Search Results (30)

Flotation was investigated to treat incineration fly ash with diesel, kerosene, TX-100, or SDS as a collector and methyl isobutyl carbinol (MIBC) or 2-Octyl alcohol as a frother. Fly ash was separated into light and residual materials. Comparison of yield, carbon and sulfur removal showed that kerosene and MIBC showed the best performance. The results revealed that flotation was a method that could simultaneously achieve the removal of organics and S-containing compounds. Specifically, approximately 7.63–9.45% of the total mass was collected as light material, which was enriched with organic carbon. Contents of organic carbon reached 14.35 wt%–14.56 wt% in the light materials from those of 2.74 wt%–3.52 wt% in the original fly ash. Elemental analysis further proved that sulfur was also accumulated in light material. Approximately 78.84–81.69% of the organic carbon and 80.47–82.66% of the sulfur were removed. Decarbonization was primarily achieved through the flotation of organic materials, while desulfurization resulted from both flotation and the dissolution of soluble salts. Furthermore, the contents of the chloride and heavy metals in the residual fly ash also decreased. Particle size analysis showed that flotation was effective in the removal of smaller particles, and those particles were also rich in heavy metals. Overall, by selecting the right collector and frother, flotation was also able to reduce the leaching toxicity of heavy metals. The residual fly ash was safe for further disposal. Organic carbon, sulfur and heavy metals were accumulated in the light materials, which accounted for less than 10% of the original mass. The portion of fly ash needing further treatment was therefore greatly reduced. Full article

The accurate prediction of hydrocracking product yields is crucial for optimizing resource allocation and improving production efficiency. However, the prediction of product flowrates in hydrocracking units often faces challenges due to insufficient data and weak correlations between input and output variables. This study proposes a hybrid framework combining a Convolutional Neural Network–Long Short-Term Memory (CNN-LSTM) model, mechanism modeling, and Particle Swarm Optimization (PSO) to address these issues. The CNN-LSTM captures spatiotemporal dependencies in operational data, while the mechanism model incorporates domain-specific physical constraints. The hybrid model is structured in both series and parallel configurations, with PSO optimizing key hyperparameters to enhance its predictive performance. The results demonstrate significant improvements in prediction accuracy, with determination coefficients (R²s) reaching 0.896 (kerosene), 0.879 (residue), 0.899 (heavy naphtha), and 0.78 (light naphtha). Shapley Additive Explanations (SHAP) and Mutual Information Coefficient (MIC) analyses highlight the mechanism model’s role in improving feature interpretability. This study underscores the efficacy of integrating kinetics modeling, deep learning, and metaheuristic optimization for complex industrial processes under data constraints, offering a robust approach to enhance hydrocracking yield prediction. Full article

The increasing requirement for distillates, accompanied by higher quantities of heavy crude oil in world production, has positioned gas oil hydrocracking as one of the most significant processes in refineries. In the petrochemical industry, hydrocracking is an essential process that converts heavy hydrocarbons into lighter and more valuable products such as LPG (liquefied petroleum gas), diesel, kerosene, light naphtha, and heavy naphtha. This method uses hydrogen and a catalyst to break down the gas oil feedstock through hydrogenation and hydrocracking reactions. However, the gas oil hydrocracking process faces significant technical, economic, and financial obstacles that must be overcome to reveal its full potential. In this study, a computer-assisted technical–economic evaluation and an evaluation of the technical–economic resilience of the gas oil hydrocracking process at an industrial scale was carried out. Twelve technical–economic and three financial indicators were evaluated to identify this type of process’s current commercial status and to analyze possible economic performance parameter optimizations. The economic indicators listed include gross profit (GP), profitability after taxes (PAT), economic potential (EP), cumulative cash flow (CCF), payback period (PBP), depreciable payback period (DPBP), return on investment (ROI), internal rate of return (IRR), net present value (NPV), annual cost/revenues (ACR), break-even point (BEP), and on-stream efficiency at the BEP. On the other hand, the financial indicators proposed by the methodology are earnings before taxes (EBT), earnings before interest and taxes (EBIT), and earnings before interest, taxes, depreciation, and amortization (EBITDA). The technical–economic resilience of the process was also evaluated, considering the costs of raw materials, the market prices of the products, and processing capacity. The gas oil hydrocracking plant described, with a useful life of 20 years and a processing capacity of 1,937,247.91 tonnes per year, achieved a gross profit (GP) of USD 58.97 million and a return after tax (PAT) of USD 39.77 million for the first year, operating at maximum capacity. The results indicated that the process is attractive under a commercial approach, presenting a net present value (NPV) of USD 68.87 million at the end of the last year of operation and a cumulative cash flow (CCF) of less than one year⁻¹ (0.34 years⁻¹) for the first year at full processing capacity, which shows that in this process, variable costs have more weight on the economic indicators than fixed costs. Full article

