Next Article in Journal
A Review on the Behavior of Ultra-High-Performance Concrete (UHPC) Under Long-Term Loads
Previous Article in Journal
A Semi-Automatic Ontology Development Framework for Knowledge Transformation of Construction Safety Requirements
Previous Article in Special Issue
Optimisation of Nearly Zero Energy Building Envelope for Passive Thermal Comfort in Southern Europe
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Evaluating the Impact of Insulation Materials on Energy Efficiency Using BIM-Based Simulation for Existing Building Retrofits: Case Study of an Apartment Building in Kanazawa, Japan

by
Xiao Teng
1,2,
Zhenjiang Shen
3,* and
Dara Citra Saraswati Tutuko
4
1
Graduate School of Environment Design, Kanazawa University, Kanazawa 920-1192, Japan
2
Youke Communication Technology, Fuzhou 350005, China
3
International Joint Laboratory of Spatial Planning and Sustainable Development (FZUKU-LAB SPSD), Fuzhou University-Kanazawa University, Fuzhou 350025, China
4
Graduate School of Natural Science and Technology, Geoscience and Civil Engineering, Kanazawa University, Kanazawa 920-1192, Japan
*
Author to whom correspondence should be addressed.
Buildings 2025, 15(4), 570; https://doi.org/10.3390/buildings15040570
Submission received: 24 December 2024 / Revised: 30 January 2025 / Accepted: 3 February 2025 / Published: 13 February 2025
(This article belongs to the Special Issue Advanced Studies in Nearly Zero-Energy Buildings and Optimal Design)

Abstract

This research aims to facilitate informed decision-making to enhance building energy simulation, reduce costs, and minimize CO2 emissions through building insulation enhancements employing BIM-based simulation. Architectural models of an apartment, a prevalent residential structure in Japan, were developed and examined under diverse insulation scenarios utilizing ArchiCAD 28. Five insulation substances were chosen based on existing guidelines to ensure conformity with local standards and were evaluated for their thermal and environmental properties: Cellulose Fiber, Glass Wool, Urethane Foam, Phenolic Board, and Rock Wool for evaluation based on thermal and environmental properties. The simulation parameters were aligned with Japan’s energy efficiency standards and climate conditions. The factors addressed encompass energy performance evaluation, economic viability, and CO2 emissions. Simulation findings highlight Urethane Foam as the most effective and environmentally friendly building insulation material. This study provides valuable perspectives for property owners, building designers, and contractors, offering a framework for insulation enhancement choices that optimizes sustainable construction, reduces environmental impact, and enhances cost-effectiveness through the implementation of BIM-based simulation.

1. Introduction

Urban areas are responsible for a significant share of global energy use and emissions. Buildings typically account for around 40% of the worldwide energy consumption [1]. The Japanese government is committed to achieving carbon neutrality by 2050 [2]. It is also supported by several actions, such as the Building Energy Efficiency Act, Zero Energy House, and Zero Energy Building initiation. Approximately 60% of existing buildings in Japan predate the 1979 Energy Saving Act. Despite advancements in energy efficiency for new constructions, the annual construction rate remains at approximately 2% [3]. The achievement of carbon neutrality is also supported by government grants, such as subsidies for buildings that meet the criteria for zero energy or effective energy buildings, emphasizing the importance of upgrading older structures to meet modern energy standards.
Renovating existing buildings to improve their energy efficiency is a complex undertaking that requires diverse strategies and factors. And considerations. Enhancing the building envelope through insulation can significantly reduce energy consumption by minimizing heat loss and gain. For instance, a study demonstrated that major retrofitting strategies could reduce energy intensity by 24.12% and CO2 emissions by 18.56% [4]. Moreover, the Ministry of Land, Infrastructure, Transport and Tourism of Japan also initiated the Energy-Efficient Homes 2024 Campaign with financial support like subsidies for buildings that meet their requirements for energy-efficient building practices, such as wall insulation renovation. This underscores the importance of upgrading buildings to achieve energy efficiency.
Conducting energy analyses helps to examine the usage patterns within a building’s designed model, supporting designers in making informed, cost-effective decisions that enhance building performance and minimize environmental impact [5]. Building Energy Modeling is a potential tool in architecture, engineering, and construction for sectors that enhance energy efficiency. BIM software allows architects to develop 3D models for multiple purposes, such as forecasting energy usage [6]. This research will leverage one BIM software, ArchiCAD 28, to perform an energy simulation of a building with several scenarios and reveal the most beneficial scenario for energy use. Determine the most efficient building insulation material for retrofitting existing buildings, with a specific focus on Kanazawa City, Japan, a region characterized by cold winters and warm summers typical of a temperate climate.
The simulation-based approach applied in this research evaluates the real-world effectiveness of five insulation materials included in Japan’s guidelines for energy-efficient housing. By considering the climatic characteristics of Kanazawa City, this study aims to provide an informed decision to optimize energy savings, reduce costs, and minimize CO2 emissions through building insulation upgrades using a BIM-based simulation. This finding is intended to support retrofitting initiatives that align with local standards and are valuable for buildings located in the same regions or climate conditions, promoting sustainable building practices.

