Building Systems Research Articles

Adapting Sustainability Certification Systems for Historic Buildings: A Qualitative Comparative Study in Denmark

Historical buildings are unique assets in any society, embodying cultural significance and architectural heritage. Denmark, with its rich architectural background, has taken steps to preserve these values. As the imperative of sustainability continues to grow, recognizing the social, economic, and environmental values of historic buildings is becoming increasingly important. As an important step towards adapting sustainability certification systems for historic buildings in order to identify and preserve their historical values, this paper aims to conduct a comparative analysis between the GBC and HB (Green Building Council–Historic Building), which has been adapted for historic buildings in Italy and the Danish GBC system (GBC-DK or so-called DGNB-DK). The study is based on a theoretical framework underpinned by a systematic approach utilizing a qualitative comparative analysis (QCA) alongside the triangulation method. This includes a systematic literature review comparing the GBC-DK and GBC-HB systems and an analysis of an actual building renovation project at a municipal hospital in Aarhus, Denmark. The findings indicate a notable absence of criteria and sub-criteria pertaining to the protection of tangible and intangible values in the application of the GBC-DK system. It is justified that in order to improve the sustainability of historic buildings in Denmark, a broader and more in-depth study on the adaptation of the GBC-DK system for historic buildings is needed.

Design and Construction of Monitoring and Control System in Swallow House Based on IoT

This study aims to design and build an Internet of Things (IoT) based monitoring and control system in a swiftlet building. Swiftlet nest farming is a rapidly growing industry in Indonesia, but still faces challenges in terms of monitoring and optimal environmental management for swiftlet productivity. The system developed integrates sensors to measure critical environmental parameters such as temperature. The research methodology includes hardware design using a microcontroller, sensors, and actuators connected to an IoT network. Software is developed to process sensor data, send it to blynk, and present information through a web interface that can be accessed remotely. This system is also equipped with an automatic control feature to keep environmental parameters within the optimal range. The results of the study show that the system is capable of real-time monitoring and providing notifications when an anomaly occurs. The automatic control feature successfully maintains temperature stability in the swiftlet building, where when the temperature read by the sensor is less than or equal to 25oC the lights will turn on and if the temperature is more than 29oC the lights will turn off. In conclusion, the implementation of this IoT-based monitoring and control system provides an effective solution to increase efficiency and productivity in swiftlet nest farming. This research opens up opportunities for further development in the application of IoT technology in the business sector, especially in swallow farming.

From data silos to seamless integration and coordination: a data-asset centric approach to smart hospital facility management

PurposeExisting hospital building operations involve numerous information technology applications and complex building systems; therefore, an intelligent facility management (FM) platform is required to ensure their continuous operation. To address the persistent issues of data silos, inefficient data interoperability, and workflow incoordination that have been identified in the current body of FM practice and literature, the present study develops a data-asset (DA) centric FM platform specifically designed for hospital buildings.Design/methodology/approachThis study proposes a semi-customized approach to develop the DA-centric FM platform for hospital buildings. To elucidate the precise function requirements of the hospital FM platform, focus group interviews are employed. By seamlessly integrating the as-built BIM model, IoT sensor data and FM workflow data, the BIM-based DA model with a data transfer mechanism is developed. The development of the FM platform with function modules in a case study is guided by a five-tier architecture and the coordination theory (CT). The case study provides an in-depth introduction to the applications of DA management, space management and maintenance management modules.FindingsThe capabilities of the developed DA-centric hospital FM platform are validated through the case application and user satisfaction survey, which assess data quality, automation level, operation efficiency, flexibility and functionality. For hospital FM activities, this DA-centric FM platform realizes data integration and seamless transformation, optimizes workflow coordination and enhances operation performance.Originality/valueThe initial scholarly contribution is the establishment of the BIM-based DA model, which serves as the data middle platform for continuous data integration, transmission and sharing within the FM platform. Subsequently, under the guidance of the CT, the business process of function modules is designed, improving the intra-module and inter-module workflow coordination. The developed DA-centric FM system along with its performance benchmarking application, assists facility managers and decision-makers in implementing smart operations for hospital buildings and achieving the management goals of safety, efficiency, energy savings and convenience.

