Oil Extraction from the Spent Coffee Grounds and Its Conversion into Biodiesel

Abstract

The depletion of fossil fuel reserves and their environmental impact have driven the search for sustainable energy alternatives. Biodiesel has emerged as a promising substitute. Being a major byproduct of the coffee industry, spent coffee grounds (SCGs) offer a viable feedstock due to their abundance, high fatty acid content, and calorific value. This study explores biodiesel production from SCGs. First, oil was experimentally extracted from SCGs using Soxhlet extraction with hexane as the solvent. The oil yield varied between 12 and 13.4% with a density of 0.9 g/mL. Reactor modeling and kinetic analysis were performed, showing that CSTRs in series are favorable for the esterification and transesterification reactions. Furthermore, Aspen Plus was used to simulate the extracted oil conversion into biodiesel through a two-step esterification and purification process. The simulation results are verified against previous experimental research. Sensitivity analyses were performed to evaluate the influence of key process parameters, including methanol-to-oil ratio, reactor residence time, and transesterification temperature. The simulation results indicate an optimal biodiesel mass yield of 90.31%, with a purity of 99.63 wt%, at a methanol-to-oil ratio of 12:1 and a transesterification temperature of 60 °C.

1. Introduction

As global energy demand continues to rise alongside population growth, the consequences of depleting energy resources are becoming increasingly alarming. Fossil fuels, currently the primary energy source, are finite and projected to run out in the near future. For instance, based on current consumption rates and proven reserves, the world has an estimated 47 years of oil remaining [1,2]. Moreover, the use of fossil fuels poses severe environmental threats, contributing to soil, air, and water pollution.

Growing concerns about sustainability have driven researchers and scientists to explore renewable energy alternatives with lower environmental impact. Among these, biomass stands out as a promising resource that can be converted into biofuels such as biodiesel. Biodiesel—comprising long-chain fatty acid alkyl esters—is produced through a catalyzed transesterification of triglycerides in the presence of alcohol. Over the past decade, biodiesel has demonstrated strong potential in reducing dependence on conventional diesel. Compared to diesel, it offers advantages such as lower greenhouse gas emissions, higher biodegradability, a higher cetane number that improves its combustion efficiency, and a higher flash point that enhances its storage safety.

Biodiesel feedstocks may be edible or non-edible. However, non-edible biomass and residues are strongly preferred. Edible sources are limited, increasingly expensive, and their use for biodiesel production raises ethical concerns related to food security. In contrast, biomass residues are abundant, do not interfere with food supply chains, and their conversion into fuel provides an environmentally friendly solution for waste management.

Coffee is the second most traded commodity after petroleum and the second most popular beverage after water [3]. According to the International Coffee Organization, the annual worldwide coffee production increased by 59.3% in the latest twenty years and it is expected to reach 11.67 million tons in 2025 [4].

Spent coffee grounds (SCGs) are the roasted and grounded coffee beans that were depleted from some of their water-soluble compounds. They are the solid coffee residues classified into three main sources: domestic, industrial including soluble and instant coffee industries, and commercial such as cafeterias, coffee shops and restaurants. These residues are very often thrown into the trash and usually end up in landfills. However, since SCGs contain significant quantities of organic substances, they constitute an environmental problem [5]. Each ton of discarded grounds can emit, as it decomposes, 340 cubic meters of methane, which is a greenhouse gas that has nearly 86 times the climate-heating impact of the same volume of carbon dioxide [6]. High concentrations of triglycerides and fatty acids are present in SCGs [7] and the latter has a high calorific value (above 20 MJ·kg⁻¹) [8]. Depending on the coffee beans type, 5 to 20 wt% of oil can be extracted from the SCGs [9]. The extracted oil can be then easily converted to biodiesel by transesterification methods [10]. The spent coffee oil does not decompose quickly, does not freeze easily, and remains viscous due to its low levels of saponified matter, making it stable and well suited for biodiesel production [11]. Around 1 billion liters of biodiesel per year is estimated to be produced from SCGs [12]. Therefore, the use of SCGs as sources for producing biodiesel is an environmentally friendly and efficient way to deal with coffee waste, ensuring economic circularity and environmental sustainability.

As a particular case, producing biodiesel from SCGs is a process that can be applied in Lebanon. Drinking the traditional ‘Lebanese Coffee’ is a well-known custom in Lebanon as well as in some Arabic and non-Arab countries, such as Cyprus and Turkey. Coffee beans are not grown on Lebanese lands. However, Lebanon primarily imports green coffee beans from Brazil. Between 80 and 95% of green coffee beans are imported from Brazil which are roasted, grinded, packaged and distributed to the local market where it is locally consumed and exported to more than 40 countries. In 2017, Lebanon imported 24,794 tons of green coffee beans. The Lebanese coffee market involved at that time the main five market players in Lebanon are Café Daniel, Café Super Brasil, Maatouk, Café Najjar, and Café Abi Nasr along with smaller producers [13]. The Lebanese coffee industry generates annually an approximate amount of 12,893 tons of waste coffee grounds [13], which could be converted to 2.2 million L of biodiesel.

Biodiesel production from SCGs is a process that takes place over several steps. The key critical phases are drying, oil extraction, two step esterification process: acid catalyzed esterification and base catalyzed transesterification, and finally purification. The process flow diagram of the biodiesel production is illustrated in Figure 1. After collecting the SCGs, they are dried in an electric oven to reduce its moisture content before proceeding with the oil extraction. SCGs can undergo several types of extraction processes, mainly Soxhlet or ultrasonic extraction using specified solvents. The ultrasound extraction and hexane are found to be the most effective method and solvent, respectively. Before proceeding to transesterification, oil properties are characterized to assess its quality. However, since the extracted oil is found to have a high viscosity, a high acidic value as well as a high saponification value, it cannot be directly converted to biodiesel. Thus, a two-step esterification process is required. The extracted oil is first esterified with methanol in the presence of sulfuric acid as a catalyst. Methanol and water are then separated from the pre-treated oil. The latter is then trans-esterified with methanol. The reaction is catalyzed by potassium hydroxide. The byproduct, glycerol, and the remaining impurities are separated from methyl ester, which is the desired product. Washing can be done for further purification. The biodiesel is then dried to remove any remaining water from the previous step. The final steps include testing the produced biodiesel for its physical and chemical properties. Finally, the fatty acid composition should be determined using Gas Chromatography technique coupled with the Flame Ionization Detector (GC-FID) [11,14,15].