2. Literature Review

2.1. Utilization of Building Information Modeling to Enhance Building Energy Efficiency

The realization of Sustainable Development Goals within the architectural sector is influenced by the advancement of artificial intelligence, smart devices, and various technological innovations [7]. Energy conservation is essential for sustainable development of the construction sector. Moreover, the energy aspect of buildings can be further implemented in broader applications, including energy monitoring systems for infrastructure monitoring systems [8]. With the increasing significance of technological advancements to aid sustainable growth for energy efficiency, one of the architectural innovation tools in this research is Building Information Modeling (BIM). BIM software enables architects to create three-dimensional models for various applications, including energy consumption prediction [6]. The shift from BIM to Building Energy Modeling (BEM) enables the refinement of building envelope designs, improving energy efficiency and economic viability [9]. Designers can utilize the approach of Building Information Modeling (BIM) and Building Energy Modeling (BEM) to evaluate design options and make design decisions efficiently during the building design process. The process of retrofitting existing structures, which involves systematic upgrading and enhancement of their energy efficiency, represents a fundamental strategy for achieving sustainability [10]. BIM is a potential tool for assessing refurbishment options through the modeling of various elements; findings indicate that the optimal refurbishment scenario can lead to a reduction of 61% in annual fuel consumption and 64% in electricity consumption for a house in Turkey [11]. A case study in China proved that evaluating the feasibility of BIM-enabled LCA by simulating scenarios for existing building refurbishment can analyze building energy factors, such as energy efficiency, environmental compatibility, and profitability tools [12]. A case study of residential buildings in Pakistan using BIM for energy simulation suggests that optimization with enhancements in window configurations and construction materials can realize savings of up to 30% over a period of 30 years [13]. Predicting accurate decision-making processes with BIM is also utilizable for a museum building in Brazil, revealing that BIM can help in the assessment of damage reconstruction planning for proper conservation methodology for project decision-making [14]. Building energy consumption is reduced by 30% when simulated with BIM in retrofitting existing public buildings in Malaysia, highlighting its potential to enhance energy efficiency [15]. BIM contributes to sustainable renovation practices across diverse building types and geographic regions.
These significant findings underscore the remarkable capacity of BIM to guide effective strategies in building energy, making BIM a valuable tool in sustainable construction practice. Within Building Information Modeling (BIM) applications, especially when appraised based on both their utilization frequency and the effectiveness of their implementation, ArchiCAD reliably stands out as prominent software [16]. Additionally, ArchiCAD complies with the ASHRAE standards, which makes it suitable as a BIM-based simulation tool for this study. Moreover, the study by Siti Birkha Mohd Ali et al. proved the leverage of ArchiCAD as a tool for effective retrofitting decision-making [17]. The energy model review range in ArchiCAD confidently integrates a wealth of information pertaining to building design, materials, environmental context, wind protection, and much more as essential components of the Energy Performance Evaluation.
Based on previous study findings, this research will further explore the energy usage of a building modeled in BIM, with a particular focus on evaluating the impact of various insulation material scenarios for residential buildings located in Kanazawa, Japan. The BIM framework exhibits significant adaptability, permitting customization for different conditions and building classifications. This versatility enhances its utility across a wide range of building types and is essential for evaluating energy consumption and refining material choices in sustainable construction methodologies. Choosing sustainable materials offers numerous benefits; thus, it will be efficient to use BIM to project their energy usage to choose the best material. The simulation will provide valuable insights, enabling informed decision-making and facilitating the selection of the most effective and sustainable options.

2.2. Building Insulation Material for Energy Efficiency

The building envelope is essential for assessing a building’s energy efficiency by affecting the heating and cooling requirements. Insulation is a vital element of a building envelope that significantly influences energy conservation. Evaluating the building envelope is one of the significant elements for optimizing building energy [18]. Building envelope renovations and phase change material can effectively reduce the energy consumption of the building [19,20]. Since the insulation layer plays an important role in energy performance, it is important for enhancing energy efficiency and minimizing environmental impacts such as gas emissions [21]. Insulation material will play a role in maintaining thermal comfort inside the building by reducing heat transfer through the building envelope. The extent of insulation significantly influences both the internal thermal conditions and energy consumption [22]. Reducing energy loss in buildings can be achieved by applying suitable insulation to the building envelope [23]. Furthermore, the thermal barrier material has a pivotal function in regulating internal moisture, preserving sound levels, and offering flame resistance, thereby enhancing comprehensive energy, ecological, economic, and comfort optimization [24]. Various insulation materials are available in the market, and buildings employ both inorganic and organic thermal insulation materials to preserve energy and avoid thermal heat loss. Organic insulation was recently used as a choice for the fabrication of economical and lightweight polymer composites such as Polystyrene and Polyurethane Foams [25]. Another organic insulation material is cellulose-based materials, which exhibit good performance in fire safety and enhance thermal insulation by 16.66% to 17.06% [26]. Additionally, there are types of natural and mineral insulation that are widely used, such as Rockwool, Glass Wool, and Wood Wool, which have notable performance for building envelope insulation performance [27,28,29]. Insulation materials play a vital role in enhancing the energy efficiency of buildings and ensuring the overall building performance and occupant comfort. Applying the right insulation material to building envelopes is essential for sustainable construction practices, balancing energy savings with environmental and economic considerations.

