Search Results (170)

One of the gaps in green building research in European and Mediterranean countries is the assessment of Leadership in Energy and Environmental Design (LEED)-certified projects in the context of the LEED rating system’s ongoing transition from a prescriptive to a performance-based approach. This study evaluates LEED certification strategies by analyzing the statistical association between five independent performance indicators and the overall LEED score for LEED for Existing Office Buildings version 4.1 (LEED-EB v4.1) gold-certified office projects in Sweden, Italy, Israel, Spain, Germany, and Ireland using simple linear regression. The results showed that each of the six above-mentioned countries demonstrated a unique LEED certification strategy for LEED-EB v4.1 gold-certified office projects. Linear regression revealed an unexpected result: the statistical association between the independent indicator (energy) and the dependent indicator (overall LEED) score was statistically insignificant (R² = 0.04 and p = 0.359; R² = 0.13 and p = 0.112, respectively) in LEED-EB v4.1 gold-certified office projects in Germany and Ireland. However, in Sweden, Italy, Israel, and Spain, this association was statistically significant (R² = 0.38, 0.46, 0.53, and 0.40 at p < 0.001 in all cases, respectively). Full article

The widespread adoption of circularity principles in the building sector fuels the need for robust and comprehensive evaluation systems, which could benefit from the approaches and indicators employed in widely accepted building sustainability assessment (BSA) methods. Simultaneously, the effective consideration of circular economy (CE) principles into BSA methods becomes increasingly urgent. An important step towards achieving these targets is the investigation of whether, and to which degree, the existing BSA methods encompass and express circularity principles; this study focuses on this relatively underexplored theme. Specifically, this study investigates the degree of association between five widely used BSA methods and the circularity strategies included in the 10R Framework. The methods examined are BREEAM, DGNB, LEED, Level(s) and SBTool (versions and criteria for new buildings). The examination was conducted at the lowest self-contained and score-attributing level of each method and was undertaken by five expert groups—each assigned one method. A quantitative scale from 0 to 5 was used to assess the strength of the association. The results are analysed in terms of (i) the criteria/thematic areas within each method receiving high/low scores, and (ii) the circularity strategies deduced to be strongly/weakly represented in and across the BSA methods. Common trends and milder differences across these axes are observed. Generally, the associations appear stronger in thematic areas relevant to, among others, resources and lifecycle performance, and weaker regarding parameters linked to user comfort. The R-strategies Reduce, Reuse, Recycle and Rethink emerge as more intensely represented in the examined methods. The study’s results indicate areas for further research and potential methodological enhancement. Full article

Despite the rapid expansion of green roof installations in the United States, little empirical evidence exists regarding their long-term persistence or post-installation management. This study evaluates post-installation outcomes for 46 green roofs across ten southeastern U.S. states using a structured survey and publicly available records. Roofs were classified by status (managed, abandoned, removed, mid-refurbishment, or unknown) and management intensity. Associations with ownership change, building type, and Leadership in Energy and Environmental Design (LEED) certification status were examined using Fisher’s Exact Tests and logistic regression. Only 47.8% of roofs were actively managed at the time of data collection, while 45.7% had been abandoned or removed. Ownership change was significantly associated with roof failure (Fisher’s Exact Test, p = 0.001), with no managed roofs experiencing post-installation ownership turnover. In contrast, LEED certification status was not associated with either roof persistence or management intensity. These findings indicate that institutional continuity and sustained management play a critical role in determining long-term green roof outcomes and suggest that installation-based incentives may overestimate the number of functioning green roofs. By shifting evaluation beyond ecological performance metrics alone, this study highlights governance and institutional stability as central factors shaping roof longevity. Full article