Spent coffee grounds (SCGs) typically have a high initial moisture content—reported between 50 and 65 wt% [9]—which poses challenges for oil extraction efficiency and yield accuracy. Therefore, proper drying is essential to reduce moisture content, inhibit microbial growth, and improve oil yield accuracy. Most studies adopt thermal drying at 105 °C for 12–24 h, as described by Mofijur et al. [14], who reported a reduction in moisture content of 20% over a 24-h period. Similarly, Al-Hamamre et al. [11] applied a drying time of 5 h at 102 °C, while Somnuk et al. [16] operated at 105 °C for 24 h. The optimal drying time depends on the initial moisture content and the SCG type.

The oil extraction from SCGs is a critical step in biodiesel production, as it directly influences the overall yield and quality of the final product. Various methods have been explored to maximize oil recovery, including Soxhlet extraction (SE), ultrasonic-assisted extraction (UAE), microwave-assisted extraction, and maceration. Among these, SE and UAE are the most employed and studied in the literature due to their balance of efficiency and simplicity at the laboratory and pilot scales.

SE, a conventional method, involves continuous solvent reflux over a solid sample, facilitating thorough extraction over time. The process is generally carried out with a large solvent volume and requires elevated temperatures and prolonged durations. Although this method yields reasonable oil quantities, it is energy-intensive and not suitable for scale-up without modification. In contrast, UAE has gained interest due to its shorter extraction time, lower solvent and energy consumption, and comparable or improved oil yields. UAE uses high-frequency sound waves, typically above 20 kHz [17].

For instance, Mofijur et al. [14] compared both methods. In SE, they used 300 mL of solvent (e.g., hexane, methanol, or chloroform) to extract oil from a 20 g SCG sample over a period of up to 3 h, resulting in a yield of 15.62% with n-hexane. In the same study, the oil yield increased to 15.84% using UAE with n-hexane as the solvent, requiring only 30 min and employing a Qsonica sonicator (20 kHz, 500 W). Tinoco-Caicedo et al. [18] demonstrated that UAE reduced the oil’s specific cost by 86% compared to SE and resulted in a lower exergy destruction rate (4.5 kJ/kg vs. 14.3 kJ/kg). Kusuma et al. [19] obtained a yield of 18.14% by weight relative to the dry SCGs by extracting oil from SCGs using the Soxhlet extraction method with n-hexane as the solvent.

The choice of extraction solvent also plays a pivotal role in oil recovery efficiency. Solvents are selected based on polarity, boiling point, density, safety, and cost. Non-polar solvents such as n-hexane and pentane consistently outperform polar solvents like ethanol, acetone, and isopropanol in terms of oil yield. Moreover, the boiling point influences solvent selection, as high-boiling solvents (e.g., isopropanol, toluene) increase energy demand for recovery, whereas very low-boiling solvents (e.g., pentane) are prone to greater volatilization losses. Al-Hamamre et al. [11] compared several solvents and found that hexane resulted in the highest oil yield of 15.28% in 30 min. Similarly, Somnuk et al. [16] reported the highest yield using hexane (14.7%) compared to anhydrous ethanol (13.1%) and methanol (7.5%). Moreover, some studies suggest that a mixture of polar and non-polar solvents can further enhance oil extraction. Haile [15] reported that a 50:50 (v/v) blend of isopropanol and hexane achieved an oil yield of 21.5%, significantly outperforming either solvent used alone. Consequently, hexane remains the most practical choice due to its balance of efficiency, energy requirements, and operational simplicity.

After extraction, the oil-solvent mixture is typically subjected to rotary evaporation to remove and recover the solvent. This step ensures that the extracted oil can be used in subsequent processing and that the solvent is available for reuse, improving economic and environmental performance.

In contrast to many other waste-derived oils (e.g., waste cooking oil, palm fatty acid distillate), SCG oil (SCGO) presents distinct challenges. Chief among these are its elevated free fatty acid (FFA) content and high acid value (AV), often exceeding 9–44 mg KOH/g [15,20], as well as its high viscosity (42–44 mm²/s). These properties require pretreatment—typically acid-catalyzed esterification—before base-catalyzed transesterification to avoid soap formation [10,15]. In the first step, acid-catalyzed esterification reduces the FFA content. Haile [15] conducted this at 54 °C using HCl and methanol (20:1 molar ratio). Uddin et al. [10] used sulfuric acid and a molar ratio of 12:1. The second step involves base-catalyzed transesterification, typically using KOH and methanol. Reaction conditions such as temperature (54–60 °C), time (90–120 min), and catalyst loading vary slightly across studies [10,15]. While other waste oils may also have high FFAs, SCGO’s combination of high FFA with variability in extraction yield (linked to coffee variety, roasting degree, and brewing method) makes consistent processing more difficult. This variability has been underexplored in the context of integrated process design and techno-economic feasibility.

Biodiesel purification is achieved by successive washing with warm water, often aided by sulfuric acid to neutralize residual soap and catalyst [10,15]. Drying is performed using sodium sulfate or a rotary evaporator. Physicochemical analysis reveals that SCG biodiesel generally meets EN 14214 and ASTM D6751 standards [21,22], though AV can remain marginally above limits in some studies [14,15]. Fatty acid methyl ester (FAME) profiling via GC-FID confirms that SCG biodiesel is dominated by linoleic, oleic, and palmitic acids, with a relatively high proportion of unsaturated fatty acids (~62%) enhancing cold flow properties but reducing oxidative stability. This trade-off—especially relevant for storage and long-term use—further distinguishes SCG biodiesel from biodiesel derived from other feedstocks.

