Search Results (82)

In the current context, where sustainability, energy efficiency, and reduction of environmental impact are omnipresent themes, the need and interest for conservation, restoration, and reuse of heritage buildings is a topic of real interest. The city of Oradea, engaged in the last decades on the path of a sustainable urban regeneration, has managed to bring back to life part of the valuable Art Nouveau architectural treasure it inherited from previous generations. This paper presents a part of a much wider research and studies on Art Nouveau buildings in Oradea, in the context of the needs arising from the many problems identified with the start of conservation and restoration works. After an introduction on the link between heritage buildings and sustainability and a review of the current context in Oradea related to this topic, one of the emblematic buildings under renovation, the Ullmann Palace, is presented, as well as the results of some physical-mechanical tests carried out. This is followed by some discussions on the innovative and sustainable character of Art Nouveau buildings and the importance of carrying out high-quality conservation and restoration works that are environmentally friendly, safe, and sustainable. Full article

Achieving both indoor environmental quality (IEQ) and energy efficiency in school buildings remains a challenge, particularly in older structures where renovation strategies often lack site-specific validation. This study evaluates the impact of energy retrofits on a 1970s primary school in France by integrating in situ measurements with a validated numerical model for forecasting energy demand and IEQ. Temperature, humidity, and CO₂ levels were recorded before and after renovations, which included insulation upgrades and an air handling unit replacement. Results indicate significant improvements in winter thermal comfort (PPD < 20%) with a reduced heating water temperature (65 °C to 55 °C) and stable indoor air quality (CO₂ < 800 ppm), without the need for window ventilation. Night-flushing ventilation proved effective in mitigating overheating by shifting peak temperatures outside school hours, contributing to enhanced thermal regulation. Long-term energy consumption analysis (2019–2022) revealed substantial reductions in gas and electricity use, 15% and 29% of energy saving for electricity and gas, supporting the effectiveness of the applied renovation strategies. However, summer overheating (up to 30 °C) persisted, particularly in south-facing upper floors with extensive glazing, underscoring the need for additional optimization in solar gain management and heating control. By providing empirical validation of renovation outcomes, this study bridges the gap between theoretical predictions and real-world effectiveness, offering a data-driven framework for enhancing IEQ and energy performance in aging school infrastructure. Full article

Energy efficiency and CO₂ emission reduction are key objectives related to climate change mitigation, sustainable development, and energy resource management. In the Nordic context, energy consumption trends in both the residential and industrial sectors are closely linked to European Union policies, technological innovation, and real estate investments. In recent decades, the development and renovation of the real estate sector has become one of the most important factors determining changes in energy consumption, especially in residential buildings, which remain among the largest energy consumers and polluters. In this context, countries’ efforts to reduce CO₂ emissions and increase energy efficiency are inseparable from the real estate sector’s contribution to these processes, by promoting investments in building modernization and energy-saving technologies. However, the real estate sector remains a complex area where economic interests need to be reconciled with environmental objectives, especially in the context of EU strategies such as the Renovation Wave and the Energy Efficiency Directive. This article examines the links between real estate investment, energy efficiency, and CO₂ emission reduction, based on quantitative analysis, to assess how the development of the real estate sector and EU policy measures affect sustainable development in Northern Europe. This study uses advanced quantitative methods, including a panel regression model, which helps better reveal the long-term dependencies between investment, energy consumption, and emissions dynamics. This article highlights the importance of the real estate sector in implementing sustainability policies and suggests strategic solutions that can help reconcile economic and environmental priorities. Full article

This study presents an integrated approach for adapting building energy systems using Machine Learning (ML), the Internet of Things (IoT), and Building Information Modeling (BIM) in a hotel retrofit in Italy. In a concise multi-stage process, long-term climatic data and on-site technical documentation were analyzed to create a detailed BIM model. This model enabled energy simulations using the Carrier–Pizzetti method and supported the design of a hybrid HVAC system—integrating VRF and hydronic circuits—further enhanced by a custom ML algorithm for adaptive, predictive energy management through BIM and IoT data fusion. The study also incorporated photovoltaic panels and solar collectors, reducing reliance on non-renewable energy sources. Results demonstrate the effectiveness of smart energy management, showcasing significant potential for scalability in similar building typologies. Future improvements include integrating a temporal evolution model, refining feature selection using advanced optimization techniques, and expanding validation across multiple case studies. This research highlights the transformative role of ML, IoT, and BIM in achieving sustainable, smart, and efficient building energy systems, offering a replicable framework for sustainable renovations in the hospitality sector. Full article

