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Reducing fuel consumption to decrease CO2 emissions has become a key development factor in the automotive industry. An effective way to decrease fuel consumption is to reduce the influence of various sources of energy loss. One way to increase engine efficiency is to use low-viscosity engine oils to reduce friction losses in the engine’s tribological systems. The aim of the article was to analyze the relationship between the type of engine oil and fuel consumption in a group of 12 passenger cars. This was a homogenous group of identical cars, equipped with the same engine, operated under very similar conditions. Three groups of engine oils (Revline, Total, Orlen) were tested in vehicles and stressed with comparable workloads. The experiment was conducted over two years (two stages of research). The collected results were presented using graphs and compared using statistical tests, split into two stages of research, with four seasonal temperature groups. The study provides a detailed description of fuel consumption differences taking into account variations in ambient temperature. The analyses were focused on finding answers to two research questions: does the type of engine oil affect the variation in combustion levels, and what is the variability of fuel consumption in different seasons due to the ambient temperature variability? Briefly, in both stages of the study, vehicles using Revline oil attained the highest average fuel consumption throughout the study period. Vehicles using Total oil showed similar results to those using Revline oil, with the difference in fuel consumption not as noticeable during warmer months. Conversely, vehicles using Orlen oil demonstrated the lowest fuel consumption values during colder months, but higher levels during warmer months.

The objective of this study is to develop a statistical model to accurately estimate the total base number (TBN) value of diesel engine oils on the basis of the Fourier transform infrared spectroscopy (FTIR) analysis. The research sample consisted of oils used in the course of 14,820 km. The samples were collected after each 1000 km and both FTIR and TBN measurements were performed. By applying the measured absorbance values, five statistical models aimed at predicting TBN values were elaborated with the use of the following information: aggregated values of measured absorbance in defined spectral ranges, extremes at wavenumbers, or the surface area of spectral bands related to the vibrations of specific molecular structures. The obtained models may be considered a continuation and an extension of previous studies of this type described in the literature on the subject. The results of the study and the analysis of the obtained data have led to the development of two models with high predictive capabilities (R2 > 0.98, RMSE < 0.5). Another model, which had the smallest number of variables in comparison to other models, had markedly lower R2 value (0.9496) and the highest RMSE (0.5596). Yet another model, where the dimensionality of the pre-processed full spectra was reduced to four aggregates through averaging, turned out to be slightly worse than the best one (R2 = 0.9728). The study contributes to a more in-depth understanding of the FTIR-based TBN prediction tools that may be readily available to all interested parties.

The aim of this study was to evaluate the influence of simultaneous, long-term exposure to increasing concentrations of three classes of antimicrobials (β-lactams, fluoroquinolones and nitroimidazoles) on: (1) the efficiency of anaerobic digestion of sewage sludge, (2) qualitative and quantitative changes in microbial consortia that participate in methane fermentation, and (3) fate of antibiotic resistance genes (ARGs). Long-term supplementation of sewage sludge with a combination of metronidazole, amoxicillin and ciprofloxacin applied at different doses did not induce significant changes in process parameters, including the concentrations of volatile fatty acids (VFAs), or the total abundance of ARGs. Exposure to antibiotics significantly decreased methane production and modified microbial composition. The sequencing analysis revealed that the abundance of OTUs characteristic of Archaea was not correlated with the biogas production efficiency. The study also demonstrated that the hydrogen-dependent pathway of methylotrophic methanogenesis could significantly contribute to the stability of anaerobic digestion in the presence of antimicrobials. The greatest changes in microbial biodiversity were noted in substrate samples exposed to the highest dose of the tested antibiotics, relative to control. The widespread use of antimicrobials increases antibiotic concentrations in sewage sludge, which may decrease the efficiency of anaerobic digestion, and contribute to the spread of antibiotic resistance (AR).

