Sustainable Building Research Articles

Life cycle assessment and multi-criteria decision-making for sustainable building parts: criteria, methods, and application

PurposeSustainable building design relies heavily on building parts, with crucial consideration for climate and environmental impact. Due to numerous criteria and diverse alternatives, employing multi-criteria decision-making (MCDM) to choose the best alternative is essential. Yet, relevant criteria and suitable MCDM methods for life cycle-based building planning still need to be determined. This study highlights prevalent environmental criteria and offers guidance on MCDM approaches for sustainable building parts.MethodsThis study introduces an innovative approach by integrating life cycle assessment and MCDM. This provides comprehensive decision support for planners. A systematic literature review identifies environmental criteria for building parts and is validated in expert workshops. Thus, the relevance of criteria across the building life cycle is established. Furthermore, the study analyzes MCDM approaches in the built environment. From this, the study employs and evaluates the Analytical Network Process (ANP) and Analytical Hierarchy Process (AHP) in a case study. Thereby, it offers insights into effective decision-making methodologies for sustainable building practices.ResultsThis research categorizes environmental criteria for building parts and buildings into emissions, energy, resources, and circularity. Among 26 building part-related criteria, the global warming potential is highlighted. While the AHP is widely used in MCDM, a standardized method in planning processes is yet to emerge. Applying the ANP and AHP reveals similar rankings for the best and worst alternatives in a case study focused on selecting the optimal ceiling structure. Ribbed or box slab ceiling constructions are favored over reinforced concrete and composite timber-concrete constructions.ConclusionsThis study presents a novel method for life cycle-based MCDM challenges, identifying key environmental criteria. While material correlations exist, evaluating building parts demands simultaneous consideration of multiple criteria. Future research aims to compare further MCDM methods regarding their applicability, transparency, and ranking to enhance decision-making in sustainable construction. These investigations are essential for refining decision-making processes in the built environment, ensuring effective and transparent sustainability planning approaches.

Governing Lateral Load on Tall Buildings in Canadian Regions

Urbanization has led to a significant increase in the construction of tall buildings in Canada. The design of tall buildings must ensure structural integrity in withstanding lateral loads, such as wind and earthquakes. The tendency for a specific lateral load to govern building design varies based on the building characteristics, building height, and location of the building. There is a need to identify the governing lateral load (i.e., wind or earthquake) for use in the preliminary design and city-scale assessment. This study examines the governing lateral loads for tall buildings across different Canadian regions through a parametric analysis of a typical high-rise building based on the Commonwealth Advisory Aeronautical Council (CAARC) building. This research evaluates varying building heights, structural systems, and geographic locations under the guidelines of the National Building Code of Canada (NBCC). The analysis identifies the dominant lateral load, providing insights into assessing the existing infrastructure and optimal design strategies for enhancing building sustainability and resilience. Our findings highlight the critical role of geographic location in determining lateral load impacts and the necessity of context-specific design to promote long-term structural performance and environmental sustainability.

Preparation and properties of alkali-activated fly ash-waste brick porous building materials

This study explores the development of sustainable porous building materials through the alkali-activation of fly ash and waste clay brick powder. Utilizing Class F fly ash and brick powder from demolished buildings, a series of alkali-activated mortars with varying brick powder replacements (0 % to 50 % by mass) were formulated and analyzed. The results reveal that a 10 % brick powder replacement optimizes the compressive strength, reaching 73 MPa at 28 days, attributed to enhanced nucleation and calcium-rich gel formation. However, higher brick content reduces strength due to the dilution of key reactive materials, with a 50 % replacement leading to a strength of 27 MPa. Porosity increases proportionally with brick content, achieving a maximum of 42 % at 50 % replacement, suggesting potential applications in insulation-centric scenarios. Microstructural analysis confirms the formation of a porous network and identifies the phase compositions and reaction products. This research demonstrates the potential of repurposing construction waste into efficient and environmentally friendly building materials, contributing to waste reduction and offering a greener alternative to traditional practices.