The primary objective of this study is to experimentally extract oil from SCG using SE, due to its availability, with hexane as the solvent. The effect of varying the hexane-to-SCG ratio on oil yield is investigated. Furthermore, selected physicochemical properties of the extracted oil are analyzed to assess its quality and suitability for biodiesel production. Reactor modeling is then carried out using ideal continuous stirred-tank reactors (CSTRs) with pseudo-first-order kinetics. In the third part of this study, the conversion of the extracted oil into biodiesel is simulated using Aspen Plus, including modeling of the associated purification units. Based on insights from the literature, key process variables—such as the methanol-to-oil ratio, reactor residence time, and transesterification temperature—are known to significantly influence biodiesel yield. Accordingly, sensitivity analyses are conducted to evaluate the impact of these parameters on biodiesel production. The simulation results are validated through comparison with data from existing studies. While extraction with varying solvent-to-solid ratios has been reported previously, this study uses SCG collected from USEK university campus so that the experimental yields reflect local feedstock characteristics, which then serve as the basis for process simulation. Unlike most prior simulations, which focus on waste cooking oil as feedstock, this work models the conversion of SCGO into biodiesel.

2. Experimental Spent Coffee Ground Oil Extraction

2.1. Collection and Drying

SCGs were collected from espresso machines located at the cafeteria of the Holy Spirit University of Kaslik (USEK) in Lebanon and stored in sealed containers. As seen in Figure 2a, a wet SCG sample of 164 g was dried in an electric oven at 105 °C for 18 h, as recommended by previous studies [10,15,16]. The initial moisture content was found to be 53% by weighing the sample before and after drying.

2.2. Oil Extraction

Oil was extracted from the dried SCGs using SE with hexane as the solvent due to its demonstrated efficiency in maximizing oil recovery. The extraction was performed using a Velp Scientifica SER 148 [23] semi-automated Soxhlet system based on the Randall method, which uses hot solvent immersion to accelerate the process. This method significantly reduces the extraction time to approximately 90 min.

Two extraction runs were carried out, each consisting of five replicate extractions, as seen in Figure 2b. For each sample, 5 g of dried SCGs was placed in a cellulosic thimble, and 60 mL of hexane were added, resulting in a solvent-to-sample ratio of 12 mL/g.

The heating temperature was set at 130 °C. The extraction process began with the immersion of the thimble containing the dried SCGs into the boiling hexane, ensuring effective contact between the solvent and the sample. This immersion phase lasted for 15 min. Upon completion, the thimble was raised above the solvent level to initiate the washing phase, during which the sample was rinsed with solvent for 30 min. The final stage, which is the recovery phase, lasted for 30 min and involved the evaporation and collection of the solvent. By the end of the extraction process, the beaker that initially contained only hexane held the extracted oil from the SCGs.

Post-extraction, the exhausted SCGs remained in the thimble, and the extracted SCGO was collected and weighed to calculate the oil yield according to:

$$\mathrm{S}\mathrm{C}\mathrm{G}\mathrm{O} \mathrm{y}\mathrm{i}\mathrm{e}\mathrm{l}\mathrm{d}\left(\mathrm{\%}\right)={\displaystyle \frac{{\mathrm{m}}_{\mathrm{S}\mathrm{C}\mathrm{G}\mathrm{O}}}{{\mathrm{m}}_{\mathrm{S}\mathrm{C}\mathrm{G}}}}\times 100\mathrm{\%}$$

(1)

where m_SCGO and m_SGC represent the weight of the extracted SCGO and the dried SCG sample in grams, respectively.

Table 1. Calculated SCGO yield for each sample in the two performed runs.

Run	1					2
Sample	1	2	3	4	5	1	2	3	4	5
SCGO yield (wt%)	13.0	12.4	12.0	12.0	13.4	13.4	13.4	13.4	13.4	13.4

summarizes the SCGO yield obtained from the extraction. Averaging the results, a SCGO yield of 12.98% is obtained for a hexane-to-SCG ratio of 12 mL/g. This yield is consistent with literature. For instance, Panpraneecharoen and Chumanee [24] reported a yield of 13.59–14.42% at a ratio of 20 mL/g, and Najdanovic-Visak et al. [25] obtained a yield of 13.6% at a ratio 15 mL/g. Therefore, a slightly lower yield is expected at lower ratios. Even though the obtained oil yield is lower than conventional oilseeds, SCGs remain attractive due to their abundance, lack of cost as a waste material, and the environmental benefits of diverting it from landfilling. Moreover, co-product valorization (biochar, antioxidants) and process intensification strategies (ultrasound, microwave-assisted, or supercritical extraction) can further enhance its industrial relevance. Finally, the extracted SCGO should be stored in a closed bottle and refrigerated at 4 °C [26,27].

All extracted oil samples were poured into a graduated cylinder, and their volume was measured by reading the level at 25 °C, which was recorded as 4.83 mL. To adjust the volume to the ASTM standard temperature of 15 °C, a volume correction factor (VCF) of 0.9915 [28] was applied by multiplying the measured volume at 25 °C. The total mass of the oil was then determined using a precision analytical balance (model: Radwag AS 220.R2 PLUS) and found to be 4.31 g. This leads to an oil density of 0.9 g/mL which falls within the ASTM range (0.86–0.90 g/mL), and is also very close to the values obtained by other studies: 0.917 g/mL [15], and 0.89 g/mL [20,29].

2.3. Influence of Hexane to Dried Spent Coffee Ground Ratio

Four additional extraction samples were conducted to assess the effect of hexane-to-SCG ratio. New SCGs were collected, dried at 105 °C for 24 h, and found to have 48% moisture content. The same Soxhlet procedure was used with varying the hexane to dried spend coffee ground (DSCG) ratios from 7 to 15 mL/g. The variation in the SCGO yield (%) against the hexane:DSCG ratio is illustrated in Figure 3. It can be clearly seen that increasing the hexane:DSCG ratio from 7 to 15 mL/g increases the SCGO yield from 11.78 wt% to 12.50 wt%.

2.4. Acid Value and Free Fatty Acid Determination

The AV corresponds to the required weight in mg of potassium hydroxide (KOH) to neutralize the free acid groups in 1 g of oil. It represents the amount of fatty acids that are free or not attached to a glycerol backbone. Alternatively, the FFA content is the percentage by weight of free acid groups present in the extracted oil. The oil with high FFA content is more susceptible to oxidation. If the FFA content exceeds 1%, pre-treatment is necessary [11].