The conversion of cattle manure into biogas in anaerobic digestion (AD) processes has been gaining attention in recent years. However, antibiotic consumption continues to increase worldwide, which is why antimicrobial concentrations can be expected to rise in cattle manure and in digestate. This study examined the long-term synergistic effects of antimicrobials on the anaerobic digestion of cattle manure. The prevalence of antibiotic resistance genes (ARGs) and changes in microbial biodiversity under exposure to the tested drugs was investigated using a metagenomic approach. Methane production was analyzed in lab-scale anaerobic bioreactors. Bacteroidetes, Firmicutes, and Actinobacteria were the most abundant bacteria in the samples. The domain Archaea was represented mainly by methanogenic genera Methanothrix and Methanosarcina and the order Methanomassiliicoccales. Exposure to antibiotics inhibited the growth and development of methanogenic microorganisms in the substrate. Antibiotics also influenced the abundance and prevalence of ARGs in samples. Seventeen types of ARGs were identified and classified. Genes encoding resistance to tetracyclines, macrolide–lincosamide–streptogramin antibiotics, and aminoglycosides, as well as multi-drug resistance genes, were most abundant. Antibiotics affected homoacetogenic bacteria and methanogens, and decreased the production of CH4. However, the antibiotic-induced decrease in CH4 production was minimized in the presence of highly drug-resistant microorganisms in AD bioreactors.

The content of heavy metals Cd, Cr, Cu, Fe, Ni, Pb and Zn in ash samples from miscanthus, oak, pine, sunflower husk, wheat straw, and willow ashes burned at 500, 600, 700, 800, 900, and 1000 °C, respectively, was determined. The statistical analysis of the results was based on multivariate methods: hierarchical cluster analysis (HCA), and principal component analysis (PCA), which made it possible to classify the raw materials ashed at different temperatures into the most similar groups, and to study the structure of data variability. Using PCA, three principal components were extracted, which explain more than 88% of the variability of the studied elements. Therefore, it can be concluded that the application of multivariate statistical techniques to the analysis of the results of the study of heavy metal content allowed us to draw conclusions about the influence of biomass properties on its chemical characteristics during combustion.

Turkmenistan is currently one of the key suppliers in the global natural gas market, and it is important to examine its competitive position in the world. The aim of this article is to forecast the development strategy of its gas sector. To achieve this aim, the authors first examined: (1) Turkmenistan’s position in the global gas market and the structure of its oil and gas sector; (2) the share of gas in Turkmenistan’s exports. They then conducted an analysis of the causal relationship between FDI and GDP. The above research made it possible to conduct a comprehensive SWOT analysis. Based on the SWOT analysis, three sector development scenarios were developed: pessimistic, realistic, and optimistic. On their basis, the gas sector in Turkmenistan can build strategies for its development, considering the impact of market and non-market factors.

The paper presents results of numerical simulations and experimental investigations of a cyclone with a square inlet and different dimensions of a vortex finder. Investigations were conducted for five, different cyclone models. The main goal of the research was to determine the influence of cyclone vortex finder geometry (diameter, length) on key parameters for a cyclone operation, such as: gas flow pattern, gas velocity and pressure distribution, pressure drop and collection efficiency. The analysis of flow pattern inside the cyclone was carried out with the use of CFD (Computational Fluid Dynamics) simulations, verified using CTA (Constant Temperature Anemometry). Similarly, pressure distributions, pressure drop and collection efficiency for cyclones were determined numerically and with measurements. The study demonstrated that dimensions of the vortex finder have a significant effect on a cyclone performance. The numerical visualisations of flow showed some unfavorable and beneficial effects and phenomena that may occur in cyclones. Moreover, the smallest pressure drop (305 Pa) was predicted for the cyclone with a maximum diameter of the vortex finder (De = 0.105 m), the largest (358 Pa) when this diameter was the smallest (De = 0.075 m). The tests did not show any significant influence of the vortex finder length on the pressure drop in a cyclone. A different tendency was observed in the case of collection efficiency. The maximum value of this parameter (89.5%) was predicted for the cyclone with the shortest vortex finder (s = 0.060 m), minimum (85.5%) when the vortex finder was the longest (s = 0.220 m). In this case, however, tests did not show a significant impact of an outlet diameter on the collection efficiency. Results and conclusions presented in this paper can be practically used for design optimization of cyclone separators, and also to select their operating parameters.

