Evaluation of Municipal Waste Compost in Relation to the Environmental Retention of Heavy Metals

Abstract

This study investigates the performance of municipal compost as a heavy metal adsorbent for environmental protection systems. The performed assays test the effects of the pH (2–9) and contact time (5–250 min) on metal retention. To simulate leaching in natural systems, the soluble organic fraction was removed, leading to variations in the surface properties, including a 10% increase in the cation exchange capacity (CEC) and a 242% increase in the BET-specific surface area, accompanied by a small decrease in the surface charge (characterized by a less negative zeta potential values) of the washed municipal compost (WMC). Notably, these variations, which have not been found in previous research, yielded improved retention of Cu(II) and Zn(II) compared to raw municipal compost (RMC), attaining 96% retention for Cu(II) and 97% retention for Zn(II) at a pH of approximately 6.8–7.2 for a contact time of 120 min. The vast availability, cost-effectiveness, and resistance to desorption make municipal compost a viable option in a circular economy context for mitigating metal pollution across various environmental conditions. It is worth noting that this study can serve as a proxy for the expected outcomes in long-term exposure to environmental protection systems, enhancing the practical relevance of using compost for metal retention purposes.

1. Introduction and Motivation

The increasing presence of heavy metals in the environment poses significant risks to both human health and ecological systems [1]. These metals, known for their toxicity, bio-accumulation, and persistence, have the potential to significantly impact humans and ecosystems. Heavy metals can enter the human body through the food chain, while their release into aquatic environments remains a major inorganic contaminant [2]. Anthropogenic activities, including industrial processes and urban stormwater runoff, are major contributors to heavy metal pollution [3,4]. Among the various heavy metals, zinc (Zn), copper (Cu), and lead (Pb) have garnered significant attention due to their prevalence and adverse effects [5]. Zinc, commonly found in abandoned base metal mines, can be toxic to humans, particularly affecting the gastrointestinal system [6]. Copper, extensively used in industries, can be highly toxic and accumulates in organs and tissues, raising concerns about its impact on human health [7]. Lead pollution, primarily stemming from past use of organolead compounds, is known for its severe neurotoxic effects and can cause damage to the nervous system and other vital processes [8]. Following decreases in emissions of the latter, the retention of zinc and copper has been gaining increased interest in the scientific community, leading to efforts to mitigate this type of pollution and related effects.

Conventional techniques, such as coagulation–flocculation, chemical precipitation, chemical oxidation or reduction, electrochemical treatment, evaporative recovery, ultrafiltration, reactive filtration, reverse osmosis, ion exchange, and membrane technologies [9,10,11,12], have been successfully employed for heavy metal removal from wastewater. However, these methods often suffer from drawbacks such as inefficiency, sensitivity to operating conditions, and expensive sludge disposal [11].

In recent years, adsorption has emerged as a promising alternative for the retention of heavy metals, and as part of natural solutions inspired by nature [13,14,15]. While activated carbon or activated alumina have been effectively used as adsorbents [16,17], their high costs limit their widespread adoption.

Compost, a type of organic material produced from the aerobic digestion of organic waste, has gained recognition for its potential application in heavy metal removal [18,19,20,21,22,23], providing several advantages as a biosorbent, including its abundant availability, low cost, and environmental sustainability. Also, compost is rich in organic matter and contains various functional groups, such as carboxyl, hydroxyl, and amino groups, which can interact with heavy metal ions through complexation, ion exchange, and electrostatic attraction [24,25]. The high porosity of compost also facilitates the diffusion of metal ions into its structure, enhancing the adsorption process.

Over the past few years, several studies on the use of adsorption for the retention of Cu(II) and Zn(II) in wastewater treatment have been published and comprehensively reviewed [14,26,27]. These studies delve into the physicochemical characteristics and the impact of experimental parameters, including the initial concentration, adsorbent dose, pH, and contact time, to assess the efficacy of the Cu(II) and Zn(II) removal processes.

Previous studies have investigated the effectiveness of compost in removing heavy metals from contaminated environments. These studies have shown that compost exhibits significant metal adsorption capacities, with removal efficiency varying depending on factors such as the compost composition, pH, contact time, and metal concentration [14,26,28,29,30]. Additionally, compost has demonstrated the potential to reduce the bioavailability of heavy metals in soils, minimizing their uptake by plants and subsequent entry into the food chain [31,32,33]. Compost can also be used as an effective amendment to inhibit the uptake of heavy metals by crops [34,35].

The removal of heavy metal contaminants using compost represents an innovative and environmentally friendly technology with significant potential. The abundant availability, low cost, and adsorption capabilities of compost make it a promising biosorbent for heavy metal removal in various environmental matrices. Further research and development in this field will contribute to the advancement of viable remediation strategies, ultimately promoting the protection of human health and ecological integrity.

