Evaluation of the Adsorption Potential of Benzo(a)pyrene in Coal Produced from Sewage Treatment Station Sludge

Abstract

This work investigates the adsorption of benzo[a]pyrene (BaP) using a charcoal adsorbent derived from sewage treatment plant sludge. BaP is a polycyclic aromatic hydrocarbon (PAH), carcinogenic to humans, which his used by the World Health Organization as a marker for all PAH mixtures. The charcoal was produced by the pyrolysis (500 °C, 4 h) of municipal sewage sludge. The resulting biochar presented mesoporous and oxygenated functional groups that are beneficial for the adsorption of benzo[a]pyrene. The material contained graphitic structures, suggesting potential sites for π–π interactions. The adsorption followed the Elovich kinetic model. A maximum adsorbed value of 60.8 µg g⁻¹ was achieved for an initial BaP concentration of 100 µg L⁻¹ of BaP at 298 K after 20 min. Parameters related to mass transfer phenomena, such as the intraparticle diffusion coefficient, were determined using the homogeneous solid diffusion model (HSDM). These experimental data demonstrate the great potential for computational fluid dynamics (CFD) applications. The value reached for the intraparticle diffusion coefficient was 1.63 × 10⁻¹³ m²s⁻¹. Adsorption equilibrium experiments showed that the Langmuir model was most suitable for experimental data, suggesting a monolayer molecular adsorption process. The results showed that charcoal can be employed as an effective material for removing BaP.

1. Introduction

Emerging contaminants (EC) are chemical compounds of synthetic or natural origin recently identified due to analytical advances. These compounds pose a potential risk to humans and the environment as they exert toxic effects and are bioaccumulative [1,2]. Polycyclic aromatic hydrocarbons (PAHs) belong to the EC group and consist of organic compounds with two or more fused benzene rings. They are commonly found in the environment due to the incomplete combustion of organic matter at high temperatures and low oxygen levels [3]. PAHs are persistent organic pollutants (POPs), and due to their carcinogenicity and widespread presence in the environment, they have raised significant concern in recent years [4,5].

Current studies have shown that PAHs exist in all environments, including water, the atmosphere, soils, and even microorganisms found in polar regions [6]. Some studies have also highlighted the widespread contamination of PAHs in water and soil [7,8]. Adsorption is a widely studied operation for remediating PAHs’ environmental contamination [9] as it is simple, has a low operational cost, and is easy to scale up [10]. In general, the main operational cost is associated with the adsorbent. Therefore, the adsorbent cost must be low to be viable operation on a large scale, such as in soil treatment and ample water sources. This raw material for coal production must be available in abundance. In this context, the sludge generated in sewage treatment plants is widely available and can be used in the pyrolysis reaction.

Sewage treatment plant sludge (STP) is generated from microbial biomass that settles during raw sewage treatment [11]. This sludge is rich in organic matter and nutrients but may contain metals, persistent organic compounds, and pathogens in concentrations harmful to health and the environment [12]. Due to its high temperatures, the pyrolysis reaction can eliminate microbiological and persistent contaminants [13]. Charcoal production from STP is a promising alternative for reducing solid waste and adding value to a material currently a liability for society [14].

To widely use charcoal produced from sewage treatment sludge in PAH environmental adsorption, it is necessary to determine its properties and elucidate its behavior as an adsorbent. Thus, this work aimed to produce charcoal from the sludge generated in a sewage treatment plant, characterize it, and subsequently test it as an adsorbent. The adsorbate chosen was benzo(a)pyrene. The World Health Organization uses benzo(a)pyrene (BaP) as a marker for all PAH mixtures, regardless of composition [15,16]. BaP is a five-ring PAH ubiquitous in the environment, mainly due to emissions from incomplete combustion of organic matter. It is relatively insoluble in water, has low volatility, and is highly lipophilic and stable, accumulating in the body as exposed [17,18]. These characteristics contribute to its environmental persistence and potential for bioaccumulation in living organisms [19].

