Sewage sludge, a by-product of wastewater treatment, is garnering increasing attention in the pursuit of closed-loop economy practices due to its highly beneficial fertilizing properties. However, like any technique, using sewage sludge as fertilizer has potential and limitations. Heavy metals within sewage sludge are a primary limitation curtailing its application as a fertilizer. This study collected sewage sludge samples from four wastewater treatment plants and soil from potential application sites. The mobility of heavy metals was then examined using a sequential BCR analysis. Furthermore, a comprehensive environmental risk assessment associated with the agricultural use of sewage sludge was conducted, using various risk indicators such as I_geo and Nemerov, to compare the cumulative metal concentrations in the sewage sludge and soil. Additionally, risk assessment codes, ecological risk indices of metal mobility, and environmental risk indices were calculated, specifically focusing on the mobility of metals in the soil environment. This research demonstrates that sewage sludge failing to meet conventional criteria for agricultural use based on total metal content does not necessarily pose a high-risk application. Understanding the mobility forms of metals in sewage sludge is crucial, influencing the analysis of their potential utilization. Importantly, sewage sludge from wastewater treatment plants utilizing biological bed technology tends to exhibit a higher tendency of heavy metals to exist in mobile forms, migrating within the soil environment.

This study presents a comprehensive analysis of the potential utilization of sewage sludge in agriculture, focusing on the assessment of heavy metal contaminants and their mobility in sewage sludge-soil mixtures. The innovative approach of investigating heavy metal fractions in these mixtures sheds light on their environmental implications. In this study, sludge and soil samples from three different soil categories were collected, and the mobility of heavy metals was investigated using sequential BCR analysis. A thorough assessment of the risk of environmental contamination associated with the agricultural use of sludge was also carried out. This study included the calculation of various risk indicators, such as the Geoaccumulation Index of heavy metals in soil (Igeo), the risk assessment code (RAC), and the author’s element mobility ratio (EMR), which included a comparison of the overall metal concentrations in sludge, soil, and mixtures. This study demonstrates that the key to using sludge is to know the form of mobility of the metals present in the sludge and how they behave once they are introduced into the soil.

The global scientific community is intensively promoting energy-plus buildings. Following the leading world trends, this paper presents a new energy-plus building concept—elevational earth-sheltered buildings with three different types of horizontal overhang photovoltaic-integrated panels: wooden support columns covered with clay tiles, steel pipes as support columns covered with sheet steel, and concrete support columns with concrete coverage. In this instance, the specific multi-numerical case study building model for the city of Kragujevac (located in central Serbia with favorable climatic conditions) was performed over 7 months (from 1 October to 30 April), taking into account the soil temperature, the effects of solar shading, the performance of the heating system—a ground source heat pump—and the characteristics of the artificial and automatic lighting control system. The simulation results show that the optimal depth of a horizontal overhang (energy-plus status) depends on the occupant’s habits, in addition to meteorological conditions. The presented methodology can be used for any other location, both in Europe and the world.

This paper presents an analytical method for the dimensioning and selection of the four glass tube collector types: single-glazed with an air layer, single-glazed with a vacuum layer, double-glazed with an air layer, and double-glazed with a vacuum layer. In the first part of the paper (dimensioning phase), the iterative thermal resistance calculation algorithms were developed for all glass tube collector types, whereby the iterative thermal resistance calculation algorithm of the single-glazed tube collector with an air layer was experimentally tested and validated. The second part of the paper (selection phase) uses a multi-criteria decision-making method to determine the optimal glass tube collector design. Unlike other papers, three indicator groups are taken into account in this case: geometric (mass, surface occupation, total surface occupation, volume occupation), economic (manufacturing and exploitation costs), and ecological (embodied energy and greenhouse gas emission). The proposed method is characterized by simple and fast calculations with satisfactory accuracy, which avoids high investment costs (experimental research), approximation and discretization of physical models (numerical research), and a large number of input parameters with boundary conditions (theoretical research). It should be noted that, with certain additions and changes, it can also be applied to other solar thermal collectors, so the authors believe such tools are handy for the global scientific public.

Photovoltaic (PV) modules undergo comprehensive testing to validate their electrical and thermal properties prior to market entry. These evaluations consist of durability and efficiency tests performed under realistic outdoor conditions with natural climatic influences, as well as in controlled laboratory settings. The overall performance of PV cells is affected by several factors, including solar irradiance, operating temperature, installation site parameters, prevailing weather, and shading effects. In the presented study, three distinct PV modules were analyzed using a sophisticated large-scale steady-state solar simulator. The current–voltage (I-V) characteristics of each module were precisely measured and subsequently scrutinized. To augment the analysis, a three-layer artificial neural network, specifically the multilayer perceptron (MLP), was developed. The experimental measurements, along with the outputs derived from the MLP model, served as the foundation for a comprehensive global sensitivity analysis (GSA). The experimental results revealed variances between the manufacturer’s declared values and those recorded during testing. The first module achieved a maximum power point that exceeded the manufacturer’s specification. Conversely, the second and third modules delivered power values corresponding to only 85–87% and 95–98% of their stated capacities, respectively. The global sensitivity analysis further indicated that while certain parameters, such as efficiency and the ratio of V_oc/V, played a dominant role in influencing the power-voltage relationship, another parameter, U, exhibited a comparatively minor effect. These results highlight the significant potential of integrating machine learning techniques into the performance evaluation and predictive analysis of photovoltaic modules.

Although the European residential sector has promoted various heating and cooling passive solar systems in many ways, ongoing climate changes affect these construction elements at an annual level. Using the weather files for three years in the recent past (2018, 2021 and 2023), this paper numerically investigates the energy, environmental and economic performance of two small single-family houses equipped with Trombe walls and fixed horizontal overhangs of different depths (0 m, 0.25 m, 0.5 m, 0.75 m and 1 m) for two characteristic European climate zones: continental (Kielce city, Poland) and moderate continental (Kragujevac city, Serbia). Both houses were created in Google SketchUp 8 software using current Statistical data and Rulebooks of energy efficiency, while adopted heating (gas boiler and radiators) and cooling (individual air-conditioning units) active thermo-technical systems were simulated in EnergyPlus 7.1 software using official specific energy, environmental and economic indicators. Compared to the appropriate reference houses—without mentioning passive solar systems—the main results of this study are as follows: (1) higher outdoor air temperatures can reduce final (thermal) energy consumption for heating by 37.74% (for the Kielce climate zone) and 52.49% (for the Kragujevac climate zone); (2) higher outdoor air temperatures can increase final (electricity) energy consumption for cooling between 5.71 and 11.75 times (for Kielce) and 4.36 and 9.81 times (for Kragujevac); (3) percentage savings of primary energy consumption and monetary savings are highest when houses are equipped with Trombe walls and 1 m deep overhangs; and (4) all considered cases of passive solar systems do not contribute to the reduction of greenhouse gas emissions. Since climate change is a consequence of greenhouse gas emissions, priority should be given to environmental indicators in future investigations.