Despite the promising results, further research is necessary to optimize the application of compost for heavy metal removal. The most promising areas of research are related to the characterization of the compost’s internal structure, modeling of metal–compost interactions, and elucidation of the factors influencing metal adsorption efficiency. These results will determine the long-term stability conditions and effectiveness of future compost-based remediation strategies. Moreover, the development of efficient and sustainable techniques for compost production, quality control, and application is also essential for scaling up compost-based remediation approaches.

The objective of the present study is to evaluate the metal retention capacity of municipal compost, specifically focusing on metal cations such as Cu(II) and Zn(II), under conditions relevant to natural systems. In natural systems, compost comes into direct contact with contaminated runoff either in natural environments or within designed structures. In these open systems, the soluble constituents of compost, both organic and inorganic, are released upon initial contact. When contaminants continuously enter the system, their retention by compost occurs simultaneously with the dissolution of soluble constituents in transient conditions. This results in continuous changes in the compost surface until it becomes essentially free of soluble constituents. By characterizing the municipal compost’s structure and the metal retention capabilities in conditions resembling those found in natural systems, this study aims to contribute to the understanding of adsorption mechanisms and kinetics, leading to more effective and viable applications of compost for contaminant removal in environmental settings.

2. Materials and Methods

2.1. Reactants

In this work, the following reagents were used as purchased without purification: copper standard solution (1000 mg/L Cu(II) in HNO₃ 0.5 mol/L, Merck Certipur—Darmstadt, Germany^®), zinc standard for AAS (1000 ± 4 mg/L in HNO₃, Sigma Aldrich TraceCERT—Darmstadt, Germany^®), sodium nitrate 99.99% (Merck Suprapur^®), nitric acid (65% for analysis, ISO, PanReac—Barcelona, Spain), 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid) (HEPES > 99.5%, Sigma—Darmstadt, Germany), and sodium hydroxide (reagent grade, ≥98% Sigma-Aldrich—Darmstadt, Germany).

The electrolyte solution used in the experiments consisted of an aqueous solution containing 0.02 mol/L HEPES, 0.002 mol/L HNO₃, and 0.01 mol/L NaNO₃. All solutions were prepared using water obtained from a Milli-Q EQ 7000 system by Millipore (18.2 M$\Omega$ cm).

The compost was obtained from the Intermunicipal Waste Management Service of Greater Porto (LIPOR), commercialized under the brand Nutrimais (pulverulent). It is a natural organic compost composed of selected raw materials. The feedstock includes a mixture of horticultural and fruit products, waste from forestry exploitation, green waste (flowers, grass, etc.), and selected food leftovers from restaurants and similar establishments. Nutrimais is commonly used as an organic amendment due to its nutrient-rich composition, as shown in

Table 1. Composition of the Nutrimais compost produced by LIPOR.

Composition	Values
Organic Matter (%)	53.2 ± 3.8
Moisture (%)	23.7 ± 3.2
Total Carbon—C (%)	28.9 ± 3.1
Nitrogen—N (%)	2.3 ± 0.1
C/N	12.4 ± 1.0
Phosphorus—P2O5 (%)	1.2 ± 0.2
Potassium—K2O (%)	2.2 ± 0.2
Magnesium—MgO (%)	0.7 ± 0.1
Calcium—CaO (%)	7.6 ± 2.5
pH	9.0 ± 0.1

Source: https://nutrimais.pt/pulverulento/, accessed on 15 December 2022.

, which complies with Portuguese legislation for fertilizing materials (Law Decree 103/2015).

2.2. Adsorbent Preparation

The laboratory compost sample used in this study was prepared by combining contents from six commercial bags (70 L each) sourced from two distinct lots. To obtain a composite sample, two portions of 3300 mL were taken from each bag and selected from different locations within each bag. These portions were thoroughly mixed inside a 100 L plastic bag by shaking. The resulting mixture was left to air-dry at room temperature (approximately 25 °C) for several days. A 3 L sample was dried in an oven at 56 °C for 12 h and then sieved through a 0.85 mm mesh sieve.

The compost was then used in adsorption assays, both directly without performing any treatment on the raw municipal compost (RMC) and after performing a washing treatment on the compost to obtain the washed municipal compost (WMC).