3. Methodology

In this study, a BIM-based simulation approach was employed to evaluate the energy efficiency, cost-effectiveness, and environmental impact of various insulation materials for retrofitting residential buildings. Figure 1 provide an overview of the methodology of this study. Firstly, a building model was developed using ArchiCAD, incorporating detailed geometry, materials, and spatial configuration to serve as a versatile framework for analyzing retrofitting strategies. Secondly, the climatic conditions of Kanazawa City, located in Japan’s 5th climate zone, were considered, and simulation parameters were aligned with national standards, including the Building Energy Conservation Act and the Energy-Saving Design and Construction of Housing 2023 guidelines. This ensured that the simulations adhered to the energy efficiency requirements and were applicable to buildings in similar contexts. Thirdly, five insulation materials—Cellulose Fiber, Glass Wool, Urethane Foam, Phenolic Board, and Rock Wool—were selected for simulation. Material properties, including thermal conductivity, density, heat capacity, embodied energy, and embodied carbon, were sourced from manufacturer specifications and adjusted using ArchiCAD’s database in alignment with the ASHRAE Standard 140-2007 [30]. Lastly, the simulation process was conducted by defining the building’s geometry, creating thermal zones and blocks based on operational profiles, and assigning utilities and material properties. Climate data, including temperature, humidity, solar radiation, and wind speed, were incorporated using Typical Meteorological Year (TMY) files. Five scenarios were generated by varying the insulation materials while maintaining consistent configurations for other building components. The simulation results were then analyzed to compare the energy consumption, cost, and CO2 emissions for each scenario.

4. Case Study in Japan

4.1. Overview of the Case Study Building

This study employs ArchiCAD as a Building Information Modeling (BIM) tool to evaluate the energy efficiency of apartment buildings. The models were created in ArchiCAD and converted into energy models by defining the building geometry, zoning, utilities, occupancy, and geographic information. The model will be simulated in five scenarios of different wall insulation materials. Building energy modeling provides simulation results for energy performance, allowing for a comprehensive comparison between scenarios.
The case study in this research is an apartment building located in Kanazawa, Ishikawa Prefecture; the building model is presented in Figure 2. The building type chosen is an apartment building, which is a typical residential type in urban areas. The housing types in Kanazawa City from 2010 to 2020 reveal three main categories: detached houses, apartment buildings, and others. In 2020, detached houses constituted 56.7%, apartment buildings 42.2%, and other types 1.1% [31]. Throughout the decade, the proportion of detached houses experienced a minor decline, whereas apartment buildings exhibited a consistent increase of about 2.68%. This pattern signifies a progressive transition in housing construction preferences in Kanazawa City, with a notable increase in the prominence of apartment buildings in recent years. Japan categorizes its climate into seven zones based on yearly average temperatures [32]. The selected case study building in Kanazawa City, Ishikawa Prefecture, is located in Japan’s 5th climate zone, characterized by an annual average temperature of 9–12 °C, making it suitable for assessing energy efficiency in moderately cold climates. The apartment is a three-story concrete building with a rectangular shape oriented facing south−north in a dense residential area. Built in 1999, it consists of a single entry 21 unit of 1R in a ground area of 217 m2. Since 1980, Japan has established five energy efficiency standards for insulation in newly built residential buildings, introduced in 1980, 1992, 1999, 2013, and 2016 [32]. Furthermore, on 13 June 2022, Japan ratified the amended Building Energy Conservation Act, setting a target for all existing buildings to meet these standards on average by 2050, demonstrating the country’s commitment to sustainable construction and energy conservation [33]. This case study is a representative example of older constructions that lack modern energy efficiency standards. This case study provides a valuable opportunity to explore retrofitting strategies to improve the energy efficiency of similar urban residential buildings.