FFA content is determined by titration as per Association of Official Agricultural Chemists (AOAC) standards. The FFA content is determined volumetrically by titrating the oil sample with 0.1 N KOH solution in the presence of using a color indicator, which is phenolphthalein [30].

To determine the FFA, 1 g of the SCGO was transferred into a clean beaker and mixed with 25 mL of ethanol along with a few drops of phenolphthalein indicator. The mixture was then titrated with a 0.1 N KOH solution until a persistent pale pink color appeared, indicating the endpoint. The volume of KOH solution required to reach this endpoint (V_b) was recorded for further calculation. The titration was performed three times, leading to a standard deviation of 0.116 mL. The titration results after blank correction are summarized in

Table 2. The volume of KOH solution required in each titration run.

Titration Run	Vb (mL)
1	1.9
2	1.7
3	1.7

.

Using the average volume (1.7 mL), the FFA content of the oil, expressed as oleic acid equivalent, is calculated according to Equation (2). A FFA of 4.8% is obtained, which matches the literature-reported value of 4.9% [15].

$$\mathrm{F}\mathrm{F}\mathrm{A}(\mathrm{\%})={\displaystyle \frac{{\mathrm{V}}_{\mathrm{b}}\left(\mathrm{m}\mathrm{L}\right)\times {\mathrm{N}}_{\mathrm{K}\mathrm{O}\mathrm{H}}\times 28.2}{{\mathrm{m}}_{\mathrm{o}\mathrm{i}\mathrm{l}}\left(\mathrm{g}\right)}}\times 100\mathrm{\%}$$

(2)

$$\mathrm{A}\mathrm{V}=\mathrm{F}\mathrm{F}\mathrm{A}\left(\mathrm{\%}\right)\times 1.99$$

(3)

where N_KOH is the normality of KOH solution (0.1 N), and m_oil is the mass of the titrated oil sample.

The AV was calculated using Equation (3) [30] and was found to be 9.55 mg KOH/g. This value significantly exceeds the maximum limit set by ASTM standards (0.50 mg KOH/g), indicating that a two-step esterification process is required. The recommended approach involves an initial acid-catalyzed esterification to reduce the FFA content, followed by a base-catalyzed transesterification to complete the conversion into biodiesel.

2.5. Peroxide Value

The peroxide value (PV) is a widely used indicator of the oxidative stability and quality of oils, with higher PVs indicating greater oxidation and potential deterioration. The PV was determined by mixing 0.5 g of SCGO with 30 mL of distilled water, followed by 30 mL of a 3:2 (v/v) acetic acid–chloroform solution and 0.5 mL of saturated potassium iodide (KI). The mixture was titrated with 0.01 M Na₂S₂O₃ while shaking until a pale-yellow color appeared. After adding a few drops of starch indicator, which turned the solution blue, titration was continued until the blue color disappeared. The obtained PV was 7.6 mEq O₂/kg oil, indicating that the extracted SCGO exhibits moderate oxidative stability. This value is within the typical range for SCGO [31,32] and suggests that the oil is reasonably stable for storage and further processing, although care should be taken to minimize exposure to heat, light, and oxygen to prevent further oxidation.

3. Reactors Design and Kinetic Modeling

According to literature, the extracted oil comprises 95.1% triglycerides (triolein, C₅₇H₁₀₄O₆) and 4.9% FFAs (oleic acid, C₁₈H₃₄O₂) by mass [33]. This composition was selected since it is consistent with the experimentally determined FFA content (4.8%) presented in Section 2.4.

3.1. Chemical Reactions

The process includes two main reactions: acid catalyzed esterification, and base catalyzed transesterification.

3.1.1. Acid Catalyzed Esterification

Oleic acid reacts with methanol in the presence of H₂SO₄ catalyst to produce methyl oleate (biodiesel) and water, according to:

$${\mathrm{C}}_{18}{\mathrm{H}}_{34}{\mathrm{O}}_2 + {\mathrm{CH}}_3\mathrm{OH} \to {\mathrm{C}}_{19}{\mathrm{H}}_{36}{\mathrm{O}}_2 + {\mathrm{H}}_2\mathrm{O}$$

(4)

A conversion of 90% was assumed for oleic acid, based on experimental studies [15].

3.1.2. Base Catalyzed Transesterification

Triolein reacts with methanol in the presence of KOH catalyst to produce methyl oleate (C₁₉H₃₆O₂) and glycerol (C₃H₈O₃₎:

$${\mathrm{C}}_{57}{\mathrm{H}}_{104}{\mathrm{O}}_6 + 3{\mathrm{CH}}_3\mathrm{OH} \to 3{\mathrm{C}}_{19}{\mathrm{H}}_{36}{\mathrm{O}}_2 + {\mathrm{C}}_3{\mathrm{H}}_8{\mathrm{O}}_3$$

(5)

Based on literature, a conversion of 95% of triglycerides was assumed [33,34].

3.2. Process Flowrates and Catalyst Requirements

The process is designed based on an oil feed rate of 10 kg/h. This low flowrate is selected based on the amount of SCG that can be collected from USEK cafeteria and the coffee shops in the neighborhood. The molar flowrate of oil is 1.25 kmol/h, calculated based on its average molecular weight (801.61 g/mol). The volumetric flowrate is 1.1 m³/h, with an average density of 909.25 kg/m³.

For acid-catalyzed esterification, 1% v/v of H₂SO₄ and a methanol-to-oil molar ratio of 12:1 are used [10], resulting in methanol and acid flowrates of 4.80 kg/h and 0.20 kg/h, respectively. For base-catalyzed transesterification, 1% w/w of KOH and a methanol-to-oil molar ratio of 9:1 are used [15], requiring 3.60 kg/h of methanol and 0.10 kg/h of KOH.

3.3. Kinetic Modeling

Due to the limited kinetic data on SCGO, reaction kinetics were adapted from studies on waste cooking oil (WCO), which has a comparable FFA content and fatty acid profile [35]. Nevertheless, this substitution introduces a degree of uncertainty, as variations in oil composition may influence the kinetic parameters and reaction pathways. The characterization of the SCGO is essential to validate this assumption in future work. Both esterification and transesterification reactions were modeled using pseudo-first-order kinetics, assuming methanol is in large excess, according to:

$$-{\mathrm{r}}_{\mathrm{A}}={\mathrm{k}}^{\mathrm{\prime }}{\mathrm{C}}_{\mathrm{A}}$$

(6)

where r_A is the reaction rate (kmol.m⁻³.min⁻¹), k′ is the pseudo-first-order reaction constant, and C_A is the concentration of the limiting reactant, which is oleic acid and triolein in Equations (4) and (5), respectively.

