Search Results (378)

The decarbonization of the energy sector drives the implementation of building-integrated and building-applied photovoltaic (BIPV–BAPV) systems. However, these systems face space and design limitations in urban environments. This study proposes an innovative methodology for the design and sizing of urban photovoltaic systems, considering diverse distributions and introducing metrics that link performance to occupied area. The methodology was applied to a university building in southern Spain, comparing the performance of rooftop photovoltaic (RTPV) and facade-applied photovoltaic (FAPV) systems. FAPV showed a larger useful area, resulting in similar self-sufficiency indices (RTPV: 22%, FAPV: 21%) and a 5% higher total emission reduction compared to the RTPV system. The proposed metrics demonstrate that FAPV outperforms RTPV both in final yield (49 vs. 21 kWh/kWp·m²) and total emission reduction (3.1 vs. 1.3 kgCO2eq/kWp·m²) normalized by installed power and occupied area. These complementary metrics are crucial for evaluating and selecting optimal photovoltaic configurations with varying generation densities and efficiencies, driving urban decarbonization and the creation of Zero Energy Buildings (ZEBs). Full article

Implementing the provisions related to energy transition, decarbonization, and, thus, the implementation of the Green Deal in the European Union requires increasing the share of renewable energy sources in the energy generation mix. On the one hand, this approach enables the acquisition of clean energy, but, on the other hand, it can affect the stability of energy supply to consumers in terms of the time and quantity required. Therefore, in the presented research, the authors proposed and verified the following thesis: Innovative coal technologies can play a temporary but crucial role in building the stability of the energy system by developing an operational stability index for the energy system in Poland. To this end, they determined the energy system stability index (ESSI) level, verified its variability over time, and simulated changes in the index when clean coal technology was used. The proposed method is highly universal and can be applied to any country, and the program written specifically for this research fully automates the ESSI calculation process. It is an excellent tool for facilitating decision making and enables the creation of simulations and scenarios of the impact of potential energy development strategies on its operational stability. The set of indicators developed by the authors characterizes the operational stability of the energy system according to the four-dimensional energy security paradigm. This allows for the consideration of the entire spectrum of operational and structural indicators when analysing the stability of the energy system. The developed ESSI allows for the assessment of the system’s stability in a technical sense, but also its adaptability, power and energy balancing, and, ultimately, its independence. Full article

The decarbonization process of the carbon emissions in the Chinese building sector exerts a profound impact on the achievement of the national goals of carbon peak and carbon neutrality. Currently, there is limited literature quantifying the impact of laws and policies on the achievement of carbon peak in the Chinese building sector and further utilizing deep learning technology to characterize the carbon emissions peak path under uncertainty in the Chinese building sector. To address this issue, a quantitative framework of legal and policy incentive intensity is constructed to capture both the immediate effects and the long-term evolution of laws and policies, and the index of legal and policy incentive intensity for carbon emissions in the building sector in China from 2010 to 2022 is calculated. Based on this, a dynamic scenario forecasting model for carbon emissions in the Chinese building sector is developed by integrating a CNN-BiLSTM-AM model with the Monte Carlo simulation algorithm, embedded within the scenario analysis method. The model projects the dynamic trajectories of carbon emissions in the Chinese building sector under different scenarios from 2023 to 2050 and identifies effective schemes for controlling carbon emissions in the Chinese building sector. Results indicate that the growth in legal and policy incentive intensity was most significant during the 12th Five-Year Plan period in China. During the 13th Five-Year Plan in China, the legal and policy system became increasingly mature, leading to a diminishing marginal effect of newly issued policies. A negative growth in legal and policy incentive intensity was observed in 2020 due to the impact of the COVID-19 pandemic. From 2021 to 2022, the annual growth rate of policy intensity began to rebound. Under the current scenario, carbon emissions in the Chinese building sector are projected to reach its carbon peak in 2036 (±1), with a peak level of 28.617 (±1.047) × 10⁸ t CO₂. Energy consumption per unit floor space, population size, legal and policy incentive intensity, integrated carbon emission factor, and floor space per capita are identified as the most critical factors influencing the timing and value of carbon peaking. The research methodology employed in this study not only provides scientific insights for the emission reduction efforts in the building sector but is also applicable to related studies in other industries’ energy conservation and emission reduction. It holds universal value for environmental policymakers and strategic planners. Full article

