The changes in geopolitical and ecological conditions brought about the need to use environmentally friendly sources of vehicle power. This impacted the accelerated activities related to the use of hydrogen fuel in transport means. Based on the observations carried out in the countries of Central and Eastern Europe, it was found that the process of implementing hydrogen-powered vehicles in public transport is connected with difficulties faced by transport companies with regard to the purchase of these transport means. This study aims to analyse the conditions for making decisions regarding the implementation of hydrogen-powered buses in urban transport. A case study was considered, and the factors influencing the decisions related to the application of hydrogen-powered buses in Poland were analysed. The survey method was used to carry out the research. A questionnaire was developed, and the survey was conducted among representatives of transport companies that provide public transport services in Polish cities. As a result of the research, it was found that city authorities play a key role in deciding on the implementation of hydrogen-powered buses. The highest ranks among the proposed criteria influencing the decision on the purchase of hydrogen-powered buses were the economic ones. The concerns and benefits resulting from the potential purchase of hydrogen-powered buses were also examined. It was revealed that the decision to buy buses is most influenced by factors such as ensuring access to hydrogen and its price. The recommendations for transport companies and city authorities were formulated.

In today's highly competitive industrial environment, continuous improvement of efficiency and optimization of processes is crucial. This paper presents an approach to the optimization of conveyor systems that uses the concept of a digital shadow. A digital shadow, as an exact digital replica of a physical conveyor system, enables detailed simulation and analysis of real operational data, providing a basis for in-depth analysis and identification of areas for improvement. The aim of this approach is not only to improve the understanding of the dynamics and performance of existing conveyor systems, but also to increase the overall efficiency through predictive simulations and optimization algorithms. In this work, we demonstrate how the integration of a digital shadow into the simulation process can contribute to a better reaction to changes in the production environment, to the reduction of downtime and to the optimization of production flows. Our methodology combines data collection / analysis, and enables the creation of accurate and flexible models of conveyor systems. These models are then used in simulations that help identify optimal settings for different production scenarios and predict potential problems before they occur. The results of applying our approach on a test laboratory line show a significant improvement in efficiency and a reduction in operating costs. This study provides important insights and practical guidelines for engineers and production managers focused on the use of digital shadow to increase the efficiency of conveyor systems. It also contributes to the development of intelligent production technologies in the era of Industry 4.0.