Greenhouse gases such as carbon dioxide and methane cause global warming and consequently climate change. Great efforts are being made to reduce greenhouse gas emissions with the objective of addressing this problem, hence the popularity of technologies conductive to reducing greenhouse gas emissions. CO₂ emissions can be reduced by improving the thermal efficiency of combustion engines, for example, by using cogeneration systems. Coal mine methane (CMM) emerges due to mining activities as methane released from the coal and surrounding rock strata. The amount of methane produced is primarily influenced by the productivity of the coal mine and the gassiness of the coal seam. The gassiness of the formation around the coal seam and geological conditions are also important. Methane can be extracted to the surface using methane drainage installations and along with ventilation air. The large amounts of methane captured by methane drainage installations can be used for energy production. This article presents a quarterly summary of the hourly values of methane capture, its concentration in the methane–air mixture, and electricity production in the cogeneration system for electricity and heat production. On this basis, neural network models have been proposed in order to predict electricity production based on known values of methane capture, its concentration, pressure, and parameters determining the time and day of the week. A prediction model has been established on the basis of a multilayer perceptron network (MLP).

Increasing emissions from mining areas and a high global warming potential of methane have caused gas management to become a vital challenge. At the same time, it provides the opportunity to obtain economic benefits. In addition, the use of combined heat and power (CHP) in the case of coalbed methane combustion enables much more efficient use of this fuel. The article analyses the possibility of electricity production using gas engines fueled with methane captured from the Budryk coal mine in Poland. The basic issue concerning the energy production from coalbed methane is the continuity of supply, which is to ensure the required amount and concentration of the gas mixture for combustion. Hence, the reliability of supply for electricity production is of key importance. The analysis included the basic characterization of both the daily and annual methane capture by the mine’s methane drainage system, as well as the development of predictive models to determine electricity production based on hourly capture and time parameters. To forecast electricity production, predictive models that are based on five parameters have been adopted. Models were prepared based on three time variables, i.e., month, day, hour, and two values from the gas drainage system-capture and concentration of the methane. For this purpose, artificial neural networks with different properties were tested. The developed models have a high value of correlation coefficient. but showed deviations concerning the very low values persisting for a short time. The study shows that electricity production forecasting is possible, but it requires data on many variables that directly affect the production capacity of the system.

Legal requirements for the use of refrigerants increasingly restrict the use of high-global warming potential (GWP) refrigerants. As a result, there is a growing interest in natural refrigerants and in those belonging to the hydrofluoroolefins (HFO) class, which can be used on their own or in mixtures. One of them is the R1234ze(E) refrigerant, an alternative to the R134a refrigerant as well as being a component of numerous mixtures. The knowledge of thermodynamic and transport properties of refrigerants is required for the analysis and calculation of refrigeration cycles in refrigeration, air conditioning, or heating systems. The paper presents analytical equations for calculating the properties of the R1234ze(E) refrigerant in the state of saturation and in the subcooled liquid and superheated vapour regions that do not require numerical calculations and are characterised by small deviations. The Levenberg–Marquardt algorithm—one of the methods for non-linear least squares estimation—was used to develop them. A total of 26 equations were formulated. The formulated equations were statistically verified by determining absolute and relative deviations between the values obtained from CoolProp software and calculated values. The maximum relative deviation was not higher than 1% in any of them.

The air swirl diffusers are popular for the ceiling level air supply system and have been widely used for Indoor Air Quality. They are nowadays one of the most popular diffusers commonly used in airconditioning systems [1, 2]. The swirl diffusers are intended to use in low- and medium-pressure ventilation systems. They allow for obtaining the swirl airflow and are especially recommended to use in spaces with the height from 3m up to 12m, where heating and cooling is performed by the ventilation system and where the exact setting of supply air velocity is important [3-6]. In the case of swirl diffusers,fluid flow is usually significantly influenced by the characteristics of different diffuser designs. In the ventilation system design phase, a typically focus on ventilation effectiveness and takes into account a large number of parameter. However, the discrepancy between design and practice are often experienced mainly because operating conditions don’t correspond to the designing conditions [7-9]. Inthis work, the airflow of swirl diffuser has been studied using Particle Image Velocimetry (PIV) method to analyse the mean airflow and geometry influence on the results. The paper presents a comparison of the results of velocity field measurements using the PIV method and the results obtained by means ofnumerical analysis CFD. Based on the analysis the velocity flow field was evaluated and the range of effective operation of the diffuser have been determined [10].

During the extraction of hard coal in Polish conditions, methane is emitted, which is referred to as ‘mine gas’. As a result of the desorption of methane, a greenhouse gas is released from coal seams. In order to reduce atmospheric emissions, methane from coal seams is captured by a methane drainage system. On the other hand, methane, which has been separated into underground mining excavations, is discharged into the atmosphere with a stream of ventilation air. For many years, Polish hard coal mines have been capturing methane to ensure the safety of the crew and the continuity of mining operations. As a greenhouse gas, methane has a significant potential, as it is more effective at absorbing and re-emitting radiation than carbon dioxide. The increase in the amount of methane in the atmosphere is a significant factor influencing global warming, however, it is not as strong as the increase in carbon dioxide. Therefore, in Polish mines, the methane–air mixture captured in the methane drainage system is not emitted to the atmosphere, but burned as fuel in systems, including cogeneration systems, to generate electricity, heat and cold. However, in order for such use to be possible, the methane–air mixture must meet appropriate quality and quantity requirements. The article presents an analysis of changes in selected parameters of the captured methane–air mixture from one of the hard coal mines in the Upper Silesian Coal Basin in Poland. The paper analyses the changes in concentration and size of the captured methane stream through the methane capturing system. The gas captured by the methane drainage system, as an energy source, can be used in cogeneration, when the methane concentration is greater than 40%. Considering the variability of CH₄ concentration in the captured mixture, it was also indicated which pure methane stream must be added to the gas mixture in order for this gas to be used as a fuel for gas engines. The balance of power of produced electric energy in gas engines is presented. Possible solutions ensuring constant concentration of the captured methane–air mixture are also presented.

Post-industrial cities across Europe are undergoing profound transformation, where sustainable building design plays an increasingly strategic role in redefining urban identity and function. The transition toward sustainable urban environments requires innovative construction technologies and performance-driven standards. This study examines the role of sustainable building design in post-industrial urban regeneration, focusing on Katowice, Poland—a city undergoing significant socio-spatial and economic transformation. Through descriptive case studies of selected buildings, the research highlights how high-performance construction techniques, including advanced insulation, energy-efficient ventilation, and integrated daylighting, contribute to prestigious certifications while reducing energy demand for heating, cooling, and lighting. Beyond technical performance, the analyzed projects demonstrate how sustainable buildings can act as catalysts for post-industrial urban renewal, fostering social engagement, environmental responsibility, and architectural innovation. The novelty of this work lies in linking building-scale sustainability interventions with city-scale urban transformation dynamics, offering practical insights for similar post-industrial contexts in Central and Eastern Europe. This research provides the first comparative analysis of certified and non-certified sustainable buildings in the context of post-industrial regeneration in this region. The post-industrial revitalization of Katowice is largely driven by advancements in building energy systems, such as high-efficiency HVAC technologies and other sustainable solutions. The findings demonstrate that sustainable architecture can act as a tangible driver of social, economic, and spatial renewal, providing practical insights for post-industrial regeneration strategies across similar urban contexts.