The European building stock is aging and needs renovation. Holistic renovation approaches, including Vertical Forest (VF) systems, are emerging as sustainable alternatives to demolition and reconstruction. This paper reviews and defines missing reliable damage and hazard intensity measures for the holistic renovation of existing reinforced concrete (RC) buildings with VF systems. Based on an extensive literature review and preliminary studies, including empirical multiparametric system evaluation assessments, Monte Carlo simulations, and System-Theoretic Process Analysis (STPA), combined structural, non-structural, vegetation, and human comfort components are examined. Key damage indicators are identified, including interstory drift ratio, residual deformation, concrete and reinforcement strains/stresses, and energy dissipation, and their applicability to VF-integrated structures are evaluated. Green modifications are found to have higher risk profiles than traditional RC buildings (mean scores from Monte Carlo method: 9.72/15–11.41/15 vs. 9.47/15), with moisture management and structural integrity as critical concerns. The paper advances the understanding of hazard intensity measures for seismic, wind, and rainfall impacts. The importance of AI-driven vegetation monitoring systems with 80–99% detection accuracy is highlighted. It is concluded that successful VF renovation requires specialized design codes, integrated monitoring systems, standardized maintenance protocols, and enhanced control systems to ensure structural stability, environmental efficiency, and occupant safety. Full article

In recent years, the applications of digital technologies in sustainable construction have gained increasing interest. However, no comprehensive literature review has been conducted. Thus, this paper analyzes 990 relevant articles in this regard published from 2014 to 2023 by using CiteSpace (version 6.3.R1) and HistCite (version Pro 2.1) and identifies the most influential journals, institutions, and regions. The knowledge base was detected through a cluster analysis, which concentrates more on seven core themes: barriers, energy efficiency and building energy performance, life cycle assessment, computer vision, renovation, building sustainability assessment, and management. A citation analysis revealed that the applications of digital technologies were based in four dimensions of sustainable construction: environmental, social, and economic performance and green building assessment are the current hotspots. Finally, the potential future research trends in this field were proposed: (1) strengthening research on the application of more digital technologies; (2) expanding the use of digital technologies in the Operation and Maintenance (O & M) and demolition phases; (3) deepening the research on multi-objective optimization; and (4) exploring how to overcome obstacles. The findings provide highly valuable information for researchers with current research ideas and future directions in this field. This paper also has the potential to deepen practitioners’ comprehension of optimal digital technologies for bolstering construction sustainability. Full article

One of the barriers to the rapid transition of societies toward a more sustainable future is a scarcity of field experts. Members of scientific and professional communities believe that this obstacle could be overcome by supplementing the decisions of non-experts with artificial intelligence. To examine this opportunity, this study examines the viability of GPT-3.5 as an expert adviser in the energy management of kindergartens. Thus, field experts investigated the deductive and inductive reasoning potential of GPT-LLM (Large Language Model). The first task was conducted on a sample of kindergartens in the Western Balkans. The LLM was instructed to provide the buildings’ specific heat consumption (SHC) by relatively detailed building descriptions and building occupancy. The second task involved kindergartens in various European locations, and the LLM was tasked with estimating energy savings using limited data about the renovation process. The study found deductive reasoning to be insufficient for estimating SHC from the building envelope details, with average accuracy below the least predictive model (R² = 0.56; MAPE = 48%). Including the factor of occupancy, the SHC estimates were relatively accurate, wherein the first deductive test proved precise (MAPE = 27%), but it was less so in the opposite case (MAPE = 67%). In terms of inductive reasoning, the LLM assumptions were relatively consistent with practice. Full article

Climate change poses significant challenges for the renovation of historic buildings, requiring a careful balance between preservation and energy efficiency, particularly considering the forecasted rise in temperatures. This study focuses on a medieval building undergoing renovation, examining thermal behaviors based on future climate settings, with particular attention to the rooms housing a book collection. Books require controlled microclimatic conditions that must be ensured for their preservation; hence, the energy use for air conditioning control must be considered during the renovation planning phase. Through on-site monitoring of the thermophysical properties of the building envelope and indoor microclimate, along with energy model software simulations, both historic climate and global warming scenarios were evaluated for their potential impact on thermal behavior and consequently on energy consumption. This study aims at contributing to the long-term sustainability and resilience of historic buildings, as well as proposing best practices for planning interventions involving sensitive cultural heritage materials, considering the effects of climate change in the renovation process. The results show strategies to address the climatic changes through a methodology optimizing renovation interventions. The sizing of air conditioning systems coupled with a less stringent microclimate control mitigates energy requirements, in line with the sustainable management approach. Full article