This review explores the pressing need for decarbonization strategies in the off-grid Indigenous communities of Northern Quebec, particularly focusing on Nunavik, where reliance on diesel and fossil fuels for heating and electricity has led to disproportionately excessive greenhouse gas emissions. These emissions underscore the urgent need for sustainable energy alternatives. This study investigates the potential for improving building energy efficiency through advanced thermal insulation, airtight construction, and the elimination of thermal bridges. These measures have been tested in practice; for instance, a prototype house in Quaqtaq achieved over a 54% reduction in energy consumption compared to the standard model. Beyond efficiency improvements, this review assesses the feasibility of renewable energy sources such as wood pellets, solar photovoltaics, wind power, geothermal energy, and run-of-river hydropower in reducing fossil fuel dependence in these communities. For instance, the Innavik hydroelectric project in Inukjuak reduced diesel use by 80% and is expected to cut 700,000 t of CO₂ over 40 years. Solar energy, despite seasonal limitations, can complement other systems, particularly during sunnier months, while wind energy projects such as the Raglan Mine turbines save 4.4 million liters of diesel annually and prevent nearly 12,000 t of CO₂ emissions. Geothermal and run-of-river hydropower systems are identified as long-term and effective solutions. This review emphasizes the role of Indigenous knowledge in guiding the energy transition and ensuring that solutions are culturally appropriate for community needs. By identifying both technological and socio-economic barriers, this review offers a foundation for future research and policy development aimed at enabling a sustainable and equitable energy transition in off-grid Northern Quebec communities. Full article

The integration of renewable energy technologies into the building sector is critical for achieving climate and energy targets, particularly within the framework of the European Union’s decarbonization policies. Building-integrated photovoltaics (BIPV) offer a promising solution by enabling the dual function of building envelope components and on-site electricity generation. However, the widespread adoption of BIPV faces significant barriers, including high initial investment costs, design and integration complexity, fragmented standardisation and a shortage of skilled labour. This study systematically identifies, evaluates and prioritises the key factors influencing the implementation of BIPV technologies using a hybrid SWOT (strengths, weaknesses, opportunities, threats) and Analytic Hierarchy Process (AHP) methodology. A comprehensive literature review and a modified Delphi method involving expert input were employed to select and rank the most relevant factors in each SWOT category. The results indicate that external factors—particularly regulatory requirements for energy efficiency, renewable energy adoption and financial incentives—are the most significant drivers for BIPV deployment. Conversely, competition from building-attached photovoltaics (BAPV), high investment costs and the complexity of integration represent the main barriers and threats, compounded by internal weaknesses such as a lack of qualified workforce and fragmented standardisation. The findings underscore the importance of targeted regulatory and financial support, standardisation and workforce development to accelerate BIPV adoption. This research provides a structured decision-making framework for policymakers and stakeholders, supporting strategic planning for the integration of BIPV in the construction sector and contributing to the transition towards sustainable urban energy systems. Full article

This study aims to evaluate the level of awareness and practical adoption of green wall systems in the Nigerian construction industry. It seeks to examine the current state of green wall implementation and recommend strategies to enhance their integration into construction practices among Nigerian construction professionals. A thorough review of the existing literature was conducted to identify different types of green wall systems. Insights from this review informed the design of a structured questionnaire, which was distributed to construction professionals based in Lagos State. The data collected were analyzed using statistical tests. The study reveals that while there is generally high awareness of green wall systems among Nigerian construction professionals, the practical use remains low, with just 8 out of the 18 systems being actively implemented, eclipsing the mean value of 3.0. The findings underscore the need for targeted education, industry incentives, and increased advocacy to encourage the use of green wall systems in the Nigerian construction sector. The results have significant implications for the Nigerian construction industry. The limited awareness and adoption of green wall systems highlight the need for strategic actions from policymakers, industry leaders and educational institutions. Promoting the use of green walls could drive more sustainable building practices, improve environmental outcomes and support the broader goals of decarbonization and circularity in construction. This research adds to the body of knowledge on sustainable construction by offering a detailed evaluation of green wall awareness and adoption within the Nigerian context. While green wall systems have been studied globally, this research provides a regional perspective, which in this case focuses on Lagos State. The study’s recognition of the gap between awareness and implementation highlights an important area for future research and industry development. Full article