4.2. Scenario Setting for Simulation

After the implementation of the Building Energy Efficiency Act in Japan, with several establishmenst of standards since 1980, all residential buildings comply with the latest regulations for newly constructed or retrofitting as mandatory [32]. Furthermore, in recent years, to realize decarbonization, it has become necessary to save energy not only in new houses but also in existing houses. The Ministry of Land, Infrastructure, Transport and Tourism (MLIT) created the Energy-Saving Design and Construction of Housing 2023 guideline [34]. With the newest guidelines, this research will follow a standard for 4~7 region energy-efficient housing design and construction. This standard covers some insulation materials that can be used, as shown in Table 1.
According to the criteria, five insulation materials will be simulated in this model. The materials chosen in compliance with the list of products that meet the criteria for renovation subsidy, which are listed on eligible renovation work for insulation renovation, are shown in Table 2. The value of material properties is indexed by the information on thermal conductivity and density from the product manufacture specification [35]. The heat capacity, embodied energy, and embodied carbon are listed by ArchiCAD, referring to the ASHRAE Standard 140-2007 [36], and they are adjusted to a similar product with the same thermal conductivity.

5. BIM Energy Simulation

5.1. BIM-Based Building Energy Simulation Steps

Designing a building in Building Information Modeling is different from drawing a conventional 2D model; beyond that, the BIM model serves as a database system with the 3D view reflecting the data stored in the system, allowing for extraction, modification, and reinsertion of information, impacting the diverse structures of models in terms of defining elements, materials, and object descriptions [37]. The BIM Modeling process entailed the identification and simulation of different architectural and structural components, such as floor area, walls, openings (doors and windows), frames, slabs, and roofs [17]. Moreover, every geometry contains detailed information that automatically recognizes the material’s essential information, such as U-Value. U-values define building energy efficiency by quantifying heat loss through the building envelope elements like walls, windows, doors, floors, and roofs, which are crucial for energy savings [38]. The steps of the BIM energy simulation in this research will be explained in the following order.
A building model is created, and prior to achieving the optimum result simulation of the energy performance evaluation, the precise building part should be defined. As presented in Figure 3, a building model is created. Adding a zone into each room with specific room usage is essential; zones in ArchiCAD’s energy modeling refer to segmented areas that are analyzed for particular energy consumption and requirements. The “Thermal blocks” are collections of these zones that possess the same operational profile and mechanical systems, facilitating customized energy analysis predicated on shared attributes, as illustrated in Figure 4.
In the energy model review, ensure that every geometric representation contains comprehensive data that identifies the fundamental information regarding materials, such as U-Value, which will affect energy efficiency by measuring thermal dissipation through the structural envelope components, including walls, windows, doors, floors, and roofs. The focus of the simulation will be on evaluating wall insulation; thus, all building structures should be aligned with the designated wall specification, and each component of the building structure should be recognized on the building energy model, as displayed in Figure 5. The next step in building energy analysis is to assign each of the thermal blocks to its utility system, as shown in Figure 6. Utilities play a major role in the energy consumption of buildings and help shape their energy profiles [39]. Setting each system directly determines the building energy system type and source.
After defining the building utility, define the building operation profile. Building occupancy affects energy consumption by influencing control systems. In this case, the operation profile is assigned as a residential occupancy type. Figure 7 shows the building’s operational profile, which was designated as a residential building for this study. Designating an actual location for modeling building energy is essential. The location and climate of a building influence its energy use. The location and climate data that are assigned in ArchiCAD will be derived into air temperature, relative humidity, solar radiation, and wind speed served in a range of a year. The climate data is obtained from the Typical Meteorological Year (TMY) climate file, a set of hourly weather data for a specific location that represents a typical year, as shown in Figure 8.
After the building energy model is established, each model is modified into several scenarios to adjust their wall material composition. The general composition of a building consists of a structure with an exterior finish, a layer of insulation and cavity, and an interior wall with a finish. A representation of the wall composite used in this simulation is shown in Figure 9. In each scenario, the insulation layer will be replaced by the designated materials chosen. Figure 10 shows the five scenarios used in this model by replacing only the insulation material while maintaining the same wall configuration.

5.2. Energy Performance Evaluation and Simulation Results

When all the building energy modeling items, such as geometry, zones, building system, building occupancy, and geographic information, are assigned, energy performance can be generated. ArchiCAD will calculate the data contained in the model and add it to the Energy Performance Evaluation Report. The details of Simulation Scenarios 1 through 5, along with their key values and project energy balance are presented in Figure 11, contain overall information about specific annual values of energy usage. The simulation result will be focused on the value in the red box.

