Experimental and Aspen Simulation Study of the Co-Pyrolysis of Refuse-Derived Fuel and Oil Shale: Product Yields and Char Characterization

Abstract

This research delves into the co-pyrolysis of refuse-derived fuel (RDF) and oil shale (OS), utilizing a 50% weight ratio for each component. The study employs a fixed-bed reactor, augmented by electrical kiln heating, to conduct the co-pyrolysis process. A significant aspect of this research is the use of Aspen Plus software for process simulation, with the simulated results undergoing validation through experimental data. A commendable correlation was observed between the experimental outcomes and the model predictions, underscoring the reliability of the simulation approach. The investigation reveals distinct product yields from the pyrolysis of 100% RDF and 100% OS. Specifically, the pyrolysis of pure RDF yielded 45.26% gas, 20.67% oil, and 34.07% char by weight. In contrast, the pyrolysis of pure OS resulted in 14.51% gas, 8.32% liquid, and a significant 77.61% char by weight. The co-pyrolysis of RDF and OS in a 50% blend altered the product distribution to 31.98% gas, 12.58% liquid, and 55.09% char by weight. Furthermore, the Aspen Plus simulation model aligned closely with these findings, predicting yields of 31.40% gas, 11.9% oil, and 56.6% char by weight for the RDF-OS blend. This study not only elucidates the co-pyrolysis behavior of RDF and OS but also contributes valuable insights into the potential of these materials to address the pressing issue of plastic waste management and energy resource utilization. The findings underscore the efficacy of RDF and OS co-pyrolysis as a viable strategy for enhancing the value extraction from waste and underutilized energy resources, presenting a promising avenue for environmental and energy sustainability.

1. Introduction

The increasing urgency of the climate crisis and the need to reduce greenhouse gas emissions have intensified efforts to develop renewable energy sources [1,2].

Currently, energy and chemical production largely depend on fossil fuels, contributing significantly to CO₂ emissions and other harmful pollutants, such as volatile organic compounds and nitrogen oxides. It is estimated that approximately 90% of global CO₂ emissions—amounting to around 34 billion tons of greenhouse gases in 2011—originated from fossil fuel combustion [3].

Among thermochemical processes, pyrolysis, which involves the decomposition of organic feedstock in an oxygen-free environment, has emerged as a promising technology for sustainable energy production. Pyrolysis enables the transformation of biomass and waste materials into valuable biofuels, providing a viable pathway for energy recovery and waste reduction [4].

The waste-to-energy (WTE) strategy offers a promising approach for municipal solid waste (MSW) management, facilitating the conversion of waste into fuels and chemicals through biochemical, thermochemical, and mechanical processes. One such approach, biochemical conversion, involves the anaerobic decomposition of MSW to produce methane-rich biogas, making it particularly suitable for biodegradable waste. However, its slow conversion rate limits its broader applicability [5]. Globally, MSW generation is estimated at 2.01 billion tons annually, with projections indicating an increase to 3.4 billion tons by 2050 [6].

Landfilling and incineration remain the most widely used waste disposal methods due to their economic viability and practical feasibility. However, these methods pose serious environmental and public health risks [7].

Additionally, the presence of microplastics in marine ecosystems has been linked to the deaths of aquatic organisms, including whales and turtles, as they often mistake plastic particles for food [8,9]. To mitigate further environmental damage, it is crucial to implement strategies for reducing plastic consumption and improving waste management practices. Furthermore, with the growing scarcity of land available for landfilling, exploring alternative waste management solutions has become an urgent necessity.

Refuse-derived fuel (RDF) is an advanced waste management approach that involves the reduction of waste size and the removal of organic and inert materials. This process results in RDF having a higher heating value, lower ash content, and reduced bulk density compared to untreated waste. Consequently, RDF derived from MSW exhibits a more consistent composition [10] and enhanced characteristics [11], making it particularly suitable for thermochemical conversion processes [12,13].

Oil shale, a sedimentary rock rich in kerogen, is considered a promising alternative to conventional fossil fuels due to its extensive reserves and potential as a crude oil substitute. Research has extensively explored the chemical composition and thermal transformation of kerogen, which undergoes pyrolytic conversion into bitumen at around 350 °C and subsequently into gas, coke, and shale oil at higher temperatures [14]. The organic composition of OS, comprising carbon, hydrogen, sulfur, and oxygen, underpins its pyrolytic potential [15].

The United States possesses an estimated 2118 billion barrels of oil shale resources, with approximately 1 trillion barrels deemed recoverable [16]. Notably, substantial reserves, such as the 1.53 trillion and 1.32 trillion barrels in the Eocene Green River Formation within the Piceance and Uinta Basins, respectively, highlight its resource abundance [17].

The pyrolytic degradation of organic matter is a multifaceted process involving both concurrent and sequential reactions when subjected to heat in an inert environment. Within this process, the thermal breakdown of organic constituents within biomass initiates within the temperature range of 350–550 °C, extending upwards to 700–800 °C in the absence of atmospheric air or oxygen [18].

Co-pyrolysis of OS with hydrogen-rich waste materials enhances shale oil quality and effectively repurposes waste. For instance, polypropylene decomposes more readily, releasing higher quantities of H radicals and H₂ than low-density polyethylene (LDPE), improving co-pyrolysis efficiency [19]. Similarly, co-pyrolysis with biomass, such as wheat straw, increases CO and CO₂ yields in the gaseous phase while reducing oxygenated compounds in liquid products [20]. These findings demonstrate the potential of co-pyrolysis as an environmentally friendly method for producing valuable chemicals and fuels [21]. This was also supported by another study that found the catalytic nature of OS stems from the existence of oxides, specifically SiO₂ and Al₂O₃, along with the inclusion of metals such as copper, chromium, and zinc [22].

Despite the growing interest in pyrolysis and co-pyrolysis processes, the specific combination of refuse-derived fuel (RDF) and oil shale (OS) remains largely unexplored in the existing literature. Most studies have focused on the co-pyrolysis of OS with biomass or individual plastics, leaving a significant research gap in understanding the synergistic effects of RDF and OS. RDF, derived from a mix of high-energy-content waste materials, introduces a unique hydrogen-rich feedstock to the process, potentially enhancing product yields and quality [14]. Investigating the co-pyrolysis behavior of these two materials could reveal valuable insights into optimizing waste management practices while leveraging underutilized energy resources. This novelty, coupled with the increasing global emphasis on circular economic strategies, underscores the importance and timeliness of this research.

This study employed a fixed-bed reactor to perform the co-pyrolysis of RDF and OS, complemented by Aspen simulation utilizing model-free kinetic parameters derived from thermogravimetric analysis (TGA). The primary objective was to investigate the interactions between RDF and OS during the pyrolysis process. The research addresses environmental concerns associated with plastic waste while demonstrating the potential of OS as a complementary feedstock in co-pyrolysis. This integration not only mitigates plastic pollution but also improves the economic feasibility of OS utilization. The approach is proposed as a sustainable strategy for environmental conservation and the optimization of energy resources. Furthermore, the study highlights product yields based on both experimental findings and Aspen simulation results.

