The natural processes of interactions between aerosol particles in the ambient air through which they agglomerate is a vast area of chamber research and are inherent to many industries and are often inter-connected with transport engineering. Further improvement of symmetric methods for aerosol particle number and mass concentration reduction made it possible to create various synergic techniques. The study used a 1.9 TDI diesel internal combustion engine, which was supplied with diesel (D100) and second-generation biofuels (NExBTL100) with the EGR exhaust system on and off. Measurements were performed using a Bruel and Kjær “Type 9727” system for measurement of vibrations, a scanning mobility particle sizer (SMPS) and an original agglomeration chamber. The three modes of particle size distributions were observed in the size range from 10 to 470 nm for both D100 and NExBTL100 fuels with and without the use of the EGR system. The application of 21.3 kHz frequency sound with SPL 144.1 dB changed the NExBTL100 generated aerosol particle number concentration but did not sufficiently affect the concentration of D100 emitted particles. The greatest agglomeration effect (21.7 ± 10.0%) was observed in the range of extremely small NExBTL100 derived particles (10–70 nm) when used in combination with an EGR system.

Statistical regression models have rarely been used for engine exhaust emission parameters. This paper presents a three-step statistical analysis algorithm, which shows increased prediction accuracy when using vibration and sound pressure data as a covariate variable in the exhaust emission prediction model. The first step evaluates the best time domain statistic and the point of collection of engine data. The univariate linear regression model revealed that non-negative time domain statistics are the best predictors. Also, only one statistic evaluated in this study was a statistically significant predictor for all 11 exhaust parameters. The ecological and energy parameters of the engine were analyzed by statistical analysis. The symmetry of the methods was applied in the analysis both in terms of fuel type and in terms of adjustable engine parameters. A three-step statistical analysis algorithm with symmetric statistical regression analysis was used. Fixed engine parameters were evaluated in the second algorithm step. ANOVA revealed that engine power was a strong predictor for fuel mass flow, CO, CO₂, NO_x, THC, CO_Sick, O₂, air mass flow, t_exhaust, whereas type of fuel was only a predictor of t_air and t_fuel. Injection timing did not allow predicting any exhaust parameters. In the third step, the best fixed engine parameter and the best time domain statistic was used as a model covariate in ANCOVA model. ANCOVA model showed increased prediction accuracy in all 11 exhausted emission parameters. Moreover, vibration covariate was found to increase model accuracy under higher engine power (12 kW and 20 kW) and using several types of fuels (HVO30, HVO50, SME30, and SME50). Vibration characteristics of diesel engines running on alternative fuels show reliable relationships with engine performance characteristics, including amounts and characteristics of exhaust emissions. Thus, the results received can be used to develop a reliable and inexpensive method to evaluate the impact of various alternative fuel blends on important parameters of diesel engines.

The removal of particulate matter (PM) from air streams is essential for advancing environmental technologies and safeguarding public health. This study explores the performance of an electrostatic precipitator (ESP) in eliminating fine and ultra-fine PM under varied experimental conditions. It uniquely examines the influence of PM size and feed rate on ESP removal efficiency. The system’s use of low voltages enhances energy sustainability, while its innovative design improves corona discharge, leading to significant reductions in fine and ultra-fine PM emissions. Plants using electrical devices are increasingly being incorporated into material processing lines to reduce pollution in the surrounding work area, as well as to collect particle emissions in the atmosphere. It is also possible to recycle some raw materials in this way with low energy consumption. This cleaning technology increases the added value of industrial equipment, which affects its competitiveness and its impact on sustainable manufacturing. The experimental results indicate a steady electrostatic field voltage of 15.1 kilovolts, with an airflow maintained at 0.8 m/s through a doser at 2.5 bar, eliminating the need for a fan. The PM feed rate varied between 2 and 20 mm/h, with six trials conducted to ensure the data were consistent. Preliminary studies devoid of ESP intervention demonstrated little PM removal, since buildup on the chamber walls distorted the results. The installation of the ESF markedly enhanced the removal efficiency, achieving up to 95.5%. Further analysis revealed that ESP performance depended on PM concentration in the agglomeration chamber, achieving a clearance rate exceeding 98% under optimal conditions. Fine PM (0.35 to 8.7 µm) was more efficiently removed than ultra-fine PM (0.2 to 0.35 µm). The highest removal efficiency was observed at a feed rate of 0.962 mg/s, while the lowest occurred at 0.385 mg/s. A strong positive correlation between particle concentration and removal efficiency (Pearson value up to 0.829) was observed, particularly at feed rates of 0.128, 0.641, and 1.283 mg/s. The study’s findings confirm that the ESP is highly effective in removing particulate matter, particularly fine and ultra-fine particles, with an optimal feed rate, significantly enhancing the system’s performance.

