Maha A Dawood (1)
General Background: Mismanagement of used lubricating oil represents a significant environmental and economic challenge due to the loss of valuable hydrocarbon resources and contamination risks to land and water systems. Specific Background: Solvent extraction technology has emerged as a promising recycling approach capable of removing contaminants and restoring physicochemical characteristics of degraded lubricating oil while supporting resource conservation strategies. Knowledge Gap: However, limited empirical validation combining solvent selection with operational parameter optimization and predictive modeling for oil recovery rate remains insufficiently addressed. Aims: This study evaluates solvent extraction performance using several solvent systems and optimizes key process parameters, including solvent-to-oil ratio, temperature, and pressure, while developing regression-based predictive models for oil recovery rate and impurity removal. Results: Findings indicate that a propane-based solvent mixture increased recovery rate and reduced secondary waste generation, with optimal operating conditions identified at a solvent-to-oil ratio of 4:1, temperature range of 180–220 °C, and pressure of 4–10 mbar; regression modeling demonstrated strong agreement between experimental and calculated values with accuracy of 94.98 and variance of 0.016. Novelty: The integration of comparative solvent evaluation with empirical least-squares regression modeling provides validated relationships linking solvent composition and operational variables to recovery performance. Implications: These outcomes support solvent extraction as a sustainable pathway for recycling used lubricating oil, enabling improved resource utilization while reducing environmental burdens associated with conventional disposal practices.
Highlights:
• Parameter Window 200 °C and 4–8 Mbar Produced Highest Distilled Volume• Regression Prediction Reached 94.98 Accuracy With 0.016 Variance• 4:1 Ratio Minimized Reagent Consumption While Maintaining Yield
Keywords: Used Lubricating Oil Recovery, Solvent Extraction Process, Propane Solvent Mixture, Process Parameter Optimization, Oil Recovery Rate Modeling
Environmental pollution is one of the most urgent international problems that endanger human health and the ecological system [1]. Among other pollutants, used lubricating oils are a huge problem because of their large production and the possible damage to the land and water sources [2]. Lubricating oils are very important in internal combustion engines, as they allow the reduction of friction, dissipation of heat, as well as wear [3]. Nevertheless, in the course of operations, the lubricating oil is degraded, and the viscosity of the lubricating oil is altered, it becomes acidic and collects mineral [4], [5], like metals, water and by-products of combustion [6].
The conventional ways of disposal, i.e. landfill or burning, are not environmental and economical [7]. As a result, recycling and relying on the used lubricating oils have become an option as a possible pollution [8][9][10][11][12][13]. There are various procedures of recycling oil and one of them is acid-clay treatment [14], acid-activated clay treatment [15], vacuum distillation [16], and solvent extraction [17]. Solvents extraction has become a potential method among them owing to its high efficiency, low amounts of energy used, and minimum environmental impact [18].
This paper dwells on the optimization of solvent extraction process to recover used lubricating oils. The experimental study of the influence of the primary parameters like the type of solvent, solvent to oil ratio, temperature and pressure is conducted. Moreover, the empirical models are constructed to forecast the rate of oil recovery and impurity removal that can be useful in industrial purposes.
A. Materials
Vehicle repair facilities were chosen as the source of samples of waste lubricating oil that was first dehydrated to remove moisture and volatile hydrocarbon compounds.
B. Solvent Extraction
Several solvents were tested for their extraction efficiency, including:
1.Propane
2.Propane with Butane
3.Ternary mixture of 25% 2-propanol, 50% 1-butanol, and 25% butanone
4.Ternary mixture of 25% 2-propanol, 35% 1-butanol, and 40% butanone
The solvent-to-oil ratio was varied from 2:1 to 6:1 to determine the optimal condition.
C. Process Description
Solvents extraction process was divided into four major steps. First, dehydration: The removal of water and volatile impurities by vacuum distillation at 200 ° C to remove water and volatile impurities. The solvent extraction follows where dehydrated oil is mixed with the solvent of choice at optimal proportion of between 2:1 to 6:1 to derive optimal impurities removal. Solvents separation and recycling through vacuum distillation in the solvent recovery step. Lastly, the last purification process is Filtration and additive blending to improve the oil characteristics.
A. Analysis of Oil Recovery Efficiency
Table 1 presents the experimental findings of the process of oil recovery under different pressure and temperature conditions. The figures denote the correlation between pressure, temperature, and oil recovery efficiency.
Table1: Oil Recovery Data from Distillation Runs
To calculate oil recovery and efficiency, you can use the following equations:
Where, distilled oil Volume is the amount of oil recovered in milliliters (ml), and charge Volume is the initial volume of oil (liter).