Poverty reduction and the promotion of sustainable human development are fundamentally dependent on having access to modern energy services. Energy supplies that are dependable, reasonably priced, and sustainable are vital to modern societies. In achieving the sustainable development goals (SDG7) and access to clean energy supplies, this study, using cross-sectional data from 180 randomly sampled rural households, analyzed the key factors determining the choice and intensity of energy sources used for lighting and cooking in rural Nigeria. Both descriptive and inferential statistics (multivariate probit (MVP) and zero-truncated Poisson (ZTP models)) were employed for the analyses. The result showed that there is evidence of fuel stacking in their choice of cooking and lighting energy, and it increases with rising income levels but is more pronounced for lighting than cooking. The result also revealed that reliable access to clean energy (9% of sampled households for LPG and 23% of the households for grid electricity) is very low, as these households still rely on fuelwood (70%) for cooking, but the predominant usage of kerosene (39%) for lighting, as reported in the literature, has drastically changed to dry cell battery (51%). The results using a multivariate probit model to capture the multiple fuel usage phenomenon among rural households show that access to clean energy, improvement in rural poverty, usage of indoor kitchens, household size, and an increase in the education of household heads’ spouses significantly influence the use of clean energy in the rural areas. In the same vein, the result of the ZTP model showed that income, access to energy sources, and occupation of the household head were the drivers of the intensity of cooking and lighting energy sources. Thus, it is recommended that any policy interventions that are targeted at encouraging rural households to use clean energy should start by improving rural access to these clean energy sources, improving their poverty status while also increasing the level of education and awareness of rural women concerning the risks of using dirty energy sources. Full article

This paper introduces a novel and cost-effective method for detecting adulterated diesel, specifically targeting contamination with kerosene, by leveraging machine learning and the refractive index values of mixed diesel samples. It proposes a laser-based sensor, employing COMSOL simulations for synthetic data generation to facilitate machine learning training. This innovative approach not only streamlines the detection process by eliminating the need for expensive equipment and specialized personnel but also enables on-site testing without extensive sample preparation. The sensor’s design, utilizing light refraction and reflection principles, allows for the accurate measurement of diesel adulteration levels. Validation results showcase the machine learning models’ high precision in predicting adulteration percentages, as evidenced by an R-squared value of 0.999 and a mean absolute error of 0.074. This research signifies a leap in sensor technology, offering a practical solution for rapid diesel adulteration detection, especially in developing countries, by minimizing reliance on advanced laboratory analyses. The sensor’s design aligns with the requirements for low-cost IoT technology, presenting a versatile tool for various applications. Full article

This study analyzed the impact of LED light on bioemulsifier production by Aureobasidium pullulans LB83 in solid-state fermentation (SSF) using pre-treated sugarcane bagasse (PSB). The biomass was subjected to alkaline pre-treatment and conducted fermentations in Erlenmeyer flasks containing 2 g of PSB that were immersed in a humectant solution with a cell concentration of 10⁸ cells/mL. The screening involved varying LED light wavelengths (green, red, orange, and blue) over a 7-day period at 28 °C. Notably, under the influence of blue light, the process achieved maximum production, yielding an EI_24% of 63.9% and 45.1% for soybean oil and kerosene, respectively. Prolonged exposure to blue light for 11 days at 28 °C resulted in maximum bioemulsifier production (75%) and cellulolytic enzyme activity (3.67 IU g⁻¹ for endoglucanase and 0.41 IU g⁻¹ for exoglucanase) with soybean oil and kerosene. Experiments in a bioreactor, with varying light conditions (dark, white light, and blue LED light), demonstrated that the blue LED bioreactor outperformed others, achieving EI_24% values of 55.0% and 45.7% for soybean oil and kerosene, respectively. The scanning electron microscopy (SEM) confirmed yeast growth under these conditions after 9 days. Our findings highlight the significant potential of LED light to enhance bioemulsifier production by A. pullulans LB83 from PSB. Full article