Although many studies involving PAH adsorption can be found, the information needed to design large-scale unit operations is still scarce. This work aims to elucidate the adsorption phenomena regarding their kinetic, equilibrium and thermodynamic behavior for the SSC-BaP system. This information is essential for industrial unit design, capable of processing large materials amounts. In addition, results of this nature are necessary so that new mathematical approaches can be used, such as computational fluid dynamics (CFD). This tool allows for a more in-depth evaluation of the heat and mass transfer phenomena in adsorption, enabling more outstanding technological advances in developing materials and equipment.

2. Materials and Methods

2.1. Material

The standard solution with BaP at 2000 µg mL⁻¹ (molecular formula C₂₀H₁₂, molecular weight 252.3 g mol⁻¹) was purchased from Supelco (USA). The optimized three-dimensional structural formula of the BaP (obtained from Molview 2.4 software) is shown in Figure 1. The deuterated PAH (perylene-d12) in a concentration of 4 mg mL⁻¹ was purchased from AccuStandard (USA). A 100 mg L⁻¹ intermediate standard was prepared using toluene as solvent. Working standard solutions were prepared daily by diluting proper amounts of the PAH mixture in hexane. All solutions were stored in amber glass flasks at −18 °C in the dark. Magnesium sulfate (purity 99.8%) and hexane HPLC grade were purchased from J.T Baker (Mallinckrodt, NJ, USA). The sewage treatment sludge samples were obtained from the wastewater treatment plant in the city of Passo Fundo, Rio Grande do Sul, Brazil (28°15′40″ S, 52°24′30″ W).

2.2. Coal Production

Sewage sludge from a municipal waste treatment plant in Passo Fundo, Brazil, was dried and subjected to pyrolysis in a pilot scale reactor with a capacity of 40 kg per batch. Reaction took place in an inert atmosphere and temperature of 500 °C to produce the sewage sludge coal (SSC). This condition was defined from preliminary tests and, at 500 °C, produced SSC in a pilot reactor presenting similar properties to that produced on a bench scale and avoid PAHs formation.

2.3. Coal Characterization

The SSC samples were characterized regarding their surface properties, including total pore volume, average pore size, specific surface area, and pore size distribution. The total pore volume and average pore size were determined based on nitrogen adsorption/desorption isotherms at 77 K, using an automated gas sorption analyzer. The specific surface area was obtained by the Brunauer–Emmett–Teller (BET) method, while the pore size distribution was obtained by the Barrett–Joyner–Halenda (BJH) method (Micromeritics, Gemini VII 2390, Japan). To evaluate the surface characteristics of the SSCs, scanning electron microscopy (SEM) (model JSM, JEOL, Japan) and energy dispersive spectroscopy (EDS) (model JSM-5800, JEOL, Japan) were used to identify the elemental composition. SSC samples were also characterized by Fourier transform infrared spectroscopy (FTIR) (Prestige, 21210045, Japan), which was performed with total attenuated reflectance (ATR) from 4500 to 450 cm⁻¹.

2.4. Kinetic Experiments and Mass Transfer Mechanism

The kinetic experiments for the adsorption of BaP were carried out using a dosage of 1.0 g L⁻¹ of SSC, within an initial total concentration of the BaP of 100 µg L⁻¹. The stirring rate was set to 150 rpm using an orbital shaker, and the temperature was maintained at 25 ± 1 °C. Samples were collected and promptly filtered through filter paper at different times (0, 2, 4, 6, 8, 10, 15, 20, 25, and 30 min). Subsequently, the quantification of BaP was performed following the procedure outlined in Section 2.7. After chromatographic determination, the adsorption capacity at any time (q_t, mg g⁻¹) was calculated using the pseudo-first-order (PFO), pseudo-second-order (PSO), and Elovich models, expressed by Equations (1), (2), and (3), respectively.

$$q_t={(C}_0-C_t){\displaystyle \frac{V}{m}}$$

(1)

$$q_t={\displaystyle \frac{t}{(1/k_2{q}_2^2)+(t/q_2)}}$$

(2)

$$q_t={\displaystyle \frac{1}{a}} \ln (1+ \mathrm{abt})$$

(3)

where q_t is the amount of adsorbate adsorbed at time t (μg g⁻¹), C₀ is the initial concentration of the adsorbate in the liquid phase (μg L⁻¹), C_t is the concentration of the adsorbate in the liquid phase at any time (μg L⁻¹), m is the mass of adsorbent (g), V is the volume of solution (L), k₂ is the rate constant of pseudo-second order model in (g μg⁻¹ min⁻¹), q₂ is the theoretical value for the adsorption capacity (mg g⁻¹), a is the initial adsorption rate (mg g min⁻¹), and b is the desorption constant (mg min⁻¹).