6. Comparative Analysis of Insulation Materials: Energy Efficiency, Cost, and Carbon Emissions

6.1. Simulation Results and Performance Overview

Based on the simulation results, the key value and project energy balance help examine the usage patterns within a building’s designed model. Some key values will be analyzed to understand which scenarios are more energy efficient, have a minimum environmental impact, and are effective in cost.
Urethane Foam is the most energy-efficient scenario with the lowest Total Energy Consumption (100.90 kWh/m2a) and Primary Energy (118.58 kWh/m2a). Phenolic board follows closely with slightly higher Total Energy Consumption (101.94 kWh/m2a) and Primary Energy (119.06 kWh/m2a). Glass Wool and Rock Wool are less efficient compared to the others, with identical Total Energy Consumption and Primary Energy levels. These differences in energy consumption highlight that foam plastic-based materials like Urethane Foam have better energy efficiency rather than fibrous materials. All scenarios have similar Net Cooling Energy requirements, with Urethane Foam being the lowest at 14.68 kWh/m2a, with the lowest Fuel Cost (1124.19 JPY/m2a) and CO2 Emissions (7.86 kg/m2a), indicating better cost and environmental performance. Glass Wool and Rock Wool are less efficient compared to the others, with identical Total Energy Consumption and Primary Energy levels. This suggests that while fibrous materials may offer some insulation benefits, the superior thermal performance and lower environmental impact of Urethane Foam make it a more viable option for energy-efficient building applications.

6.2. Energy Efficiency Factor

This research focuses on a case study located in Kanazawa City, Ishikawa Prefecture, which is part of Japan’s 5th regional climate zone, including the Hokuriku region. The Hokuriku region stands out for having the highest intensity of electricity consumption in both residential and industrial sectors across Japan, boasting a mean usage of approximately 6620 kWh/year for residential buildings [40]. In comparison, the simulation shows that the best-performing scenario reduces energy consumption by 58.89% compared to the regional average. The building, relying on electrical energy and using Urethane Foam insulation, has an energy consumption intensity of 100.90 kWh/m2/year, totaling approximately 57,150.77 kWh/year for the entire building. With 21 units in the building, this amounts to 2721.47 kWh/year per unit. This demonstrates that the simulated energy consumption is significantly lower than the regional average. This comparison between the simulation results and real-world data highlights that the simulated value is significantly lower than the regional average. However, it is important to note that the operational usage of each unit may vary. Nevertheless, a consumption value of 2721.47 kWh/year per unit is highly efficient, with basic utility usage settled in this scenario and well below the regional mean electricity usage.
Based on the simulation results in Table 3, the best- and least-performing materials can be ranked by order number. Urethane foam is 1st preferable option, followed by Phenolic board; 2nd, Rock Wool and Cellulose Fiber had a similar result and placed in 3rd, and Glass Wool placed in 4th as the least preferable option.
A database from a website provided by the Sustainable Open Innovation Initiative is accessible for the Zero Energy Home (ZEH) case study inquiry search tool for the Fiscal Year 2024, providing insights into energy-saving performance, insulation, and equipment specifications from over 1500 adoption cases across Japan [41]. Table 4 shows several case studies that use similar materials to those used in this simulation, compared with the simulation result performance rank of this study.
Only four materials from the database match the material studied in this simulation. The web data case study corresponds to the priorities identified in the simulation outcomes. In general, it is evident that Glass Wool and Rockwool display comparatively low energy reduction, whereas Phenolic and Urethane Foam exhibit significant energy reduction values. Among these materials, Urethane Foam attains the highest energy reduction with a 40% reduction, while Glass Wool demonstrates the most minimal performance with a 21% reduction. Nevertheless, particular cases, such as Case Study 2, Case Study 6, and Case Study 7, reveal scenarios in which both low-performing and high-performing materials attain equivalent energy reduction values with a 26% reduction. This signifies that energy reduction is profoundly affected by other factors. Building types and floor areas may differ, prompting a comparison between real-world data and the simulated performance of these materials, including equipment and other elements affecting building energy performance. Consequently, employing Building Information Modeling (BIM) in simulations provides a proficient approach for executing comparisons customized to specific structures.

6.3. Cost Efficiency Consideration

As a consideration to choose the best insulation material, based on the simulation, Urethane Foam consistently outperforms the others, with the lowest Total Energy Consumption (100.9 kWh/m2/year) and CO2 emissions (7.86 kg/m2/year). However, Urethane Foam is considered an expensive material, with an estimated cost of 5000–9000 JPY/m2. Phenolic Board also performs well, offering a strong alternative to the material cost of approximately 3500–7000 JPY/m2. Fibrous materials such as Glass Wool, Rock Wool, and Cellulose Fiber have low-cost material prices (approximately 2000 JPY/m2–5000 JPY/m2).
Renovating the building insulation may require additional labor and preparation, while new constructions allow for seamless integration. The labor and installation costs of the reconstruction project are relatively similar for each material; the difference lies in the cost per quantity of material to be installed. According to the Energy-Saving Design and Construction of Housing 2023 guideline [34], fibrous materials such as cellulose fiber, Rock Wool, and Glass Wool need to be installed with careful consideration of their moisture absorption properties. Glass Wool and Rock Wool are non-combustible; however, it requires vapor barriers to prevent moisture infiltration, as moisture can degrade their performance over time. In contrast, foam plastic materials, such as Urethane Foam and phenolic boards, are durable and can form continuous layers.
When choosing insulation material for an existing building, decision-makers must consider the compromises between efficiency, expense, and the structure’s lifespan. Nevertheless, these materials require careful selection of the current building conditions and the property owner’s budget. As reflected in Table 5, by evaluating the priorities of expense and efficiency, the building owner can choose the most suitable materials for their reconstruction needs.