This literature review examines weighting schemes within Building Sustainability Assessment Systems (BSASs). Given the widespread adoption of BSASs and their direct link to significant economic benefits for investors and owners, weighting schemes serve as critical tools for policymaking in the sustainable building sector. The review synthesizes findings from 102 articles, covering multiple building types, subsystems, design parameters, lifecycle phases, locations, and sustainability dimensions. The identified schemes are categorized as subjective, objective, hybrid, or equal, based on established definitions. First, the weighting schemes of Leadership in Energy and Environmental Design (LEED) and Building Research Establishment Environmental Assessment Method (BREEAM)—the two most frequently referenced BSASs—are analyzed within this framework. Second, a systematic analysis of novel weighting schemes proposed in the literature is conducted. Among these methodologies, 75% employed subjective weighting schemes, while objective, hybrid, and equal weighting schemes accounted for 12%, 6%, and 3%, respectively. No discernible temporal trend was observed in these proportions over the last 25 years. The geographical analysis further underscores the global dominance of subjective schemes. Notably, nearly 71% of the studies focus on developing countries in Asia and Africa, where the proportion of subjective schemes reaches 75% and 85%, respectively. Consequently, the results indicate the pivotal role of experts in shaping BSASs priorities. Finally, the discussion evaluates the advantages and limitations of these weighting approaches regarding their capacity to guide the building sector toward sustainability goals. Full article

Green building rating systems (GBRS) (e.g., LEED and BREEAM) assess sustainability in the built environment but require extensive data collection and processing. In this context, digitalization strategies, such as building information Modeling (BIM), enable centralized data management throughout the building’s life cycle. This study presents a PRISMA-based systematic literature review (SLR) of BIM-GBRS integration methods, identifying 83 articles and 13 reviews. The analysis is structured around three key phases defined to enable a systematic comparison of the existing approaches. Phase 1, “Data acquisition”, involves collecting the values of the investigated parameters either from the BIM model or through analysis software (e.g., Insight, One Click LCA) grouped into eight categories. Phase 2, “compliance verification”, focuses on comparing collected data with GBRS requirements using manual or automated tools (e.g., Dynamo). Phase 3, “optimization”, involves improving alternative design scenarios using tools such as plug-ins and MATLAB-based algorithms (e.g., NSGA-II, DWKNN). Emerging digital technologies (e.g., AI, digital twins, IoT) are analyzed to enable automated workflows, while interoperability is examined by distinguishing format-based (e.g., gbXML, IFC) and tool-based (e.g., APIs, VPL) approaches. The study identifies fragmented and limited interoperability in BIM-GBRS integration, highlighting the need for an automated end-to-end framework to support sustainability in the construction sector. Full article

Accurate early-stage assessment of building energy and carbon performance is essential for informed sustainable design yet remains challenging due to limited design detail and simulation effort. This study presents a Building Information Modeling–Machine Learning (BIM-ML) framework for predicting office building energy and carbon performance at early design stages using simulation-based datasets. A reduced-factorial Design of Experiments (DOE) generated 210 parametric office building models for Orlando, Florida (ASHRAE Climate Zone 2A), complemented by additional climate scenarios. Systematic variations in geometry, envelope, building systems, and operational schedules produced a dataset with 14 independent variables and five performance indicators: Energy Use Intensity, Operational Energy, Operational Carbon, Embodied Carbon, and Total Carbon. Four regression methods—Linear Regression, Model Tree (M5P), Sequential Minimal Optimization Regression, and Random Forest—were trained and evaluated using 10-fold cross-validation. Random Forest showed the strongest overall predictive performance. Feature-importance analysis identified HVAC system type, Window-to-Wall Ratio, and operational schedule as the most influential parameters, while geometric factors had lower impact. Cross-climate analysis and validation with measured data from two university office buildings indicate that the framework is adaptable and generalizable, supporting reliable early-stage evaluation of energy and carbon performance. Full article

This study critically examines the relationship between neoliberal environmentalism and green certification systems by quantitatively analyzing LEED-certified buildings in Istanbul. It explores how green building practices intersect with market-oriented urban environmental governance through an analysis of the spatial distribution, ownership types, access typologies, and functional uses of certified projects. The findings reveal that nearly 80% of LEED-certified buildings in Istanbul are developed by private companies, and that 88.6% of these buildings are private spaces with limited or no public access. These projects are predominantly high-end offices or residential developments, with a large share holding “Gold” certification. Correlation analysis identifies an inverse relationship between LEED project density and socioeconomic vulnerability, raising critical questions about spatial justice and equity in access to sustainable urban environments. This study contributes to the growing body of critical literature that frames urban sustainability not merely as a technocratic checklist of standards but as a normative and contested terrain in which justice, equity, and inclusivity must be placed at the center. Full article