A novel clay-coated mesh was fabricated via a simple brush-coating method without the use of special equipment, chemical reagents, and complex chemical reactions and operation processes. Possessing superhydrophilicity and underwater superoleophobicity, the clay-coated mesh can be used for efficiently separating various light oil/water mixtures. The clay-coated mesh also exhibits excellent reusability, maintaining a high separation efficiency of 99.4% after 30 repeated separations of the kerosene/water mixture. Full article

Photoelectric smoke detectors are used for early detection of building fires, and sensitivity adjustment is generally performed using white smoke generated by the burning of filter paper. Therefore, when black smoke of the same concentration is introduced, the detector is often not activated. To address this problem, differences in the distribution of light scattered by smoke of various colors were analyzed. A light-scattering chamber with a light-receiving unit for various scattering angles was constructed to measure the scattered light generated inside the chamber of the smoke detector. The light scattering distribution was measured for smoke generated from three combustibles—filter paper (white smoke), kerosene (black smoke), and polyurethane (gray-black smoke)—and three analysis criteria were applied. By identifying a section where the measured values were concentrated for a specific analysis criterion and scattering angle, it was confirmed that some combustibles can be distinguished. Specifically, criterion III, a probabilistic section, was presented to determine which combustible smoke particles were close by applying the proposed section in a complex manner. A preliminary study was conducted to evaluate a methodology for the color classification of smoke particles flowing into a smoke detector chamber; this can be utilized as a foundation for determining optical properties. Full article

Palm oil is, from an economic, environmental, and social point of view, a vegetable oil with great potential and the state of Pará-Brazil is Brazil’s great producer. In addition, soap phase residue or palm oil neutralization sludge (PONS), a byproduct of the neutralization step of the chemical refinement of palm oil, is produced, posing a huge problem for waste disposal and management in the production process of refined palm oil (RPO). In this context, this work aims to systematically investigate the economic analysis of the thermal–catalytic process of crude palm oil (CPO) and palm oil neutralization sludge (PONS). The thermocatalytic processes of CPO and PONS carried out at pilot scale and their economic feasibility were analyzed. The yields of biofuels produced by fractional distillation were also presented. The physicochemical properties of CPO and PONS, as well as those of organic liquid products obtained by the thermal–catalytic process of CPO and PONS were taken into account in the economic analysis. In addition, the chemical composition organic liquid products obtained by thermal–catalytic process of CPO and PONS, as well as its distillation fractions (green gasoline, green kerosene, green light diesel and heavy diesel), used as key factors/indicators on the economic analysis. The analysis of the key factors/indicators from the thermocatalytic processes of CPO and PONS showed economic viability for both crude palm oil (Elaeis guineensis, Jacq) and palm oil neutralization sludge. The minimum fuel selling price (MFSP) obtained in this work for the biofuels was 1.59 USD/L using crude palm oil (CPO) and 1.34 USD/L using palm oil neutralization sludge (PONS). The best breakeven point obtained was of 1.24 USD/L considering the PONS. The sensibility analysis demonstrated that the pyrolysis and distillation yields are the most important variables that affect the minimum fuel-selling price (MFSP) in both economic analyses. Full article