6.4. Carbon Emission Factor

In recent years, a concept has emerged in sustainable construction practices in Japan known as LCCM (Life Cycle Carbon Minus) house certification. An LCCM (Life Cycle Carbon Minus) house is a dwelling that attains a negative CO2 balance throughout its life cycle, encompassing the CO2 emissions during construction, operation, and disposal by minimizing CO2 emissions as much as feasible over its extended lifespan [42]. Achieving net-zero targets and lowering the carbon footprint of buildings throughout their life cycle is crucial, and this can be accomplished by the reduction of embodied carbon, structural optimization, and recycling of construction waste [43,44]. Thus, in a renovation project, the disposal of the building material can be processed into construction waste recycling, and the building can renew insulation with a better material and contribute to minimizing energy and carbon consumption. Accordingly, through renovation projects, building materials can be processed as recycled construction waste, and building insulation can be upgraded with better materials, contributing to reduced energy consumption and lower carbon emissions.
All scenarios exhibit slightly different energy performance levels. In contrast, to highlight the comparison between cost and environmental impact, the bar chart of Figure 12 represent a comparison between Fuel Cost and CO2 emission. Fuel Cost (JPY/m2a), represented as a blue bar to show the annual operational cost of fuel required per square meter. CO2 Emissions (kg/m2a), as the red line represents the annual carbon dioxide per square meter. The costs of materials and manufacturing profoundly influence the carbon footprint of a product, as carbon emissions are influenced by material production, transport, and disposal [45,46,47]. While the production of building materials significantly impacts the overall carbon footprint, the use of highly durable materials is encouraged. The BIM-based simulation tool in this research reveals the CO2 emissions of the material by each carbon factor, making this method suitable for assessing the carbon footprint of the building.

6.5. Material Selection Considering Energy Efficiency, Cost, and CO2 Emission

Referring to the heat map in Figure 13, it provides a clearer visual representation of the difference’s comparative performance of the material in terms of energy consumption, CO2 Emission, and material cost. It is obvious that Urethane Foam emerges as the most economically advantageous and sustainable insulation alternative, consistently exhibiting the lowest fuel expenditures and CO2 emissions across all evaluated scenarios. In contrast, Glass Wool demonstrates the least optimal performance, characterized by the highest fuel expenditure and CO2 emissions, making it a less desirable option in terms of economic efficiency and ecological sustainability.
This comparative analysis shows the significance of choosing materials such as Urethane Foam that have a balanced economic advantage and the least environmental impact. As the demand for sustainable construction methodologies increases, comprehending the performance metrics of insulation materials becomes important. In comparison to the investigation conducted by Siti Birkha Mohd Ali et al., which similarly employed ArchiCAD as a tool for energy simulation, it was demonstrated that the combination of window parameters markedly enhanced the infiltration rate and heat transfer coefficient, culminating in a reduction in the cooling load ranging from 3% to 6% [17]. In a parallel manner, this study underscores the significance of selecting optimal insulation strategies, with the most favorable scenario incorporating Urethane Foam resulting in a Total Energy Consumption reduction of 58.98% in relation to the regional mean. Aligned with the study by Nasrollahzadeh, this research underscores that the insulation of the building envelope constitutes one of the paramount factors affecting energy performance [21].
The diverse insulation scenarios simulated in this research will provide guidance to property owners and contractors in selecting the most efficient insulation materials for buildings located in climates similar to those in Kanazawa City. As demonstrated in the result simulation, the best scenario will enhance 57.98% of energy consumption use compared to regional consumption intensity; it conforms to the study of [19,20] that the renovations of the building envelope and phase change material can reduce building energy consumption. The combability of BIM for energy efficiency projection and CO2 emission underscores the effective approach for decision-making and enhances building energy and sustainability practice, which corresponds to the usage of BIM from previous studies [10,11,12,15]. Therefore, this research not only corroborates previous studies pertaining to the application of BIM for energy assessment but also contributes to the progressive study of building insulation materials and renovation decision-making with BIM.

