical interactions that enhance zinc immobilization. The primary mechanisms include (Figure 17):

(a)

Alkaline Precipitation

The soil amended with bone meal increases the soil pH due to its alkaline nature, promoting the formation of sparingly soluble zinc hydroxide:

Zn²⁺ + 2OH⁻ → Zn(OH)₂(s)

This precipitation mechanism plays a significant role in reducing the mobility and bioavailability of zinc in alkaline environments.

Under strongly alkaline conditions the surplus OH⁻ promotes formation of zinc hydroxide. Bone meal provides nucleation sites and releases phosphate from hydroxyapatite, enabling co-precipitation and/or transformation to Zn–phosphate phases:

$${3\mathrm{Zn}}^{2+} + 2{\mathrm{P}\mathrm{O}}_4^{3-}\to {\mathrm{Zn}}_3{({\mathrm{PO}}_4)}_2(\mathrm{s})$$

These pathways reduce dissolved Zn²⁺ rapidly (also seen in the high initial rate and large a_e at pH 12 in Table 5), while breaching Langmuir’s monolayer assumption; hence the better performance of the Freundlich model and the appearance of non-physical Langmuir parameters.

• (b) Surface Complexation with Functional Groups

The surface of soil amended with bone meal contains oxygenated functional groups such as hydroxyl (-OH) and carboxyl (-COOH), which can form inner-sphere complexes with Zn²⁺ ions.

Hydroxyl complexation: R-OH + Zn²⁺ → R-O-Zn⁺ + H⁺

Carboxyl complexation: R-COOH + Zn²⁺→ R-COO-Zn⁺ + H⁺

These coordination reactions lead to a strong binding of zinc ions to the adsorbent surface, decreasing their leachability.

• (c) Electrostatic interactions

At neutral to slightly alkaline pH, the deprotonation of surface groups on adsorbent results in negatively charged sites. These sites attract and retain Zn²⁺ ions through electrostatic attraction: R-COO⁻ ··· Zn²⁺.

While these interactions are generally weaker than covalent complexation, they significantly contribute to the overall retention capacity of the material.

• (d) Physical and Chemical Adsorption

Zinc ions can be retained via non-specific adsorption on the porous surface of adsorbent, involving van der Waals forces, hydrogen bonding, and partial surface complexation:

Adsorbent + Zn²⁺ → Adsorbent-Zn²⁺ (adsorbed)

This process enhances short-term retention and contributes to the initial immobilization of Zn²⁺ upon adsorbent application [52,53,54,55,56].

The retention mechanism of zinc ions (Zn²⁺) on the soil–bone meal mixture is complex and governed by several synergistic processes. First, physical and chemical adsorption occurs on the surface of the adsorbent, facilitating the fixation of Zn²⁺ ions. Second, under alkaline conditions—promoted by the presence of bone meal, which raises the pH—precipitation of Zn(OH)₂ takes place, significantly contributing to zinc retention. Additionally, complexation of zinc ions with functional groups such as –-COOH and -OH present on the adsorbent surface plays an important role. Finally, electrostatic interactions between the negatively charged adsorbent surface and the positively charged Zn²⁺ ions further support the retention process,

Beyond these mechanisms, bone meal promotes the transformation of zinc into sparingly soluble phosphate and hydroxide phases (e.g., zinc hydroxyapatite). This process reduces zinc mobility and its bioavailability to plants, demonstrating that bone meal acts not only as an adsorbent but also as a chemical stabilizer, thereby lowering the ecological risk of zinc contamination in agricultural soils.

4. Conclusions

This study highlighted the considerable potential of bone meal and bone meal-derived biochar in retaining zinc from soils contaminated with wastewater. Adsorption equilibrium and kinetic studies conducted at different pH levels confirmed the effectiveness of the soil–bone meal mixture for zinc retention, with maximum performance observed under neutral conditions (around pH 6). The experiments showed that the pH is a key factor, with higher pH values enhancing the retention of metal ions.

The adsorbent mixture, functioned as an efficient sorbent, significantly reducing the mobility and bioavailability of zinc. Its chemical composition—rich in phosphorus, calcium, and hydroxyapatite—makes bone meal suitable for agricultural and environmental applications.

This study does not include a soil-only control in the adsorption tests; the assessment of the specific contribution of bone meal relies on convergent evidence from the biological (germination) and morphological/chemical (SEM–EDX) results, which indicate more efficient Zn immobilization in the presence of bone meal at pH ≈ 6. Future studies should explicitly include this soil-only control under identical conditions (solid mass, volume, Zn concentration, contact time, pH) to directly quantify the contribution of bone meal relative to soil alone.

This research is based on controlled experiments under controlled laboratory conditions and should be validated under real agricultural and environmental conditions before large-scale application.

In germination tests, bone meal increased cress germination to 80% and mitigated zinc phytotoxicity across all tested species, with species-specific differences observed.

Thus, while excess zinc inhibits germination, bone meal mitigates its toxicity and improves seed viability, supporting the hypothesis that natural amendments (such as bone meal) can be effective in remediating polluted soils.

The long-term application of bone meal as a phosphate source can have several agronomic benefits for soil health and sustainability. Bone meal is a slow-release fertilizer, providing phosphorus (P) and calcium (Ca) gradually over time, which reduces the risk of nutrient leaching compared to highly soluble synthetic fertilizers [57,58]. This gradual nutrient release supports sustained plant growth and improves phosphorus use efficiency, particularly in acidic or phosphorus-deficient soils. The calcium content can also help buffer soil acidity, contributing to improved pH stability and enhanced microbial activity [59]. Additionally, bone meal contributes to organic matter input and supports beneficial soil microbial communities, which are key drivers of nutrient cycling and long-term soil fertility [60]. From a sustainability perspective, using bone meal recycles a by-product of the meat processing industry, reducing waste disposal needs and greenhouse gas emissions associated with synthetic fertilizer production [61].

However, potential risks and management practices must also be considered. Long-term and excessive application should be managed carefully to avoid phosphorus accumulation in soil, which could increase the risk of runoff and eutrophication in surrounding water bodies [62]. Therefore, integrating bone meal into nutrient management plans, alongside soil testing and crop requirements, ensures both agronomic benefits and environmental protection over the long term.

Therefore, this research supports the use of the soil–bone meal adsorbent as a sustainable, efficient, and cost-effective solution for the remediation of heavy metal-contaminated soils, emerging as a promising option with multiple environmental and agricultural benefits [7,56].

Through an integrated approach combining chemical analysis, adsorption process modeling, and biological germination tests, this study validates the use of bone meal as a practical and sustainable solution for the remediation of soils affected by heavy metal pollution.

Limitations and Future Work

The results demonstrate the effectiveness of bone meal in zinc immobilization under controlled laboratory conditions; however, the long-term stability of zinc retention in amended soils remains to be assessed. Previous column studies (e.g., Sneddon et al., 2006 [63]) demonstrated sustained retention for up to 18 months under leaching conditions, with metal release becoming detectable only after ~300 days in lower amendment ratios (1:25), while higher ratios (1:10) retained metals throughout the experiment. Potential re-mobilization under varying environmental conditions (e.g., pH changes, flooding, or prolonged drought) should be investigated. Additionally, field-scale trials are needed to evaluate the scalability and practicality of this approach in real agricultural or environmental scenarios.

In summary, bone meal emerges as a promising, sustainable amendment capable of both immobilizing zinc and enhancing soil quality, offering a dual chemical–biological approach to remediating polluted soils.