Mass transfer in the adsorption operation occurs at the solid–fluid interface. Therefore, it is correct to state that this phenomenon is affected by both solid and fluid phase diffusion. Gradient concentration effect in liquid phase (fluid phase in this case) can be disregarded due to mechanical mixing. Thus, the adsorbate concentration in the liquid phase can be treated as a function of time only and not as a function of position. Thus, according to Suzuki [20] and Sonetaka et al. [21], external mass transfer can be represented by Equation (4).

$${\displaystyle \frac{d{q}_t}{dt}}={\displaystyle \frac{k_{f}A}{m}}\left(C_t-C_{st}\right)$$

(4)

where C_st (µg L⁻¹) represents the adsorbate concentration on the solid surface, A (m²) is the adorbent surface area, and k_f (m s−¹) is the external mass transfer coefficient. Substituting Equation (1) into Equation (4), we obtain the following.

$${\displaystyle \frac{d{C}_t}{dt}}={\displaystyle \frac{k_{f}A}{V}}\left(C_t-C_{st}\right)$$

(5)

Integrating Equation (5) and considering that when t→0, C_st→0 and C_t→C₀, we obtain [22] the following.

$$ln\left({\displaystyle \frac{C_t}{C_0}}\right)=-{\displaystyle \frac{k_{f}A}{V}}t$$

(6)

Intraparticle diffusivity is a more complex phenomenon and takes into account different factors, making the development of models for these systems a very challenging task. Therefore, the most used model for this purpose is known as homogeneous solid diffusion model (HSDM). In this model, the adsorbent is considered a spherical, amorphous and homogeneous particle and the mass transfer is considered unidirectional and isothermal [20,21,23]. HSDM model is shown in Equation (7).

$${\displaystyle \frac{\partial q}{\partial t}}=\left({\displaystyle \frac{1}{r^2}}\right){\displaystyle \frac{\partial }{\partial r}}\left(r^2{D}_i{\displaystyle \frac{\partial q}{\partial r}}\right)$$

(7)

where D_i (m² s⁻¹) is the intraparticle diffusion, and r (m) is the radial coordinate. If D_i is considered constant [21,24], the following applies.

$${\displaystyle \frac{\partial q}{\partial t}}=D_i\left({\displaystyle \frac{{\partial }^{2}q}{\partial r^2}}+{\displaystyle \frac{2}{r}}{\displaystyle \frac{\partial q}{\partial r}}\right)$$

(8)

Taking $q\left(r,0\right)=0$ as the initial condition and $q\left(R_p,t\right)=q_e$ and ${\left(\partial q/\partial r\right)}_{r=0}=0$ as the boundary conditions.

Under the conditions posed, and for a Fourier number greater than 0.2, Crank (1975) [25] solved the model. This solution can be reduced to the first term of the series, obtaining Equation (9) [20].

$${\displaystyle \frac{q}{q_e}}=1-\left[{\displaystyle \frac{6\alpha \left(\alpha +1\right)exp\left(-q_n^2{D}_{i}t/R_p^2\right)}{9+9\alpha +q_n^2{\alpha }^2}}\right]$$

(9)

where q_n values are the non-zero roots of Equation (10) as follows.

$$\tan q_n={\displaystyle \frac{3q_n}{3+\alpha q_n^2}}$$

(10)

2.5. Equilibrium Experiments

The adsorption equilibrium experiment was carried out in a thermostated stirrer (FANEM, 315, SE, Brazil). Flasks containing 100 mL of ultrapure water spiked with 100 μg L⁻¹ of BaP were prepared, and SSC was added at different dosages of 0.1, 0.5, 1, 2, 3, 4, and 5 g L⁻¹. The solutions were stirred at 150 rpm for a period of 24 h at 25, 35, 45, and 55 °C to construct the isotherms. Afterwards, the solutions were filtered through filter paper, the PAHs were extracted by salting-out-induced liquid–liquid microextraction (SILLME) and quantified by GC-MS/MS, as described in detail in Section 2.7.