2. Material and Methods

2.1. RDF and OS Materials

RDF was sourced from Medina, OH, USA, and prepared in the Idaho National Laboratory (INL). The OS feedstock was obtained from the Uinta Basin in UT, USA. Both RDF and OS underwent grinding and sieving processes, reducing them to particle sizes ranging between 0.125 mm and 0.600 mm, as illustrated in Figure 1. Subsequently, equal masses (50%) of both materials were combined and thoroughly mixed. The RDF and OS samples underwent comprehensive characterization in accordance with ASTM standards ASTM D5142-02a [23] utilizing thermogravimetric analysis (TGA) employing the NETZSCH-manufactured STA 449F5 equipment from Selb, Bayern, Germany. Moisture content assessment followed ASTM D-2216-19 protocols [24]: 50 g of each sample underwent a 24 h drying process at 105 °C within the Material Research Center (MRC lab) at Missouri University of Science and Technology, utilizing the Fisher ISOTEM vacuum oven model 281 manufactured by Fisher Scientific, Pittsburgh, PA, USA. Elemental analysis, including carbon, hydrogen, nitrogen (CHN), and sulfur content, and calculation of oxygen content by difference, was conducted at LECO Corporation in Saint Joseph, MI, USA. The higher heating value (HHV) of RDF and OS was determined using Equation (1) [25]. All analyses were performed in triplicate to ensure precision and repeatability.

Table 1. Physicochemical properties of RDF and OS.

Analyses	RDF	OS
Proximate Analysis (wt.%)
Moisture	6.47	0.70
Volatile	66.03	31.30
Fixed carbon	13.98	0.90
Ash	13.52	67.10
Ultimate Analysis (wt.%)
Carbon	45.7	18.40
Hydrogen	6.10	1.70
Nitrogen	0.52	0.44
Sulphur	0.19	0.54
Oxygen *	33.97	11.82
Calorific value (MJ/kg)	20.16	6.34

* Calculated by difference.

presents the essential physicochemical properties of the RDF and OS.

$$\mathrm{HHV}(\mathrm{MJ}/\mathrm{kg})={\displaystyle \frac{354.68\mathrm{C}+1376.29\mathrm{H}-15.92\mathrm{Ash}-124.69(\mathrm{O}+\mathrm{N})+71.26}{1000}}$$

(1)

2.2. TG and XRD Analysis

The TGA was carried out at the Material Research Center (MRC) in Missouri S&T using the NETZSCH STA 449F5 Thermogravimetric Analyzer. Prior to analysis, the samples underwent shredding and sieving to ensure a particle size below 600 µm. The experiments involved three distinct heating rates (5, 10, and 20 °C/min) under atmospheric pressure, utilizing nitrogen as an inert gas with a flow rate set at 250 mL/min. The initial phase comprised heating the samples from room temperature to 150 °C in a nitrogen atmosphere, maintaining the temperature at 150 °C for 15 min to facilitate dehydration. Subsequently, the temperature was elevated from 150 °C to 900 °C under N₂ atmosphere, with an additional isothermal treatment at 900 °C for 15 min to ensure thorough consumption of volatiles. Oxygen gas was introduced thereafter to combust the fixed carbon at 900 °C for 30 min, with the remaining residue identified as ash. Additionally, two vital complementary analyses were conducted. The first, known as derivative thermogravimetry DTG, depicts the derivative change in the sample’s weight concerning temperature. DTG aids in identifying the temperature range associated with a material’s thermal decomposition. The second analysis linked to TGA is differential scanning calorimetry DSC, a technique measuring the heat absorbed or released during the sample’s heating or cooling process. This enables the understanding of the reaction nature occurring during the pyrolysis process.

For the char analysis, a fine powder sample was placed in a sample holder for X-ray diffraction XRD analysis. The analysis was conducted using a PANalytical X’Pert Multipurpose Diffractometer manufactured by Malvern Panalytical, Great Malvern, UK. It is equipped with a copper (Cu) source and a PIXcel detector. The sample range was 5–90 degrees at a scan rate of 3 degrees per minute.

2.3. Pyrolysis Setup and Conditions

The pyrolytic degradation of RDF and OS was carried out in a fixed-bed reactor with a volumetric capacity of 103 cm³. The reactor was heated using a SKUTT electrical kiln, Model KS-818-3, manufactured by Skutt Ceramic Products, Inc., Portland, OR, USA, as shown in Figure 2 and Figure 3. Temperature regulation within the furnace was achieved via a temperature controller made by Watlow company in St. Louis, MO, USA, which, in conjunction with multiple-embedded temperature sensors, ensured precise thermal control throughout the experimental process. To maintain an oxidative-inert environment, nitrogen gas was supplied with a flow rate of 150 mL/min from a dedicated cylinder, thereby minimizing the potential for combustion or oxidation reactions. The concentration of oxygen within the system was continuously monitored by employing an oxygen sensor made by BOSCH in Gerlingen, Germany, ensuring the maintenance of an inert atmosphere during the pyrolysis process. Additionally, a water chiller was integrated into the system to provide cooling water at a temperature of 5 °C. This component played a critical role in the condensation of vapors generated during the pyrolysis process, facilitating the subsequent collection of liquid pyrolytic products. The operational temperature for the pyrolysis was meticulously set at 650 °C. Upon achieving this target temperature within the reactor, it was maintained for a duration of 30 min to ensure comprehensive pyrolysis of the RDF and OS feedstock.

Following the completion of the pyrolysis process, the resultant products, categorized as char and oil, were collected and their masses quantified. The yield of gaseous products was deduced through a differential calculation, relying on the mass balance principle [26,27,28].

Y_Oil = M_Oil/Mt × 100%

(2)

Y_Char = M_Char/Mt × 100%

(3)

Y_Gas = 100 − (Y_Oil + Y_Char)

(4)

In the context of this study, Y_Oil, Y_Char, and Y_Gas denote the yields of oil, char, and gas products, respectively, expressed as a percentage of the initial feedstock mass. The variables M_t, M_oil, and M_char correspond to the initial mass of the feedstock, the mass of the oil product, and the mass of the char product, respectively. These parameters are fundamental in quantifying the efficiency and effectiveness of the pyrolysis process in converting the initial feedstock into the desired pyrolytic products. The yield of each product category is calculated as the ratio of its respective mass to the initial feedstock mass (Mt), multiplied by 100 to convert the value to a percentage. This approach facilitates a precise assessment of the pyrolytic conversion process, providing insights into the distribution of product yields under the experimental conditions employed.

2.4. Kinetic Analysis

The mathematical modeling of a pyrolysis process relies on the kinetic triplet, comprising energy activation Ea, the frequency factor A, and the reaction mechanism (f(α)). For non-isothermal pyrolysis, the degradation process is described by Equation (2) [29]:

$${\displaystyle \frac{d\alpha }{dt}}=\mathrm{k}(\mathrm{T})\text{·}\mathrm{f}(\alpha )$$

(5)

In the equation above, α represents the conversion, t is time, f(α) is the function linked to the reaction mechanism, and k(T) denotes the temperature-dependent reaction constant. The conversion during pyrolysis can be expressed as:

$$\alpha ={\displaystyle \frac{m_0-m_t}{m_0-m_{\mathrm{\infty }}}}$$

(6)

where m is the sample mass, and m₀, m_t, and m_∞ refers to the initial, current, and final masses, respectively.

If the rate constant depends on temperature and follows the Arrhenius equation, Equation (2) is modified as follows:

$$\mathrm{k}(\mathrm{T})=\mathrm{A}\exp ({\displaystyle \frac{-E_a}{RT}})$$

(7)

where R is the universal gas constant (8.314 J/K⋅mol).