7. Conclusions

In conclusion, this study provides informed decisions to optimize energy savings, reduce costs, and minimize CO2 emissions through building insulation upgrades using BIM-based simulation. The comparative analysis of insulation materials highlights Urethane Foam as the superior choice for both economic efficiency and environmental sustainability. In contrast, Glass Wool’s higher costs and environmental impact make it a less favorable option. As the demand for sustainable construction continues to grow, understanding the performance metrics of insulation materials becomes crucial. Utilizing tools like Building Information Modeling (BIM) can significantly aid designers and building owners in making informed decisions that balance cost-effectiveness, energy efficiency, and ecological responsibility. Ultimately, the choice of insulation material plays a vital role in promoting sustainable building practices and minimizing environmental impact.
Retrofitting existing buildings requires careful consideration of factors such as the building’s current condition, budget constraints, and energy efficiency goals. In this research, the best retrofitting scenario is one that achieves minimal energy consumption, revealing that the insulation material will have lower energy consumption compared to the regional mean. However, this scenario may involve the use of high-cost materials compared to other options. While upgrading an existing building may require significant upfront investment, choosing the best-performing insulation material can lead to substantial cost savings over the building’s lifespan by reducing energy consumption and associated operational expenses. This holistic approach ensures that retrofitting strategies are both economically viable and environmentally sustainable. For a building that is located in the same geographical condition in Japan, this research will be valuable to apply, supported by current standards and government campaign incentives for retrofitting existing buildings.
As the construction sector transitions toward sustainable methodologies, the strategic selection of insulation materials becomes a cornerstone for achieving energy-efficient and environmentally responsible buildings. Through the leveraging of tools like Building Information Modeling (BIM) and the adoption of a comprehensive framework for retrofitting, this investigation highlights the critical necessity of reconciling financial considerations, energy efficiency, and environmental impact. Ultimately, investing in high-performance insulation materials not only reduces long-term operational costs but also contributes significantly to mitigating climate change and fostering a more sustainable built environment.

Author Contributions

Conceptualization, Z.S.; Methodology, X.T. and D.C.S.T.; Software, D.C.S.T.; Validation, X.T. and D.C.S.T.; Formal analysis, X.T. and D.C.S.T.; Investigation, D.C.S.T.; Data curation, X.T. and D.C.S.T.; Writing—review & editing, X.T. and Z.S.; Visualization, X.T. and D.C.S.T.; Supervision, Z.S.; Project administration, Resource, X.T.; Funding acquisition, Z.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by the Fujian Science & Technology Innovation Laboratory for Optoelectronic Information of China under the project ‘Application of virtual reality technology in smart urban planning’ (Grant Number: 2021ZR139).

Data Availability Statement

All data used in this research are publicly available on the official websites in Japan, https://portal-data.city.kanazawa.ishikawa.jp/, (accessed on 23 December 2024). Ministry of Land, Infrastructure, Transport and Tourism, https://kosodate-ecohome.mlit.go.jp/material/, (accessed on 23 December 2024).

