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An agrovoltaic system combines agricultural crop production and energy production in the same place, emphasizing the dual use of land. This article provides a bibliometric analysis of agrivoltaic topics based on publications indexed in SCOPUS, in which either economic assessments of agrivoltaics, agrivoltaic systems for crops and livestock animals, photovoltaic greenhouse and agrivoltaics with open field are discussed, or its ideas are used to analyze certain locations. A bibliometric analysis was conducted using the SCOPUS database. Multiple bibliometric tools, such as R Studio and Biblioshiny, were applied to analyze data for this study. Finally, 121 relevant articles were obtained and reviewed. The results show that the focus topic is a brand-new research area, with the majority of relevant scientific publications concentrated in the last three years, and with much ongoing research. This is why AV-specialized scientific conferences might be the best place to get relevant and up-to-date information, with the highest number being offered in the USA and China. A typical trend in recent years has been researched, focusing on different agricultural aspects. The research results show that scientific publications in recent years mainly focus on short-term predictions, there is no recognized evaluation standard for various prediction analyses, and it is difficult to evaluate various prediction methods so far.

Spatial planning has to deal with trade-offs between various stakeholders’ wishes and needs as part of planning and management of landscapes, natural resources and/or biodiversity. To make ecosystem services (ES) trade-off research more relevant for spatial planning, we propose an analytical framework,which puts stakeholders, their land-use/management choices, their impact on ES and responses at the centre. Based on 24 cases from around the world, we used this framing to analyse the appearance and diversity of real-world ES trade-offs. They cover a wide range of trade-offs related to ecosystem use, including: land-use change, management regimes, technical versus nature-based solutions, natural resource use, and management of species. The ES trade-offs studied featured a complexity that was far greater than what is often described in the ES literature. Influential users and context setters are at the core of the trade-off decision-making, but most of the impact is felt by non-influential users. Provisioning and cultural ES were the most targeted in the studied trade-offs, but regulating ES were the most impacted. Stakeholders’ characteristics, such as influence, impact faced, and concerns can partially explain their position and response in relation to trade-offs. Based on the research findings, we formulate recommendations for spatial planning.

Machine learning (ML) methods has recently contributed very well in the advancement of the prediction models used for energy consumption. Such models highly improve the accuracy, robustness, and precision and the generalization ability of the conventional time series forecasting tools. This article reviews the state of the art of machine learning models used in the general application of energy consumption. Through a novel search and taxonomy the most relevant literature in the field are classified according to the ML modeling technique, energy type, perdition type, and the application area. A comprehensive review of the literature identifies the major ML methods, their application and a discussion on the evaluation of their effectiveness in energy consumption prediction. This paper further makes a conclusion on the trend and the effectiveness of the ML models. As the result, this research reports an outstanding rise in the accuracy and an ever increasing performance of the prediction technologies using the novel hybrid and ensemble prediction models.

The biological conversion of hydrogen (H2) and carbon dioxide (CO2) to methane (CH4), is accomplished by the hydrogenotrophic methanogens (HM). HMs are difficult to cultivate in pure culture, but they are readily available in the mixed culture of effluents from the anaerobic degradation of organic matter, i.e., the fermentation effluent of biogas plants. The rate-limiting step in the work of CH4-forming microbial communities is the low solubility of H2 in the aqueous environment. In our approach, the simple fed-batch fermentation technique was selected to supply the gaseous substrates for the microbial community at laboratory scale and mesophilic temperature. Periodically withdrawn samples were analyzed for process parameters and the microbial communities were studied using Terminal Restriction Fragment Length Polymorphism (T-RFLP) of the mcrA gene and Ion Torrent whole metagenome DNA sequencing. The metagenome data were evaluated by both read-based and genome-centric bioinformatics tools. The rearrangements in the mixed microbial communities, triggered by switching the operating conditions to biological power-to-biomethane (bio-P2M), have been established. The production rates were 6.30 mL CH4 L−1 h−1 during the acclimation phase and 9.21 mL CH4 L−1 h−1 by the fully adapted community, respectively. The diversity of the anaerobic microbiota decreased as the bio-P2M process progressed. Feeding the community with H2 apparently promoted the abundance of several genera, in particular Candidatus Cloacimonas and Herbinix. The diversity of the Archaea community decreased considerably upon daily feeding with H2 and CO2. The predominant Archea genus was Methanobacterium in every reactor, Methanothrix persisted for the first 4 weeks, while the initially less abundant genus Methanoculleus gained advantage during the adaptation to the sustained bio-P2M process. The accumulation of acetate indicated a strong involvement of homoacetogenic bacteria.

Product sustainability has moved beyond being an elective preference to becoming a certain necessity. However, earthquakes in different regions, particularly Türkiye–Syria, Afghanistan, and Morocco, have produced a substantial amount of construction waste and debris. In the context of green urban initiatives and environmental preservation, theeffective management and reduction of environmental impact (EI) are imperative. This urgency underscores the significance of the study’s focus on a ten-story reinforced concrete (RC) dormitory building in Győr, Hungary, chosen as a case study. The research delves into the incorporation of three distinct concrete compositions through seismic design, aligning with the innovative approach of emphasizing recycled aggregate-based concrete to mitigate the EI. Utilizing AxisVM X7 and Revit software, the study meticulously created and analyzed a detailed building model, revealing a significant percentage (35%) and amount (1519.89 tons) of concrete waste that could be incorporated into construction. The results also showed a reduction in both total carbon emissions and the price of materials by falling 27.5% and 9.13%, respectively. We propose an eco-friendly way to effectively reuse debris from earthquakes, focusing on the case study of the 2023 Türkiye–Syria earthquake and encouraging resource efficiency while also addressing the construction waste problems that arise after an earthquake.

The aim of this research study was to investigate the energy recovery potentials in ventilation systems under different climatic conditions. The well-known heating degree day from the literature was updated using the weather data of cities with different climates from the past 40 years. As the novelty of this research with the developed procedure drawn up in this study, the energetic possibilities of heat recovery under various climate and operating conditions may be examined in more detail and more realistically than with the methods and available information of current engineering practices. To achieve this long-term and high definition the weather data of several cities are processed in order to evaluate the possibilities of heat recovery on a daily and annual basis.