When the conversion is expressed as a function of temperature and the heating rate (β), and both sides are integrated, Equation (4) transforms into [30]:

$${\displaystyle \frac{d\alpha }{dT}}={\displaystyle \frac{\mathrm{A}}{\beta }}\exp ({\displaystyle \frac{-E_a}{RT}})·\mathrm{f}(\alpha )$$

(8)

$$\mathrm{g}(\alpha )={\int }_0^{\alpha }{\displaystyle \frac{d\alpha }{\mathrm{f}(\alpha )}}={\displaystyle \frac{\mathrm{A}}{\beta }}{\int }_0^T\mathrm{e}\mathrm{x}\mathrm{p}\left({\displaystyle \frac{-E_a}{RT}}\right)\mathrm{d}\mathrm{T}={\displaystyle \frac{\mathrm{A}{E}_a}{\beta R}}P(x)$$

(9)

Here, g(α) represents the integral function of conversion (α), and P(x) is calculated using various approximation methods. In this study, model-free methods were applied, including the Kissinger–Akahira–Sunose (KAS) [31], Flynn–Wall–Ozawa (FWO) [32], and Starink [33] approaches, represented by Equations (10), (11), and (12), respectively. The kinetic analysis was carried out at three heating rates: 5, 10, and 20 °C/min. The corresponding equations are as follows:

$$\mathit{ln}\left({\displaystyle \frac{\beta }{T^2}}\right)=\mathit{ln}\left[{\displaystyle \frac{AR}{E_{a}g(\alpha )}}\right]-{\displaystyle \frac{E_a}{RT}}$$

(10)

$$\mathit{ln}\beta =\mathit{ln}\left[{\displaystyle \frac{A{E}_a}{Rg(\alpha )}}\right]-5.331-1.052{\displaystyle \frac{E_a}{RT}}$$

(11)

$$\mathit{ln}\left({\displaystyle \frac{\beta }{T^{1.92}}}\right)=\mathit{ln}\left[{\displaystyle \frac{A{R}^{0.92}}{{E_a}^{0.92}g(\alpha )}}\right]-0.312-1.0008{\displaystyle \frac{E_a}{RT}}$$

(12)

2.5. Aspen Plus Simulation

By combining all material and energy balances, reaction kinetics, and physical property data into one software, Aspen Plus is a powerful tool for the modeling and simulation of chemical processes [34]. Additionally, of other process simulation software, Aspen Plus is unique for its wide range of functionality for user-defined blocks as well as extensive analysis and optimization. Therefore, developing an Aspen Plus V10.0 [35] simulation for RDF and OS co-pyrolysis will be helpful in further economic and environmental analysis of the process.

Process modeling for the pyrolysis of blended feedstocks involves many unique challenges. For instance, it is difficult to model the complex feedstock as well as the numerous reactants, intermediates, and products involved in the RDF-OS pyrolysis reactions. This difficulty is made worse due to the variable composition of RDF feedstock [32] and the complex structure of OS [36]. Also, determining the various reaction rates of these complex processes through reaction kinetic models can be especially challenging. Interactions between the various species within different feedstocks and the presence of inherent inorganic components can cause significant changes in the reaction rate and present challenges in predicting the reaction kinetics [37]. To overcome these difficulties, many modeling approaches have been used, such as empirical process models [38] and lumped kinetic models [39,40]. It has been noted that implementing a model that is entirely based on chemical equilibrium can lead to inaccuracy [41]. For this work, by implementing model-free kinetics parameters with empirical and chemical equilibrium sub-models, an ASPEN Plus simulation for RDF-OS pyrolysis was developed.

The RDF and OS feedstocks were specified in Aspen Plus as non-conventional components with a particle size distribution (NCPSD). To do this, experimental values for the proximate and ultimate analysis (PROXANAL and ULTANAL) of each feedstock were input into Aspen Plus V10.0. A typical sulfur analysis (SULFANAL) for RDF and OS had to be assumed. To estimate the enthalpy and density of the feedstocks, the HCOALGEN and DGOALIGT methods were implemented, as has been suggested for similar components [42]. The stream class used was MIXNCPSD because both non-conventional and conventional components were included in the process model. The Peng–Robinson with Boston–Mathias equation of state was chosen as the property method in Aspen Plus as it has been cited as accurately describing hydrocarbon products at high temperatures [18]. Descriptions of each block of this simulation are shown in

Table 2. Aspen Plus block descriptions.

Aspen Plus ID	Block ID	Description
RYield	DRYER	The moisture content in the non-conventional feedstock is converted to conventional water.
Flash2	DRYER2	A heating utility is used to heat the feedstock and evaporate all of the water.
RYield	KINETIC	A flowsheet calculator in Excel is used to calculate the yield of char and a variety of conventional volatile components based on the feed temperature and heating rate.
Sep	SEP	The bio-oil and biogas conventional components are separated to individually find the relative equilibrium component concentrations.
RGibbs	GIBBS1	The concentrations of the bio-oil components are found at equilibrium for the maximum pyrolysis temperature.
RGibbs	GIBBS2	The concentrations of the biogas components are found at equilibrium for the maximum pyrolysis temperature.
Mixer	MIX	The biogas, bio-oil, and char are combined into one stream.
Cylone	CYCLONE	The biogas and bio-oil are separated from the char.
Heater	E1	A utility is used to cool the volatile products.
Heater	E2	A utility is used to cool the volatile products.
Flash2	FLASH	The biogas and bio-oil are separated in a vapor–liquid flash.

, and the complete flowsheet is depicted in Figure 4.

As accomplished in [40,42], the heat duty required to dry the RDF-OS blend was calculated using an RYield block (DRYER) and a Flash2 block (DRYER2). Then, an RYield block (KINETIC) was configured with a flowsheet calculator linked to Microsoft Excel [43] in order to model the amount of remaining unreacted dry RDF-OS blend based on the heating rate and temperature. The activation energy (Ea) and pre-exponential factor (A) obtained from the KAS, FWO, and Starink methods, as presented in

Table 3. The kinetic parameters results using KAS, FWO, and Starink methods for RDF, OS, and RDF-OS (1:1) using heating rates of 5, 10, and 20 °C/min, following the method KAS.

	KAS			FWO		Starink
	α	Ao	Ea	Ao	Ea	Ao	Ea
		min−1	kJ·mol−1	min−1	kJ·mol−1	min−1	kJ·mol−1
RDF
	0.1	60.35	286	60.35	286	60.35	286
	0.2	52.65	256	52.65	256	52.65	256
	0.3	51.64	257	51.64	257	51.64	257
	0.4	121.87	765	121.87	765	121.87	765
	0.5	44.57	279	44.57	279	44.57	279
	0.6	34.64	211	34.64	211	34.64	211
	0.7	32.42	197	32.42	197	32.42	197
	0.8	31.13	189	31.13	189	31.13	189
	0.9	30.36	186	30.36	186	30.36	186
Average		51.07	292	51.07	292	51.07	292
OS
	0.1	52.51	198	52.51	198	52.51	198
	0.2	54.32	213	54.32	213	54.32	213
	0.3	54.88	221	54.88	221	54.88	221
	0.4	54.70	224	54.70	224	54.70	224
	0.5	55.27	230	55.27	230	55.27	230
	0.6	63.89	276	63.89	276	63.89	276
	0.7	32.42	197	32.42	197	32.42	197
	0.8	70.86	364	70.86	364	70.86	364
	0.9	53.10	273	53.10	273	53.10	273
Average		54.66	244	54.66	244	54.66	244
RDF-OS (1:1)
	0.1	59.64	234	59.64	234	59.64	234
	0.2	60.21	246	60.21	246	60.21	246
	0.3	59.27	248	59.27	248	59.27	248
	0.4	52.03	220	52.03	220	52.03	220
	0.5	39.58	176	39.58	176	39.58	176
	0.6	67.16	343	67.16	343	67.16	343
	0.7	61.53	319	61.53	319	61.53	319
	0.8	12.47	34	12.47	34	12.47	34
	0.9	38.15	236	38.15	236	38.15	236
Average		50.00	229	50.00	229	50.00	229

, were utilized to characterize the decomposition reactions. The functional relationship between the conversion (α) and temperature, as described by the equations, was used to calculate the yield of primary decomposition products (gas, liquid, and char) as a function of temperature and heating rate.