Governments worldwide have set ambitious targets for decarbonising energy grids, driving the need for increased renewable energy generation and improved energy efficiency. One key strategy for achieving this involves enhanced energy management in buildings, often using machine learning-based forecasting methods. However, such methods typically rely on extensive historical data collected via costly sensor installations—resources that many buildings lack. This study introduces a novel forecasting approach that eliminates the need for large-scale historical datasets or expensive sensors. By integrating custom-built models with existing energy data, the method applies calculated weighting through a distance matrix and accuracy coefficients to generate reliable forecasts. It uses readily available building attributes—such as floor area and functional type to position a new building within the matrix of existing data. A Euclidian distance matrix, akin to a K-nearest neighbour algorithm, determines the appropriate neural network(s) to utilise. These findings are benchmarked against a consolidated, more sophisticated neural network and a long short-term memory neural network. The dataset has hourly granularity over a 24 h horizon. The model consists of five bespoke neural networks, demonstrating the superiority of other models with a 610 s training duration, uses 500 kB of storage, achieves an R² of 0.9, and attains an average forecasting accuracy of 85.12% in predicting the energy consumption of the five buildings studied. This approach not only contributes to the specific goal of a fully decarbonized energy grid by 2050 but also establishes a robust and efficient methodology for maintaining standards with existing benchmarks while providing more control over the method. Full article

According to the United Nations Environment Programme reports, buildings are responsible for nearly 40% of energy-related emissions; therefore, energy-optimized building design is crucial to reduce the reliance on non-renewable energy sources as well as greenhouse gas emissions. The OECD reports indicate the use of Building Information Modelling (BIM) as one of the effective strategies for decarbonization of buildings, since a 3D digital representation of both physical and functional characteristics of a building can help to design a more efficient infrastructure. An efficient integration of solar energy in building design can be vital for the enhancement of energy performance in terms of heating, cooling, and lighting demand. This paper presents results of an analysis of how factors related to the use of daylight, such as automatic control of artificial lighting, external shading, or the visual absorptance of internal surfaces, influence the energy efficiency within an example room in two different climatic zones. The simulation was conducted using Design Builder software, with predefined occupancy schedules and internal heat gains, and standard EPW weather files for Warsaw and Genua climate zones. The study indicates that for the examined room, when no automatic sunshades or a lighting control system is utilized, most of the final energy demand is for cooling purposes (45–54%), followed by lighting (42–43%), with only 3–12% for heating purposes. The introduction of sunshades and/or the use of daylight allowed for a reduction of the total demand by up to half. Moreover, it was pointed out that often neglected factors, like the colour of the internal surfaces, can have a significant effect on the final energy consumption. In variants with light interior, the total energy consumption was lower by about 3–4% of the baseline demand, compared to their corresponding ones with dark surfaces. These results are consistent with previous studies on daylighting strategies and highlight the importance of considering both visual and thermal impacts when evaluating energy performance. Similarly, possible side effects of certain actions were highlighted, such as an increase in heat demand resulting from a reduced need for artificial lighting. The results of the analysis highlight the potential of a simulation-based design approach in optimizing daylight use, contributing to the broader goals of building decarbonization. Full article

Urban transport is a key driver of greenhouse gas emissions in Europe, making its decarbonization essential to achieving EU climate neutrality targets. This study examines how European strategies, such as the Green Deal, the Sustainable and Smart Mobility Strategy, and the Fit for 55 package, are reflected in Romania’s transport policies, with a focus on implementation challenges and urban outcomes in Bucharest. By combining policy analysis, stakeholder mapping, and comparative mobility indicators, the paper critically assesses Bucharest’s current reliance on private vehicles, underperforming public transport satisfaction, and limited progress on active mobility. The study develops a context-sensitive reform framework for the Romanian capital, grounded in transferable lessons from Western and Central European cities. It emphasizes coordinated metropolitan governance, public trust-building, phased car-restraint measures, and investment alignment as key levers. Rather than merely cataloguing policy intentions, the paper offers practical recommendations informed by systemic governance barriers and public attitudes. The findings will contribute to academic debates on urban mobility transitions in post-socialist cities and provide actionable insights for policymakers seeking to operationalize EU decarbonization goals at the metropolitan scale. Full article