A Data Mining-Based Method to Disclose Usage Behavior Patterns of Fresh Air Systems in Beijing Dwellings during the Heating Season

As the popularity of fresh air systems (FAS) in residential buildings increases, exploring the behavioral characteristics of their use can help to provide a comprehensive understanding of the potential for demand flexibility in residential buildings. However, few studies in the past have focused on the personalized usage behavior of FAS. To fill this gap, this study proposes a method based on data mining techniques to reveal the behavioral patterns of FAS usage and the motivations behind them, including motivational patterns, operation duration patterns, and human–machine interaction patterns, for 13 households in Beijing. The simultaneously obtained behavioral patterns, in turn, form the basis of association rules, which can classify FAS usage behavior into two typical residential user profiles containing user behavioral characteristics. This study can not only provide more accurate assumptions and inputs for behavioral stochastic models but also provide data support for the development and optimization of demand response strategies.

Analysis and prediction of energy consumption in office buildings with variable refrigerant flow systems: A case study

Accurately predicting building air-conditioning energy consumption is particularly important for energy management. However, for small datasets, there is a lack of simple and effective prediction methods applicable to multiple buildings. In order to fully explore the energy consumption mode of Variable Refrigerant Flow (VRF) air conditioning system and improve the accuracy of the model. This study uses the weather data of an outdoor meteorological data collection system and the air conditioning system and energy consumption data of an office building in Jinan. Initial analysis revealed that occupant behavior and daily variations in outdoor air temperatures significantly impact the energy consumption of air conditioning systems. Then, by applying the random forest algorithm and Pearson correlation analysis, the study identified daily average outdoor air temperature and VRF indoor unit running time as critical features for prediction. Subsequently, three machine learning models—Multiple Linear Regression (MLR), Back Propagation Neural Network (BPNN), and Long Short-Term Memory (LSTM) neural network—were developed and assessed using a 4:1 training-to-testing set ratio. Comparative analysis revealed that all models performed robustly, with the MLR model exhibited superior predictive accuracy (R2 (Coefficient of Determination) = 0.98, MAE (Mean Absolute Error) = 0.005 kWh/(m2·day), and RMSE (Root Mean Square Error) = 0.007 kWh/(m2·day) for the testing set) and simplicity. Furthermore, the effectiveness of the MLR model in handling small sample sizes was confirmed through cross-validation of data from two additional office buildings, highlighting its suitability for predicting energy consumption of VRF air conditioning systems in office buildings.

Morphological and geological responses of barrier estuaries to dam-opening systems

River discharge depending on the dam gate operation method is an important factor underlying changes in estuarine sedimentation dynamics, but comprehensive studies are limited by data collection constraints. The hydrological operation of Nakdong Dam, designed to prevent seawater intrusion by opening during ebb tides and heavy rains and closing during flood tides, presents an ideal setting for such investigations. This study focused on the Nakdong River Estuary (NRE), utilizing aerial photography, bathymetry data, and sedimentation rate data to determine alterations in sediment transport and deposition patterns within the two tributary estuaries. Spatial discrepancies in sedimentation patterns across the eastern and western regions of the NRE were particularly evident in the spatial variations of textural characteristics and sedimentation rates. An enhanced ebb tidal prism resulting from dam gate opening in the eastern region caused the development of erosional topography and a rough depositional environment, forming a landward migrating (transgressive) barrier island system. Conversely, the predominantly closed dam gates in the western region maintained a consistent deposition pattern due to a regular tidal prism, facilitating the formation of sedimentary topography and fine sediment deposition. Consequently, barrier islands followed a seaward building (prograding) system. Therefore, the results suggested a role of modern dam gate operation as a major sedimentation mechanism, providing valuable insights for the sustainable management of estuarine sediment environments.