Table 2: Oil recovery and Efficiency Results for each run
Effect of Temperature on Oil Recovery:
It is clear, based on the analysis, that increased temperatures improve oil recovery, as Figure 1 demonstrates that the maximum recovery is at 200° C (Run 1). This is evidenced in the data by Run 1 which has a final temperature of 200°C resulting in maximum recovery of 25 ml. Conversely, run 2 with a final temperature of 158° C has a lower recovery of 15 ml which points to the pattern that low temperatures lead to low recovery. On the same note, Run 3 with temperature of 166° C recovers 22 ml, which once again confirms that temperature is positively correlated with the oil recovery
Figure 1: Effect of Temperature on Oil Recovery
Effect of Pressure on Oil Recovery
The findings imply that at lower pressure (4-8 mbar), there are high volumes of oil recovery and on the other hand, there are reduced volumes of oil recovery at a high pressure (12 mbar) as depicted in Figure 2. To demonstrate this point, the oil recovery at 4 mbar (Runs 1, 2, and 3) is also much greater, with 25 ml of oil being recovered at 200 °C in Run 1, 15 ml in Run 2, and 22 ml in Run 3. Conversely, at an 12 mbar (Runs 6 and 7), although the final temperature gets to 215 C, the recovery volumes go down, with 5 ml in Run 6 and 10 ml in Run 7. It means that with low pressure the separation efficiency increases, as the boiling point of hydrocarbons decreases.
Cooling Temperature and First Drop Temperature:
The temperature at which the condensation process began and thus the recovery of oil was initiated was noted to vary depending on the pressure of the system and the final temperature which was reached. Experiment 3, as an example, at an initial condensation point of 115 ° C, there was the suggestion of premature volatilization, which would lead to process efficiency. On the other hand, the temperature of the cooling process also had a great impact on the recovery rates, showing low temperatures favoring better condensation and separating solvents. Indicatively, the Experiment 7 operated under a cooling temperature of 4 ° C that enabled good results in condensation.
B. Optimization of Process Parameters
More important operational parameters such as temperature, pressure and solvent to oil ratio were optimized so as to maximize the efficiency of oil recovery without compromising the quality of oil. The optimization strategy was to balance these factors in order to have the highest yield without destroying the integrity of the oil during the extraction process. It was found that a solvent to oil ratio of 4: 1 was ideal since it was known to give maximum recovery with minimum solvent usage. The temperature was kept between 180 ° C and 220 ° C to avoid thermal degradation and to have good separation. Also, the work under vacuum pressure of 4-10 mbar helped to recover the solvents and reduce the oxidative damage.
Predictive modeling of the oil recovery rate (ORR) was done by way of least-squares regression analysis on the LINEST tool of Microsoft Excel in order to come up with the empirical relationships. The models are associated with the correlation of solvent composition ratios to both oil recovery efficiency and impurity removal, which allows the prediction of the effect of changes in process parameters on the rate of recovery to be accurately predicted. Two empiric equations were developed out of a large body of laboratory experimental evidence.
a. For oil recovery:
b. For ash reduction:
Where, Lny1 oil recovery percent, Lny2 is the oil recovery percentage, Lny2: ash reduction percent is the ash reduction percent, and X1,X2,X3 are the weight percentages of the solvent components. Figure 3 depicts the relationship between oil recovery and the solvent components 1 i.e. the experimental and theoretical values are plotted against the weight percentage of the solvent component 1.
Figure 3 Oil Recovery vs. Solvent Component 1
Figure 4 indicates the ash reduction against the solvent Component 1, where this plot is used to compare experimental and theoretical ash reduction according to the weight percentage of the solvent component 1 (X1).
Figures 4 Ash Reduction vs. Solvent Component 1
This paper establishes that solvent extraction, especially on the propane-based solvents is an effective and quick method to recover and purify used lubricating oils and this is environmentally friendly process. Key findings include:
Temperature and pressure critically influence recovery efficiency, with optimal conditions at 200°C and 4–8 mbar.
A solvent-to-oil ratio of 4:1 maximizes recovery while minimizing solvent use.
Empirical models accurately predict oil recovery and ash reduction, facilitating process optimization.
The method offers economic and environmental benefits by reducing waste and conserving resources.
Future work should focus on scaling up the process and exploring alternative solvents to further enhance sustainability.
R. E. Millemann, R. J. Haynes, T. A. Boggs, and S. G. Hildebrand, “Enhanced oil recovery: Environmental issues and state regulatory programs,” Environ. Int., vol. 7, no. 3, pp. 165–177, 1982, doi: 10.1016/0160-4120(82)90103-9.