Circular Steel for Fast Decarbonization: Thermodynamics, Kinetics, and Microstructure Behind Upcycling Scrap into High-Performance Sheet Steel

Steel production accounts for approximately 8% of all global CO2 emissions, with the primary steelmaking route using iron ores contributing approximately 80% of those emissions, mainly due to the use of fossil-based reductants and fuel. Hydrogen-based reduction of iron oxide is an alternative for primary synthesis. However, to counteract global warming, decarbonization of the steel sector must proceed much faster than the ongoing transition kinetics in primary steelmaking. Insufficient supply of green hydrogen is a particular bottleneck. Realizing a higher fraction of secondary steelmaking is thus gaining momentum as a sustainable alternative to primary production. Steel production from scrap is well established for long products (rails, bars, wire), but there are two main challenges. First, there is not sufficient scrap available to satisfy market needs. Today, only one-third of global steel demand can be met by secondary metallurgy using scrap since many steel products have a lifetime of several decades. However, scrap availability will increase to about two-thirds of total demand by 2050 such that this sector will grow massively in the next decades. Second, scrap is often too contaminated to produce high-performance sheet steels. This is a serious obstacle because advanced products demand explicit low-tolerance specifications for safety-critical and high-strength steels, such as for electric vehicles, energy conversion and grids, high-speed trains, sustainable buildings, and infrastructure. Therefore, we review the metallurgical and microstructural challenges and opportunities for producing high-performance sheet steels via secondary synthesis. Focus is placed on the thermodynamic, kinetic, chemical, and microstructural fundamentals as well as the effects of scrap-related impurities on steel properties.

Development of eco-efficient limestone calcined clay cement (LC3) mortars by a multi-step experimental design

Calcined clays and calcium carbonates can be used to reduce clinker factor in blended cements, offering significant economic and environmental benefits. Limestone calcined clay cements (LC3) combine them as supplementary cementitious materials (SCMs) for delivering a sustainable alternative to conventional Ordinary Portland Cement products, with envisioned applications in construction and rehabilitation of historical buildings.This study reports a chemometric approach to the development of LC3 mortars, targeting to minimize clinker content while maintaining or improving the technical characteristics. To evaluate their performance, apparent density, modulus of elasticity, open porosity, water absorption, flexural and compressive strength have been considered as responses. Multiple Linear Regression (MLR) and Principal Component Analysis (PCA) were employed in a three-step mixture-process design allowing to obtain LC3 mixtures with a 21 wt% reduction in clinker while achieving notable enhancements in the physical properties (open porosity −9% and water absorption −10 %), along with commendable increases in compressive strength (+17 %) when compared to benchmark mortars produced without SCMs. The successful integration of multivariate techniques in designing sustainable building materials is showcased, highlighting the potential of chemometric methodologies to reduce the environmental impact as well as to increase the performance of building materials.

An artificial intelligence framework for explainable drift detection in energy forecasting

Accurate energy consumption forecasting is crucial for reducing operational costs, achieving net-zero carbon emissions, and ensuring sustainable buildings and cities of the future. Despite the frequent use of Artificial Intelligence (AI) algorithms for learning energy consumption patterns and predictions in Building Science, relying solely on these techniques for energy demand prediction addresses only a fraction of the challenge. A drift in energy usage can lead to inaccuracies in these AI models and subsequently to poor decision-making and interventions. While drift detection techniques have been reported, a reliable and robust approach capable of explaining identified discrepancies with actionable insights has not been discussed in extant literature. Hence, this paper presents an Artificial Intelligence framework for energy consumption forecasting with explainable drift detection, aimed at addressing these challenges. The proposed framework is composed of energy embeddings, an optimized dimensional model integrated within a data warehouse, and scalable cloud implementation for effective drift detection with explainability capability. The framework is empirically evaluated in the real-world setting of a multi-campus, mixed-use tertiary education setting in Victoria, Australia. The results of these experiments highlight its capabilities in detecting concept drift, adapting forecast predictions, and providing an interpretation of the changes using energy embeddings.