The adsorption capacity at equilibrium (q_e) was determined using Equation (11).

$$q_e=\left({\displaystyle \frac{C_0-C_e}{m}}\right)V$$

(11)

where C_e is the equilibrium concentration (μg L⁻¹). The Langmuir and Freundlich isotherm models were used to establish the correlation of the equilibrium curves, according to Equations (12), and (13), respectively.

$$q_e={\displaystyle \frac{q_m{k}_L{C}_e}{1+k_L{C}_e}}$$

(12)

$$q_e=k_F{C}_e^{1/n}$$

(13)

where q_m is the saturated adsorption capacity (µg g⁻¹), k_L is related to the affinity of the adsorbate for the adsorbent (L mg⁻¹), k_F is the Freundlich constant ((µg g⁻¹)(µg L⁻¹)^−1/n), and 1/n is the heterogeneity factor.

2.6. Adsorption Thermodynamics

The thermodynamic parameters, namely, Gibbs free energy (ΔG, kJ mol⁻¹), enthalpy of adsorption (ΔH, kJ mol⁻¹), and entropy of adsorption (ΔS, kJ mol⁻¹ K⁻¹) were evaluated. These values indicate the spontaneity of the reaction and the way in which the thermal energy exchange occurs and inform about the energetic heterogeneity of the adsorbent surface. Gibbs free energy can be calculated by Equation (14), where K_D is the thermodynamic equilibrium constant (L mol⁻¹), T is the temperature (K), and R is the universal gas constant (8.314 J mol⁻¹ K⁻¹). The K_D values were estimated from the parameters of the best-fit isotherm model [26].

$$∆G=-RT\ln K_D$$

(14)

The thermodynamic parameters ΔH and ΔS were determined by the Van’t Hoff equation (Equation (15)).

$$\ln K_D={\displaystyle \frac{-∆H}{RT}}+{\displaystyle \frac{∆S}{R}}$$

(15)

2.7. BaP Determination

BaP was extracted from SSC samples using the SILLME technique, adapted from Oliveira Arias et al. [27]. For this, 5 mL of the sample and 1 mL of hexane were vortexed for 1 min. Then, 2 g of MgSO₄ were added to the mixture, which was agitated again, followed by centrifugation for 5 min at 7793 rpm. Finally, 700 µL of the upper hexane layer was transferred to a GC vial, 35 μL of deuterated internal standard mix was added, and the extract was ready to be injected into the chromatographic system. All analyses were performed in triplicate.

BaP determination was carried out using a gas chromatograph tandem mass spectrometry (model TQ 8050, Shimadzu) equipped with a Combipal AOC 6000 autosampler and a triple quadrupole mass spectrometer detector. A capillary column Rtx^®-5MS (30 m × 0.25 mm × 0.25 μm) was used (Restek, Bellefonte, PA, USA). Helium (99.999% purity) was used as a carrier gas at constant flow rate of 1.35 mL min⁻¹. The electron impact (EI) ionization mode was used with a collision energy of 70 eV. The injection volume was 2 μL, the injector temperature was 280 °C, and the in the spitless mode was 150 kPa. The initial oven temperature was 60 °C and held for 1 min. It was then increased to 310 °C at 5 °C min⁻¹ and was kept at this temperature for 10 min, resulting in a total analysis time of 61 min. The interface temperature was set at 290 °C, and the ion source temperature was 250 °C.

Compounds were monitored using the selective ion monitoring (SIM) mode. Data acquisition and treatment were performed by the software GCMS solution (version 4.45 SP1, Shimadzu, Japan). The retention times of the monitored ions were compared to those available in a previous study [28].