The washing treatment consisted of rinsing the compost three times with water (type II) in order to remove the most soluble constituents, such as inorganic constituents (salts) and small organic molecules (fulvic-like acids). This procedure was carried out in order to mimic the conditions in natural systems and decrease the number of equilibria that would take place simultaneously with the interaction of the metals and the compost. In each wash, a portion of compost (0.125, 0.25, 0.5, or 1.0 g) was left in contact with 50 mL of water for at least 3 h. The compost suspension was centrifuged for 20 min at 6000 rpm, and the compost was separated. The process was repeated, and after the third centrifugation, the compost was placed in contact with the electrolyte solution for a period of at least 3 h before adsorption tests were started.

To assess the potential release of metals from the compost into the solution, a control experiment was conducted. In this assay, the RMC was brought into contact with the electrolyte solution under experimental conditions similar to the batch tests. Metal concentrations in the supernatant solution, determined by ICP-MS using the NF EN ISO 17294-2 standard method [36], revealed that only 5.1% of the Cu(II) and 5.6% of the Zn(II) present in the compost (51.0 mg/kg for Cu(II) and 150.0 mg/kg for Zn(II)) were released into the electrolyte solution. These results demonstrate that the amount of Cu(II) and Zn(II) released by the compost into the electrolyte solution is not significant.

2.3. Adsorbent Characterization

Several tests were conducted to characterize the surface properties of the RMC and WMC. The cation exchange capacity (CEC) was determined using inductively coupled plasma atomic emission spectrometry (ICP-OES) after extraction using hexaminocobalt(III) chloride, according to standard ISO 23470-2007 [37]. This analysis was carried out at the A2—Análises Químicas laboratory.

The surface morphology of the compost was studied using scanning electron microscopy (SEM) with a Hitachi model SU70 operated at an acceleration voltage of 4 kV. The Brunauer–Emmett–Teller (BET)-specific surface area of the RMC and WMC was determined using the nitrogen adsorption method. The analysis was performed using a Micromeritics Instrument Corp. (Norcross, GA, USA), Gemini Model: 2380. The equilibrium time for nitrogen adsorption was set to 5 s, and the saturation pressure was maintained at 101.3250 kPa. The zeta potentials ($Z_p$) of the RMC and WMC were measured using the batch equilibrium method with Zetasizer Nano ZS Malvern equipment (Malvern, UK).

2.4. Adsorption Batch Assays

Batch experiments were conducted at room temperature using both the RMC and WMC.

Standard solutions of Cu(II) and Zn(II) were added to suspensions of compost to obtain various concentrations (0.5, 1.0, 3.0, 6.0, and 9.0 mg/L). The suspensions were prepared by adding the appropriate mass of compost (0.125, 0.25, 0.50, and 1.0 g) to 50 mL of the electrolyte solution and allowing them to remain in contact for at least 3 h. The adsorption assays were performed in conical flasks, agitated at 200 rpm in a rotary shaker for 240 min. After centrifugation (6000 rpm, for 20 min), the concentration of metal cations remaining in the supernatant solution was determined by ICP-MS using the NF EN ISO 17294-2 standard method [36].

The effect of pH on metal ion adsorption was studied in the pH range of 2.0 to 9.0. Adjustments were made using 0.1 mol/L HNO₃ or NaOH solutions. Assays were carried out using a 9.0 mg/L solution of Cu(II) or Zn(II) in 0.5 g of compost in 50 mL of electrolyte solution, corresponding to a compost dose of 10 g/L.

The metal removal efficiency (R) for the process was obtained using Equation (1):

$$R(\%)=\frac{C_0-C_e}{C_0}·100$$

(1)

where $C_0$ is the initial concentration of the metal ions (mg/L) and $C_e$ is the concentration of metal ions remaining in the solution at adsorption equilibrium (mg/L).

The adsorption capacity of the compost at equilibrium, $q_e$ (mg/g), was calculated using Equation (2):

$$q_e=\frac{C_0-C_e}{m}·V$$

(2)

where V is the volume of the solution (L) and m is the mass of the adsorbent (g).

Adsorption kinetics assays were conducted using an initial concentration of 9.0 mg/L and a compost dose of 10 g/L. The adsorption times tested were 0, 5, 10, 20, 45, 120, and 240 min. To characterize the metal ion adsorption to the WMC, two kinetic models were employed: the pseudo-first-order model, represented by Equation (3), and the pseudo-second-order model, represented by Equation (4).

$$ln(q_e-q_t)=ln{q}_e-k_1·t$$

(3)

$$\frac{t}{q_t}=\frac{1}{k_2·q_e^2}+\frac{1}{q_e}·t$$

(4)

where $q_t$ is the amount of metal ion adsorbed by the compost (mg/g) at time t (min), $k_1$ is the pseudo-first-order adsorption constant (min⁻¹), and $k_2$ is the pseudo-second-order adsorption constant (g mg⁻¹ min⁻¹).