This study examines LEED certification strategies for Existing Buildings 4.1 (LEED-EB v4.1)-certified office projects in major US cities and their relationship with local green building policies. LEED-EB v4.1 is the latest program with an appropriate sample size to conduct significance tests and draw robust statistical inferences. LEED-EB v4.1 features six performance indicators: “transportation”, “water”, “energy”, “waste”, “indoor environmental quality (IEQ)”, and “overall LEED”. The purpose of this study was to evaluate LEED-EB v4.1 gold-certified office projects in San Francisco (SF), New York City (NYC), and Washington, D.C. (DC). Exact Wilcoxon–Mann–Whitney and Cliff’s δ tests were used to compare the same LEED variables between two cities. Pearson’s or Spearman’s correlation tests were used to assess the strength/direction between two LEED variables, and a simple linear regression (SLR) model was applied to predict the overall LEED variable. It was found that SF outperforms NYC in “IEQ” (δ = 0.53 and p = 0.009) and outperforms both NYC and DC in “overall LEED” (δ = 0.66 and p = 0.001; δ = 0.59 and p = 0.001). “Energy” and “waste” were positively and significantly correlated with “overall LEED” in NYC (r = 0.61 and p = 0.001; r = 0.40 and p = 0.044, respectively) and DC (r = 0.83 and p < 0.001; r = 0.65 and p = 0.009, respectively). The SLR results showed that one-point increases in “energy” and “waste” scores resulted in an increase in NYC’s overall LEED scores by approximately 0.78 and 1.72 points, respectively, and one-point increases in “energy” and “waste” scores resulted in an increase in DC’s overall LEED score by approximately 0.96 and 1.97 points, respectively. It is hypothesized that the difference in the “IEQ” of LEED-EB-certified office buildings between SF and NYC may be due to differences in these cities’ green building policies. According to the “overall LEED” indicator, office buildings in SF are more sustainable than those in NYC and DC. “Energy” and “waste” showed a stronger positive relationship with “overall LEED” in NYC and DC than the other indicators. However, the correlation analysis for SF presented in the Limitations Section is speculative due to the small sample size (n = 11). Full article

Building Information Modeling (BIM) is increasingly used to support green building design practices, yet its alignment with established green building assessment (GBA) tools remains underexamined. This study evaluates the extent to which Autodesk Revit, as a BIM tool, supports the calculation of energy-related indicators in GBA tools such as the Leadership in Energy and Environmental Design (LEED) method. A quasi-empirical, multi-method approach was employed, combining content analysis, a Revit-based simulation of a residential building, and structured evaluation by a panel of four experts. Using both subjective and objective measures, the experts assessed Revit’s effectiveness and the role of Revit’s media channels—modeling, simulation, data integration, and text documentation—in supporting and calculating LEED Energy and Atmosphere (EA) indicators. Results reveal that Revit is capable of effectively supporting 7 out of 11 LEED EA indicators. The highly supported indicators included minimum energy performance, building-level energy metering, optimized energy performance, advanced energy metering, renewable energy production, and enhanced refrigerant management while the fundamental refrigerant management indicator was evaluated as a moderately supported indicator. These highly supported indicators are core energy-related indicators; three of them are prerequisite indicators, while the remaining are credit indicators that cover 66.7% of the weight assigned for the EA indicators. The results also demonstrated that the remaining four indicators—fundamental commissioning and verification, enhanced commissioning, demand response, green power, and carbon offsets—were evaluated as poorly supported by Revit. The consistency of results across two rounds of survey, along with the expert’s consensus on 73% (8 out of 11) of the examined indicators, provides empirical validation of Rivet’s capacity to support LEED GBA. Findings also showed that modeling and simulation, followed by data integration, are the most impactful channels in supporting and calculating LEED EA criteria and requirements, with significant statistical correlation confirmed through Kendall’s Tau correlation. The findings have theoretical and practical implications for designers, green building practitioners, and BIM developers and suggest areas for further research. Full article