As shown in Equation (13), a cubic least-squares regression was used to approximate the final mass percent yield of the Y_char, as a function of maximum pyrolysis temperature based on the TGA data for the RDF-OS blend.

$$Y_{char}=-2.080\times {10}^{-6}{T}^3+3.603\times {10}^{-3}{T}^2-2.090T+463.5$$

(13)

This regression had an adjusted R² of 0.999 and an RMSE of 0.11%. A heating rate of 10 °C/min was used to gather the TGA data. Therefore, this model assumes that the effect of temperature on the final yield of the char is much more significant than the effect of the heating rate, and for the limits of this model (β ≤ 50 °C/min and T ≥ 500 °C), this appears to be a reasonable assumption [44].

Also, similar to the definition of the non-conventional feedstocks, the char was defined in Aspen Plus via the experimental proximate and ultimate analyses from the TGA and LECO CHN for the RDF-OS (1:1) char. Literature values [45] were used to assume a sulfur fraction in the char, and the breakdown of the sulfur type was assumed to be same as the feedstocks.

Cubic expressions given in the literature [34] were used to model the final oil yield as a function of maximum process temperature. The models were used together by assuming the abilities of the models for wood, paper, textile, and plastic pyrolysis to simulate the oil yield of RDF-OS. The pyrolysis oil was modeled as a mixture of C₆H₆, C₆H₆O, and C₁₀H₁₂O₄ [34,42]. A mass balance was performed separately in Microsoft Excel by considering all conventional and non-conventional components in the process, such that the specific yields of these conventional components could be input to the KINETIC block in Aspen Plus.

After the KINETIC block, the GIBBS1 and GIBBS2 blocks were used to find the relative equilibrium composition of the gas and oil, respectively. The gas was assumed to be predominantly made up of H₂, CO, CO₂, CH₄, C₂H₄, C₃H₆, C₃H₈, and C₄H₁₀ [34,40,46]. The light gases, pyrolysis oil, and char were combined again in MIX and represent all of the pyrolysis products. Then, to model the separation of the solids from the volatiles, a Cyclone block (CYCLONE) was implemented into the Aspen Plus model. A particle size distribution of the char from the literature [47] was assumed. After the non-conventional char was removed, cooling water utilities referenced in the Heater blocks, E₁ and E₂, were used to cool the volatile component stream (VOL1) to 40 °C and 5 °C, respectively. Finally, this liquid–vapor–gas mixture (VOL3) was separated using a Flash2 block (FLASH).

3. Results and Discussion

3.1. Physicochemical Properties of RDF and OS

RDF exhibits favorable properties for thermochemical conversion due to its high volatile matter content (66.03%) and relatively low ash content (13.52%). Its higher carbon (45.7%) and hydrogen (6.10%) content contribute to an elevated calorific value of 20.16 MJ/kg, making it a suitable candidate for combustion and gasification. Additionally, the oxygen content (33.97%) in RDF enhances its combustion efficiency. The low nitrogen (0.52%) and sulfur (0.19%) levels help minimize NOx and SOx emissions, making RDF an environmentally viable energy source. Compared to conventional fuels, RDF demonstrates characteristics that align with efficient energy recovery and sustainable waste management.

When compared to RDF processed from municipal solid waste (MSW), which is considered more suitable for thermochemical valorization, the RDF in this study falls within the expected range. RDF from MSW typically has a high calorific value of 18–24 MJ/kg, a low moisture content of 3–6%, and a high volatile matter content of 50–84% along with a carbon content of 47–56% [48,49]. This suggests that the RDF used in this study aligns well with the characteristics favorable for energy recovery.

Oil shale, in contrast, has significantly lower volatile matter (31.3%) and a much higher ash content (67.1%), which makes it less ideal for direct combustion. The low carbon (18.4%) and hydrogen (1.7%) content results in a much lower calorific value of 6.339 MJ/kg. While its oxygen content (11.82%) is lower than that of RDF, the elevated ash content presents operational challenges in energy extraction. The sulfur content (0.536%) is slightly higher than RDF, which could contribute to increased sulfur emissions. However, oil shale can still be utilized for energy production through pyrolysis or other advanced processing techniques to extract valuable hydrocarbons.

A previous study by Y. Fan et al. [50] reported similar findings, indicating that oil shale typically contains 12.08% carbon, 2.383% hydrogen, 14.40% oxygen, 0.57% nitrogen, and 1.57% sulfur. The proximate analysis results for oil shale from their study showed a volatile matter content of 22.78%, fixed carbon of 8.39%, and ash content of 68.83%, which align closely with the findings in this study. These values confirm the low energy potential of oil shale due to its high ash content and low combustible fractions.

3.2. TG and DTG Results

The results of TG and DTG analyses of RDF, OS, and a 1:1 binary mixture of RDF and OS can be found in Figure 5, Figure 6, Figure 7 and Figure 8. As shown in Figure 5, RDF was found to have four distinct peaks due to its complex composition. The first peak corresponds to the dehydration of the sample, the second peak is due to degradation of cellulose and hemicellulose, the third peak represents the decomposition of plastics and final peak represents the decomposition of char within the sample. OS on the other hand displayed three distinct peaks. The initial peak due to dehydration is comparatively smaller than the one seen with RDF, which can be attributed to the lower moisture content of OS. The second peak signifies the decomposition of kerogen, and the final peak is due to the decomposition of bitumen within the OS sample. Figure 6 holds the TG and DTG curves with a 5, 10, and 20 °C/min heating rate.

Table 4. Thermal decomposition behavior of RDF, OS, and RDF-OS (1:1).

Feedstock	Heating Rate	Peak 1				Peak 2				Peak 3
	(°C/min)	Ti	Max T	Tf	Max DTG	Ti	Max T	Tf	Max DTG	Ti	Max T	Tf	Max DTG
RDF	5	201	324	367	4.0	378	457	485	1.4	611	653	680	0.2
	10	199	334	373	7.8	395	464	504	2.0	635	690	720	0.55
	20	192	337	398	15.5	411	471	532	4.2	631	691	745	0.75
OS	5	180	450	500	0.8	550	730	750	1.1	-	-	-	-
	10	175	455	520	1.8	550	745	765	2.2	-	-	-	-
	20	170	475	530	3.3	550	765	775	3.8	-	-	-	-
RDF-OS (1:1)	5	200	325	365	2.1	370	455	490	1.8	610	710	720	0.7
	10	180	335	370	3.5	375	470	500	2.3	615	723	758	1.3
	20	175	345	385	7.5	400	480	545	4.7	622	726	770	2.3

provides further results from the thermal analysis for the decomposition peaks of the samples.

For OS, pyrolysis begins with a dehydration DTG peak in the range of 25 °C to 150 °C. Due to the small quantity of moisture content in OS, this peak does not clearly appear on the DTG plot. The second major peak falling in the range of 350 °C to 500 °C corresponds with the decomposition of kerogen and corresponds to roughly 10% of the sample mass. The final peak beginning at 550 °C and terminating at 770 °C corresponds to carbonate decomposition within the sample [51]. The Type 1 kerogen found within Green River OS is a high molecular weight, complex organic compound that is highly aliphatic [52]. In pyrolysis, complex kerogen molecules are converted into char, oil, and gas in the temperature range of 300–550 °C, which matches the second major peak seen in the OS DTG graph [53,54,55]. The final DTG peak in the sample is attributed to the breakdown of mineral carbonates found in the sample. The remaining matter from the pyrolysis is considered to be char and includes the fixed carbon and ash content. The effects of the heating rate can be seen in Table 4, wherein the degradation peaks were shifted to a higher temperature with the increased heating rate, which corresponds to the restriction of heat and mass transfer resulting in temperature change within the samples [56].