Adsorption isotherm studies were conducted to investigate the relationship between the initial metal ion concentrations ($C_0$), ranging from 0.50 to 9.0 mg/L, and the mass of the compost (m), ranging from 0.125 to 1.0 g (corresponding to a compost dose ranging from 2.5 to 20 g/L), at pH 7.2. Two widely used isotherm models, namely the Langmuir and Freundlich models, were employed to analyze the experimental data. The Langmuir isotherm model assumes a monolayer adsorption process on a homogeneous surface, considering that adsorption occurs at specific sites with no interaction between the adsorbed species. It can be expressed by Equation (5):

$$q_e=\frac{K_L·C_e·q_{max}}{1+K_L·C_e}$$

(5)

where $C_e$ is the concentration of metal ions remaining in the solution at adsorption equilibrium (mg/L), $q_e$ is the adsorption capacity of the compost at equilibrium (mg/g), $q_{max}$ is the maximum adsorption capacity (in mg/g), and $K_L$ is the Langmuir constant (in L/mg).

The Freundlich isotherm model, on the other hand, assumes a multilayer adsorption process on a heterogeneous surface, allowing for the presence of different adsorption sites with varied affinities. It can be represented by Equation (6):

$$q_e=K_F·C_e^{1/n}$$

(6)

where $K_F$ expresses the adsorption capacity (mg/g) and $1/n$ relates to the adsorption intensity and surface heterogeneity.

3. Results and Discussion

3.1. Adsorbent Preparation

In the present study, the ability of compost to retain metal cations was evaluated through batch experiments using raw municipal compost (RMC) and washed municipal compost (WMC) following the procedure described in Section 2. The preliminary washing treatment was performed to remove the most soluble components of the compost, thereby preventing interference with solubilization equilibria and the presence of these soluble substances in the retention process. The solubilization of low-molecular-weight humic and non-humic substances occurs through various hydrolysis equilibria [38,39,40,41], including dissociation and acid–base reactions, which are likely to involve the insoluble components of compost. These processes are inherently complex and can interfere with both the kinetics and extent of contaminant retention [42]. In addition to continuously modifying the structure of the compost surface, the soluble species released from the compost can alter the medium composition, conductivity, and pH, thereby affecting both the speciation of contaminants and the ionization extent of the functional groups on the compost surface. This, in turn, impacts the intensity of the electrostatic forces and/or complexation reactions, ultimately affecting the extent of retention. The retention process in batch experiments can be more or less affected by the simultaneous occurrence of the aforementioned equilibria, depending on the experimental conditions and nature of the contaminant.

In open systems, the retention of contaminants by compost takes place through continuous or intermittent flows. In these systems, the soluble components of compost, both organic and inorganic, are released into the aqueous medium during the initial water flux and subsequently removed from the system [43]. This creates a transient state where the dissolution of soluble constituents continuously modifies the compost surface, providing varying retention conditions for incoming contaminants. Once this initial state is reached, the compost surface becomes essentially free of soluble constituents, and the composition of the incoming solution will not be significantly affected, keeping it relatively unchanged.

The effect of the washing treatment on the retention efficiency of the compost from separate urban organic residues was evaluated by examining its surface features and retention capability in relation to Cu(II) and Zn(II). The surface modifications resulting from the removal of soluble constituents from the compost were characterized using various techniques, including the evaluation of the cation exchange capacity (CEC), zeta potential, and BET-specific surface area, and conducting a surface morphology analysis via SEM. The results obtained from these complementary techniques confirm that the removal of soluble fractions leads to significant modifications of the compost surface.

The CEC values, which measure the amount of positive charge that can be exchanged by the solid matrix surface and are particularly important for the retention of metal cations, showed a slight increase (approximately 10%) following the washing treatment of the compost (

Table 2. Cation exchange capacity (CEC) and BET-specific surface area of the RMC and WMC.

	CEC	BET
	(cmol/kg)	(m2/g)
RMC	51.4 ± 0.6	1.4175
WMC	56.2 ± 0.6	3.4327

). This suggests that the release of the soluble species leads to a net increase, albeit small, in the concentration of groups capable of retaining metal cations.

The zeta potential ($Z_p$) curves obtained for both compost samples (RMC and WMC) consistently showed negative values across the entire pH range (2 to 12), indicating that the surface charge is always negative (Figure 1). This trend is consistent with the presence of strong and weak acids that are deprotonated within this pH range. It is worth noting that the data from the WMC displayed fewer negative values compared to the RMC, with the difference reaching a maximum of 25% at pH 7.