The building sector contributes significantly to energy consumption and greenhouse gas emissions, with many buildings being energy inefficient. In response, the European Green Deal promotes improving energy efficiency to support decarbonization goals. However, managing energy consumption and integrating data from multiple sources presents challenges, especially for large building portfolios. This study introduces a novel methodology designed to optimize energy renovation strategies, balancing technical, financial, and maintenance considerations. The methodology is implemented in CERPlan 1.0, a web-based decision-support platform that combines data on building energy performance, renovation costs, and maintenance needs. Through simulations, CERPlan 1.0 helps decision-makers prioritize retrofit interventions based on economic criteria while leveraging synergies between energy improvements and regular maintenance. Application of this methodology to real estate portfolios reveals opportunities to enhance cost-effectiveness and energy savings. The results show that integrating maintenance into renovation planning reduces payback times and allows for more comprehensive renovation strategies. The conclusions highlight CERPlan 1.0’s potential to improve decision-making, making building renovations more efficient and sustainable. Full article

With emphasis on constructing low-carbon cities, the renovation of the riverbank highlights energy conservation and carbon reduction. However, methods and standards for quantifying carbon emissions during ecological river channel construction are currently lacking. There is a scientific gap in research into carbon footprint assessment and reduction potential in ecological revetment technologies in water networks of China. This study attempts to clarify the carbon emission factors of different ecological revetment technologies and explore the carbon reduction potential during the construction stage of ecological rivers from the river revetment design, construction process and materials. The results show that in the carbon emission factors of six ecological revetment technologies, building materials have the largest adjusting potential for carbon reduction. The concrete material is responsible for 55.37–95.86% of carbon emissions in six ecological river technologies, with an average proportion of 69.96%. Accordingly, the concrete material emerges as the primary contributor to carbon emissions in ecological river engineering, followed by gasoline truck transportation and earthwork excavation. Moreover, the carbon emissions from ecological frame structures were the largest, followed by those of block structures, gabion structures, planted concrete and interlocking blocks and the wooden stake structure has the smallest carbon footprint. The choice of ecological revetment technologies is not only related to the realisation of regional water conservancy functions, but it also affects the carbon emissions of water conservancy projects. Engineers and decision-makers should pay great attention to the optimal design of the project, selection of low-carbon materials, energy saving and emission reduction in the construction process. This research not only provides guidance for design units in selecting appropriate river revetment technologies but also offers a theoretical foundation and data support for construction units to optimise their construction process management. Full article

In the architecture, engineering and construction (AEC) industry, many efforts have provided remarkable contributions to construction planning and control processes during work execution. Nevertheless, frequent coordination issues among stakeholders and difficulties in dealing with unexpected events can be explained by the complexity featuring the construction sector. Several approaches to deal with this issue were investigated in the manufacturing area, among which this paper looks at the holonic approach as one of the most promising strategies. This study first analyzes the more fragmented and dynamic nature of the construction industry as compared with the manufacturing one. Secondly, it suggests developing a process-based holonic construction management system based on building information modeling (BIM) and a conceptual architecture for manufacturing control called Product Resource Order Staff Architecture (PROSA). The process-based paradigm ensures exploiting the benefits of BIM towards the development of sustainable and efficient regeneration methods of the built environment. Subsequently, a first management system prototype was developed and tested for the purpose of renovation works management. For the first time, results from an actual implementation of PROSA were applied to a real construction site, and its feasibility was assessed using the data on the field. Key performance indicators (KPIs) evaluated during the onsite demonstration confirmed a good performance of PROSA and the presented holonic approach, which contributed to the overall success of the energy efficient refurbishment project. Full article