The pyrolysis of RDF exhibits four distinct decomposition peaks. The first peak is caused by the dehydration process beginning at 32 °C and ending at 150 °C. The second peak, associated with cellulose and hemicellulose decomposition, starts at 200 °C and displays a similar pattern to the pyrolysis of woody biomasses, which can be attributed to the presence of paper components in RDF. The third peak corresponds to the decomposition of plastics in the range of 380 °C to 600 °C. A fourth peak is seen in the range of 650 °C and 740 °C, representing the interaction between char and gases [57]. A similar trend to the effect of higher heating rates for OS was observed with the pyrolysis of RDF where the degradation peaks were shifted to higher temperatures with increased heating rates.

For the co-pyrolysis of RDF and OS, four peaks were observed. The first peak is due to the drying of the sample. The second peak is attributed to the decomposition of hemicellulose and cellulose within RDF. Of particular interest are the third and fourth decomposition peaks, where the decomposition of kerogen in the OS falls within the same temperature range as the decomposition of plastics in the RDF and the decomposition of carbonaceous compounds in the OS falls within the same temperature range as the char–gas interactions seen in the RDF pyrolysis.

3.3. Product Distribution from Experimental Pyrolysis Setup and Aspen Plus Simulation

As shown in Figure 9, RDF primarily produces a high yield of gas (45.26%), followed by oil (20.67%) and char (34.07%). The high gas yield is attributed to its significant volatile matter content (77–84%), which facilitates thermal decomposition and gasification. This aligns with findings from previous studies of RDF pyrolysis, which demonstrate that RDF’s composition—high in volatile matter and carbon (47–56%)—makes it highly suitable for thermochemical valorization [58].

The oil yield, though lower than the gas fraction, suggests RDF’s potential for liquid fuel recovery, as also highlighted in literature discussing pyrolysis as a waste-to-energy pathway [58]. Meanwhile, the char residue, accounting for approximately one-third of the total mass, represents the solid byproduct containing residual carbon and ash. The presence of this char is consistent with other studies that emphasize RDF’s substantial carbon content, which contributes to char formation during thermal degradation [11].

These findings reinforce RDF’s viability as a feedstock for pyrolysis, supporting both energy recovery and material reuse in line with circular economy principles.

Oil shale (OS), in contrast to refuse-derived fuel (RDF), generates a significantly lower gas yield (14.51%) due to its lower volatile matter content, a characteristic well-documented in pyrolysis studies of oil shale kerogen by Mu et al. [14]. Unlike RDF, which has a high proportion of volatile compounds that facilitate thermal decomposition, OS primarily consists of kerogen—a complex macromolecular organic material that requires higher temperatures for decomposition and primarily yields solid residues, as described by Peters [59].

The oil yield (8.32%) from OS pyrolysis is also considerably lower than that of RDF, reflecting the inherently lower hydrocarbon content in OS. Studies by Lyons Cerón and Konist [60] indicate that oil shale typically produces shale oil in the range of 5–20%, depending on the type of shale and processing conditions. This lower liquid fuel recovery is attributed to the presence of a more complex and oxygen-rich organic matrix, which leads to greater solid residue formation rather than volatile or liquid hydrocarbons, as observed by Mu et al. [14].

Char formation dominates the pyrolysis of OS, accounting for 77.61% of the total product. This high char yield is consistent with findings by Pihl et al. [61], who reported that OS contains a substantial mineral fraction, with ash contents often exceeding 50%, making it less efficient for gas or liquid fuel production. The high inorganic content in OS contributes to its extensive solid residue, limiting its suitability for conventional pyrolysis-based energy recovery unless modified with additives or co-pyrolyzed with hydrogen-rich feedstocks, as suggested by [14].

These findings reaffirm that, while OS can undergo pyrolysis, its efficiency for fuel production is constrained by its inherent composition, favoring solid byproduct formation over gas or liquid fuel recovery.

The co-pyrolysis of RDF and OS shows distinct interactions between the feedstocks. The calculated gas yield from the individual feedstocks was 29.89%, but the experimental co-pyrolysis yield was slightly higher at 32.33%, indicating a synergistic effect that enhances gas production. The oil yield from the calculated average was 14.49%, while the experimental result showed a slight reduction to 12.58%, suggesting that the blend’s interaction might inhibit oil formation. Char yield remained consistent, with a calculated value of 55.84% and an experimental result of 55.09%, showing only a minor deviation.

While no direct research on the co-pyrolysis of RDF and OS was found, studies have investigated the co-pyrolysis of oil shale with other feedstocks, such as plastic waste, biomass, and hydrogen-rich waste. Research by [14] on the co-pyrolysis of oil shale and waste tires found that co-pyrolysis enhances the yield of gaseous volatiles and promotes the formation of lighter shale oil fractions with reduced oxygen content, improving fuel quality. Similarly, Fan et al. [50] demonstrated that co-combustion of oil shale with municipal solid waste (MSW) resulted in increased volatile release, indicating interactions between the feedstocks that enhance thermal decomposition. Furthermore, Lyons Ceron et al. [58] observed that blending biomass with oil shale reduced char formation by up to 34.4 wt%, improving the overall efficiency of pyrolysis. These findings suggest that co-processing OS with alternative high-energy feedstocks can optimize product yields and improve overall energy recovery.

Future research could explore optimizing RDF-OS ratios and reaction conditions to maximize desirable product yields. Previous studies of co-pyrolysis of oil shale with plastics indicate that tuning reaction temperatures and adding catalysts such as zeolites can further improve oil yield and fuel quality, providing a potential direction for further optimization [62].

The comparative analysis indicates that RDF is a more efficient feedstock for energy recovery due to its higher calorific value, lower ash content, and greater volatile matter. Oil shale, while containing some combustible fractions, has a lower energy yield and presents challenges related to high ash content and low volatility. Further refinement or blending with higher-energy fuels may be necessary to improve its viability as an energy source [50]. The co-pyrolysis process reveals a synergistic effect that enhances gas production, making it a promising approach for improving the overall efficiency of thermal conversion processes.

The accuracy of these findings is further reinforced by Aspen Plus simulations, which closely replicate the experimental results. As shown in Figure 10, the Aspen Plus model predicts pyrolysis product yields of 31.40% gas, 11.9% liquid, and 56.6% char, which align closely with the experimental values of 31.98% gas, 12.58% liquid, and 55.09% char. The small discrepancies between the two datasets may stem from experimental uncertainties, variations in feedstock composition, or differences in modeling assumptions. However, the strong agreement between simulation and experimental results underscores the reliability of Aspen Plus in capturing the key trends in OS pyrolysis. These findings validate the use of computational models for predicting product distributions and optimizing pyrolysis conditions, particularly in co-pyrolysis scenarios where multiple feedstocks interact.

3.4. Char Analysis

3.4.1. Proximate and Ultimate Analysis of Char

As shown in

Table 5. Proximate and elemental analysis results of char from RDF, OS, and RDF-OS (1:1).

Analyses	RDF-Char	OS-Char	RDF-OS (1:1)-Char
Proximate Analysis (wt.%)
Volatile	20.28	20.21	18.57
Fixed carbon	43.43	3.52	13.03
Ash	36.29	76.27	68.39
Ultimate Analysis (wt.%)
Carbon	50.10	9.03	18.65
Hydrogen	3.21	0.16	0.56
Nitrogen	0.55	0.11	0.13
Sulphur	0.23	0.54	0.38
Oxygen *	9.62	13.90	11.89
Calorific value (MJ/kg)	20.41	0.53	4.87

* Calculated by difference.

