In an era characterized by rapid economic growth, globalization, and pressing environmental challenges, the role of education in advancing sustainability has become paramount. This paper's primary focus is on sustainability, aiming to provide meaningful insights into the function of educational attainment, specifically lifelong learning, in promoting sustainable development. The paper's novel approach lies in its data-driven perspective, utilizing international indices to quantify the relationship between educational metrics and the UN Sustainable Development Goals. This paper adopts a quantitative, index-based methodology to compare lifelong learning performance across four countries with similar economic circumstances, utilizing sustainability indicators from the SDG Index, Youth Progress Index, and Social Progress Index. The key findings reveal that while Estonia exhibited leading performance, Hungary's index value declined between 2016 and 2022. In contrast, Turkey demonstrated the most substantial improvement during this period, despite starting from the lowest point. The paper emphasizes the importance of carefully managing educational incentives and innovations to strengthen the alignment between sustainability and lifelong learning, particularly in addressing specific sustainability challenges through targeted ESG strategies.

Urban lighting systems contribute significantly to energy consumption and light pollution, raising environmental and societal concerns. This paper explores the potential of Artificial Intelligence (abbreviation: AI)-driven adaptive urban lighting as a sustainable solution, framed within a multi-level perspective on socio-technical transitions. At the landscape level, increasing urbanization and global sustainability targets exert pressure for energy-efficient practices, while traditional street lighting regimes remain largely rigid and resource-intensive. At the niche level, we propose a novel adaptive lighting system integrating real-time Internet of Things (abbreviation: IoT) sensor data and machine learning algorithms to dynamically adjust illumination based on traffic, pedestrian activity, weather conditions, and ambient light. Studies demonstrate that the proposed approach can significantly reduce energy use while minimizing light pollution, without compromising safety or visibility. The results indicate that such niche innovations, supported by AI and renewable energy integration, have the potential to influence broader regime change and contribute to sustainable urban development. This research highlights the importance of combining technological innovation with socio-technical frameworks to address pressing urban environmental challenges, offering insights for policymakers, urban planners, and energy managers seeking to balance efficiency, safety, and ecological impact.

Članek obravnava povezavo med korozivno močjo prsti in skalnimi oblikami v apnencu. V ta namen so vzorcem iz različnih škrapljiπč, drugih oblik kraškega površja in vrtač v Severni Angliji, določili pH in delež karbonatov. Rezultati meritev so potrdili, da so oblike pod kislo prstjo globlje in da prisotnost apnenca močno zvišuje pH prsti.The goal of the research was to verify the connection between the solutional power of soil and the shape of rocky features in limestone. Soil samples from runnels, grikes, foot of pavements, top of limestone, grass patches and dolines were collected on limestone pavement areas of North England and examined for the pH and carbonate content. The results of the measurements proved that the soils with lower pH are related to deeper solution features and that proximity to limestone causes a higher soil-pH.

Microplastic (MP) pollution in river systems has become an increasing environmental concern, particularly in transboundary rivers such as the Danube. This study provides the first detailed assessment of microplastic contamination in the Szigetköz section of the Danube and its major tributary, the Mosoni-Danube. Depth-resolved pumped water samples were collected at three locations (Rajka, Mecsér and Gönyű) and analysed using Fourier Transform Infrared (FTIR) spectroscopy combined with automated spectral evaluation. MP concentrations showed a clear downstream increase, with average values of 83.8 particles/m³ at Rajka, 237.6 particles/m³ in the Mosoni-Danube at Mecsér, and 795.9 particles/m³ at Gönyű. Polyethylene (PE) was the dominant polymer in the tributary (70.6%), whereas both PE and alkyd resins were prevalent at the main Danube sites (Rajka: alkyd 37.7%, PE 31.8%; Gönyű: alkyd 39.9%, PE 37.3%). Particle size distribution also shifted downstream, with a higher proportion of smaller (50–100 μm) particles detected at Gönyű compared to upstream sites. The results suggest that the tributary may represent an important input to the main Danube channel in this section, while differences in polymer composition point to varying source characteristics within the study area. These findings provide an important baseline for future monitoring and support the development of targeted mitigation strategies in this transboundary river system.

In the near future, food production will encounter numerous challenges. The world’s population, per capita intake of calories, protein, and cereals is growing, and expected to continue increasing in the future. According to the World Resources Institute, feeding 9-10 billion people by 2050 will require a 70% increase in food calorie compared to 2006 levels. The expansion of crop and livestock production, the increasing use of fertilisers and pesticides at global level, and the growing adoption of precision farming methods may not be appropriate in the light of problems such as soil degradation, the impact of climate change on yields, the depletion of fish stocks and the reduction of arable land per capita in certain areas. Mitigation of food waste can be a possible way to sustainable food supply but it alone cannot solve the problem. The paper focuses on examining disparities in the generation of food waste from a spatial and sustainability perspective within EU-countries. Data related to food waste and various environmental, social and economic indicators are collected for EU countries. Correlation between these parameters is investigated to find possible connections. Cluster analysis is applied to food waste data to find the groups of countries with similar characteristics. The distribution of environmental, economical, and social parameters is calculated for these groups, and statistical methods are applied to investigate their differences.

The aim of our research was the identification of nosocomial pathogens found in the internal drinking water network of healthcare facilities which can cause infections in hospitals. In this study, the composition of bacterial communities from the internal water network of a health institution in Győr (Hungary) was examined using standard culturebased methods. Identification of the bacterial isolates was performed using Analytical Profile Index (API). Members of 13 bacterial taxa were recovered from a multi-storey healthcare institution. 10 species were identified via API20E and API20NE testing, out of which isolates of generaAeromonas, Pseudomonas andSphingomonaswere found in the highest proportion on different media. These bacteria can cause nosocomial infections in clinical environments, leading to serious illnesses mainly in patients, as they may have multiresistance genes. In addition,Legionellaspecies were also identified in the water samples, which are also known to be nosocomial pathogens, since they can be spread with aerosols in hospital environments and can cause severe respiratory diseases in immunocompromised individuals.