Assessing opportunities for enhanced lighting energy conservation via occupancy and daylight monitoring

Efficient energy utilization in buildings is crucial for sustainability. This work proposes an intelligent system that leverages computer vision techniques and CCTV images to assess indoor lighting energy usage based on occupancy, artificial lighting, and daylight conditions. Object detection models - You Only Look Once (YOLO) version 3 (v3) and v8 are employed to detect people, lights, and windows, achieving promising accuracies of 94.9 ​%, 73.3 ​%, and 98.7 ​%, respectively. The system categorizes scenarios as energy-efficient, wasteful, or neutral by integrating these outputs, highlighting opportunities for improving efficiency by harmonizing lighting infrastructure with occupancy and daylight exposure. Performance analyses, including training and validation metrics, are presented. This study demonstrates the potential of computer vision and AI for optimizing energy utilization, enabling sustainable building operation and promoting energy-positive occupant behaviors through sensor-driven methodologies.

Integration of LSTM networks with gradient boosting machines (GBM) for assessing heating and cooling load requirements in building energy efficiency

Due to rising demand for energy-efficient buildings, advanced predictive models are needed to evaluate heating and cooling load requirements. This research presents a unified strategy that blends LSTM networks and GBM to improve building energy load estimates’ precision and reliability. Data on energy usage, weather conditions, occupancy trends, and building features is collected and prepared to start the process. GBM model attributes are created using sequential relationships and initial load projections using LSTM networks. Combining LSTM with GBM takes advantage of each model's strengths: LSTM's sequential data processing and GBM's complex nonlinear connection capture. Performance measures like RMSE and MAE are used to evaluate the hybrid model's validity. Compared to individual models, the integrated LSTM-GBM method improves prediction accuracy. This higher predictive capacity allows real-time energy management systems, improving building operations and reducing energy use. Implementing this integrated model in Building Management Systems (BMS) shows its practicality in achieving sustainable building energy efficiency.

Novel sustainable techniques for enhancing shear strength of RC beams mitigating construction failure risk

The aim of this study is to evaluate the effectiveness of various innovative and sustainable methods for improving the shear performance of reinforced concrete (RC) beams. The potential risk of failure for such elements is considered a potential threat, therefore, this study addresses it through experimental tests and numerical analyses to be mitigated carefully in order to enhance the safety and sustainability of buildings. A total of eleven specimens, comprising two control specimens and nine strengthened specimens, underwent three-point testing. Several proposed strengthening techniques, each involving multiple parameters, were examined. In the initial approach, glass fiber-reinforced polymer (GFRP) textile embedded in an external fiber-reinforced cementitious mortar (FRCM) jacket was utilized, with an evaluation of the number of the GFRP textile layers (1, 2, and 3 layers). The second technique incorporated near surface mounted (NSM) GFRP bars along with the FRCM jacketing, where the diameter of the GFRP bars (10, 12, and 16 mm) served as the primary parameter. In the final technique, externally bonded stainless-steel strips (SSSs) of varying thicknesses (1, 1.25, 1.50 mm) were affixed to the beams’ surface. The obtained results revealed that the application of the FRCM jacketing method yielded positive results, showing a significant 30.7 % average increase in the crack initiation load and a 17.1 % improvement in the failure load compared to the defected beam. However, issues of debonding beneath the loading point were observed in the FRCM jacket, particularly with three layers of the GFRP textile, leading to the separation of the concrete cover. Moreover, combining the NSM GFRP bars with an FRCM jacket addressed the absence of shear stirrups. The most remarkable improvement was noted utilizing the NSM GFRP bars and an FRCM jacket, followed by employing SSSs with an FRCM jacket.

SUSTAINABLE ENVIRONMENTAL DESIGN STRATEGY AND ITS IMPACT ON SUSTAINABLE BUILDINGS

Sustainable environmental design solutions are crucial to reducing negative environmental impacts and maximizing the comfort of building inhabitants. This article emphasizes how these practices and ideas affect building performance and delves into the essentials of sustainable environmental design. Energy efficiency, water conservation, sustainable material use, and renewable energy source integration are some of the measures examined in the project, which aim to lessen environmental consequences and promote sustainability. This study aims to illuminate effective, sustainable design solutions by analyzing current case studies and sustainable building certifications like LEED and BREEAM. Modern ventilation systems, green roofs, and passive solar architecture are just a few examples of the creative ideas shown in these case studies that help make buildings more sustainable. Considerations of economics, regulatory frameworks, and technical developments are among the opportunities and threats that the article lists as consequences of embracing sustainable design approaches. The findings show that sustainable environmental design offers many economic and social benefits, including reduced operational costs, enhanced indoor air quality, and increased occupant happiness. The paper concludes with suggestions for how sustainable design concepts might be more widely used in architectural practices and policy frameworks to create truly sustainable built environments. It argues for a comprehensive strategy that combines economic, social, and environmental objectives.