The concept of sustainability introduced in 1987 has characterised the world of research in the AEC (Architecture, Engineering, and Construction) sector, directing it to try to tackle the problems inherent to the impacts of climate change on buildings. In addition, the advent of COVID-19, disrupting the world and people’s habits, has obviously also strongly affected the academic world. Indeed, this paper aims to analyse the changes and differences between the pre- and post-pandemic periods through a two-stage hybrid literature review. First, through a systematic literature review, 90 articles were selected, filtered through different keywords (sustainability, climate, architecture, and buildings). Once the reasoned selection of papers had been made, it was possible to proceed to the second phase, which involved a thematic analysis according to the three classic macro themes of sustainability (Environment, Social, and Economic) and the inclusion of a fourth macro theme (Management and Development), which made it possible to reintroduce a holistic view of the problem. The results of this literature review revealed the presence of a growing interest in the topic analysed and a more homogenous distribution across all continents, with no distinction between developed and developing countries. Economic sustainability interests emerge post-COVID-19 through the deepening of the themes of clean energy and direct control of consumption. At the level of Environmental sustainability, on the other hand, COVID-19 replaced the house at the centre of people’s lives. In addition, the Management and Development macro theme highlighted the need for an integrated view of the problem and the unexpected return of researchers preferring new constructions, which, despite alternative green approaches and renovations, can guarantee better performance. Full article

This paper aims to provide discernment toward establishing a general framework, dedicated to data analysis and forecasting in smart buildings. It constitutes an industrial return of experience from an industrialist specializing in IoT supported by the academic world. With the necessary improvement of energy efficiency, discernment is paramount for facility managers to optimize daily operations and prioritize renovation work in the building sector. With the scale of buildings and the complexity of Heating, Ventilation, and Air Conditioning (HVAC) systems, the use of artificial intelligence is deemed the cheapest tool, holding the highest potential, even if it requires IoT sensors and a deluge of data to establish genuine models. However, the wide variety of buildings, users, and data hinders the development of industrial solutions, as specific studies often lack relevance to analyze other buildings, possibly with different types of data monitored. The relevance of the modeling can also disappear over time, as buildings are dynamic systems evolving with their use. In this paper, we propose to study the forecasting ability of the widely used Long Short-Term Memory (LSTM) network algorithm, which is well-designed for time series modeling, across an instrumented building. In this way, we considered the consistency of the performances for several issues as we compared to the cases with no prediction, which is lacking in the literature. The insight provided let us examine the quality of AI models and the quality of data needed in forecasting tasks. Finally, we deduced that efficient models and smart choices about data allow meaningful insight into developing time series modeling frameworks for smart buildings. For reproducibility concerns, we also provide our raw data, which came from one “real” smart building, as well as significant information regarding this building. In summary, our research aims to develop a methodology for exploring, analyzing, and modeling data from the smart buildings sector. Based on our experiment on forecasting temperature sensor measurements, we found that a bigger AI model (1) does not always imply a longer time in training and (2) can have little impact on accuracy and (3) using more features is tied to data processing order. We also observed that providing more data is irrelevant without a deep understanding of the problem physics. Full article

According to the latest energy efficiency European directive (EED 2023/1791/EU), the expected energy renovation rate of at least 3% of the buildings’ floor area each year towards nearly zero-energy buildings (nZEBs) is extended to include public buildings not only of the central government (as per the first EED 2012/27/EU) but also of regional and local authorities. This poses a great challenge, especially for Municipalities that often manage large building stocks with high energy demands. In response to this challenge, this paper presents the application of the so-called “typology approach” for conducting public buildings’ energy renovation plans at the local level. A computational survey is initially introduced to decide the optimal set of building-stock clustering criteria among all possible combinations, involving the minimization of the RMSE index regarding the primary energy consumption of each building. For a representative building from each identified typology, the key performance indicators (KPIs) are computed for alternative energy-upgrading scenarios. Exploiting the IMPULSE Interreg-MED project tools, the KPIs from each representative building are at first extrapolated to all buildings of the examined stock and, finally, a gradual energy renovation plan is automatically produced based on user-defined decision parameters including the required annual renovation rate. The methodology is applied for the case of the Municipality of Hersonissos in Greece. For the specific 44-buildings’ stock it was found that the optimal clustering set included four criteria, building use, construction year, heating, and a cooling system, leading to 15 building typologies. Finally, assuming a 7% renovation rate per year, a 12-year gradual renovation (nZEB transformation) plan is obtained foreseeing an 85% CO₂ emissions’ reduction. Full article