Rapid urbanization, rising energy consumption, and the environmental pressures of the 21st century have led the construction sector to focus on sustainable design solutions to protect the natural environment and combat climate change. Technological advances are leading to an increasing number of ultratall buildings. However, due to the complex issues involved, these structures currently serve primarily as symbols and serve as testing grounds for technological innovation. Therefore, there is a clear need to analyze the issues involved in designing high-rise buildings sustainably in the context of contemporary environmental challenges. Global multi-criteria certifications exist to establish parameters verifying a building’s impact on its surroundings. This study systematically assessed the sustainable strategies of the world’s twenty tallest buildings using a four-category model: A—passive design, B—active mechanical systems, C—renewable energy integration, and D—materials, water, and circularity strategies. The quantitative assessment (0–60) was supplemented with qualitative analysis and correlational research, including LEED certification. A novel element of the study is a multi-criteria comparative analysis, culminating in an assessment of the degree of implementation of sustainable development strategies in the world’s tallest buildings and linking the results to LEED certification levels. The results identify categories requiring further improvement. The results indicate that Merdeka 118 (46.7%), followed One World Trade Center (43.3%) and Shanghai Tower (41.7%) received the highest scores. Category B dominated all buildings, categories A and D demonstrated moderate implementation, and category C demonstrated the lowest performance due to economic and technical constraints at extreme heights. LEED Platinum-certified buildings demonstrated significantly higher levels of technology integration than Gold or non-certified buildings. The study results emphasize the need for integrating passive design strategies early in the design process, improving renewable energy solutions, and long-term operational monitoring supported by digital tools (such as IoT and digital twins). Full article

This study evaluates and compares the sustainability performance of selected historic, commercial, and institutional buildings in Istanbul to identify effective climate-responsive and energy-efficient design strategies. The objectives are to assess performance using LEED-based criteria, examine variations across building typologies, and outline implications for future sustainable design. Using an evaluation matrix, responses from 175 experts were analysed across key LEED categories for seven case study buildings. The comparative assessment reveals notable variations in sustainability performance across the seven evaluated buildings. ERKE Green Academy consistently achieved the highest mean scores (≈4.40–4.60), particularly in Sustainable Sites, Water Efficiency, Energy and Atmosphere, and Indoor Environmental Quality. This strong performance reflects its integration of advanced green technologies, optimised daylighting strategies, biophilic elements, and smart system controls. Modern commercial towers, such as the Allianz Tower and Sapphire Tower, recorded strong mean scores (≈4.20–4.50) across categories related to Integrative Design, Energy Efficiency, and Materials and Resources. Their performance is largely driven by intelligent façade systems, double-skin envelopes, automated shading, and high-performance mechanical systems that enhance operational efficiency. In contrast, heritage buildings including Hagia Sophia and Sultan Ahmed Mosque demonstrated moderate yet stable performance levels (≈4.00–4.40). Their strengths were most evident in Indoor Environmental Quality, where passive systems such as thermal mass, natural ventilation, and inherent spatial configurations contribute significantly to occupant comfort. Overall, the findings underscore the complementary value of combining traditional passive strategies with modern smart technologies to achieve resilient, low-energy, and user-responsive architecture. This study is novel as it uniquely demonstrates how traditional passive design strategies and modern smart technologies can be integrated to enhance climate-responsive and energy-efficient performance across diverse building typologies. The study recommends enhanced indoor air quality strategies, occupant education on system use, and stronger policy alignment with LEED standards. Full article

This study examines how climatic factors influence the predictive power of LEED credits in determining certification outcomes for hotel buildings across the United States. Using data from 259 LEED-NC v2009 certified hotels, project-level information was integrated with 30-year climate normals from the PRISM database and Building America climate zones. A three-step hierarchical linear regression was conducted to identify the LEED credits that most strongly predict total certification points while controlling for project size, certification year, and baseline climatic conditions, and to test whether climatic factors moderate these relationships. Regularized Linear Regression (LASSO) was then applied to address multicollinearity and assess model stability, followed by Support Vector Regression (SVR) to capture potential nonlinear relationships. This integrated methodological framework, combining hierarchical regression for interpretability, LASSO for coefficient stability, and Support Vector Regression for nonlinear verification, provides a novel, multi-dimensional assessment of climate-sensitive credit behavior at the individual credit level. Results show that energy- and site-related credits, particularly Optimize Energy Performance (EA1), On-Site Renewable Energy (EA2), Green Power (EA6), and Alternative Transportation (SS4), consistently dominate LEED performance across all climate zones. In contrast, indoor environmental quality credits exhibit modest but significant climate sensitivity: higher mean temperatures reduce the contribution of Increased Ventilation (EQ2) while slightly enhancing Outdoor Air Delivery Monitoring (EQ1). Cross-model consistency confirms the robustness of these findings. The findings highlight the need for climate-responsive benchmarking of indoor environmental quality credits to improve regional equity and advance the next generation of climate-adaptive LEED standards. Full article