Environmental Impact Assessment of Using Vernacular Materials for Sustainable Developments: Insights from an Eco-Sensitive Resort in India

It is known that quantification of embodied carbon and associated carbon emissions of different building types gives indications of the environmental impact of a structure during its construction, operation, and demolition stages and the various levels of boundary conditions within the framework of life cycle analysis (LCA). In this context, this study examines an eco-sensitive resort, located in a warm and humid climate. It conducts a comparative assessment of embodied carbon and resultant carbon emission by using conventional and alternative vernacular construction materials for foundation, superstructure, walling, roofing, flooring, joinery, finishing details, and site-work. The research method includes calculation of total quantum of materials used in the selected eco-sensitive resort project with one case scenario of using conventional construction materials and another case scenario of using their vernacular alternatives for all the different blocks with MS Excel© tool. The resultant values of their embodied carbon and carbon emission are calculated by using the globally recognized database and other calibrated LCA tools. The results show that in the high-end cottages with conventional brick and RCC construction systems, the superstructure and finishing cause the major amount of energy consumption during the construction stage. Using alternative vernacular materials like bamboo in the super structure, local tandoor stones in flooring reduce the embodied energy and carbon emission level significantly. The assessment shows that a 38.8% reduction can be achieved in embodied energy. The carbon emissions decrease by 1680 MT if vernacular materials are used. This finding is useful for building owners and designers in selecting holistic and environmentally sustainable building materials to produce sustainable buildings.

Sustainable building materials (SBMs) and their impact on displaced persons health/wellbeing in selected IDP facilities, Nigeria

Sustainable building materials (SBMs) and their impact on displaced persons health/wellbeing in selected IDP facilities, Nigeria

Performance Study on Laterite Block with Perlite

Abstract The term “perlite” refers to an amorphous volcanic silicate/alumina rock that can expand at temperatures between 900 and 1200 ∼C when heated fast. Because perlite is so versatile, it can be applied in a variety of sectors, including construction, horticulture, petrochemical, and industrial. An item that is used in the construction sector is expanded perlite (EP). It can be used as an input for geopolymers or mixed with aggregate or cement to create conventional cementitious materials. EP offers low density, effective thermal and acoustic insulation, and exceptional fire resistance for buildings. Perlite appears to be a necessary material as a result. The author of this article examines the effects of EP, a chemical used in building materials, on the properties of geopolymers, different types of binder, and regular cementitious materials, both in their fresh and hardened states. The usefulness of using perlite-reinforced laterite blocks as a sustainable building material is investigated in this work. We investigate this composite’s potential for usage in building applications by thoroughly examining its mechanical and thermal properties. The results provide insight into how robust and eco-friendly construction practices could be supported by increasing structural strength and thermal efficiency.

A multi-aspect approach of a building to achieve optimization in India’s major green building rating systems by incorporating BIM

Abstract This paper delves into the concept of “green buildings,” structures designed to enhance the quality of life within their geographical context through their unique attributes. In the context of India, this study focuses on three primary green building rating systems: LEED (Leadership in Energy and Environmental Design), IGBC (Indian Green Building Council), and GRIHA (Green Rating for Integrated Habitat Assessment). The objective of this article is to present an optimized three-dimensional model for a commercial building, employing Building Information Modelling (BIM) techniques. To achieve this, a checklist is developed based on the maximum rating points stipulated by the aforementioned rating systems. Using this checklist as a guideline, a three-dimensional model is constructed, integrating key parameters of sustainability and environmental performance. Subsequently, a cost analysis is conducted on the model to determine the payback time, thus establishing a holistic framework for sustainable building design. This research contributes to the advancement of sustainable architectural practices by integrating BIM technology with green building rating systems, providing a valuable methodology for architects and stakeholders to optimize commercial building designs with an emphasis on sustainability and environmental responsibility.