In this work, a techno-economic assessment of the production of bio-oil, coke and gas, via thermo-catalytic pyrolysis followed by distillation, is accomplished. The raw materials were two solid wastes: lipid-based material (residual fat/scum from a fat retention box from the University Restaurant at the Federal University of Pará—UFPA) and a lignin-cellulosic material of açaí seed (Euterpe oleracea Mart.). From the literature, a review is made of the physicochemical analysis of the raw materials, of the bio-oil, and of the chemical composition of the biofuels produced (kerosene, light diesel, and heavy diesel). The bio-oil yields for each experiment of pyrolysis and distillation are also presented and compared with the literature. The economic indicators for the evaluation of the most viable cracking (pyrolysis) and distillation process of bio-oils were: (a) the simple payback criterion, (b) discounted payback, (c) net present value (NPV), (d) internal rate of return (IRR), and (e) index of profitability (IP). The analysis of the indicators showed the economic viability of the lipid-based material and unfeasibility for the açai seed (Euterpe oleracea Mart.). The breakeven point obtained was 1.28 USD/L and the minimum fuel selling price (MFSP) obtained in this work for the biofuels was 1.34 USD/L). The sensibility analysis demonstrated that the pyrolysis and distillation yields are the most important variables to affect the minimum fuel selling price (MFSP). Full article

Conventional storable bipropellants make use of hydrazine and its derivatives as fuels and nitrogen tetroxide as an oxidizer. In recent years, the toxicity character of these chemicals pushed the propulsion community towards “green” alternatives. Several candidates have been proposed among existing and newly developed chemicals, highlighting the need for a common and robust selection methodology. This paper aims at reviewing the most important selection criteria in the field of toxicity and discusses how to objectively define a green propellant, considering both the health and environmental hazards caused by the chemicals. Additionally, consistent figures of merit in the field of safety and handling operations and performance are proposed. In particular, operating temperatures, flammability and stability issues are discussed in the framework of physical hazards and storage requirements, while vacuum impulses, adiabatic flame temperature and sooting occurrence of the investigated couples are compared to the UDMH/NTO benchmark case. Hydrogen peroxide and nitrous oxide, and light hydrocarbons, alcohols and kerosene are selected from the open literature as promising green oxidizers and fuels, respectively. The identified methodology highlights merits and limitations of each chemical, as well as the fact that the identification of a universally best suited green couple is quite impractical. On the contrary, the characteristics of each propellant lead to a scenario of several “sub-optimal” couples, each of them opportunely fitting into a specific mission class. Full article

Plastic has made our lives comfortable as a result of its widespread use in today’s world due to its low cost, longevity, adaptability, light weight and hardness; however, at the same time, it has made our lives miserable due to its non-biodegradable nature, which has resulted in environmental pollution. Therefore, the focus of this research work was on an environmentally friendly process. This research work investigated the decomposition of polypropylene waste using florisil as the catalyst in a salt bath over a temperature range of 350–430 °C. A maximum oil yield of 57.41% was recovered at 410 °C and a 40 min reaction time. The oil collected from the decomposition of polypropylene waste was examined using gas chromatography-mass spectrometry (GC-MS). The kinetic parameters of the reaction process were calculated from thermogravimetric data at temperature program rates of 3, 12, 20 and 30 °C·min⁻¹ using the Ozawa–Flynn–Wall (OFW) and Kissinger–Akahira–Sunnose (KAS) equations. The activation energy (Ea) and pre-exponential factor (A) for the thermo-catalytic degradation of polypropylene waste were observed in the range of 102.74–173.08 kJ·mol⁻¹ and 7.1 × 10⁸–9.3 × 10¹¹ min⁻¹ for the OFW method and 99.77–166.28 kJ·mol⁻¹ and 1.1 × 10⁸–5.3 × 10¹¹ min⁻¹ for the KAS method at a percent conversion (α) of 0.1 to 0.9, respectively. Moreover, the fuel properties of the oil were assessed and matched with the ASTM values of diesel, gasoline and kerosene oil. The oil was found to have a close resemblance to the commercial fuel. Therefore, it was concluded that utilizing florisil as the catalyst for the decomposition of waste polypropylene not only lowered the activation energy of the pyrolysis reaction but also upgraded the quantity and quality of the oil. Full article