The evidence provided by the CEC and $Z_p$ results shows that despite the slight decrease in the surface charge of the WMC, the groups involved in metal cation retention were more efficient, resulting in a small increase in the CEC value. Furthermore, as evaluated by the BET analysis (Table 2), the BET-specific surface area indicates that the washing treatment induced a significant increase of approximately 242% in the surface area. This increase in the surface area is also evident when comparing the SEM images obtained for the RMC and WMC (Figure 2). The SEM images of the compost surface reveal a heterogeneous structure composed of grains with different shapes and sizes. The images demonstrate the rough structure of the RMC (Figure 2a,c,e), which underwent a dramatic change after washing (Figure 2b,d,f), with the surface exhibiting a finer-looking microstructure.

3.2. Analysis of Surface Structure Distinctiveness in Retention Efficiencies

The effect of the washing treatment on the surface features of compost was evaluated through batch retention assays of Cu(II) and Zn(II). The efficiency of the uptake process (calculated using Equation (1)) for both Cu(II) and Zn(II) was studied by varying the initial concentrations of the metal ions and the compost dose using both the RMC and WMC. In Figure 3, the removal efficiencies of Cu(II) and Zu(II) by compost (at a dose of 10 g/L) are presented for assays with initial concentrations ($C_0$) ranging from 0.5 to 9.0 mg/L.

The removal percentages for both metals consistently exceeded 65%, regardless of whether the RMC or WMC was employed. Notably, an unusual increase in removal efficiency with increasing metal concentration was observed for the adsorption of both metals on the RMC. This phenomenon can be attributed to competing reactions. The availability of metal ions for interactions and retention by the adsorbent may be reduced due to metal–ligand complexation with the dissolved humic substances present in the solution in contact with the RMC. Since this effect was expected to be more pronounced at lower metal concentrations, a decrease in removal efficiency is likely to occur as metal concentrations decrease.

Figure 4 illustrates the effect of the compost dose on the removal efficiencies of Cu(II) and Zu(II) using a fixed $C_0$ of 6.0 mg/L and compost doses ranging from 2.5 to 20 g/L. The effect of the compost dose shows a similar trend to that observed for the initial metal concentration, with higher removal efficiencies achieved at higher compost doses. Significantly higher removal efficiencies were obtained for both metal ions when using the WMC compared to the RMC (Figure 3 and Figure 4). This effect was particularly noticeable at lower concentrations of metal ions (0.50 mg/L) and compost doses (2.5 g/L), especially for Cu(II).

The retention capacity, $q_e$ (calculated using Equation (2)), for Cu(II) showed an increase of 38% and 34% with the WMC using a low $C_0$ (0.5 mg/L) and a low compost dose (2.5 g/L), respectively. For Zn(II), increases in the $q_e$ of 23% and 16% were observed with a $C_0$ of 0.5 mg/L and a compost dose of 2.5 g/L, respectively. The enhancement of the removal efficiency observed in the WMC assays can be attributed to the increased amount of functional groups in the compost that are capable of retaining metal cations due to the release of soluble material. For both metals, the removal efficiencies were above 90% for the WMC after 120 min of contact time. The more pronounced impact of the compost dose on the removal efficiencies observed with the RMC, as indicated by the noticeable variation in retention efficiencies when reducing the compost dose, can be attributed to its lower number of active sites, evident from the lower specific surface area.

It was observed that the washing treatment of the compost had a significant effect on the metal retention, indicating that significant changes in the surface features of compost occur and influence the retention process. This phenomenon was not found to be documented in previous research. Since the WMC demonstrated higher efficiency in removing metal ions compared to the RMC, subsequent studies were conducted using this adsorbent.

For the WMC, the qe values were 2.18 mg/g for Cu(II) and 2.22 mg/g for Zn(II), achieved with initial concentrations of 6.0 mg/L. Previous studies on metal retention in various composts yielded qe values of 4.7 mg/g using pine bark compost [30], 12 mg/g using municipal garden waste compost [29], and 11.1 mg/g using municipal solid waste compost [44] for Cu(II). Regarding Zn(II), the qe values were 2.6 mg/g using pine bark compost [30], 12 mg/g using municipal garden waste compost [29], and 6.8 mg/g using municipal solid waste compost [44]. Although these values slightly exceed those obtained in the present work, it is important to note the differences in the experimental conditions, particularly the initial metal concentration and compost dose. The authors of [30] utilized three absorbents (pine bark compost, pine bark–goat manure compost, and pine bark–sewage sludge compost) under identical experimental conditions, reporting significantly different qe values of 4.7, 52.1, and 8.2 mg/g for Cu(II) and 2.6, 12.5, and 4.2 mg/g for Zn(II). Notably, the qe values for the pine bark compost align more closely with the results of the current study.

