The indoor environmental quality of a building has attracted everyone’s attention since a worldwide pandemic was declared and forced people indoors. After several months, people were able to return to their usual activities, but with strict safety measures added due to the circumstances. This paper focuses on the impact of safety measures on students’ thermal comfort, a case study performed in a continental climate zone, during the winter. The methodology used involved the collection of both quantitative and qualitative data. Descriptive statistics and frequencies alongside correlations and cross-tabular methods were used to analyze the collected data. The results indicated that the predicted mean vote (PMV) underestimated students’ thermal perception. A difference of 1.5 °C was found between the operative neutral temperature of the PMV and students’ thermal sensation votes while wearing masks. Likewise, a lower neutral operative temperature was found for students wearing masks than for those without masks. Students wearing masks preferred a slightly cooler environment and a significant difference was found (p = 0.001) between students’ thermal comfort votes. All of these findings indicate that there is a potential for energy savings without affecting students’ thermal comfort.

The paper analyses the power-quality effects of connecting LED luminaires to street lighting installations. The power quality impact of LED luminaires and the implementation of smart control systems are discussed. Several power-quality measurements have been performed to determine the effect of connecting multiple LED luminaires to the electrical power network. Three LED street lighting systems were selected, each equipped only with LED luminaires of different power ratings and numbers, produced by different manufacturers. The measurements were performed at the lighting connection box, and the results are presented and discussed for each case.

This article demonstrates how positioning residents as active co-designers fundamentally transforms both the process and outcomes of carbon-positive building development. Through structured collaborative workshops, shared decision-making protocols, and continuous partnership throughout the building lifecycle, the REN+HOMES Positive Carbon Building methodology challenges the conventional expert-driven approach to sustainable construction. Developed and validated through the H2020 REN+HOMES project, this resident-centered approach achieved remarkable technical performance—65.9% reduction in final energy demand—while simultaneously enhancing community ownership and long-term sustainability practices. By integrating participatory design with Zero Emissions Building (ZEB) criteria, renewable energy systems, and national carbon offset programs, the methodology proves that resident collaboration is not merely beneficial but essential for creating buildings that truly serve both environmental and human needs. This research establishes a new paradigm where technical excellence emerges from authentic partnership between residents and sustainability experts, offering a replicable framework for community-driven environmental regeneration.

The increasing demand for the energy-efficient and occupant-centred operation of educational buildings requires accurate and interpretable models capable of predicting indoor environmental conditions under real operating constraints. This study proposes a residual learning-enhanced grey-box modelling framework for predicting indoor air temperature and assessing indoor environmental quality indicators in a KNX-enabled educational building operating under simple thermostatic heating control. The approach combines a reduced-order discrete-time RC thermal model with a data-driven machine learning component trained to model the next-step residual between measured and simulated indoor temperatures. High-resolution KNX monitoring data were recorded at a 5 min sampling interval over three consecutive months (October–December) during the heating season. Using a chronological 70/30 train–test split, the identified RC grey-box model achieved a pooled test RMSE of 0.269 °C, an MAE of 0.126 °C, and an R² of 0.987. The proposed hybrid formulation achieved RMSE = 0.343 °C, MAE = 0.106 °C, and R² = 0.978 across 62,456 test samples. While the pooled RMSE remains influenced by occasional larger deviations in a small number of rooms, the hybrid model yields a consistent reduction in absolute error (≈16% MAE reduction) and reduced inter-room variability compared to the physics-based baseline. These results indicate that residual learning can enhance predictive robustness under decentralized thermostatic operation and limited sensing, while preserving physical interpretability. The proposed framework provides a practical and scalable solution for indoor temperature prediction and IEQ assessment in educational buildings using existing KNX automation data.

The present article outlines the Positive Carbon Building certification's pioneering approach, aiming to establish a clear and rigorous methodology for buildings that are not only neutral in their environmental impact but are net positive. This certification challenges the industry by setting a higher bar — achieving net positivity. The approach does not just mitigate harm but actively contributes to environmental regeneration, thereby pushing the construction and real estate sectors towards innovative practices and collaborations. It calls for a reevaluation of how buildings are designed, constructed, and operated, encouraging the incorporation of renewable energy sources, energy-efficient designs, and materials with lower embodied carbon. This ambition signifies a move towards structures that produce more energy than they consume annually, thereby offering a surplus to the energy grid and reducing their carbon footprint comprehensively. This certification intends to work in conjunction with existing green building certifications, emphasizing net-positive energy production and ensuring alignment with both European and national legislations concerning nearly Zero Energy Buildings (nZEB) [1]. Traditionally, the focus has been on minimizing the negative environmental impacts of buildings, but the methodology for Positive Building Certification will mark a significant shift in the conceptualization of green building standards.

In order to design a ventilation system based on the volumetric airflow rate, which will ensure satisfactory indoor air quality and, at the same time, do not oversize the system, it is necessary to know the quantities of pollutants emissions. The concentration of produced pollutants allows the calculation of the required fresh air volumetric flow rate. Two previous published studies are analysed in this article, whose results complement each other. From the calculated values, the graphical dependence between the required fresh air volumetric flow rate and the level of physical activity was developed. It was noticed that, according to the Slovak and Romanian legislation, for the studied gym, there is insufficient air ventilation. At an allowed maximum CO2 concentration level of 1,000 ppm, the required fresh air volumetric flow rate, according to legislative requirements, will ensure a percentage of only 75.59% to 23.25% of the necessary rate (depending of the type of physical activity). For a lower allowed maximum CO2 concentration level, the ensured fresh air volumetric flow rate will be even smaller. The aim of the article is to contribute to the development of healthy environments in fitness centres and gyms and to optimize the design requirements for their