In this paper, dynamic simulations of the seasonal coefficient of performance (SCOP) of Air-Source Heat Pumps will be presented by considering three different heat pump systems coupled with the same building located in three different Italian municipalities: S. Benedetto del Tronto (42°58′ North, 13°53′ East), Milan (45°28′ North, 9°10′ East), and Livigno (46°28′ North, 10°8′ East). Dynamic simulations were conducted by employing the software package TRNSYS and by considering real weather data (i.e., outdoor air temperature and humidity as well as solar radiation) referring to the three abovementioned cities for a period of 8 years (2013–2020) and collected from on-site weather stations. Attention has been paid to the modeling of the heat pump defrost cycles in order to evaluate their influence on the unit’s seasonal performance. Results show that, when referring to different years, the thermal energy demand displays huge variations (in some cases it can even double its value), while the effective SCOP is characterized by scarce variability. Sensible variations in SCOP values are achieved for Livigno.

Indoor air quality (IAQ) plays a vital role in supporting both the physical and mental well-being of individuals in enclosed spaces, and the role of mechanical ventilation systems has gained increasing attention due to building design’s focus on energy efficiency and thus airtight constructions. This study investigated the pre–post effects of installing a heat recovery mechanical ventilation system (MVHR) on indoor air quality in a high school classroom in Ferrara, Italy. The analysis focused on experimental measurements of temperature (T), relative humidity (RH), and carbon dioxide (CO₂) both inside and outside the same classroom, which had constant occupancy (17 students) for an entire school year, allowing a comparison between natural and mechanical ventilation. With a comprehensive approach, particulate matter (PM_2.5), volatile organic compounds (VOCs), and radon levels (Rn) were monitored as well, after the installation of the MVHR. By comparing natural and mechanical ventilation, the study highlights the strengths and limitations of the ventilation system implemented, together with an evaluation of the system’s energy consumption, including a 2 kW post-heating battery. In terms of results, the MVHR demonstrated clear benefits in managing CO₂ levels and improving sensory, olfactory, and psychophysical well-being, as well as the attention levels of students. In detail, under natural ventilation, peak concentrations exceeded 4500 ppm, while mechanical ventilation kept them below 1500 ppm. The average CO₂ concentration during occupancy dropped from 2500 ppm to around 1000 ppm, achieving a 62% reduction. However, beneficial effects were not observed for other parameters, such as PM_2.5, VOCs, or radon. The latter displayed annual average values around 21 Bq/m³ and peaks reaching 56 Bq/m³.

The coefficient of performance (COP) is a crucial metric for evaluating the efficiency of heat pump systems. Real-time monitoring of heat pump system performance necessitates continuously collecting and processing data from various components utilizing multiple sensors and controllers. This process is inherently complex and presents significant challenges. In recent years, artificial intelligence (AI) models have increasingly been applied in refrigeration, heat pump, and air conditioning systems due to their capability to identify and analyze complex patterns and data relationships, demonstrating higher accuracy and reduced computation time. In this study, multilayer perceptron (MLP), support vector machines (SVM), and random forest (RF) are used to develop COP prediction models for solar-assisted heat pumps. By comparing the predictive accuracy and modeling time of the three models built, the results demonstrate that the random forest model achieves the best prediction performance, with a mean absolute error (MAE) of 2.42% and a root mean squared error (RMSE) of 4.01% on the train set. On the test set, the MAE was 2.35% and the RMSE was 3.84%. The modeling time for the RF model was 6.57 s.

In agreement with the decarbonization of the building sector to meet the 2050 climate neutrality targets, borehole thermal storage for solar energy represents a potential solution to increase the energy efficiency of renewable energy plants. As is well known, electricity is not the optimum solution to integrate large inflows of fluctuating renewable energy. In the present paper, we investigate the possibility to use the solar collector to give energy to the borehole field. In detail, a solar-assisted geothermal heat pump is applied to a school located in Milan, Italy. In winter, both the energy from the solar collector and the heat pump are collected into a storage tank connected to the emission terminals, whereas, in summer, as there is no energy demand, the hot water from the solar collector flows into the geothermal probes. By means of this seasonal thermal energy storage technology, the intermittent solar energy collected and stored during the summer months can be utilized during the winter months when the heating demand is high. A long-term dynamic analysis is performed by employing Trnsys. The results show that solar collectors coupled with ground-source heat pumps can give an important contribution to the soil temperature drift, and this also applies in cases of un-balanced loads during the heating season. Moreover, the employment of solar collectors increases the seasonal coefficient of performance of the heat pumps and may rise to reductions to the probes field.

In the framework of reducing carbon dioxide emissions and energy consumption, the energy retrofit of existing buildings plays a significant role and is often supported by numerical analyses of the planned activities and expected results. This study analyses a public building (a kindergarten) located in Bialystok (Poland) and aims to determine the building’s energy performance prior to and after thermal modernization. The building was examined by employing two different software packages, Audytor OZC 7.0 Pro and Trnsys 18. The thermal efficiency improvement applied to the renovated building in Bialystok was also analyzed by virtually locating the building in Bologna (Italy). Moreover, a comfort analysis focused on the classrooms of the kindergarten was carried out employing Trnsys. As a novelty, in the analysis, particular attention is paid to ventilation losses and to the influence of envelope elements properties on the building energy demand. The results arising from analyses were compared to real consumption data for the heating season. The results obtained from the two software programs display excellent agreement, and they also match the real consumption data if the heating demand is considered, while some differences arise when the cooling demand is considered.

The circular economy model is based on the 4R framework—reduce, reuse, recycle, and recover. While recycling was the primary focus in the past, the shortage of raw materials and the desire to reduce carbon footprints have led to a change in focus: end-of-life materials are now considered resources rather than waste. When discharged, end-of-life materials still possess properties that can be exploited. For this reason, a comprehensive characterization of reusable materials is mandatory to reduce waste and increase material availability. The reuse of waste materials, such as surgical masks, is of particular interest in giving people in disadvantaged contexts the opportunity to self-produce and self-install panels within their homes, with the dual result of improving indoor comfort and increasing human capital. This paper focuses on the identification of a possible second application for surgical face masks through experimental characterization. Panels made of masks were tested for water vapor permeability, thermal conductivity, and fire resistance and their use as insulating material in the building sector was discussed. Based on the results, surgical face masks are suitable as thermal insulating materials, do not pose safety concerns, and can reduce energy consumption and improve thermal comfort when installed indoors.