Waste solid residue from the hydrothermal extraction of pectin derived from sugar beet pulp was used as feedstock in the production of 5-hydroxymethylfurfural (5-HMF). The depolymerization of pectin-free sugar beet pulp (PF-SBP) to monosaccharides and their dehydration to 5-HMF were conducted in subcritical water using a batch reactor. The experimental design methodology was used in order to model the hydrothermal process and to optimize the operational parameters of the reaction, namely temperature and holding time. These parameters are required to achieve the highest yield of 5-HMF. The model predicts, in good agreement with experimental results (R2 = 0.935), an optimal yield of 5-HMF (of approximately 38% in relation to the cellulosic fraction content in the PF-SBP) at a temperature of 192.5 °C and a holding time of about 51.2 min. 5-HMF was successfully isolated from the reaction mixture using the liquid–liquid extraction method. The results are suitable for industrial upscaling and may become an incentive to introduce a new, environmentally friendly, uncomplicated, and efficient waste treatment method. The method would be used to treat products from the sugar refining industry, the treatment of which has proven to be problematic until now.

The primary objective of the research was to compare the viscosity parameters of the same viscosity grade engine oils, as declared by the manufacturers, to the actual laboratory measurements. The secondary objective was to briefly investigate (1) what kind of information oil manufacturers provide in the product data sheets of the studied oils, and (2) the potential savings resulting from the use of the energy efficient oils. The study material consisted of 42 selected synthetic engine oils that belong to the 5W-30 viscosity grade. Stabinger SVM 3001 viscometer was used to determine kinematic viscosity at −20 °C, 40 °C, 100 °C and 130 °C. The HTHS (high temperature high shear), CCS (cold cranking simulator), FTIR (Fourier-transform infrared spectroscopy) and GC (Gas Chromatography) measurements were also performed for the samples that had the lowest and the highest kinematic viscosity. Large differences (5–25%) between oil producers’ declarations and the results of laboratory tests were found. Although all of the engine oils tested met the 5W-30 grade standards, the high variability of viscosity measurements needs to be reported. The difference between the oil with the highest and the oil with the lowest kinematic viscosity at −20 °C was 11,804 mm2/s. The outlying temperature-related viscosity profiles were recovered using Mahalanobis distances which identified 16 out of 42 analyzed oil samples as atypical.

The aim of the article was to analyze the decision-making process of professional drivers regarding the choice of new engine oil with additional attention to the eco-friendliness aspect of the product. Survey data were collected from Polish consumers, using a self-administered questionnaire. The main data analysis tools used in the study were finite mixture models. It was found that professional drivers do not constitute a single homogenous group. They cluster into two segments with differing importance profiles. The largest consumer segment, over 80% of consumers, consider the quality classification, viscosity classification, and OEM specifications as the most important criteria during the decision-making process. The importance of oil being environmentally friendly is a factor moderately differentiating the subgroups. In the first segment, a strong preference for engine oil with the same technical parameters as the previously purchased one, but additionally marked as environmentally friendly, was indicated by 29% of the respondents, whereas in the second segment by only 15%. The analysis of the consumer decision-making process showed that there is a need to put additional efforts to provide easily accessible and clearly visible technical specifications on the product label. The vast majority of professional drivers surveyed were mainly guided by such specific data in their purchasing process. Engine oils and specially used engine oils belong to a group of products that are considered to have a major negative impact on the environment. As a result, more research is needed into the sustainability of this class of products. The shift into the eco-friendly production, exploitation and subsequent management of engine oils may cause a profound effect on petroleum energy markets.