2.8. Data Analysis

The kinetic and equilibrium parameters were estimated by nonlinear regression using the software Statistica 7.0 (Statsoft, USA). The objective function was quasi–Newton, and the fit quality was evaluated by the coefficient of determination (R²) and the average relative error (ARE). ARE calculation was performed according to Equation (16), where q_t,exp and q_t,pre are the experimental and theoretical adsorption capacity values.

$$ARE={\displaystyle \frac{100}{n}}\sum \left|{\displaystyle \frac{q_{t,exp}-q_{t,pre}}{q_{t,exp}}}\right|$$

(16)

3. Results

3.1. Coal Characterization

The charcoal samples were characterized for their total pore volume, average pore size, specific surface area, and pore size distribution. The average pore diameter was 113.21 Å, indicating that the material is mesoporous, type III, according to the IUPAC classification [27]. This result suggests that the SSC produced in this work is adequate for BaP adsorption due to the presence of mesopores. The obtained values for the total pore volume and for the specific surface area were 0.021 cm³ g⁻¹ and 17.68 m² g⁻¹, respectively. Similar findings were reported by Zielińska et al. [28], who produced charcoal from sewage sludge for pyrene adsorption. The researchers showed that pyrene, a molecule similar in size to BaP, filled the mesopores, and found a similar value for the specific surface area (18.13 m² g⁻¹). Most studies that use charcoal produced from biomass obtain a higher surface area [29,30]. However, these results are a consequence of the chemical activation of the material, which is commonly applied to increase the surface area. Figure 2 presents the adsorption and desorption isotherms for sewage sludge coal. These isotherms are type IVa with hysteresis loop type H3, indicating that the material is mesoporous and corroborating previous findings [31].

Figure 3 shows the SEM images of SSC at 400× (Figure 3A) and 1000× (Figure 3B). The surface morphology appears heterogenous with pores of varying sizes. It is possible to identify some well-defined pores and others with fibrous and rough structures, as well as the presence of ash, tar and other non-volatile compounds. It is important to mention that cylindrical structures with longitudinal pores are a favorable characteristic for the adsorption of BaP in the coal. These structures are a consequence of the precursor material decomposition as no chemical treatment was performed to activate the charcoal in the present study [32].

Moreover, the images presented in Figure 3 demonstrate that the surface has low porosity. Similar images were presented by Shah et al. [33], which also characterized a biochar obtained from sewage sludge. This heterogeneity of the sample surface is clearly observed in Figure 4, in which some points were selected for qualitative elemental analysis through EDS. It was possible to observe significant variations in the proportion (%, w/w) of some elements at different surface points. At all points, C, O, Fe, Si, Ca, Mg, Al, P, K, and Ti were found. At point 1, which corresponds to the largest area, 33.2% of O, 25.2% of C, 13.2% of Fe, 7.2% of Si, 5.9% of Ca, 5.4% of N, and 4.1% of P were identified, along with minor amounts of Na, Al, K, Mg, and Ti. The mass fraction of C and O was lower at points 2, 3, and 4. For Fe and P, points 2 and 3 presented higher concentrations, reaching 38% of Fe. Si was identified in smaller amounts in points 2 and 3 and in a greater amount at point 4. N was not identified at points 2, 3, and 4. This result also highlights the absence of heavy metals on the biochar surface. This type of contaminant is a source of great concern when charcoal is produced from sewage sludge treatment since they are not eliminated by thermal pyrolysis treatment, as occurs through microbiological contamination.

The large amount of carbon may indicate that the biochar structure is aromatic and may result in π–π interactions with aromatic groups in organic pollutants [34]. Regarding oxygen, a large amount of this element is possibly presented in the material in the form of oxides combined with other elements detected in the spectrum, such as Si, Al, Mg, Ca, and Fe. These oxides are important in the adsorption process of organic substances in aqueous solutions as they facilitate interaction with the adsorbent. Silicon corresponds to approximately 6% of the material mass. The presence of this element was expected since sludge contains large amounts of clay, silt, and sand. Calcium was also detected, and its presence is possibly due to the addition of lime, in the form of a Ca(OH)₂ suspension during the sludge treatment. The presence of Fe and Al may be due to the use of iron-based and aluminum sulfate anticoagulants in sewage treatment. Moreover, small amounts of other elements were also detected, possibly because they remain attached to the carbon structure in the precursor material, located on the surface of the ring blades [32].

3.2. Kinetics Experiments and Mass Transfer Mechanism

Initially, before carrying out the adsorption experiments, tests were carried out to verify whether any compound would be released by the SSC, and no release of any compound by the adsorbent was detected.