, the RDF char produced in this study exhibited notable differences in its elemental composition compared to values reported in the literature at 650 °C [11], particularly in terms of carbon, hydrogen, nitrogen, and sulfur content. The carbon content of RDF char in this study (50.10%) was higher than the 45.23% reported in the literature, indicating a greater retention of carbonaceous material, which enhances its potential as a solid fuel. Similarly, the hydrogen content (3.21%) was significantly higher than the 0.98% observed in the literature, suggesting that the RDF feedstock used in this study contained a higher fraction of hydrogen-rich compounds, likely originating from plastic or biomass components. In contrast, the nitrogen content (0.55%) was lower than the 1.31% reported in the literature, suggesting a reduced presence of nitrogenous compounds in the RDF feedstock, which may contribute to lower NOx emissions upon combustion. Additionally, the sulfur content (0.23%) was considerably lower than the 0.71% reported in the literature, which is advantageous in minimizing sulfur-related emissions and mitigating environmental concerns associated with RDF char utilization. These variations underscore the influence of feedstock composition and pyrolysis conditions on the physicochemical properties of RDF char, which ultimately affect its combustion characteristics, emission profile, and suitability for energy recovery applications.

The OS char exhibits drastically different properties due to the mineral-rich nature of oil shale. It has an extremely low fixed carbon content of 3.52%, coupled with high ash content (76.27%), reflecting the dominance of inorganic compounds in the residual char. The ultimate analysis shows a low carbon content (9.03%) and hydrogen content (0.16%), contributing to its very low calorific value of 0.53 MJ/kg. The sulfur content is notably higher in OS char (0.54%) compared to RDF, which can influence its environmental impact when used for energy applications.

These findings are supported by a study of Huadian oil shale and its shale char, which reported a significant reduction in carbon content from 27.33% in raw oil shale to 17.88% in shale char, along with a drastic increase in ash content from 48.24% to 73.79% after pyrolysis. Additionally, the study noted a decrease in volatile matter from 36.21% to 16.16% and an increase in fixed carbon from 4.02% to 9.84%, indicating the partial retention of carbonaceous material after pyrolysis [63]. These findings align well with the results obtained in this study, further reinforcing the high ash content and low energy potential of OS char.

Similarly, another study of shale char properties reported comparable trends. The study found that shale char exhibited a carbon content of 17.99%, a hydrogen content of 0.88%, and an oxygen content of 5.42%, confirming the low organic composition of OS char. The ash content was measured at 73.44%, while volatile matter decreased significantly to 16.08% after pyrolysis, highlighting the loss of organic components. The fixed carbon content increased to 9.79%, further supporting the partial retention of carbonaceous material [64].

These findings align well with the results obtained in this study, reinforcing the high ash content, low carbon retention, and poor energy potential of OS char. The comparative analysis highlights that despite slight variations in values, the general trend remains consistent across multiple studies—showing that OS char is predominantly mineral-rich with limited fuel applications, unless further treated or blended with other feedstocks to enhance its energy properties.

The RDF-OS co-pyrolysis char exhibits intermediate properties, reflecting a blend of organic and inorganic characteristics from both RDF and OS. The volatile matter content decreases to 18.57%, suggesting interactions between RDF and OS during pyrolysis. The fixed carbon content (13.03%) is lower than RDF but higher than OS, indicating that OS dilution affects carbon retention. The ash content is 68.39%, significantly higher than RDF but slightly lower than OS, confirming the dominant influence of OS minerals in the blend.

The ultimate analysis shows that RDF-OS char has moderate carbon content (18.65%) and a hydrogen content of 0.56%, suggesting a balance between RDF’s carbon-rich nature and OS’s mineral-heavy composition. The calorific value (4.90 MJ/kg), while lower than RDF, is notably higher than OS, suggesting potential applications in energy recovery.

These results demonstrate that co-pyrolysis offers a way to balance energy content and mineral composition, making RDF-OS char a viable material for fuel applications while mitigating RDF waste and utilizing underutilized fossil resources.

3.4.2. X-Ray Photoelectron Spectroscopy Analysis of Char

X-ray photoelectron spectroscopy (XPS) was utilized to investigate the surface chemical composition and bonding states of chars derived from the pyrolysis of RDF, OS, and their mixture (RDF-OS). The results provide insight into the elemental transformations, mineral interactions, and retention of different functionalities during pyrolysis.

The XPS analysis provides key parameters, including binding energy (BE), which refers to the energy required to remove an electron from a specific atomic orbital and helps identify the chemical state of elements. The height (CPS, counts per second) represents the maximum intensity of a spectral peak, indicating the relative abundance of an element. Full width at half maximum (FWHM, eV) describes the broadness of the peak at half of its maximum intensity, reflecting the chemical environment and sample uniformity [65]. Lastly, peak area (Area (P) CPS·eV) represents the integrated intensity of the peak, providing a more accurate measure of elemental concentration compared to peak height alone

Table 6. XPS binding energies and elemental composition of RDF, OS, and RDF-OS (1:1) char samples.

RDF
Name	Start BE	Peak BE	End BE	Height CPS	FWHM eV	Area (P) CPS.eV
Cu2p3	934.08	931.78	930.08	1520.78	0.92	3355.88
C1s	291.28	284.56	277.28	527,260.82	2.35	1,492,940.18
O1s	537.88	532.05	525.48	271,221.88	2.97	880,964.53
Si2p	110.08	102.35	96.08	17113	2.59	51,176.12
Al2p	79.88	74.2	65.88	4907.17	2.27	16,615.05
Ca2p	359.28	347.03	339.68	13,188.33	2.48	78,452.75
N1s	410.08	399.19	391.68	6869.89	2.16	41,707.04
Na1s	1075.08	1071.46	1061.88	6393.02	2.42	27,284.72
Cl2p	202.58	198.97	196.08	2014.3	2.99	6894.71
OS
Name	Start BE	Peak BE	End BE	Height CPS	FWHM eV	Area (P) CPS.eV
O1s	538.28	531.24	523.08	532,662.92	3.01	1,752,819.16
C1s	297.68	284.3	277.28	368,182.67	2.25	1,146,424.63
Mg1s	1307.48	1303.85	1298.68	42,815.64	2.27	119,073.61
Ca2p	360.08	346.98	342.48	177,430.56	2.32	789,727.96
Si2p	106.88	102.24	96.08	52,930.42	2.93	166,824.74
F1s	694.88	684.8	679.68	28,394.61	2.56	94,805.8
Al2p	79.88	74.01	67.88	12,705.07	2.57	38,477.12
N1s	408.88	399.89	394.08	16,581.1	3.82	78,917.86
Na1s	1079.08	1071.77	1066.28	24,830.76	2.52	87,596.26
Fe2p	731.55	710.8	706.53	18,287.46	4.8	148,018.43
K2p	297.08	293.22	291.58	11,408.17	1.69	26,922.03
S2p	171.58	168.42	165.58	4081.32	3.27	14,103.49
RDF-OS (1:1)
Name	Start BE	Peak BE	End BE	Height CPS	FWHM eV	Area (P) CPS.eV
O1s	538.68	531.09	523.08	360,263.63	3.21	1,251,433.6
C1s	298.08	284.4	277.28	384,540.64	2.26	1,186,146.21
Ca2p	360.08	347.07	341.68	185,899.63	2.31	770,523.38
Mg1s	1309.08	1303.68	1297.08	32,162.2	2.86	127,953.39
Si2p	107.28	102.01	96.48	33,444.07	3.34	115,972.21
Al2p	81.88	74.13	69.48	9373.11	2.4	29,884.55
Na1s	1077.88	1072.04	1067.48	27,294.86	2.51	84,360.57
N1s	410.08	399.65	392.08	11,631.64	4.45	77,675.3
F1s	698.08	684.94	677.28	16,857.21	2.53	92,691.99
Fe2p	729.6	710.65	705.07	12,712.22	3.87	123,404.22

.