The Role of Agriculture Waste in Achieving High Efficacy in Residential Sustainable Buildings in Egypt

The Role of Agriculture Waste in Achieving High Efficacy in Residential Sustainable Buildings in Egypt

Physico-chemical characterization of cupola slag: Enhancing its utility in construction

Cupola slag is a waste material of the steel and iron industries. Its composition is determined by the cupola furnace and other elements used in steel and iron manufacturing. This paper investigates the characterization behavior of various cupola slag materials. As a result, x-ray fluorescence (XRF), x-ray diffraction (XRD), thermogravimetry differential thermal analysis, and scanning electron microscopy (SEM) methods were used to characterize three cupola slag samples from distinct origins. In addition, various physical properties were used to compare different cupola slags. The specific gravity values of CS-1 (cupola slag-1 sample), CS-2 (cupola slag-2 sample), and CS-3 (cupola slag-3 sample) are 1.36, 2.5, and 2.917, respectively. The density and water absorption for CS-1, CS-2, and CS-3 are 1414.86, 1477.71, and 1796 kg/m3, and 0.37%, 0.32%, and 0.26%, respectively. Cupola slag also includes a larger percentage of lime, according to XRF data, which contributes to its improved binding characteristics. A higher calcium oxide content in CS-3 could facilitate the pozzolanic process. The presence of angular particles that aid in material binding is seen in the SEM image. Compounds with a nanostructure are then flawlessly blended into the mixture and grouped with calcium alumina silicates formed by cement hydration. The XRD pattern of cupola slag exhibits high peaks, indicating that the material is crystalline in character and can be utilized as sand. It also shows the presence of other chemical compounds, such as silica, which ranges from 30% to 45%. CS-1 and CS-2 have comparable XRD patterns. However, CS-3 has a somewhat different pattern because of the greater CaO content. Weight loss begins at higher temperatures, which shows that the material is stable at higher temperatures, according to a thermo-gravimetric study. The differential thermal analysis curve of CS-3 indicates that the material remains stable up to a temperature of 600 °C. The physical characteristics of all cupola slag samples show that cupola slag may be utilized to make sustainable building materials because of its lower specific gravity, density, and water absorption.

Harvesting energy horizons: Bifacial PV and reversible fuel cells unite for sustainable building solutions

This study explores the integration of bifacial photovoltaic (PV) panels with proton exchange membrane (PEM) reversible fuel cells (RFC) to enhance renewable energy storage across various U.S. climates. It assesses the impact of environmental variables like sunlight exposure, climate fluctuations, and energy demands on system efficiency and resilience. The cities considered in the study were Tucson, Los Angeles, Denver, Dallas, and Minneapolis. Each city was chosen for its unique climatic characteristics, ranging from the arid heat of Tucson to the cold temperatures of Minneapolis. This diverse selection helps to evaluate the system's performance and economic viability across a broad spectrum of environmental conditions. Economic analysis focuses on metrics such as the Levelized Cost of Electricity (LCOE), Levelized Cost of Hydrogen (LCOH), and Levelized Cost of Storage (LCOS). Findings indicate significant economic benefits through varying bifacial PV gains from 0 to 20% yield with reductions in LCOE by 16%, LCOH by 14%, LCOS by 13%, and overall system LCOE by 18%. The results highlight the potential of bifacial PV and PEM-RFC systems to boost energy yield and economic efficiency amid dynamic environmental conditions. This analytical framework offers detailed insights into the economic viability and advantages of these systems in different climatic zones in the United States.

