Creating products and services that satisfy individual and community needs is impossible without raw materials. This study takes a novel approach by integrating the economic dynamics and raw material consumption indicators of the European Union (EU). The study uses different econometric methods to analyze the relationship between GDP (gross domestic product) and the EU’s raw material consumption (RMC) from 2014–2023. Among the results, the panel data analysis model shows that the resource productivity of the EU improved during the period under review, whereas the material intensity decreased significantly. These trends significantly contributed to the relative decoupling of material consumption from GDP in the last decade. The results of the K-means cluster analysis highlight the regional economic differences within the EU. According to the results of the correlation analysis, EU member countries differ significantly in the efficiency of raw material use. Nevertheless, five member countries are robustly vulnerable to large-scale raw material use. The divergence calculation results show that while some countries use raw materials extremely efficiently to produce GDP, others achieve low efficiency. This unique approach and the resulting findings provide a new perspective on the complex relationship between economic growth and raw material use in the EU.

This research introduces a novel framework integrating stochastic finite element analysis (FEA) with advanced circular statistical methods to optimize heat pump efficiency under material uncertainties. By modeling directional variability in thermal conductivity using both uniform and Von Mises distributions, the study highlights the superiority of the Von Mises distribution in providing consistent and efficient thermal performance. The Von Mises distribution, known for its concentration around a mean direction, demonstrates a significant advantage over the uniform distribution, resulting in higher mean efficiency and lower variability. The findings underscore the importance of considering both stochastic effects and directional consistency in thermal systems, paving the way for more robust and reliable design strategies.

Electricity generation around the world is mainly produced by using non-renewable energy sources especially in the commercial buildings. However, Rooftop solar Photovoltaic (PV) system produced a significant impact on environmental and economical benefits in comparison to the conventional energy sources, thus contributing to sustainable development. Such PV’s system encourages the production of electricity without greenhouse gas emissions that leads to a clean alternative to fossil fuels and economic prosperity even in less developed areas. However, efficiency of rooftop solar PV systems depends on many factors, the dominant being geographical (latitude, longitude, and solar intensity), environmental (temperature, wind, humidity, pollution, dust, rain, etc.) and the type of PV (from raw material extraction and procurement, to manufacturing, disposal, and/or recycling) used. During the feasibility analysis of the environment, geographical conditions are keep in well consideration, but the pollution level of the city is always overlooked, which significantly influences the performance of the PV installations.     

Therefore, this research work focused on the performance of rooftop solar PV installed in one of the most polluted city in India. Here, the loss in power generation of rooftop solar PV has been studied for the effect of deposited dust particles, wind velocity before and after the cleaning of the panels. The actual data has been utilized for the calculation of the energy efficiency and power output of the PV systems. According to the results, it has been concluded that dust deposition, wind speed and pollution level in city significantly reduces the efficiency of solar photovoltaic panel. Hence, an overview of social and environmental impacts of PV technologies is presented in this paper along with potential benefits and pitfalls.

The properties of the beta batteries are compared, which are made on the basis of the different β-isotopes with beta decay. Tritium and Ni-63 make it possible to make β-sources of high activity, without harmful associated emissions, with low self-absorption, emitting high-energy β-electrons that penetrate deep into the semiconductor and generate a large number of electron-hole pairs. The efficiency of beta batteries needs to be analyzed based on the real energy distribution of β-electrons. It makes possible to obtain the real value of the energy absorbed inside the β-source, correctly estimate the amount of self-absorption of the β-electrons and part of the β-electronsthere is a penetrate into the semiconductor, the number of electrons and holes that are generated in the semiconductor, and the magnitude of the idling voltage. Formulas for these quantities are calculated in this paper.

Two kinds of solar thermal power generation systems (trough and tower) are selected as the research objects. The life cycle assessment (LCA) method is used to make a systematic and comprehensive environmental impact assessment on the trough and tower solar thermal power generation. This paper mainly analyzes the three stages of materials, production and transportation of two kinds of solar thermal power generation, calculates the unit energy consumption and environmental impact of the three stages respectively, and compares the analysis results of the two systems. At the same time, Rankine cycle is used to compare the thermal efficiency of the two systems.