The obtained values were adjusted using the Arrhenius equation:

$$\mathrm{k}=\mathrm{A}{\mathrm{e}}^{-{\displaystyle \frac{{\mathrm{E}}_{\mathrm{a}}}{\mathrm{R}\mathrm{T}}}}$$

(7)

where k is the reaction rate constant, A is the pre-exponential factor, E_a is the activation energy, R is the universal gas constant and T is the temperature.

Hazrat et al. [35] reported that at 60 °C, the pre-exponential factor was 4.73 × 10⁷ min⁻¹ for the acid catalyzed esterification and 1.96 × 10⁸ min⁻¹ for the base catalyzed transesterification. Their corresponding activation energies were 57,369 J/mol and 61,903 J/mol, respectively. The adjustments accounted for the specific methanol-to-oil molar ratios used in this study (12:1 and 9:1, respectively), compared to reference studies.

3.4. Reactor Type Selection and Design

A Continuous Stirred-Tank Reactor (CSTR) was chosen for both steps due to its superior temperature control, which is critical for maintaining the 60 °C reaction temperature. Unlike plug flow reactors (PFRs), CSTRs allow better handling of feedstock variability, facilitate temperature control, and are commonly employed in biodiesel production processes, although at the cost of larger reactor volumes and longer residence times. While PFRs can be efficient in certain large-scale continuous processes, they are less favorable for heterogeneous feedstock such as SCG oil, where mixing and residence time distribution are critical.

For an ideal CSTR under a steady state, the molar balance is given as follows:

$$\mathrm{V}={\displaystyle \frac{{\mathrm{F}}_{\mathrm{A}0}\mathrm{X}}{{-\mathrm{r}}_{\mathrm{A}}}}$$

(8)

where V is the reactor volume (m³), F_A0 is the inlet molar flowrate of limiting reactant, and X is the conversion.

In terms of the residence time, which is expressed by $\mathsf{\tau }={\displaystyle \frac{\mathrm{V}}{\dot{\mathrm{V}}}}$, the design equation becomes the following:

$$\mathsf{\tau }={\displaystyle \frac{\mathrm{X}}{{\mathrm{k}}^{\mathrm{\prime }}\left(1-\mathrm{X}\right)}}$$

(9)

Equation (9) gives the residence time required for a given conversion in a single CSTR. However, as conversion X increases, the required residence time increases non-linearly, making a single reactor less efficient or impractically large. To address this, the conversion through multiple identical CSTRs in series can be expressed using the following relationship:

$${\mathrm{X}}_{\mathrm{n}}=1-{\displaystyle \frac{1}{{\left(1+\tau {\mathrm{k}}^{\prime }\right)}^{\mathrm{n}}}}$$

(10)

where X_n is the overall conversion after n reactors, $\tau$ is the residence time per reactor, and n is the number of reactors in series.

3.5. Reactor Design Results

The main reactor design parameters derived from the kinetic modeling and sizing calculations presented in this section are summarized in

Table 3. Summary of reactor design parameters.

Parameter	Acid Catalyzed Esterification	Base Catalyzed Transesterification
Pseudo-rate constant, k′ (min−1)	0.062	0.051
Desired conversion, X	90%	95%
Residence time, τ (min)	34.94	33.56
Volumetric flowrate, $\dot{\mathrm{V}}$(m3/h)	0.0172	0.0156
Reactor volume, V (m3)	0.01	0.0087
Number of reactors in series	2	3
Reactor type	CSTR	CSTR
Reaction temperature	60 °C	60 °C
Methanol-to-oil molar ratio	12:1	9:1
Catalyst	H2SO4 (1% v/v)	KOH (1% w/w)

. For the acid catalyzed esterification step, two CSTRs in series were determined to be sufficient to achieve a 90% conversion of FFA with a residence time of approximately 35 min per reactor. Similarly, three CSTRs in series were required for the base catalyzed transesterification step to reach a 95% conversion of triglycerides, each with a residence time of roughly 34 min. The table below presents the key design specifications and operating conditions for both reaction steps.

4. Aspen Plus Process Simulation: Oil to Biodiesel

The process of SCGO conversion into biodiesel was modeled by the simulator, Aspen Plus^® V14. The NRTL property method was adopted as it properly predicts non-ideal liquid-liquid or liquid-vapor mixtures under different conditions [33,36,37].

4.1. Components

The different components that are used in the process and listed in

Table 4. List of chemical components used in the simulation.

ID	Type	Component Name	Formula
TRIOL-01	Conventional	Triolein	C57H104O6
METHANOL	Conventional	Methanol	CH4O
METHY-01	Conventional	Methyl-oleate	C19H36O2
GLYCEROL	Conventional	Glycerol	C3H8O3
H2SO4	Conventional	Sulfuric-acid	H2SO4
KOH	Conventional	Potassium-hydroxide	KOH
WATER	Conventional	Water	H2O
OLEIC-01	Conventional	Oleic-acid	C18H34O2

. According to the literature [36,38], the SCGO can be estimated as a mixture of triolein, which represents the triglycerides, and oleic acid, which represents the free fatty acids. In addition, the main product, which is biodiesel or FAME, is represented by methyl oleate (C₁₉H₃₆O₂) whereas the byproduct is glycerol (C₃H₈O₃) [33]. Furthermore, methanol is the alcohol used for both esterification reactions [33]. The acid catalyst used in the first esterification reaction is sulfuric acid and the base catalyst used in the transesterification is potassium hydroxide [10,15].

Even though the triolein properties were available in the software data banks, some parameters were missing and had to be corrected manually, as shown in Figure 4. The ideal gas heat capacity data for triolein was absent and could not be determined using property estimation. The values for ideal gas heat capacity were therefore manually introduced based on data from existing study [39].