Securing thermal comfort while minimizing energy consumption in educational buildings is vital for achieving sustainable development goals. Drawing on the Environmental, Social, and Governance (ESG) framework, this systematic review synthesizes findings from 84 peer-reviewed studies published over the past decade, with a focus on how thermal comfort and energy use are assessed in educational contexts. The review identifies three primary research themes: climate resilience, multidimensional human-centric design, and energy decarbonization. However, it also reveals that existing studies have placed disproportionate emphasis on the environmental dimension, with insufficient exploration of issues related to social equity and governance structures. To address this gap, this study introduces an ESG-driven theoretical framework encompassing seven dimensions: thermal environment stability, multimodal thermal comfort assessment integration, sustainable energy use, heterogeneous thermal demand equality, passive–active design synergy, participatory thermal data governance, and educational thermal well-being inclusivity. By fostering interdisciplinary convergence and emphasizing inclusive stakeholder engagement, the proposed framework provides a resilient and adaptive foundation for enhancing indoor environmental quality in educational buildings while advancing equitable climate and energy strategies. Full article

The global climate crisis has driven unprecedented agreements among nations on carbon mitigation. With China’s commitment to carbon peaking and carbon neutrality targets, the building sector has emerged as a critical focus for emission reduction, particularly because office buildings account for over 30% of building energy consumption. However, a systematic and regionally adaptive low-carbon technology evaluation framework is lacking. To address this gap, this study develops a multidimensional decision-making system to quantify and rank low-carbon technologies for office buildings in Beijing. The method includes four core components: (1) establishing three archetypal models—low-rise (H ≤ 24 m), mid-rise (24 m < H ≤ 50 m), and high-rise (50 m < H ≤ 100 m) office buildings—based on 99 office buildings in Beijing; (2) classifying 19 key technologies into three clusters—Envelope Structure Optimization, Equipment Efficiency Enhancement, and Renewable Energy Utilization—using bibliometric analysis and policy norm screening; (3) developing a four-dimensional evaluation framework encompassing Carbon Reduction Degree (CRD), Economic Viability Degree (EVD), Technical Applicability Degree (TAD), and Carbon Intensity Degree (CID); and (4) conducting a comprehensive quantitative evaluation using the AHP-entropy-TOPSIS algorithm. The results indicate distinct priority patterns across the building types: low-rise buildings prioritize roof-mounted photovoltaic (PV) systems, LED lighting, and thermal-break aluminum frames with low-E double-glazed laminated glass. Mid- and high-rise buildings emphasize integrated PV-LED-T8 lighting solutions and optimized building envelope structures. Ranking analysis further highlights LED lighting, T8 high-efficiency fluorescent lamps, and rooftop PV systems as the top-recommended technologies for Beijing. Additionally, four policy recommendations are proposed to facilitate the large-scale implementation of the program. This study presents a holistic technical integration strategy that simultaneously enhances the technological performance, economic viability, and carbon reduction outcomes of architectural design and renovation. It also establishes a replicable decision-support framework for decarbonizing office and public buildings in cities, thereby supporting China’s “dual carbon” goals and contributing to global carbon mitigation efforts in the building sector. Full article

The life-cycle carbon emissions (LCCE) assessment of dairy barns is crucial for identifying low-carbon transition pathways and promoting the sustainable development of the dairy industry. We applied a life cycle assessment approach integrated with building information modeling and EnergyPlus to establish a full life cycle inventory of the material quantities and energy consumption for dairy barns. The LCCE was quantified from the production to end-of-life stages using the carbon equivalent of dairy barns (CEDB) as the functional unit, expressed in kg CO₂e head⁻¹ year⁻¹. A carbon emission assessment model was developed based on the “building–process–energy” framework. The LCCE of the open barn and the lower profile cross-ventilated (LPCV) barn were 152 kg CO₂e head⁻¹ year⁻¹ and 229 kg CO₂e head⁻¹ year⁻¹, respectively. Operational carbon emissions (OCE) accounted for the largest share of LCCE, contributing 57% and 74%, respectively. For embodied carbon emissions (ECE), the production of building materials dominated, representing 91% and 87% of the ECE, respectively. Regarding carbon mitigation strategies, the use of extruded polystyrene boards reduced carbon emissions by 45.67% compared with stone wool boards and by 36% compared with polyurethane boards. Employing a manure pit emptying system reduced carbon emissions by 76% and 74% compared to manure scraping systems. Additionally, the adoption of clean electricity resulted in a 33% reduction in OCE, leading to an overall LCCE reduction of 22% for the open barn and 26% for the LPCV barn. This study introduces the CEDB to evaluate low-carbon design strategies for dairy barns, integrating building layout, ventilation systems, and energy sources in a unified assessment approach, providing valuable insights for the low-carbon transition of agricultural buildings. Full article