Evaluating the impacts of printing operations on indoor air quality in a printing press

PurposeBuilding operations and human activities indoors continuously affect air quality, contaminating the air and sometimes exceeding permissible limits which can be health threatening either in the short or long time. This implies a need for strict awareness and compliance with air quality standards, particularly in workplaces prone to air contaminants emissions. This study aims to evaluate printing-related pollutant concentrations and their effects on indoor air quality (IAQ). The study investigated a printing press's total volatile organic compounds (TVOC), particulate matter (PM), carbon monoxide and carbon dioxide emissions.Design/methodology/approachThis study used mainly an experimental research design supported by physical assessment by identifying the major printing-related pollutants, assessing the existing situation and measuring pollutant concentration levels using literature reviews, walkthrough inspections and experiments, respectively. The measurements were conducted in two scenarios: with and without printing activities, and the results were compared with relevant standards and guidelines.FindingsThe outcomes indicate that TVOC concentration reaches 120 ppb during printing and binding activities, exceeding the 75 ppb acceptable limit based on the time-weighted average. The PM2.5 concentrations reach 49 µg/m3 and PM10 up to 150 µg/m3, exceeding acceptable levels given by the US Environmental Protection Agency (EPA), which are 35 µg/m3 and 150 µg/m3 for PM2.5 and PM10, respectively. These high concentrations of TVOC and PM indicate a significant risk to the health of building occupants, particularly those with respiratory conditions. PM concentrations do not exceed permissible levels when no printing or bookbinding occurs, suggesting that printing-related activities can contribute to elevated TVOC and PM concentrations.Social implicationsThe social implication of the study lies in its ability to promote awareness among workers and improve their well-being which in turn relates to productivity. The study outcome could also encourage businesses to adopt more responsible environmental and social practices as part of corporate social responsibility practices.Originality/valueThe study's findings, which highlight the need for improved ventilation in printing halls, have the potential to significantly benefit building system designers, facility managers, policymakers and decision-makers. By providing information and theoretical support, the research can help integrate policies that regulate IAQ by reducing pollutant concentrations. This protects workers' health and helps update and enforce stricter IAQ regulations for industrial operations.

Economic viability of decentralised battery storage systems for single-family buildings up to cross-building utilisation

Due to the great cost decrease of photovoltaics as well as battery storage, especially in the segment of decentralised home storage, the number of grid-connected battery-supported photovoltaic systems being installed in recent years is steadily increasing. However, the scientific community has intensively discussed that lithium-based battery storage systems cannot yet be operated economically in most cases. This paper addresses the level to which the cost of lithium battery storage needs to decrease in order to be economically viable. For this purpose, the economic viability of battery storage systems in single-family buildings, multi-apartment buildings and across-buildings is analysed on the basis of a linear optimisation model and the method of the internal rate of return. The utilisation of the storage system is optimised for different battery and photovoltaic capacities on the basis of generation and consumption. The internal rate of return method is used to compare the savings resulting from the reduced consumption from the electricity grid with the investment costs and the operation and maintenance costs. In order to be able to estimate the influence of the most important parameters a sensitivity analysis is also carried out. The analysis concludes that, depending on the combination of capacities of photovoltaics, battery storage and in relation to the load profile, the battery storage costs would have to drop by at least 85% in order to generate a certain predefined return over a depreciation period of 25 years. Furthermore, the more different load profiles can be covered directly with photovoltaic electricity, e.g. in a multi-apartment building or across buildings, the less electricity needs to be stored and this reduces the benefit and the utilisation of the battery storage and therefore the specific investment costs must further decrease. Another conclusion that emerges from the sensitivity analysis is that the electricity price and the spread between the electricity price and the feed-in tariff have the greatest influence on the investment costs and profitability. Due to limited space for photovoltaics and simultaneously high consumption, self-consumption is already quite high with cross-building utilisation and can no longer be increased to the necessary extent by the battery storage system, which is why the investment costs must also be lower. The novelty of this paper lies in particular in the fact that it deals with the target costs of battery storage systems in various scenarios for certain rates of return. The analyses in this paper are intended to provide a deeper understanding of the framework conditions for the economic operation of a battery storage system in the aforementioned scenarios. However, this paper does not take into account alternative sources of income other than savings on grid consumption. The possibility of time-variable (grid) tariffs, for example, is also not considered in detail in this paper and should be analysed further in future work.