4.2. Process Flowsheet

A simplified process flow diagram of the SCGO conversion into biodiesel is illustrated in Figure 5, while the detailed process flow diagram, in which all the stream and block names are indicated, is shown in Figure A1. The extracted oil (OIL) is pumped by “PUMP2” to a heat exchanger (HEX1) to reach a temperature of 60 °C. The heated oil (OIL3) is then fed to two CSTRs in series (C1 and C2) where it undergoes an acid catalyzed esterification reaction, which corresponds to the pretreatment step. The acid catalyst, sulfuric acid (H2SO4) is mixed with alcohol, which is methanol (MEOH), in the mixer (MIXER1). The mixture is introduced by “PUMP1” to the first reactor (C1). The reactor product, which is the pretreated oil (PRTOIL), is then introduced into a flash drum (FLASH) to separate the unreacted methanol from the product. The recovered methanol stream (METOUT), exiting the drum as a vapor phase, is cooled down to 25 °C by the cooler (HX2). The cooled stream (METOUTC) is divided by the splitter (SPLIT) into two streams: MET1, which can be later recycled into the process, and “MET2” which is the methanol fed to the transesterification reactor. The split fraction is set based on the methanol mass flowrate needed for the transesterification reaction and it is found to be 0.884. Therefore, 88.4% of the recovered methanol is fed to the mixer (MIXER2), where it is mixed with potassium hydroxide (KOH). The mixture (MIX3) is pumped by “PUMP3” to the reactor (C3). The pretreated oil purified from excess methanol (PRTOILP), leaving the flash unit, enters the series of CSTRs (C3, C4, and C5) to undergo a transesterification reaction. The reaction product (C5OUT) is then fed to a RadFrac distillation column (METREC) where the methanol is separated from the product stream. The bottom product (EST) enters the separator (SEP) to separate the main product, methyl oleate, from glycerol and the remaining impurities. The aqueous stream (AQU1) is fed into a RadFrac distillation column (GLYCECOL), where glycerol is recovered as the bottom product whereas the distillate (MEOHWAT2) consists mainly of methanol and water in excess. The stream (EST2), consisting of the desired product, is sent for further purification to another RadFrac distillation column (FAMECOL), where excess methanol and water (MEOHWAT) are separated from the desired final product which is biodiesel (FAME).

4.2.1. Streams Inputs

The required input stream variables are summarized in

Table 5. Summary of the flowrates, and composition of the input streams.

Stream	Stream Name	Mass Flowrate (kg/h)	Mass Composition
Oil feed	OIL	10	wtriolein = 0.951 woleic acid = 0.049
Methanol	MEOH	4.7964	wmethanol = 1
Sulfuric acid	H2SO4	0.2013	wsulfuric acid = 1
Potassium hydroxide	KOH	0.1	wKOH = 1

. Ambient operating conditions (T = 25 °C, P = 1 bar) are considered for the different input streams.

4.2.2. Blocks Inputs

Table 6. Summary of the main operating parameters in the different unit operations of the conversion process of SCGO into biodiesel.

Block	Block Name	Operating Conditions
Acid catalyzed esterification reactors	C1 and C2	T = 60 °C P = 4 bar Residence time = 34.94 min
Cooler	HX2	T = 25 °C
Flash drum	FLASH	T = 60 °C P = 0.5 bar
Base catalyzed transesterification reactors	C3, C4, and C5	T = 60 °C P = 4 bar Residence time = 33.56 min
Methanol recovery distillation column	METRECOV	Number of stages = 7 Condenser type = Total Reboiler type = Kettle Feed stage (above stage) = 4 Distillate rate = 2.25 kg/h Mass reflux ratio = 2 Pressure at stage 1 = 0.5 bar
Separator	SEP	Split fractions for stream EST2: Triolein = 0.99 Methanol = 0.015 Methyl oleate = 1 Glycerol = 0 Water = 0.02 Oleic acid = 0.99
Glycerol recovery distillation column	GLYCECOL	Number of stages = 6 Condenser type = Total Reboiler type = Kettle Feed stage (above stage) = 4 Distillate rate = 1 kg/h Mass reflux ratio = 2 Condenser pressure = 0.4 bar Column pressure drop = 0.1 bar
FAME recovery distillation column	FAMECOL	Number of stages = 6 Condenser type = Partial Reboiler type = Kettle Feed stage (above stage) = 4 Bottom rate = 1 kg/h Mass reflux ratio = 1 Condenser pressure = 0.1 bar Condenser temperature = 148.3 °C

shows the different operating parameters for the various process blocks. The parameters were carefully selected based on several references and studies [33,34,38,39]. For both reactors, the reaction equations and rate law, which were developed in the previous part of this study, were considered.

5. Results

5.1. Model Validation and Results

The mass flowrates of the main streams that reflect the process productivity and the product purity are summarized in

Table 7. Summary of the mass flowrates of the process streams.

Stream ID	OIL	MIX1	PRTOIL	METOUT	PRTOILP	C5OUT	FAME	GLYCEROL
Component	Mass Flowrate (kg/h)
Triolein	9.51		9.51	Trace	9.51	0.47	Trace	0.01
Methanol		4.80	4.75	4.07	0.68	3.29	0.01	0.03
Methyl Oleate			0.46	3 PPM	0.46	9.55	9.03
Glycerol						0.94		0.94
H2SO4		0.20	0.20	5 PPM	0.20	0.20		0.20
KOH						0.10		0.10
Water			0.03	0.02	0.01	0.03	400 PPM	0.02
Oleic Acid	0.49		0.05	30 PPB	0.05	0.05	0.03	0.01
Total	10.00	5.00	15.00	4.08	10.91	14.62	9.07	1.30

. It can be seen that the mass flowrate of oleic acid, present initially in the extracted oil (OIL) decreased from 0.49 kg/h (4.9 wt%) to 0.048 kg/h (0.32 wt%) in the stream leaving the acid catalyzed esterification reactors (PRTOIL). This indicates a 90% conversion of oleic acid to methyl oleate. The remaining methanol after the reaction is separated from the treated oil in the flash unit. The stream results show that 85 wt% of the total methanol present in the stream PRTOIL was recovered in the stream METOUT that consists mainly of methanol (99.5% by mass) and traces of water. The pre-treated oil is then fed to the series of CSTRs where the triolein is converted into methyl oleate. The mass flowrate of triolein decreased from 9.51 kg/h to 0.466 kg/h, indicating a conversion of 95%. The mass flowrate of methyl oleate, which is the main reaction product, increased from 0.464 kg/h to 9.549 kg/h. As for glycerol, which is the byproduct, 0.941 kg/h were produced. The stream leaving the base catalyzed transesterification reactors (C5OUT) undergoes several purification steps. Consequently, 100% of the produced glycerol can be recovered as it can be seen in the “GLYCEROL” stream, and around 94.57 wt% of the methyl oleate was recovered in stream “FAME”. The latter consists of 99.63% by mass of methyl oleate. This purity meets the ASTM standards for biodiesel, which should be greater than 96.5 wt% [40].