The polyolefin to lighter molecules reaction reduces the waste-plastic residues to produce fuels and valuable chemicals. Commercial MgO light and CaO were used as catalysts for the direct polyethylene and polypropylene liquefaction in N₂ or CO₂ atmospheres. The products were analyzed (ATR-FTIR, GC-FID/TCD, GC-FID, density, refractive index). The use of MgO light and CaO improved the conversion of propylene and ethylene to liquid products. In addition, low gaseous and solid products yields were obtained. A good production of organic liquids in the gasoline, diesel and kerosene boiling range was obtained. The use of CO₂, in some cases, led to a higher conversion into liquids compared with the reactions performed in the N₂ atmosphere. In addition, the use of the CO₂ atmosphere led to a higher content of products with a boiling range in the diesel and kerosene ranges. Full article

In the recent past, the world in general and Pakistan in particular faced a drastic fuel price change, affecting the economic productivity of the country. This has drawn the attention of empirical researchers to analyze the abrupt change in fuel prices. This study takes a lead and investigates for the first time, in the literature related to Pakistan, the presence of multiple fuel price bubbles, with the purpose of knowing if the price driver is due to demand or it is exuberant consumer behavior that prevails and contributes to a sudden boom in fuel price series. The empirical analysis is performed through a recently proposed state-of-the-art generalized sup ADF (GSADF) approach on six commonly used fuel price series, namely, LDO (light diesel oil), HSD (high-speed diesel), petrol, natural gas, kerosene, and MS (motor spirit). The bubble analysis for each of the six fuel price series is based on monthly data from July 2005 to August 2020. The findings provide evidence of the existence of multiple bubbles in all series considered. Specifically, four bubbles are detected in each of the kerosene and natural gas price series, whereas three bubbles are noted in each of the HSD, LDO, petrol and MS price series. The maximum duration of occurrence of bubbles is of 12 months for kerosene. The date-stamping of the bubbles shows that the financial crisis of 2008 contributed to the emergence of bubbles that pushed oil prices upward and caused a depreciation in the national currency. Full article

This work investigates the effect of production scales (laboratory, bench, and pilot) by pyrolysis of Açaí (Euterpe oleracea Mart.) seeds at 450 °C and 1.0 atmosphere, on the yields of reaction products and acid value of bio-oils. The experiments were carried out in batch mode using a laboratory scale reactor of 143 mL, a bench scale reactor of 1.5 L, and a pilot scale reactor of 143 L (≈1:10:1000). The bio-oil was obtained in pilot scale, fractionated by distillation to produce biofuel-like fractions. The distillation of bio-oil was carried out in a laboratory column. The physical-chemistry properties (density, kinematic viscosity, acid value, and refractive index) of bio-oils and distillation fractions were determined. The qualitative analysis was determined by FT-IR and the chemical composition by GC-MS. The pyrolysis showed bio-oil yields from 4.37 to 13.09 (wt.%), decreasing with reactor volume. The acid value of bio-oils varied from 68.31 to 70.26 mg KOH/g. The distillation of bio-oil produced gasoline, light kerosene, and kerosene-like fuel fractions, and the yields were 16.16, 19.56, and 41.89 (wt.%), respectively. The physical-chemistry properties of distillation fractions increase with temperature. The FT-IR analysis of bio-oils and distillation fractions identified the presence of functional groups characteristic of hydrocarbons (alkenes, alkanes, aromatics, and aromatics rings) and oxygenates (carboxylic acids, ketones, esters, ethers, alcohols, phenols). The GC-MS identified 48.24 (area.%) hydrocarbons and 51.76 (area.%) oxygenates in the bio-oil produced in bench scale and 21.52 (area.%) hydrocarbons and 78.48 (area.%) oxygenates in the bio-oil produced in pilot scale. The gasoline-like fraction was composed by 64.0 (area.%) hydrocarbons and 36.0 (area.%) oxygenates, light kerosene-like fraction by 66.67 (area.%) hydrocarbons and 33.33 (area.%) oxygenates, and kerosene-like fraction by 19.87 (area.%) hydrocarbons and 81.13 (area.%) oxygenates. Full article