3.3. Identification of Design Conditions for Environmental Protection

To assess the impact of the pH on the retention efficiency of the Cu(II) and Zn(II), batch assays were conducted using a starting concentration, $C_0$, of 9.0 mg/L, a compost dose of 10 g/L and an electrolyte solution pH ranging from 2 to 9.

The results depicted in Figure 5 indicate that the retention efficiency of metal ions was influenced by the pH level. This effect was more visible for Zn(II), for which a significant decrease in removal efficiency was observed at lower pH values (below or equal to 3). The presence of higher concentrations of $H^{+}$ at a low pH impacted the adsorption of metal ions, indicating that these ions competed with metal cations for the available adsorption sites on the compost.

The resilience to leaching and its significance for environmental protection was also investigated through the following experiment. Compost, with varying doses of 2.5 or 10 g/L, was loaded with Cu(II), Zn(II), or a mixture of both metals. Subsequently, the metal-loaded compost was placed in contact with water and stirred at a rate of 200 rpm for 4 h. This experiment revealed that the amount of Cu(II) and Zn(II) released into the water was consistently less than 4% under all the tested conditions. This finding indicates that the compost effectively retained the metal ions and did not leach into the surrounding environment.

These findings are in accordance with those of previous studies [45], where employing a reactive filter media based on kaolin over a 260-day period resulted in a high efficiency of above 90% in retaining these metals. Furthermore, the longevity of the filter media was demonstrated, confirming its effectiveness in retaining Cu(II) and Zn(II) under experimental conditions. Additionally, the study evaluated the environmental risk associated with these metals and found that Zn(II) exhibited the highest mobility, with an environmental availability (estimated by the mass at pH 6 and pH 2) ranging from 12% to 18%. On the other hand, Cu(II) and Pb(II) demonstrated a larger resistance to desorption, with less than 5% observed.

However, it is important to note that the results obtained in our experiments using compost with pH levels of 6.8 and 2 showed higher desorption resistance for Zn(II) (3.4%) and lower desorption resistance for Cu(II) (15.6%) when compared to kaolin [45]. These results highlight the potential of compost as an effective adsorbent for Zn(II) and suggest the need for further investigation into its desorption properties in relation to Cu(II).

3.4. Retention Kinetics

To assess the rate of Cu(II) and Zn(II) retention by the WMC, changes in the metal ion concentration were monitored over time through batch experiments. The kinetic curves of retention, representing the amount of metal ions retained ($q_t$) as a function of contact time (t), were obtained using an initial concentration, $C_0$, of 9.0 mg/L and a compost dose of 10 g/L. These curves are displayed in Figure 6.

To estimate the kinetic parameters of adsorption, non-linear regression was performed using pseudo-first-order (Equation (3)) and pseudo-second-order (Equation (4)) equations. These results are summarized in

Table 3. Pseudo-second-order kinetic fitting model ($q_e$ and $k_2$) and quality fitting parameters (r and error) for Cu(II) and Zn(II) using the WMC.

Parameters	Cu(II)	Zn(II)
$q_e$ (mg/g)	0.832 ± 0.015	0.873 ± 0.019
$k_2$ (g/(mg · min))	0.72 ± 0.13	0.391 ± 0.064
r	0.997	0.996
Error (mg/g)	0.025	0.030

.

However, the results obtained from the pseudo-first-order model revealed high uncertainties for either $q_e$ (the equilibrium adsorption capacity) or $k_1$ (rate constant), along with significant differences between the experimental data and the mathematical model. As a result, the fitted parameters from the pseudo-first-order model were deemed to lack physical meaning.

Conversely, the pseudo-second-order model yielded more reliable results. The correlation coefficients (r) obtained for both metals were larger than 0.996, indicating a good fit between the model and the experimental data. The uncertainties for $q_e$ and $k_2$ (pseudo-second-order rate constant) were relatively low at 2% and 17% (expressed as a relative standard deviation), respectively. The estimated values of $q_e$ (0.832 for Cu(II) and 0.873 for Zn(II)) aligned well with the experimental $q_e$ values obtained for both Cu(II) and Zn(II), which were 0.839 and 0.865 mg/g, respectively. Notably, the pseudo-second-order rate constant for Cu(II) adsorption was almost twice as high as that for Zn(II), indicating that Cu(II) is adsorbed more rapidly than Zn(II).

3.5. Adsorption Isotherms

The adsorption equilibrium data were analyzed by correlating them with the Langmuir (Equation (5)) and Freundlich (Equation (6)) isotherm models. This analysis was conducted under various compost doses ranging from 2.5 g/L to 20 g/L and initial metal concentrations ranging from 0.50 to 9.0 mg/L.