The biodiesel yield for the overall plant, which is calculated according to Equation (11), is found to be 90.31 wt%.

$$\mathrm{B}\mathrm{i}\mathrm{o}\mathrm{d}\mathrm{i}\mathrm{e}\mathrm{s}\mathrm{e}\mathrm{l} \mathrm{y}\mathrm{i}\mathrm{e}\mathrm{l}\mathrm{d}={\displaystyle \frac{\mathrm{M}\mathrm{a}\mathrm{s}\mathrm{s} \mathrm{f}\mathrm{l}\mathrm{o}\mathrm{w}\mathrm{r}\mathrm{a}\mathrm{t}\mathrm{e} \mathrm{o}\mathrm{f} \mathrm{p}\mathrm{r}\mathrm{o}\mathrm{d}\mathrm{u}\mathrm{c}\mathrm{e}\mathrm{d} \mathrm{b}\mathrm{i}\mathrm{o}\mathrm{d}\mathrm{i}\mathrm{s}\mathrm{e}\mathrm{l}}{\mathrm{M}\mathrm{a}\mathrm{s}\mathrm{s} \mathrm{f}\mathrm{l}\mathrm{o}\mathrm{w}\mathrm{r}\mathrm{a}\mathrm{t}\mathrm{e} \mathrm{o}\mathrm{f} \mathrm{o}\mathrm{i}\mathrm{l} \mathrm{f}\mathrm{e}\mathrm{d}}}\times 100$$

(11)

The biodiesel yield obtained in this study, which reached 90.31 wt%, is in good agreement with the values reported in previous experimental and simulation-based studies, as summarized in

Table 8. Biodiesel yield obtained from the conversion of SCGO.

Study	Focus	Main Findings and Biodiesel Yield
Mofijur et al. [14]	Experimental	The biodiesel yield was tested against the reaction time. Results showed that the biodiesel yield increased from 74% for a residence time of 30 min, until reaching a peak of 98.25% at 60 min.
Haile [15]	Experimental	A biodiesel yield of 82% w/w of SCGO was obtained after purification
Al-Hamamre et al. [11]	Experimental	A biodiesel yield varying from 68.75% to 85.5% was obtained through a one-step esterification. The yield increased to reach 99% by adaption a two steps transesterification process.
Gu et al. [36]	Simulation	The biodiesel yield was not clearly stated. The final biodiesel stream, having a purity ranging between 99.6 and 99.78 wt%, has a mass flowrate varying from 45.6 to 376.64 kg/h for an extracted oil flowrate between 54 and 433 kg/h. This leads to a biodiesel yield ranging between 84.44 and 86.93 wt%.

. For instance, Mofijur et al. [14] achieved a maximum yield of 98.25% under optimized reaction time, while Haile [15] reported a yield of 82% after purification. Similarly, Al-Hamamre et al. [11] observed yields ranging from 68.75% to 85.5% in a one-step process, increasing up to 99% with a two-step transesterification. Additionally, the simulation study by Gu et al. [36] reported yields between 84.44% and 86.93% depending on process conditions. It should be noted that the simulated value used in this study represents the maximum biodiesel yield obtained under optimized conditions, and similar to previous literature, only the optimized yield is reported rather than multiple operating points. Therefore, statistical metrics such as RMSE could not be applied, and the simulated yield was benchmarked against reported literature ranges. The consistency of the current simulation results with these experimental and simulation-based findings further validates the accuracy and reliability of the model developed in this study.

5.2. Sensitivity Analysis

In process engineering projects, identifying the key parameters that significantly affect the performance of the desired outputs is essential. Aspen Plus offers a valuable feature known as sensitivity analysis, which allows users to evaluate how variations in specific input parameters impact overall process behavior. This is achieved by systematically adjusting one or more input variables while holding the remaining parameters constant, thereby revealing which factors exert the most influence on process results.

5.2.1. Impact of Methanol-to-Oil Ratio on Oleic Acid Conversion and FFA Content

The objective of this analysis was to identify an optimal methanol-to-oil ratio in the acid catalyzed esterification reactors that balances biodiesel quality and production efficiency with economic feasibility. Lower FFA content enhances the oil oxidative stability, which is a critical quality criterion for biodiesel [10,33,39]. Consequently, a sensitivity analysis was conducted to evaluate the effect of varying the oil flowrate for a fixed methanol flowrate on the oleic acid conversion and the residual free fatty acid (FFA) content, which is expressed as the mass fraction of oleic acid, in the outlet stream PRTOILP of flash separator downstream the reactor C2. The methanol-to-oil molar ratio was varied within the range of 8:1 to 15:1. Figure 6 shows the variation in the oleic acid conversion X (%) and the mass percentage of oleic acid in the stream leaving the flash separator function of the methanol-to-oil molar ratio.

As shown in Figure 6, the oleic acid conversion remained nearly constant at approximately 90% across the tested range. However, the FFA content slightly decreased from 0.446% to 0.439% as the methanol flowrate increased due to the composition change, indicating improved conversion efficiency. While this improvement is beneficial, higher methanol usage not only increases solvent consumption costs but also raises downstream separation and recovery expenses, as excess methanol must be removed and recycled. These additional steps can significantly impact operating costs, especially at industrial scale. Thus, a methanol-to-oil molar ratio of 12:1 was considered a suitable compromise, offering a balance between product quality and process cost-effectiveness.