Improving the energy efficiency of residential buildings is essential for achieving global climate goals and reducing environmental impact. This study analyzes the Total Performance approach using the example of a modern semi-detached house built by a Polish developer, as an example. The building is designed with integrated systems that minimize energy consumption while maintaining resident comfort. The building is equipped with an air-to-water heat pump, underfloor heating, mechanical ventilation with heat recovery, and automatic temperature control systems. Energy efficiency was assessed using ArCADia–TERMOCAD 8.0 software in accordance with Polish Technical Specifications (TS) and verified by monitoring real-time electricity consumption during the heating season. The results show a PED from non-renewable sources of 54.05 kWh/(m²·year), representing a 23% reduction compared to the Polish regulatory limit of 70 kWh/(m²·year). Real-time monitoring conducted from December 2024 to April 2025 confirmed these results, indicating an actual energy demand of approximately 1771 kWh/year. Domestic hot water (DHW) preparation accounted for the largest share of energy consumption. Despite its dependence on grid electricity, the building has the infrastructure to enable future photovoltaic (PV) installation, offering further potential for emissions reduction. The results confirm that Total Performance strategies are not only compliant with applicable standards, but also economically and environmentally viable. They represent a scalable model for sustainable residential construction, in line with the European Union’s (EU’s) decarbonization policy and the goals of the European Green Deal. Full article

This study investigates the potential of Eucalyptus benthamii wood from planted forests in southern Brazil for the production of cross-laminated timber (CLT) panels. The performance of E. benthamii CLT panels is compared to that of Pinus spp. panels and European commercial panels (KLH^®), using the finite element method applied to a two-story building model. Class 2 of the Brazilian standard ABNT NBR 7190-2 was adopted as the reference for the physical and mechanical properties of Pinus spp., while the European commercial specifications from KLH^® were used to represent European reference panels. The results indicate that E. benthamii wood exhibits superior mechanical properties, enabling reductions of 12.5% to 27.3% in panel thickness and a 20.7% decrease in wood volume when compared to Pinus spp., without compromising structural safety. Relative to the KLH^® and ETA 06/0138 standards, E. benthamii wood demonstrates higher stiffness (modulus of elasticity of 15,325 MPa vs. 12,000 MPa) and greater flexural strength (109.11 MPa vs. 24 MPa), allowing for the use of thinner panels. Stress and displacement analyses confirm that E. benthamii CLT slabs can withstand critical loads (wind and vertical) within normative limits, with maximum displacements of 18.5 mm. The reduction in material volume (22.8 m³ versus 28.7 m³ for Pinus spp.) suggests potential benefits in terms of environmental impact and logistical efficiency. It can be concluded that E. benthamii represents a sustainable and efficient alternative for CLT panels, combining high structural performance with resource optimization and contributing to the decarbonization of the construction industry. Full article

Owing to the need for continuous improvement in building energy performance standards (BEPSs), facilities must adhere to benchmark performances in their quest to achieve net-zero performance. This research explores machine learning models that leverage historical energy data from a cluster of buildings, along with relevant ambient weather data and building characteristics, with the objective of predicting the buildings’ energy performance through the year 2040. Using the forecasted emission results, the portfolio of buildings is analyzed for the incurred carbon non-compliance fees based on their on-site fossil fuel CO_2e emissions to assess and pinpoint facilities with poor energy performance that need to be prioritized for decarbonization. The forecasts from the machine learning algorithms predicted that the portfolio of buildings would incur an annual average penalty of $31.7 million ($1.09/sq. ft.) and ~$348.7 million ($12.03/sq. ft.) over 11 years. To comply with these regulations, the building portfolio would need to reduce on-site fossil fuel CO_2e emissions by an average of 58,246 metric tons (22.10 kg/sq. ft.) annually, totaling 640,708 metric tons (22.10 kg/sq. ft.) over a period of 11 years. This study demonstrates the potential for robust machine learning models to generate accurate forecasts to evaluate carbon compliance and guide prompt action in decarbonizing the built environment. Full article