As depicted in Figure 11 and

Table 7. The quantitative analysis of metals for RDF, OS, and RDF-OS (1:1) using XPS.

Elements	RDF (Wt.%)	OS (Wt.%)	RDF-OS (1:1) (Wt.%)
Cu2p	0.09	-	-
C1s	66.44	33.68	38.67
O1s	21.43	28.37	22.45
Si2p	5.26	11.42	8.8
Al2p	2.6	4.01	3.45
Ca2p	2.02	13.5	14.61
N1s	1.38	1.75	1.9
Na1s	0.47	1.01	1.08
Cl2p	0.31	-	2.7
F1s	-	1.46	1.58
Fe2p	-	1.96	1.81
K2p	-	0.55	-
S2p	-	0.59	-
Co2p	-	-	0.94
Total	100	100	100

, the XPS spectrum of RDF char revealed carbon (C 1s, ~285 eV) as the dominant peak (66.44%), indicating a high carbon content, characteristic of char derived from organic-rich feedstocks. The presence of oxygen (O 1s, ~21.43%) suggests surface oxygen-containing functional groups, such as carbonyl, hydroxyl, and carboxyl species, which influence RDF char’s reactivity and adsorption capabilities.

In addition to carbon and oxygen, the XPS spectrum identified several inorganic elements, including silicon (Si 2p, 5.26%), aluminum (Al 2p, 2.6%), calcium (Ca 2p, 2.02%), nitrogen (N 1s, 1.38%), sodium (Na 1s, 0.47%), chlorine (Cl 2p, 0.31%), and copper (Cu 2p, 0.09%). These elements originate from inorganic additives, salts, and residual metals in RDF feedstock, influencing the surface chemistry of the resulting char. The presence of chlorine is particularly significant, as it suggests potential implications for catalytic activity and environmental emissions when RDF char is utilized in thermochemical applications.

The catalytic potential of RDF char has been demonstrated in previous studies. Li and Williams [66] highlighted that RDF-derived char can function as an effective catalyst in steam reforming, enhancing hydrogen production and syngas quality due to its high metal content, including Ca, Al, and Fe. Kusz et al. investigated the catalytic properties of RDF-derived char for tar decomposition, showing that iron-enriched char (Fe 6–11 wt%) significantly enhances CO and H₂ production while reducing CO₂ and CH₄ emissions [67]. These findings reinforce the potential multi-functionality of RDF char, not only as a carbonaceous adsorbent but also as a low-cost catalyst for hydrogen production and syngas upgrading.

As shown in Figure 12, the XRD analysis of OS char reveals a composition rich in quartz (SiO₂), calcite (CaCO₃), muscovite (KAl₂(AlSi₃O₁₀)(OH)₂), kaolinite (Al₂Si₂O₅(OH)₄), and iron sulfides (FeS/FeS₂). These results indicate that OS char retains a significant fraction of its original mineral matrix post-pyrolysis. The dominance of quartz and calcite aligns with previous studies highlighting the high silica and carbonate content of oil shale residues. Li and Ma (2016) reported similar findings, where XRD analysis demonstrated the persistence of quartz and calcite as major mineral phases in oil shale char due to their thermal stability [63].

The presence of iron sulfides suggests incomplete oxidation of pyrite during pyrolysis, leading to FeS retention in the char. This observation is consistent with the findings of Fan et al., who identified pyrite-derived FeS phases in shale char that subsequently transformed into Fe₂O₃ (hematite) under oxidative conditions. Moreover, the persistence of muscovite and kaolinite suggests that the clay mineral structure of OS remains relatively stable under pyrolysis conditions, with phase transitions occurring at higher temperatures. Fan et al. further demonstrated that the decomposition of kaolinite begins at around 500 °C, with muscovite undergoing gradual transformation at temperatures exceeding 700 °C [64].

Additionally, the mineral matrix significantly influences the pyrolysis behavior of OS char. The interaction between inorganic minerals and organic matter can alter the thermal decomposition pathways, delaying the release of volatile components and influencing the oxidation reactions of residual carbon. Studies have shown that inorganic components, such as carbonate-associated cations, may act as oxidation catalysts, enhancing the reactivity of shale char during combustion.

These findings highlight the importance of mineralogical composition in shaping the thermal stability and reaction mechanisms of OS char, reinforcing the role of quartz, calcite, and iron sulfides as key indicators of oil shale residue transformation.

The XRD spectrum of RDF-OS char (Figure 13) reflects a hybrid composition, with quartz and calcite remaining dominant. The presence of muscovite and kaolinite suggests that stable aluminosilicate phases persist post-pyrolysis, contributing to the structural stability of the char. The incorporation of transition metals from OS such as Fe and Co indicates potential catalytic properties, while the detection of NaCl and MgO suggests that certain inorganic salts from RDF remain stable in the co-pyrolyzed product.

The elemental composition of RDF-OS char reveals an intermediate carbon content (38.67%), bridging the gap between RDF (66.44%) and OS (33.68%). The increased calcium concentration (14.61%) reflects the mineral influence of OS, while the presence of cobalt (0.94%) suggests incorporation from RDF waste components, potentially enhancing catalytic activity. Additionally, chlorine (2.7%) is detected in RDF-OS char but absent in OS char, indicating retention from RDF waste.

The high-resolution XPS spectra for RDF, OS, and RDF-OS chars (Figure 14, Figure 15 and Figure 16) provide deeper insights into the electronic states of key elements. The interpretation of the elemental peaks was based on the research studies referenced in [66,68,69,70,71,72,73,74] as summarized in

Table 8. Functional groups identified from XPS analysis for OS char, RDF char, and RDF-OS (1:1) char.

Element	Functional Group Assignment	Peak BE (eV)	RDF Char	OS Char	RDF-OS (1:1) Char
O1s (Oxygen)	Metal oxides (M–O), Hydroxyl (-OH), Carbonyl (C=O), Si–O bonds	531.09–531.24	Present	Present	Present
C1s (Carbon)	Graphitic carbon (C–C/C=C), C–O (alcohols, ethers), C=O (carbonyls), O–C=O (carboxyls)	284.30–284.40	Present	Present	Present
Mg1s (Magnesium)	MgO, Mg(OH)2	1303.68–1303.85	Present	Present	Present
Ca2p (Calcium)	CaCO3 (calcium carbonate), CaO (calcium oxide)	346.98–347.07	Present	Present	Present
Si2p (Silicon)	SiO2 (silica), Silicates (Si–O–Si)	102.01–102.24	Present	Present	Present
F1s (Fluorine)	Metal fluorides (e.g., CaF2, MgF2)	684.80–684.94	Present	Present	Present
Al2p (Aluminum)	Al2O3 (alumina), Al–O–Si bonds	74.01–74.13	Present	Present	Present
N1s (Nitrogen)	Pyridinic-N (C=N), Pyrrolic-N (C-NH), Quaternary-N (graphitic N), N-O (nitrates)	399.65–399.89	Present	Present	Present
Na1s (Sodium)	Na2CO3 (sodium carbonate), Na–O bonds	1071.77–1072.04	Present	Present	Present
Fe2p (Iron)	Fe2O3 (iron oxide), FeOOH (oxyhydroxides), Fe–C interactions	710.65–710.80	Present	Present	Present
Cl2p (Chlorine)	Cl-Functional Groups (C–Cl, metal chlorides)	198.84	Absent	Absent	Present
Co2p (Cobalt)	CoO, Co3O4	780.5	Absent	Absent	Present
K2p (Potassium)	K2CO3, KCl, K2O	293.22	Absent	Present	Absent
S2p (Sulfur)	Sulfates (SO42−), Sulfides (S2−)	168.42	Absent	Present	Absent

.