Figure 5 presents the amount of BaP adsorbed over time (0 to 30 min). The kinetic analysis was carried out using BaP (100 μg L⁻¹) and SSC (1 mg L⁻¹) at 298 K and a stirring rate of 150 rpm. It is possible to observe that the maximum adsorption was 60.81 μg L⁻¹, achieved after 20 min of the process. To explain the adsorption kinetics, the experimental data were fitted to PFO, PSO, and the Elovich models. The outcomes of this analysis are presented in

Table 1. Parameters of adsorption kinetic for benzo[a]pyrene.

Elovich	a (g µg−1)	b (µg g−1 min−1)	R2	ARE (%)
	0.16	1478	0.90	8.43
Pseudo-First Order	q1 (µg g−1)	k1 (min−1)	R2	ARE (%)
	47.11	1.85	0.77	13.20
Pseudo-Second Order	q2 (µg g−1)	k2 (g µg−1 min−1)	R2	ARE (%)
	51.40	0.04	0.83	12.44

, and the kinetic curves are presented in Figure 5. The results revealed that the Elovich model was the most suitable for representing the experimental kinetic data, presenting higher R² value (≥0.9) and lower ARE (<10%). The Elovich model characterizes the chemisorption process on heterogeneous surfaces [35]. According to this model, the rate of adsorption depends on the amount of solute adsorbed on the adsorbent’s surface and the amount adsorbed at equilibrium. It also indicates that the rate decreases over time due to increased surface coverage as chemisorption is an irreversible process [36].

Chemical interactions also govern the adsorption process in this study through the sharing or exchange of electrons between the adsorbate and the adsorbent [37]. As observed in the sample characterization analyses, the presence of functional groups allows for greater adsorption of the molecules on the adsorbent. The most likely adsorption mechanisms occurred through π–π interaction, pore filling, hydrophobic interactions, and hydrogen bonds between PAHs and biochar [38].

Using kinetic information was possible to determine external and intraparticle mass transfer parameters, as shown in

Table 2. Mass transfer parameters for BaP in biochar.

${\mathit{k}}_{\mathit{f}}$ (m s−1)		${\mathit{D}}_{\mathit{i}}$ (m2 s−1)
Value $\times {10}^4$	2.15	Value $\times {10}^{13}$	1.31
R2	0.93	R2	0.92
ARE (%)	1.73	ARE (%)	5.94

. To determine kf, the first points of the kinetic curve were used, which present the linear behavior represented by Equation (6). Results show good agreement with experimental data (>0.9) and a relatively small error (ARE < 2%). To determine the intraparticle diffusion coefficient (Di), the first points of the kinetic curve were excluded. This was undertaken because the model used considers that the concentration on the particle adsorbent surface in R_p is saturated. This consideration is quite far from reality when $t\to 0$. Under this consideration, the model for intraparticle mass transfer also showed good correlation with the experimental results, and ARE indicates good data prediction.

Although these models can be used for many applications, they have the limitation of not being extrapolated to other operational conditions such as prediction at other temperatures or other mechanical mixing conditions. These parameters will only present good results if the process conditions are approximately the same as the experimental ones. Thus, CFD (computational fluid dynamics) tools can present more promising ways of modeling adsorption operations, allowing us to understand the phenomena involved in this operation more deeply and to develop more comprehensive models.

3.3. Isotherms and Thermodynamics

Figure 6 shows the experimental data of BaP adsorption onto SSC adjusted by equilibrium models. The results show that higher temperatures lead to increased adsorption capacities, with maximum values ranging from 58 to 114.52 µg L⁻¹. To determine the most suitable correlation for the equilibrium curves and estimate the isotherm parameters, two mathematic models, Langmuir and Freundlich, were applied to the experimental data.

Table 3. Isotherm parameters for benzo[a]pyrene adsorption onto sewage sludge coal.

	Temperature (°C)
	25 °C	35 °C	45 °C	55 °C
Langmuir
qm (μg g−1)	70.840	77.030	110.430	124.311
kL	0.023	0.022	0.012	0.019
R2	0.9128	0.9452	0.9564	0.8755
ARE (%)	23.9	25.82	21.82	39.8
Freundlich
kF	7.786	7.401	5.295	10.429
N	2.745	2.570	2.009	2.509
R2	0.8176	0.8716	0.8976	0.7799
ARE (%)	36.79	34.57	35.23	53.89

provides the isotherm parameters obtained for all the temperatures studied.