Study on the performance temporal variation of rainwater harvesting systems based on the dynamic change of rainfall pattern and domestic water demands

Rainwater harvesting systems (RWHs) in buildings are benefits in alleviating urban water scarcity. However, climate change and changes in building water demand affect the expected performance of RWHs over their life cycle. Previous studies have only focused on the adaptability of RWHs to climate change without considering the changes in building water demand. To address this issue, this study explores the impact of combined changes in precipitation patterns and domestic water demand on the water-saving efficiency of RWHs over their 25-year life cycle based on historical observations. Three cities in Japan were selected as case studies. The results indicate that during 25-year life cycle of RWHs, precipitation in different cities in Japan shows an increasing trend, while domestic water demand shows a decreasing trend. Such trend resulted in a change of -2.90–4.02% in the water-saving efficiency of the established RWHs and a change of -2.90–3.82% in the theoretical optimal water-saving efficiency, and these effects were greater in RWHs in buildings with high non-potable water demands. Therefore, RWHs in buildings with low non-potable water demand can appropriately reduce the rainwater tanks, while RWHs in buildings with high non-potable water demand must increase the rainwater tank size to eliminate this adverse effect. Furthermore, both reductions in domestic water demand and increases in precipitation have a positive effect on the water-saving efficiency of RWHs. However, when both domestic water demand and precipitation increase or decrease simultaneously, the change in water-saving efficiency of RWHs is related to the non-potable water demand of the building. This study can provide data support and theoretical evidence for the further implementation of RWHs under climate change, and can help stakeholders to optimize and update RWHs to ensure system feasibility.

Study on properties and simulation application scenarios of flame retarded modified konjac glucomannan organic and inorganic composite aerogel

In this paper, a new organic-inorganic biomass composite aerogel was prepared by freeze-drying method with glucomannan, hydrophilic isocyanate, water-soluble flame retardant, and water glass as raw materials. Biomass Konjac glucose mannan (KGM) was used as the main network framework, KGM was chemically cross-linked and alkali-cross-linked with hydrophilic isocyanate and Na2SiO3 solution, and flame retardant modified with water-soluble flame retardant and water glass. The microstructure showed an obvious organic-inorganic interpenetrating network structure. The compressive strength of sample K2S4P2 was 4.751 ± 0.089 MPa, and the compression modulus of sample K2S4P1B modified by boric acid hydrolysis of Na2SiO3 was 63.76 ± 1.81 × 103 m2/s2. The introduction of boron ions contributes to the thermal stability of organic components. The peak and total heat release rates of sample K2S4P1A4 decreased by 80.3 % and 50.8 %, respectively. In addition, the thermal simulation calculation of the external wall in winter and summer using ANSYS software showed that the thickness of the insulation layer with the best insulation effect is 40–60 mm. The organic-inorganic composite aerogel provides a simple and environmentally friendly method for the application of external wall insulation systems in low-energy buildings with both mechanical properties and flame retardant properties.