Energy (including thermal) needs are growing rapidly worldwide thus leading to increased energy production. Considering stricter requirements for the employment of non-renewable energy sources, the use of biofuel in energy facilities appears as one of the best options, having high potential for growth that will increase in the long run both in the Baltic region and the European Union as a whole. This publication investigates the possibilities of using various blends of biofuel containing lignin for heat production and emissions to the air during combustion processes. The paper examines the chemical composition of lignin and bottom ash and explores the impact of a different ratio of lignin in the fuel mixture, the effect of the power of biofuel combustion plants (boilers) and the influence of fuel supply to the combustion chamber on gaseous pollutants (CO, NO_x, SO₂) and particulate matter emissions. The results of the conducted study demonstrate that, in contrast to pure lignin, the concentrations of alkali metals, boron and, to a lesser extent, nickel and chlorine have increased the most in bottom ash. The use of lignin can effectively reduce the need for conventional biofuel by 30–100% and to increase the temperature of exhaust gases. The lowest emissions have been observed using a mixture of 30% of lignin and biofuel at the lowest range of power (2.5–4 MW). Under the optimal oxygen/temperature mode, carbon monoxide concentrations are approximately 20 mg/Nm³ and those of nitrogen oxides–500 mg/Nm³. Particulate matter emissions reach 150 mg/Nm³, and hence applying air treatment equipment is required.

Biogas has increasingly been used as an alternative to fossil fuels in the world due to a number of factors, including the availability of raw materials, extensive resources, relatively cheap production and sufficient energy efficiency in internal combustion engines. Tightening environmental and renewable energy requirements create excellent prospects for biogas (BG) as a fuel. A study was conducted on a 1.6-L spark ignition (SI) engine (HR16DE), testing simulated biogas with different methane and carbon dioxide contents (100CH₄, 80CH₄_20CO₂, 60CH₄_40CO₂, and 50CH₄_50CO₂) as fuel. The rate of heat release (ROHR) was calculated for each fuel. Vibration acceleration time, sound pressure and spectrum characteristics were also analyzed. The results of the study revealed which vibration of the engine correlates with combustion intensity, which is directly related to the main measure of engine energy efficiency—break thermal efficiency (BTE). Increasing vibrations have a negative correlation with carbon monoxide (CO) and hydrocarbon (HC) emissions, but a positive correlation with nitrogen oxide (NO_x) emissions. Sound pressure also relates to the combustion process, but, in contrast to vibration, had a negative correlation with BTE and NO_x, and a positive correlation with emissions of incomplete combustion products (CO, HC).

The work of traditional cyclones is based on the separation of solid particles using only the centrifugal forces. Therefore, they do not demonstrate high gas-cleaning efficiency, particularly in the cases where gas flows are polluted with fine solid particles (about 20 µm in diameter). The key feature of a new-generation multi-channel cyclone separator’s structure is that its symmetrical upgraded curved elements, with openings cut with their plates bent outwards, make channels for the continuous movement of the gas flows from the inflow opening to the central axis. The smoke flue of the vertical gas outflow is located near the cover of the separating chamber. The present work is aimed at studying the applicability of two various viscosity models and their modified versions to simulate aerodynamic processes in an innovative design for a multi-channel cyclone separator with a single inflow, using the computational fluid dynamics. The research results obtained in the numerical simulation are compared to the experimental results obtained using a physical model. The main purpose of this study is to provide information on how the new design for the multi-channel cyclone affects the distribution of gas flow in the cyclone’s channels. The modified viscosity models, k-ε and k-ω, and computational meshes with various levels of detailed elaboration were analyzed. The developed numerical models of a single-inlet multi-channel cyclone separator allow the researchers to describe its advantages and possible methods of improving its new structure. The developed models can be used for simulating the fluid cleaning phenomenon in the improved fourth-channel cyclone separator and to optimize the whole research process.