M. de Oliveira Estevo et al., “Immediate social and economic impacts of a major oil spill on Brazilian coastal fishing communities,” Mar. Pollut. Bull., vol. 164, no. July 2020, 2021, doi: 10.1016/j.marpolbul.2021.111984.
K. Asraf Rahim and S. N. S. Al-Humairi, “Influence of Lubrication Technology on Internal Combustion Engine Performance: An Overview,” Proceeding - 2020 IEEE 8th Conf. Syst. Process Control. ICSPC 2020, vol. 184, no. December, pp. 184–189, 2020, doi: 10.1109/ICSPC50992.2020.9305811.
I. Mangas, M. A. Sogorb, and E. Vilanova, Lubricating Oils, Third Edition., vol. 3. Elsevier, 2014.
W. Chokelarb, P. Sriprom, L. Permana, and P. Assawasaengrat, “Assessment of overall remaining useful life of lubricants by integrating oil quality and performance,” Heliyon, vol. 10, no. 18, 2024, doi: 10.1016/j.heliyon.2024.e37486.
M. Fingas, Introduction to Oil Chemistry and Properties. Elsevier Inc., 2011.
M. M. Gertsen et al., “Degradation of Oil and Petroleum Products in Water by Bioorganic Compositions Based on Humic Acids,” Energies, vol. 16, no. 14, 2023, doi: 10.3390/en16145320.
S. Widodo, K. Khoiruddin, D. Ariono, S. Subagjo, and I. G. Wenten, “Re-refining of waste engine oil using ultrafiltration membrane,” J. Environ. Chem. Eng., vol. 8, no. 3, 2020, doi: 10.1016/j.jece.2020.103789.
I. C. Ossai, A. Ahmed, A. Hassan, and F. S. Hamid, “Remediation of soil and water contaminated with petroleum hydrocarbon: A review,” Environ. Technol. Innov., vol. 17, 2020, doi: 10.1016/j.eti.2019.100526.
R. Jain, L. Urban, H. Balbach, and M. D. Webb, Energy and Environmental Implications. Elsevier Inc., 2012.
M. R. Islam Sazzad et al., “Advancing sustainable lubricating oil management: Re-refining techniques, market insights, innovative enhancements, and conversion to fuel,” Heliyon, vol. 10, no. 20, p. e39248, 2024, doi: 10.1016/j.heliyon.2024.e39248.
M. Shahbaz, N. Rashid, J. Saleem, H. Mackey, G. McKay, and T. Al-Ansari, “A review of waste management approaches to maximise sustainable value of waste from the oil and gas industry and potential for the State of Qatar,” Fuel, vol. 332, no. P2, p. 126220, 2023, doi: 10.1016/j.fuel.2022.126220.
M. Yu, H. Ma, and Q. Wang, “Research and Recycling Advancement of used Oil in China and All Over the World,” Procedia Environ. Sci., vol. 16, pp. 239–243, 2012, doi: 10.1016/j.proenv.2012.10.033.
J. D. Udonne and O. A. Bakare, “Recycling of Used Lubricating Oil Using Three Samples of Acids and Clay as a Method of Treatment,” Int. Arch. Appl. Sci. Technol., vol. 4, no. 2, pp. 8–14, 2013.
I. Al Zubaidi, A. Al Tamimi, and M. Al-Zubaidi, “Applications of de-oiling and reactivation of spent clay,” Environ. Technol. Innov., vol. 21, p. 101182, 2021, doi: 10.1016/j.eti.2020.101182.
M. M. Khudhair, T. M. Hameed, and H. A. Alameer, “Using Vacuum Distillation Technique to Treat Waste Lubricating Oil and Evaluation its Efficiency by Chromatographic Methods,” J. Al-Nahrain Univ., vol. 20, no. 2, pp. 17–24, 2017, doi: 10.22401/jnus.20.2.03.
A. H. Nour, E. O. Elamin, A. H. Nour, and O. R. Alara, “Dataset on the recycling of used engine oil through solvent extraction,” Chem. Data Collect., vol. 31, p. 100598, 2021, doi: 10.1016/j.cdc.2020.100598.
I. Efthymiopoulos, P. Hellier, N. Ladommatos, A. Kay, and B. Mills-Lamptey, “Effect of Solvent Extraction Parameters on the Recovery of Oil From Spent Coffee Grounds for Biofuel Production,” Waste Biomass Valorization, vol. 10, no. 2, pp. 253–264, 2019, doi: 10.1007/s12649-017-0061-4.