Monitoring of indoor environmental quality and acoustic comfort in university classrooms

Indoor Environmental Quality (IEQ) in university classrooms affects students' well-being, comfort and learning performance, thus its evaluation is strongly needed. This work presents an in-field study on the acoustic monitoring, along with thermal, visual and air quality domains, in four recently built university classrooms of Politecnico di Torino. The monitoring was performed in the spring/summer and winter periods, through wall mounted multi-sensor devices. While the monitoring was ongoing, students attending lessons were asked to answer an online anonymous questionnaire on comfort perception, which included questions regarding the four domains and additional personal information. Results show that students are more satisfied with the overall conditions in classroom 3P and more dissatisfied with the overall conditions in classroom 4P. The less satisfying domains are the thermal and air quality ones, whereas the more satisfying are the acoustic and visual ones. Furthermore, at the increasing of TVOC and CO2 concentrations the overall satisfaction decreases. The final aim of this project, based on the monitoring results, is the optimization of the building systems management to reduce energy consumptions and ensure occupants' well-being and comfort.

Wooden multistorey acoustic test facility for vibration reduction indices measurement on different junctions of floor decking used to reduce flanking transmissions

FCBA, CSTB and Cerqual joint forces together with the French acoustic wood technical commission, to create in 2020, an in-situ measurement mockup: the "Maquette Acoustique Bois". The mockup is a CLT based building of three floors construction, with four rooms on each level. Measurements from junction characterization to air-borne and impact sound insulations can be performed. In this paper the "Maquette Acoustique Bois" is used to measure vibration reductions levels indexes Kij, in different configurations, where smart building systems junctions are implemented to reduce flanking transmissions. Measurement results presented are generated from 4 types of junctions in between 2 rooms. The load bearing structure is Cross Laminated Timber (CLT). The measurement strategy is Statistical Energy Analysis (SEA). SEA involves cutting the structure into subsystems and decomposing the spectrum into third-octaves or octaves. In this way, the exchange of energy flow in the substructures can be analyzed. The parameters that govern vibrational transmission between subsystems are damping and coupling loss factors and can be identified experimentally by reversing the problem. The approach is, first, based on sub-structuring strategy of structure; second, on experimentally measured coupling and damping loss factors; third, on extracting vibration level difference one by one all flanking passes.

A comprehensive study for a classification scheme for dwellings in Brazil

ABNT NBR 15575 was published in 2013 and establishes acoustic insulation criteria for residential buildings in Brazil. This standard presents three levels of performance - minimum (mandatory), intermediate, and superior - through an informative annex that classifies the acoustic performance for each requirement. Even after ten years of publication, the application of the standard is still not fully consolidated, although its application is mandatory under Brazilian law. This article proposes a classification of the entire acoustic system of dwellings, intending to enable the general public to understand acoustic performance quickly and intuitively, thus encouraging its application. The proposed classification scheme is based on ISO/TS 19488:2021, which presents harmonized criteria for different acoustic requirements. A large database of field measurements of building systems, typical of Brazil and obtained in different regions, was analyzed to verify the distribution of samples using this new scheme. An A/B/C/D scale is proposed, and results are presented for airborne sound insulation/impact between dwellings, airborne sound insulation for facades, and criteria for equipment sound levels in commercial buildings.

Structural System and Computational Dynamic Model of a Life-Saving Multi-Storey Building with a Kinematic Seismic Isolation System

Introduction. In design of a life-saving multi-storey building, a seismic isolation system in the form of the kinematic supports is used to ensure the seismic resistance and reduce the seismic loads. The structural system, the computational dynamic model and the results of the intermediate in-situ tests of a life-saving multi-storey building with a kinematic seismic isolation system being built in Grozny have been analysed in the article.Materials and Methods. The research included modeling and computation of the structural system of a building with a kinematic seismic isolation system. In-situ tests were carried out to confirm the working capacity of the seismic isolation system connections.Results. A multi-storey life-saving building was designed according to a frame-core wall structure, where the vertical load-bearing elements were core walls, columns and connections between the columns in the form of the stiffening diaphragms. The high-rise part of a building was designed using a kinematic seismic isolation system consisting of the seismic isolating concrete-filled steel tubular supports. The results of the calculations of the main and specific load combinations and internal forces in the load-bearing structures have been presented.Discussion and Conclusion. The research has shown that the use of the developed structural system of seismic isolation with kinematic supports makes it possible to reduce the seismic loads and the total weight of a building and at the same time to increase its mechanical reliability and safety. The conducted intermediate in-situ tests have confirmed the working capacity of the joints connecting the supports with the monolithic reinforced concrete structures of a building, which makes it possible to implement the kinematic seismic isolation supports into the construction industry practices.