Selecting Construction and Demolition Waste (CDW) credits in LEED-certified projects is essential for sustainable building management, often requiring specialised expertise and contextual sensitivity. However, existing studies provide limited analytical insight into why certain CDW credits succeed or fail across different project contexts, and no explainable AI–based framework has been proposed to support transparent credit decisioning. This gap underscores the need for a data-driven, interpretable approach to CDW credit evaluation. This study proposes an explainable artificial intelligence (XAI)-based model to support CDW credit selection and to identify the key factors influencing credit performance. A dataset of 407 LEED green building projects was analysed using twelve machine learning (ML) algorithms, with the top models identified through Bayesian optimisation. To handle class imbalance, the SMOTE was utilised. Results showed that MRc2 and MRc4 credits had high predictive performance, while MRc1.1 and MRc6 credits exhibited relatively lower success rates. Due to data limitations, MRc1.2 and MRc3 were excluded from analysis. The CatBoost model achieved the highest performance across MRc1.1, MRc2, MRc4, and MRc6, with F1 scores of 0.615, 0.944, 0.878, and 0.667, respectively. SHapley Additive exPlanations (SHAP) analysis indicated that the Material Resources feature was the most influential predictor for all credits, contributing 20.6% to MRc1.1, 53.4% to MRc2, 36.5% to MRc4, and 22.6% to MRc6. In contrast, the impact of design firms on credit scores was negligible, suggesting that although CDW credits are determined in the design phase, these firms did not significantly influence the decision process. Higher certification levels improved the performance of MRc1.1 and MRc6, while their effect on MRc2 and MRc4 was limited. This study presents a transparent and interpretable XAI-based decision-support framework that reveals the key sustainability drivers of CDW credit performance and provides actionable guidance for LEED consultants, designers, and decision-makers. Full article

Buildings have a significant impact on the health and well-being of their occupants through factors such as thermal comfort, humidity, air quality, access to natural light, acoustics, and radiation protection. The purpose of this study was to identify factors that contribute to healthy construction and to define the competencies needed in technical education to support the design and operation of health-promoting buildings. The study utilised expert brainstorming, an analysis of legal regulations in partner countries, a review of educational programmes, and a systematic review of the scientific literature. The research confirmed the positive impact of green buildings (e.g., LEED Certification) on occupant health. Gaps in technical education programmes were identified, particularly in the practical teaching of modern technologies and health-promoting design solutions. A competence matrix was developed, divided into educational levels, encompassing knowledge, skills, and social competencies related to the health-promoting aspects of buildings. Knowledge about healthy construction should include indoor environmental parameters, universal and ecological design, and conscious operating practices. The prepared competence matrix provides a foundation for further educational development and guides further research in this area. Full article

This study examines the influence of vegetation on indoor daylight performance in school buildings located in the hot–humid climate of Chennai, India. With increasing urban development leading to the cutting or relocation of trees, their role in modulating interior daylight conditions has become critically relevant but remains underexplored in the literature. Recognizing a significant research gap in this area, this study employed a simulation-based approach using DesignBuilder 7.4 software. A government school in South Chennai, India, was chosen for this study. A total of 208 scenarios were generated by varying the window-to-wall ratio (WWR), facade orientation, floor level, and tree presence. Daylight performance was evaluated using spatial daylight autonomy (sDA), annual sunlight exposure (ASE), and useful daylight illuminance (UDI), based on IES LM-83-12 and LEED v4 standards. Simulation results showed that a 20% window-to-wall ratio (WWR) failed to meet daylight standards, while a 30–40% WWR with shading consistently performed well. Trees significantly improved daylight metrics, like sDA, UDI, and ASE, more so than orientation or floor level. This study urges regulatory mandates for climate-resilient schools, emphasizing fenestration and landscape integration. Full article