Table 4 summarizes the best-fit parameters, correlation coefficients, errors, and uncertainties associated with the Freundlich isotherm model. The Freundlich model demonstrated the best fit for the entire set of experiments, except for the adsorption of Zn(II) to the WMC, where a higher correlation coefficient, r, was observed for the Langmuir model, despite similar uncertainties obtained in the fitted parameters.

It is worth noting that different studies in the literature on the removal of metals using compost have chosen fitted isotherm models based on specific criteria such as the r value and error. For example, in [46], the isotherm fit with the best correlation coefficient was chosen. In contrast, [44] considered the error given by the residuals to determine the best isotherm fit.

Table A1. Isotherm parameters of the Langmuir model for the adsorption of Cu(II) and Zn(II) from the aqueous solution onto the WMC and RMC.

Compost	Metal	${\mathit{K}}_{\mathit{L}}$ (L/mg)	${\mathit{q}}_{\mathbf{max}}$ (mg/g)	r	Error (mg/g)
WMC	Cu(II)	0.16 ± 0.25	17 ± 24	0.94	0.26
WMC	Zn(II)	1.59 ± 0.24	2.87 ± 0.24	0.991	0.10
RMC	Cu(II)	*	*	0.91	0.23
RMC	Zn(II)	*	*	0.91	0.26

* The values obtained for the fitting of $K_L$ and $q_{max}$ of the Langmuir model are 7.3 $\times {10}^{-5}$ L/mg and 1.7 $\times {10}^5$ mg/L for Zn(II), and 3.9 $\times {10}^{-5}$ L/mg and 1.6 $\times {10}^5$ mg/L for Cu(II).

presents the fitted parameters obtained for the Langmuir model.

In the Freundlich model, the parameters $K_F$ (adsorption capacity) and n (heterogeneity factor) were estimated to describe the adsorption equilibrium data under different compost doses and initial metal concentrations. The assessment of the performance of the Freundlich model, shown in Table 4, allows us to evaluate its ability to fit the experimental data. The r value, which represents the correlation coefficient between the experimental and fitted data, is relatively high (>0.9) for all cases, indicating a good fit of the Freundlich model to the experimental data. The similarities in the r values suggest that the Freundlich model adequately captured the adsorption behavior of both the WMC and RMC, regardless of the specific metal ion. The error values are relatively low for all cases, indicating a good agreement between the experimental data and the fitted model. The low error values suggest that the Freundlich model provided a good approximation of the experimental data for both the WMC and RMC. The similarities in the error values indicate that the model performed consistently for both adsorbents and metal ions, without significant deviations or discrepancies.

Table 4. Parameters of the Freundlich fitted model for the adsorption of Cu(II) and Zn(II) onto the WMC, RMC, and different composts.

	Compost	${\mathit{K}}_{\mathit{F}}$ (mg/g)	n	r	Error (mg/g)	Reference
	WMC	2.39 ± 0.28	1.06 ± 0.15	0.93	0.12	This work
	RMC	0.431 ± 0.037	0.500 ± 0.039	0.994	0.067	This work
	MGW	2.36	0.794	0.997		[29]
Cu(II)	SS	1.4187	2.386	0.985	0.6301	[44]
	PM	0.0538	0.982	0.994	3.2093	[44]
	MSW	1.7	2.04	0.94		[47]
	MG	3.51	2.08	0.95		[48]
	WMC	1.40 ± 0.12	1.99 ± 0.23	0.97	0.19	This work
	RMC	1.579 ± 0.073	0.651 ± 0.052	0.993	0.083	This work
	MGW	2.94	1.96	0.992		[29]
Zn(II)	SS	4.1115	3.145	0.979	2.0516	[44]
	PM	0.025	0.685	0.994	0.672	[44]
	MSW	2.076	2.01	0.967		[49]

DM—dairy manure; MG—mowed grass compost; MGW—municipal garden waste compost; MSW—municipal solid waste compost; PM—poultry manure compost; RMC—raw municipal compost; SS—sludge sewage compost; WMC—washed municipal compost.

Table 4. Parameters of the Freundlich fitted model for the adsorption of Cu(II) and Zn(II) onto the WMC, RMC, and different composts.