THE ROLE OF PROPERTY MANAGEMENT IN PROMOTING ENERGY-EFFICIENT SOLUTIONS FOR RENTALS

Real estate management plays a key role in promoting energy efficient solutions when renting out properties. The purpose of the study is to analyze the impact of management companies on the introduction of energy-efficient technologies to increase the competitiveness of facilities and reduce operating costs. The methodology is based on the analysis of data on the application of modern energy-efficient solutions, including lighting, heating and automation systems in buildings in the Czech Republic. The results showed that the use of such technologies helps to reduce utility costs by 20-40% and increases the attractiveness of facilities for tenants. In conclusion, property management aimed at energy efficiency ensures the achievement of sustainable development and economic benefits for owners and tenants. These measures increase the market value of the properties and extend the lease terms, which strengthens the position in the real estate rental market.

Development of optimization control system for chiller plant based on a predictive model with Multi Stack LSTM and Deep Learning Neural Network Multi Output

Net-zero emissions become necessary for every country, implementing energy efficiency is the way to achieve it. Released report by the International Energy Agency in September 2022 stated that energy efficiency and electrification are the main priorities for Indonesia in achieving NZE. Currently, more than 50 % of energy consumption in buildings is intended for cooling systems (chillers plants). Thus, energy efficiency in buildings cooling systems has great potential to help achieve NZE and support SDGs. This research is intended to find an optimization control system for chiller plant in order to reduce energy consumption of cooling system in building. The development of this optimization control system is based on predictive model with Multi Stack LSTM and Deep Learning Neural Network. This research developed four different optimization control system frameworks. Every developed framework then will be tested by carrying out simulation with Chiller Plant model. The important parameter was found by using correlation matrix. Based on the correlation matrix, it was found that the most influence parameter that affect chiller plant performance are Tcws and Twb. It leads developed Frameworks 1 become the best compared with others developed frameworks in this research, because it used Twb as a variable input in parallel with performance prediction. This developed framework has deficient error MAE, MSE, RMSE respectively 0.8079, 0.6527, 0.8079 and able to reduce energy consumption by 10.72 %.

Benefits derived from WASP (a Grasshopper plugin) to Design for Disassembly Principles in the Built Environment

Abstract Design for Disassembly (DfD, henceforth) is a way to improve the effectiveness of the disassembly process in built environments, and it mainly contains ten principles. Examples of the principles include deconstruction techniques; selected materials; reachable connections; utilizing connections with fewer bolts, screws, and nails; the straightforwardness of the structure and design; and versatility. On the other hand, the WASP plugin for Grasshopper (on Rhinocheros©) is a toolkit for discrete computational design to simulate the aggregation and assembly possibilities in the building system. This paper explores the integration of the WASP plugin within the context of DfD through three criteria: the aggregation processes of part geometries, connection locations, and their orientation toward the building elements. Design with discrete elements, which can be defined as shape grammars for building structure, is the primary approach for the joining behavior and detaching behavior of elements discussed in this paper. Also, this type of component-based design can optimize the geometry and data-driven generation of the structure. The design process in this way can be disassembly sequence planning and knowledge-based design by applying the design constraints. To illustrate the integration, research is conducted through WASP simulation in designing a traditional Iranian timber pavilion-inspired structure with a 3×3m footprint in a roof structure. The fusion of WASP and DfD represents a promising avenue for advancing circular design principles and achieving more sustainable, resource-efficient buildings. It is concluded from this study that WASP makes the aggregation simulation and assembly possibilities of the vertical and horizontal components in a building more accessible.