DESIGN AND OPTIMIZATION OF A COST-EFFECTIVE NET-ZERO ENERGY MOSQUE LOCATED IN A HOT AND DRY CLIMATE

ABSTRACT This research paper presents a comprehensive analysis to develop an energy-efficient and net-zero-energy (NZE) model for a proposed hypothetical mosque model located in Riyadh, Saudi Arabia. The study employs a sequential optimization analysis using BEopt software (Building Energy Optimization Tool) to explore various energy conservation measures (ECMs) from three main categories: HVAC, lighting, and building envelope. The ECMs are evaluated based on energy savings and life-cycle cost, with the most cost-effective options selected for the proposed energy-efficient design package. Furthermore, a passive downdraught evaporative cooling (PDEC) system is introduced as a passive cooling strategy to further reduce the cooling energy consumption. Computational fluid dynamics (CFD) analysis is utilized to optimize the airflow around the building and PDEC tower, determining the optimal PDEC dimensions for enhanced ventilation performance. The PDEC system is found to contribute 12% to cooling energy savings, which further enhances the energy efficiency of the proposed mosque. A rooftop solar PV system is incorporated into the optimal energy-efficient design to achieve a NZE mosque. The results demonstrate that the NZE model achieves 80% energy savings, with the remaining 20% offset by the solar PV system. Moreover, life-cycle cost analysis reveals that the NZE model offers the lowest cost, making it the most cost-effective design option. This research provides valuable insights into designing sustainable mosques in hot and dry climates, such as Riyadh, offering a comprehensive solution to significantly reduce energy end-use and promote sustainable building practices.

Hygrothermal resilience of typical lightweight steel-framed wall assemblies in hot-humid areas under future climate uncertainty

Ensuring the hygrothermal performance of lightweight steel-framed (LSF) wall assemblies is critical for the sustainability of LSF buildings in hot-humid regions; however, climate change poses new challenges. Therefore, this study aimed to bridge the gap in understanding the characteristics of hygrothermal load changes and the hygrothermal resilience of different LSF wall assemblies. Future climate data for each decade of this century (from 2030 to 2090), under various carbon emission scenarios, were generated based on a typical meteorological year (TMY) for hot-humid areas to evaluate the impact of climate change on hygrothermal loads. The hygrothermal resilience of four typical LSF wall assemblies, with either ventilated rainscreen cladding or face-sealed stucco cladding, with or without external insulation, was evaluated through simulation and comparative analysis. The results indicated that the thermal load would increase with increasing carbon emissions and over time, with the annual average external temperature peaking at 25.8 °C by the end of this century. The frequency of months with a high or critical moisture load would increase, although the moisture load may fluctuate across scenarios and years. Consequently, the cooling and dehumidification loads may increase by 52–60 % and 40–88 %, respectively. The hygrothermal risk within the walls may increase, with maximum increases of 2.8–8.0 % in the annual average relative humidity, 2.7–3.0 °C in the annual average temperature, and 10–35 % in the wetness duration. However, the impacts could be reduced by using ventilated rainscreens and external insulation, with further precautions needed to mitigate the increasing hygrothermal risk in areas with thermal bridges and rainwater leakage, as well as at the outer interface of the external insulation. These findings could provide a reference for the design of LSF buildings adapted to climate change in hot-humid areas.

Thermal Image Based Occupant Count Measurement Model using Human Body Temperature for Smart Building

Objectives: The proposed Occupant Count Measurement (OCM) model aims to enhance sustainability, energy efficiency, comfort, and safety in smart buildings by accurately determining occupant count using thermal camera images and body temperature data. Methods: The model leverages real-time thermal camera images without the need for a pre-existing dataset. Key parameters include temperature threshold, occupant motion, size, and shape to ensure accurate occupancy estimation. The K-means algorithm identifies and clusters regions of interest (ROI) in thermal images corresponding to human body temperatures. The model also employs sensors like PIR, RGB cameras, and thermal image sensors. Manual counting serves as a benchmark for comparison. Findings: The K-means algorithm extracts regions with elevated temperatures related to human bodies from thermal images, partitioning them into K-clusters based on temperature ranges and assigning each pixel to one of the clusters. A temperature threshold differentiates human clusters in the thermal image, while connected component labeling refines human object segmentation by identifying blobs, which are then used for occupant counting. The model's precision is assessed using diverse image sensors and compared to the actual number of occupants. The proposed OCM model achieves an accuracy of about 90.2% compared to traditional methods. Novelty: This study introduces an OCM model that uses thermal images to estimate the number of occupants in a room based on their body temperature. The method focuses on detecting and counting occupants by their overall thermal body signature, providing a novel approach to occupant measurement in smart buildings. Keywords: Thermal Images, Segmentation, Occupant Estimation, Occupant Comfort, Smart Building