The results in Table 3 show that the Langmuir model presented higher R² and lower ARE values, indicating that this model provided the best fit to the experimental equilibrium data in all of the conditions studied. Other authors also found that the Langmuir model was the most suitable one for the adsorption of Cr (VI) using biochar from sewage sludge [39]. As to the maximum adsorption capacity (q_m), it increased with temperature, reaching a maximum value of 124.3 μg g⁻¹ at 55 °C. These findings suggested that BaP adsorption was a monolayer molecular adsorption process and that chemisorption was involved. The chemisorption process may be related to the abundant functional groups on the SSC samples. These results were corroborated by the FTIR analysis, which suggested the presence of π–π EDA interactions, indicating adsorption mechanism. The aromatic structure of BaP could serve as an electron donor for π–π EDA interactions with the electron-deficient aromatic structures on the surface of SSC [40].

The thermodynamic adsorption characteristics of BaP by SSC were assessed by calculating the enthalpy, entropy, and Gibbs free energy changes, and the results are presented in

Table 4. Thermodynamic parameters for the benzo[a]pyrene adsorption.

T (°C)	KD	ΔG (kJmol−1)	ΔS (J·mol−1K−1)	ΔH (kJmol−1)
25	598.23	−15.84	151.98	30.04
35	533.83	−16.80
45	831.25	−17.77
55	1803.60	−20.44

. The enthalpy change in the process was calculated by Arrhenius equation using the K_D values derived from the Langmuir parameters with the adjusted data presented in Figure 7. The negative ΔG values indicated that the BaP adsorption by SSC was a spontaneous and favorable process. The values ranging from −15.84 to −20.44 indicated that the spontaneity increased with the increase in temperature. The positive ΔH value show that the adsorption process was endothermic, and the positive ΔS value indicated that the disorder in the solid–liquid interface increased during the adsorption process.

After achieving results for kinetic and equilibrium experiments, it is possible to verify that the SSC has a moderate adsorption capacity compared to high-performance adsorbents. This can be attributed to the low initial concentration of the adsorbate since this research tried to use concentrations similar to the real effluent. Moreover, it is essential to emphasize that the sludge used as a raw material for charcoal production is available in great abundance, and its natural state represents a problem for society due to the possibility of microbiological contamination. Thus, transforming this material into biochar can represent a solution for communities and environmental remediation processes when large quantities of adsorbent are needed. The matrix effect can affect adsorption operations in real and complex systems, which is generated by competing other compounds for the adsorption sites on the solid surface. However, it is necessary to know the adsorption mechanism to elucidate the adsorption phenomenon. This adsorbent–adsorbate interaction can only be elucidated using a model system.

4. Conclusions

This study focused on exploring the utilization of sewage sludge coal to remove benzo[a]pyrene from aqueous solutions by adsorption. The charcoal was produced by pyrolysis from sewage sludge at 500 °C for 4 h, yielding a material with satisfactory properties. Since sludge is available in large quantities, this highlights its potential for large-scale charcoal production. Furthermore, the pyrolysis heat treatment ensures the elimination of pathogenic biological contaminants. In preliminary texts, the adsorbent did not release any toxic compounds, showing that the sludge obtained from this station can be used. The characterization analysis suggested that interactions between BaP and SSC occurred by pore filling and π–π EDA interactions. Experimental results could be satisfactorily correlated by mathematical models, evidencing a regular behavior of the SSC-BaP system. The Elovich model presented adequate fit with the experimental kinetic data (R² > 0.90 and ARE < 9.00). The Langmuir model was the most adequate to represent the equilibrium adsorption isotherms as it presented higher R² and lower ARE than the Freundlich model. The maximum adsorption capacity was 124.3 µg g⁻¹ obtained at 55 °C. The negative values of ΔG and positive values of ΔH showed that the BaP adsorption by SSC was a spontaneous favorable and endothermic process. The reasonable adjustment of models to experimental data provides an essential tool for process and equipment design. Due to the complexity of adsorption studies, the search for more comprehensive phenomenological models remains a significant challenge. Tools like CFD can solve complex mathematical models developed to correlate this information, proposing a paradigm shift in the modeling of adsorption processes.