Particle Swarm Optimization for multi-chiller system: Capacity configuration and load distribution

This study applies Particle Swarm Optimization (PSO) to enhance the energy efficiency of a multi-chiller system in a large office building, with a focus on optimizing capacity configuration and load distribution. Given the rising demand for sustainable energy solutions in buildings, where HVAC systems, particularly chillers, account for a significant portion of energy consumption, this research aims to reduce energy use and improve system performance. EnergyPlus simulations, based on Baltimore weather data and a reference large office model, were conducted to build a baseline dataset. This dataset was then used in Python to calculate energy consumption and optimize load distribution and capacity configuration. PSO was applied in three stages: optimizing capacity configuration using five built-in EnergyPlus algorithms, optimizing load distribution, and simultaneously optimizing both. The results showed that optimizing capacity configuration alone improved performance, even using traditional load distribution methods. Load distribution optimization outperformed other algorithms and converged at a 0.7 Part Load Ratio (PLR) for staging. The integrated PSO application achieved an 11.3 % reduction in energy consumption, a 21.5 % improvement in Coefficient of Performance (COP), and a 12.8 % increase in the Seasonal Energy Efficiency Ratio (SEER) by precise operation of 15 different combinations throughout the entire load range. These results demonstrate the potential of PSO to significantly enhance the efficiency of multi-chiller systems, providing a novel approach to optimizing both capacity configuration and load distribution. This research contributes to a robust framework for improving energy performance in building systems and offers valuable insights for future sustainable energy solutions.

Building stock energy modeling to assess annual progress in stock energy efficiency and carbon emission reduction of commercial buildings

Short-term progress assessments of carbon dioxide emission reductions are essential for nations to meet their medium/long-term targets. Bottom-up building stock energy modeling (BSEM) methods can contribute to this issue but have not been applied because of the need to represent short-term building stock dynamics in building systems and energy conservation measures (ECMs). To fill this gap, this study developed a BSEM framework that integrates top-down building stock decomposition, including building systems and ECMs, and bottom-up physics-based energy demand quantification using reference building models representing building stock segments. The framework was verified through a case study of a Japanese commercial building stock. The results indicate that the developed model effectively captures the short-term dynamics and contributions of the technologies. Although there are significant errors in estimating some building subsectors and end uses, the model predicts the changes in the aggregated energy consumption with acceptable accuracy. The Japanese 2030 emission reduction target cannot be achieved with the current technology deployment trends; however, the shortfall can be addressed by applying additional measures. Owing to its applicability to diverse building stocks, the framework promotes the use of BSEM for policy assessment and evidence-based policymaking for climate change mitigation.

Assessing the Potential of Smart Windows for Energy Efficiency in Tropical Buildings: A Review of Current Research and Future Directions

Abstract Smart windows have energy-saving potential in buildings in tropical climates. Characterized by high solar radiation, humidity, and temperature, tropical climates demand innovative solutions for energy-efficient building design. Smart windows, which can regulate the transmission of light and heat through different thermochromic, photochromic, or electrochromic technologies, are promising to reduce energy consumption in such buildings. Several emerging window technologies, such as gasochromic, hydrochromic, polymer-dispersed liquid crystal, and suspended particle device technologies, also have promising energy-saving potential. However, their high initial costs, durability, and reliability of these technologies limit their applicability. Prospects for smart windows in buildings in tropical climates include advancements in materials science, cost reduction, and integration of smart window technology with other building systems, such as lighting and heating, ventilation, and air conditioning systems. The potential benefits of smart windows for energy-saving s in buildings in tropical climates are substantial, up to 37%. Thus, further research and development in this area would lead to significant advancements in sustainable building design for a better future.