5.2.2. Impact of Residence Time on Methyl Oleate Produced and FFA Content

The influence of the residence time on the methyl oleate produced in the acid catalyzed esterification and on the mass fraction of FFA (oleic acid) in the outlet stream PRTOIL of the reactor C2 is studied by running a sensitivity analysis. The residence time for each of the identical reactors C1 and C2 is varied between 25 and 60 min with an increment of 5 min. Figure 7 shows the variation in methyl oleate flowrate in kg/h and the mass percentage of oleic acid in the stream leaving the esterification reactor C2 function of the residence time in minutes in reactors C1 and C2.

As shown in Figure 7, increasing the residence time from 25 to 60 min results in a noticeable improvement in process performance. Specifically, the mass flowrate of methyl oleate rises from 0.436 kg/h to 0.492 kg/h, while the FFA content significantly decreases from 0.49% to 0.14%. This trend is consistent with the expected behavior, as longer residence times allow for more complete conversion of reactants, thereby enhancing both product yield and quality. A higher residence time contributes to greater biodiesel productivity and improved oxidative stability due to the lower residual FFA content.

However, this improvement comes at the expense of increased reactor volume and the corresponding capital costs associated with larger equipment purchase, installation, and maintenance. These costs can be substantial in industrial settings, as larger reactors not only require higher initial investment but may also need higher utility requirements for heating and mixing. The residence time calculations presented in the previous sections showed that a residence time of 35 min per reactor is required to achieve a 90% conversion in the acid catalyzed esterification step. This value is further supported by the results of the sensitivity analysis, which demonstrate that beyond 35 min, the increase in methyl oleate production begins to plateau, indicating diminishing returns in productivity. Moreover, at this residence time, the FFA content is reduced to below 1%, thereby meeting the threshold required for the subsequent base catalyzed transesterification step. This ensures both process efficiency and compliance with biodiesel quality standards.

5.2.3. Impact of the Flash Drum Pressure on Methanol Recovery

To study the impact of the flash drum pressure on the amount of methanol recovered in the stream METOUT and on the duty of the flash drum, the flash drum pressure is increased from 0.1 to 1 bar with an increment of 0.1 bar through a sensitivity analysis.

The graphical results presented in Figure 8 illustrate the effect of pressure on methanol recovery and reboiler duty in the flash drum. The maximum methanol recovery is achieved at a pressure of 0.1 bar, with 4.684 kg/h of methanol recovered in the vapor phase out of 4.7463 kg/h. As pressure increases, the amount of methanol recovered decreases gradually, reaching 4.06 kg/h at 0.5 bar, and then declining more sharply to 3.58 kg/h at 0.6 bar. Beyond this point, specifically at 0.8 bar and higher, methanol recovery drops drastically as it fully condenses into the liquid phase, resulting in no vapor recovery. These results indicate that the operating pressure should be maintained at or below 0.6 bar to ensure effective methanol separation, while also balancing energy costs.

A similar trend is observed in the flash drum duty. The highest energy demand occurs at 0.1 bar, with a duty of 1.46 kW. As the pressure increases, the duty decreases moderately, reaching 1.26 kW at 0.5 bar, and further to 1.11 kW at 0.6 bar. At 0.8 bar and above, the duty drops to zero, reflecting the absence of vapor–liquid separation. Therefore, from both recovery efficiency and energy consumption perspectives, operating below 0.5 bar is considered optimal. This is also justified by previous research analysis that operated the flash drum at 0.5 bar [38].

5.2.4. Impact of Base Catalyzed Transesterification Reactor Temperature on the Biodiesel Production

To assess the impact of the base catalyzed transesterification reactor temperature on biodiesel production, a sensitivity analysis was carried out by varying the reactor temperature from 55 °C to 80 °C in increments of 5 °C. Figure 9 shows the variation in the methyl oleate mass flowrate in the stream leaving the biodiesel production plant (FAME) function of the reactor temperature in °C.

It can be seen in Figure 9 that the methyl oleate mass flowrate increased only slightly, from 9.012 kg/h at 55 °C to 9.045 kg/h at 80 °C. Based on a 10 kg/h oil feed, this corresponds to an increase in the plant overall yield from 90.12% to 90.45%, representing a marginal improvement of just 0.33%. Given the limited gain in productivity relative to the additional energy required for heating, maintaining a temperature of 60 °C is considered the most practical and energy-efficient operating condition. The selected temperature is similar to the operating temperature that was reported in the literature [10].

6. Conclusions

In this study, SCGs collected from espresso machines at USEK’s cafeteria were dried at 105 °C, yielding a moisture content of 53%. Oil extraction using semi-automated Soxhlet equipment and hexane at a 12:1 solvent-to-solid ratio produced oil yields of 12–13.4%, aligning well with literature values. The extracted oil exhibited a density of 0.9 g/mL (at 15 °C), compliant with ASTM standards, and a FFA content of 4.8%, corresponding to an AV of 9.5 mg KOH/g.

The subsequent conversion into biodiesel was modeled in Aspen Plus^®, incorporating key process units and sensitivity analyses. From a 10 kg/h feed of SCGO, the simulated process produced 9.031 kg/h of biodiesel, resulting in an overall mass yield of 90.31% and a product purity of 99.31%.

The results show that SCGs, major byproducts of the global coffee industry, offer a promising non-edible feedstock for biodiesel production. Utilizing SCGs not only avoids competition with food resources but also provides an effective waste management strategy by converting organic waste into clean energy [11]. In countries like Lebanon, where coffee consumption is substantial, local-scale biodiesel production from SCGs presents a viable and sustainable opportunity. This potential can be realized if the process is thoroughly studied and properly implemented.

However, several limitations should be acknowledged. The study did not include experimental conversion of SCGO into biodiesel, and the kinetic modeling relied on assumptions from the literature. Additionally, while this study does not include experimental FAME profiling, the simulation results provide a basis for understanding process performance and optimization. Future work will therefore focus on experimental validation, including GC-FID analysis of the produced biodiesel, pilot-scale trials, and the evaluation of alternative extraction techniques such as mechanical pressing.

Overall, this work underscores the promise of integrating waste valorization into renewable energy systems and highlights the need for continued research to bridge the gap between simulation and practical implementation. Valorizing the SCG waste stream can contribute to circular economy efforts, reduce landfill burden, and support renewable energy goals.