In Figure 14, the deconvoluted C1s spectrum of RDF char shows distinct peaks corresponding to graphitic carbon (C=C, ~284.3 eV), oxygenated carbon (C–O, ~286 eV), and carboxyl groups (O–C=O, ~289 eV). Similarly, Figure 15 reveals that OS char contains significant Si–O (102–104 eV) and metal–oxide (M–O) interactions, indicating the strong mineral matrix of oil shale [63,65]. The RDF-OS char spectrum in Figure 16 exhibits features from both RDF and OS, confirming the hybrid nature of the material, with peaks corresponding to C=C (graphitic), Si–O (silicates), and Ca–O (carbonates).

As shown in Table 7 and Table 8, the XPS spectrum of RDF char revealed carbon (C 1s, Peak BE: 284.56 eV, 1,492,940.18 CPS·eV) as the dominant peak, indicating a high carbon content, characteristic of char derived from organic-rich feedstocks. The presence of oxygen (O 1s, Peak BE: 532.05 eV, 880,964.53 CPS·eV) suggests surface oxygen-containing functional groups.

In addition to carbon and oxygen, the XPS spectrum identified several inorganic elements, including silicon (Si 2p, Peak BE: 102.35 eV, 51,176.12 CPS·eV), aluminum (Al 2p, Peak BE: 74.2 eV, 16,615.05 CPS·eV), calcium (Ca 2p, Peak BE: 347.03 eV, 78452.75 CPS·eV), nitrogen (N 1s, Peak BE: 399.19 eV, 41,707.04 CPS·eV), sodium (Na 1s, Peak BE: 1071.46 eV, 27,284.72 CPS·eV), chlorine (Cl 2p, Peak BE: 198.97 eV, 6894.71 CPS·eV), and copper (Cu 2p, Peak BE: 931.78 eV, 3355.88 CPS·eV). These elements originate from inorganic additives, salts, and residual metals in RDF feedstock, influencing the surface chemistry of the resulting char.

The XPS analysis of OS char reveals a composition rich in oxygen (O 1s, Peak BE: 531.24 eV, 1,752,819.16 CPS·eV) and carbon (C 1s, Peak BE: 284.3 eV, 1,146,424.63 CPS·eV), along with significant mineral contributions. The high calcium (Ca 2p, Peak BE: 346.98 eV, 789,727.96 CPS·eV) and silicon (Si 2p, Peak BE: 102.24 eV, 166,824.74 CPS·eV) content suggests that OS char retains a significant fraction of its original mineral matrix post-pyrolysis.

The XPS spectrum of RDF-OS char reflects a hybrid composition, with oxygen (O 1s, Peak BE: 531.09 eV, 1,251,433.6 CPS·eV) and carbon (C 1s, Peak BE: 284.4 eV, 1,186,146.21 CPS·eV) as the dominant components. The presence of calcium (Ca 2p, Peak BE: 347.07 eV, 770,523.38 CPS·eV), silicon (Si 2p, Peak BE: 102.01 eV, 115,972.21 CPS·eV), and magnesium (Mg 1s, Peak BE: 1303.68 eV, 127,953.39 CPS·eV) suggests that OS minerals influenced the char composition, while elements from RDF, such as chlorine (Cl 2p, Peak BE: 684.94 eV, 92,691.99 CPS·eV) and sodium (Na 1s, Peak BE: 1072.04 eV, 84,360.57 CPS·eV), were retained in the final char.

These results demonstrate that co-pyrolysis leads to a redistribution of elements between RDF and OS, affecting the char’s composition and potential applications. The presence of transition metals from OS, such as Fe, suggests that RDF-OS char could possess catalytic properties, while stable aluminosilicate phases contribute to its structural integrity post-pyrolysis. The retention of chlorine and sodium in RDF-OS char, as indicated in Table 7, suggests potential environmental implications when used in thermochemical applications.

Overall, the XPS results, in combination with the functional group analysis, confirm the unique chemical characteristics of RDF, OS, and RDF-OS chars, emphasizing their potential use in energy and catalytic applications.

4. Future Work

Future research efforts will concentrate on analyzing the solid, liquid, and gas products generated from the co-pyrolysis of RDF and OS. In addition, investigations will be directed toward optimizing operational parameters, such as temperature, heating rates, and feedstock ratios, to improve product yields and energy efficiency. Scaling up the co-pyrolysis process and conducting techno-economic analyses will also be crucial in assessing its feasibility and commercial potential for large-scale waste-to-energy conversion. Sensitivity analysis will be employed to examine the effects of variables like feed composition, temperature, pressure, and reaction kinetics on process performance. Furthermore, optimization techniques will be utilized to maximize product yields, minimize energy consumption, and reduce costs. After optimization, strategies for process and heat integration will be implemented to enhance resource utilization, minimize waste generation, and improve overall efficiency.

5. Conclusions

This study has successfully demonstrated the viability of co-pyrolysis of refuse-derived fuel (RDF) and oil shale (OS) at a 50:50 weight ratio as a promising approach for both waste valorization and energy recovery. By employing a fixed-bed reactor with electrical kiln heating and leveraging the predictive capabilities of Aspen Plus simulation, a strong correlation between experimental data and model predictions was established, confirming the reliability of computational modeling in pyrolysis process optimization. A comparative analysis of product yields from the pyrolysis of pure RDF, pure OS, and their blend highlights the synergistic advantages of co-pyrolysis in modifying product distribution. The process yielded 31.98% gas, 12.58% liquid, and 55.09% char by weight, closely aligning with the Aspen Plus simulation results (31.40% gas, 11.9% liquid, and 56.6% char). The observed synergy between RDF and OS facilitated a more balanced distribution of pyrolysis products, improving gas and liquid yields compared to OS alone. This suggests that the hydrogen-rich volatile compounds from RDF enhanced the decomposition of OS, leading to improved energy recovery and more efficient feedstock conversion.

Beyond its technical implications, this research underscores the potential of co-pyrolysis as a dual-purpose strategy: mitigating plastic waste accumulation while simultaneously enhancing energy recovery from underutilized fossil resources. The synergistic interactions between RDF and OS contribute to a more thermally efficient decomposition, reducing the limitations associated with OS pyrolysis, such as high char formation and low volatile yield.

The XRD analysis further confirms that RDF-OS char exhibits a hybrid crystalline structure, integrating RDF-derived carbonaceous material with OS-derived mineral phases. The presence of quartz (SiO₂), calcite (CaCO₃), muscovite, and kaolinite suggest that silicate and carbonate minerals remain thermally stable, while transition metals such as Fe and Co contribute to catalytic activity.

Additionally, the retention of NaCl and MgO indicates that certain inorganic salts from RDF persist post-pyrolysis, potentially influencing the char’s reactivity and adsorption properties. These findings highlight the structural and functional stability of RDF-OS char, making it a promising material for catalytic applications, pollutant adsorption, and energy conversion processes. This highlights co-pyrolysis as an effective means of integrating waste valorization with energy production, advancing circular economy principles, and reducing reliance on conventional fossil fuels. The findings of this study open new avenues for optimizing feedstock blending, process parameters, and reactor designs to further enhance the efficiency and scalability of co-pyrolysis systems. Future research should explore catalytic enhancements, process scale-up, and techno-economic assessments to fully realize the industrial applicability of this approach in sustainable waste and energy management.