	Compost	${\mathit{K}}_{\mathit{F}}$ (mg/g)	n	r	Error (mg/g)	Reference
	WMC	2.39 ± 0.28	1.06 ± 0.15	0.93	0.12	This work
	RMC	0.431 ± 0.037	0.500 ± 0.039	0.994	0.067	This work
	MGW	2.36	0.794	0.997		[29]
Cu(II)	SS	1.4187	2.386	0.985	0.6301	[44]
	PM	0.0538	0.982	0.994	3.2093	[44]
	MSW	1.7	2.04	0.94		[47]
	MG	3.51	2.08	0.95		[48]
	WMC	1.40 ± 0.12	1.99 ± 0.23	0.97	0.19	This work
	RMC	1.579 ± 0.073	0.651 ± 0.052	0.993	0.083	This work
	MGW	2.94	1.96	0.992		[29]
Zn(II)	SS	4.1115	3.145	0.979	2.0516	[44]
	PM	0.025	0.685	0.994	0.672	[44]
	MSW	2.076	2.01	0.967		[49]

DM—dairy manure; MG—mowed grass compost; MGW—municipal garden waste compost; MSW—municipal solid waste compost; PM—poultry manure compost; RMC—raw municipal compost; SS—sludge sewage compost; WMC—washed municipal compost.

The results obtained for the Freundlich model regarding the adsorption of Cu(II) and Zn(II) for the WMC can be compared to those obtained for the RMC in terms of the fitted parameters, $K_F$ (mg/g) and n, and the fitting quality, considering the r value and error (mg/g).

For Cu(II) adsorption, the $K_F$ value was higher in the WMC compared to the RMC, suggesting that the WMC has a higher adsorption capacity. The higher $K_F$ value in the WMC indicates that the WMC has a higher concentration of active sites or functional groups that can bind and retain the metal ions. The different surface characteristics of the WMC may enhance its adsorption capacity. This behavior was not observed for Zn(II) adsorption, as the $K_F$ values were similar for the RMC and WMC. The differences observed can be attributed to variations in the affinity or specificity of the adsorbent toward different metal ions. In terms of the adsorption intensity or surface heterogeneity (represented by $1/n$), it is evident that the adsorption process for both metals in the WMC was favorable, as this value was less than 1. Conversely, in the case of the RMC, the adsorption process was unfavorable, as indicated by a value greater than 1 ($1/n>1$).

Overall, the comparisons suggest that the WMC generally exhibits higher adsorption capacity for Cu(II) and Zn(II) compared to the RMC.

In Table 4, the parameters of the Freundlich model for some studies presented in the literature using composts of diverse origins are provided. The $K_F$ values for Cu(II) retention in these composts range from 0.0538 mg/g for poultry manure compost to 3.51 mg/g for mowed grass compost. In the case of Zn(II), the values range from 0.025 mg/g for poultry manure compost to 4.1115 mg/g for sludge sewage compost. The $K_F$ values obtained in our study for the WMC were 2.39 mg/g for Cu(II) and 1.40 mg/g for Zn(II), which aligns with the range of $K_F$ values presented in Table 4. Regarding the n values (1.06 for Cu(II) and 1.99 for Zn(II)), it is noteworthy that they also fell within the range of values observed in other studies.

4. Conclusions

In this study, the performance of municipal compost in heavy metal retention and environmental protection was evaluated. The adsorbent specificity of the compost was characterized, and the effects of the pH and contact time on heavy metal retention and environmental release were investigated. The washing of the soluble fraction of organic substances present in the municipal compost was performed to simulate leaching in natural systems. The surface properties of the washed municipal compost (WMC) exhibited variations that justified the improvement in the retention of Cu(II) and Zn(II) compared to the raw municipal compost (RMC), including a 10% increase in the cation exchange capacity (CEC) and a 242% increase in the BET-specific surface area, despite the decrease in the surface charge (fewer negative zeta potential values).

Despite the lower efficiency of the WMC ($q_e$ values ranging from 0.8 to 2.9 mg/g depending on the $C_0$/compost dose ratio) compared to the other studied adsorbents, its environmental presence justifies its use for the removal of such contaminants. It is important to note that the values obtained in this study were not derived from laboratory tests using raw compost, but rather served as a proxy for the results expected in long-term exposure environmental protection systems. This practical relevance increases the interest in using compost in systems designed for metal retention.

Future research should focus on further optimizing conditions for heavy metal retention using compost. Investigating the influence of additional factors such as temperature, concentration gradients, and the presence of competing ions would provide a more comprehensive understanding of the compost’s performance. Moreover, assessing long-term stability through column studies and the potential leaching of adsorbed metals from compost under realistic field conditions is necessary to validate its applicability in environmental protection systems.

In conclusion, municipal compost demonstrates promising potential as an environmentally friendly and cost-effective adsorbent for metal retention. Its wide availability, low cost, and high resistance to desorption make it a viable option for addressing metal pollution in various environmental settings. Further research and development in this field can contribute to the advancement of viable solutions for environmental protection and the remediation of heavy metal-contaminated sites.