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Akram, M.W.; Zublie, M.F.M.; Hasanuzzaman, M.; Rahim, N.A. Global Prospects, Advance Technologies and Policies of Energy-Saving and Sustainable Building Systems: A Review. Sustainability 2022, 14, 1316. [Google Scholar] [CrossRef]
  2. Kuwahara, R.; Kim, H.; Sato, H. Evaluation of Zero-Energy Building and Use of Renewable Energy in Renovated Buildings: A Case Study in Japan. Buildings 2022, 12, 561. [Google Scholar] [CrossRef]
  3. Rauschen, M.; Ikaga, T.; Thomas, S.; Hoshi, H.; Karwatzki, J.; Winterseel, B. Energy Efficiency in Buildings, Particularly for Heating and Cooling; Wuppertal Institute for Climate, Environment and Energy: Wuppertal, Germany, 2020. [Google Scholar]
  4. Sharma, S.K.; Mohapatra, S.; Sharma, R.C.; Alturjman, S.; Altrjman, C.; Mostarda, L.; Stephan, T. Retrofitting Existing Buildings to Improve Energy Performance. Sustainability 2022, 14, 666. [Google Scholar] [CrossRef]
  5. Gardezi, S.S.S.; Haris Ali, S.H.; Fayaz, R.; Shah, H.H. Energy Performance Analysis of a Multi-Story Building Using Building Information Modeling (BIM). J. Sustain. Perspect. 2022, 2, 16–23. [Google Scholar] [CrossRef]
  6. Del Ama Gonzalo, F.; Moreno Santamaría, B.; Montero Burgos, M.J. Assessment of Building Energy Simulation Tools to Predict Heating and Cooling Energy Consumption at Early Design Stages. Sustainability 2023, 15, 1920. [Google Scholar] [CrossRef]
  7. Teng, X.; Shen, Z.; Xixi, W.; Tri, N. Pre-evaluation and visual simulation of energy consumption influencing factors of smart and healthy architecture in the design stage. In IOP Conference Series: Earth and Environmental Science; Institute of Physics: London, UK, 2023. [Google Scholar]
  8. Teng, X.; Shen, Z. Design of a smart visiting service management system for personal information collection in order to integrate tourism management into an isolated island. Appl. Sci. 2020, 10, 6442. [Google Scholar] [CrossRef]
  9. Truong, N.S.; Luong, D.L.; Nguyen, Q.T. BIM to BEM Transition for Optimizing Envelope Design Selection to Enhance Building Energy Efficiency and Cost-Effectiveness. Energies 2023, 16, 3976. [Google Scholar] [CrossRef]
  10. Chen, Z.S.; Yang, L.P.; Rodríguez, R.M.; Zhu, Z.; Pedrycz, W.; Skibniewski, M.J. BIM-aided large-scale group decision support: Optimization of the retrofit strategy for existing buildings. Appl. Soft Comput. 2022, 131, 109790. [Google Scholar] [CrossRef]
  11. Yildirim, M.; Polat, H. Building Information Modeling Applications in Energy-Efficient Refurbishment of Existing Building Stock: A Case Study. Sustainability 2023, 15, 13600. [Google Scholar] [CrossRef]
  12. Dauletbek, A.; Zhou, P. BIM-based LCA as a comprehensive method for the refurbishment of existing dwellings considering environmental compatibility, energy efficiency, and profitability: A case study in China. J. Build. Eng. 2022, 46, 103852. [Google Scholar] [CrossRef]
  13. Khan, A.M.; Tariq, M.A.; Alam, Z.; Alaloul, W.S.; Waqar, A. Optimizing energy efficiency through building orientation and building information modelling (BIM) in diverse terrains: A case study in Pakistan. Energy 2024, 311, 133307. [Google Scholar] [CrossRef]
  14. González, J.; Figueiredo, K.; Hammad, A.W.A.; Tam, V.W.Y.; Haddad, A.N.; Illankoon, C. Heritage BIM (HBIM) applied in emergency scenarios: A case study of the National Museum in Brazil. Int. J. Constr. Manag. 2024, 1–15. [Google Scholar] [CrossRef]
  15. Hmidah, N.A.; Bin Haron, N.A.; Hizami, A.A.; Law, T.H.; Altohami, A.B.A. Energy Consumption of Retrofitting Existing Public Buildings in Malaysia under BIM Approach: Pilot Study. Sustainability 2023, 15, 10293. [Google Scholar] [CrossRef]
  16. Dolzhencko, A.V.; Grebenik, A.V.; Sedashova, M.A.; Rudenskyi, D.S. Expanding the capabilities of the ARCHICAD software package for effective solution of construction design tasks. In Journal of Physics: Conference Series; IOP Publishing Ltd.: Bristol, UK, 2021. [Google Scholar]
  17. Ali, S.B.M.; Mehdipoor, A.; Samsina Johari, N.; Hasanuzzaman, M.; Rahim, N.A. Modeling and Performance Analysis for High-Rise Building Using ArchiCAD: Initiatives towards Energy-Efficient Building. Sustainability 2022, 14, 9780. [Google Scholar] [CrossRef]
  18. Fitriaty, P.; Shen, Z. Predicting energy generation from residential building attached Photovoltaic Cells in a tropical area using 3D modeling analysis. J. Clean. Prod. 2018, 195, 1422–1436. [Google Scholar] [CrossRef]
  19. Rashid, F.L.; Dulaimi, A.; Hatem, W.A.; Al-Obaidi, M.A.; Ameen, A.; Eleiwi, M.A.; Jawad, S.A.; Bernardo, L.F.A.; Hu, J.W. Recent Advances and Developments in Phase Change Materials in High-Temperature Building Envelopes: A Review of Solutions and Challenges. Buildings 2024, 14, 1582. [Google Scholar] [CrossRef]
  20. Riantini, L.S.; Machfudiyanto, R.A.; Rachmawati, T.S.N.; Rachman, M.D.A.; Fachrizal, R.; Shadram, F. Energy Efficiency Analysis of Building Envelope Renovation and Photovoltaic System in a High-Rise Hotel Building in Indonesia. Buildings 2024, 14, 1646. [Google Scholar] [CrossRef]
  21. Nasrollahzadeh, N. Comprehensive building envelope optimization: Improving energy, daylight, and thermal comfort performance of the dwelling unit. J. Build. Eng. 2021, 44, 103418. [Google Scholar] [CrossRef]
  22. Rijal, H.B.; Yoshida, K.; Humphreys, M.A.; Nicol, J.F. Development of an adaptive thermal comfort model for energy-saving building design in Japan. Archit. Sci. Rev. 2021, 64, 109–122. [Google Scholar] [CrossRef]
  23. Lakatos, Á. Novel Thermal Insulation Materials for Buildings. Energies 2022, 15, 6713. [Google Scholar] [CrossRef]
  24. Kumar, D.; Alam, M.; Zou, P.X.W.; Sanjayan, J.G.; Memon, R.A. Comparative analysis of building insulation material properties and performance. Renew. Sustain. Energy Rev. 2020, 131, 110038. [Google Scholar] [CrossRef]
  25. Abu-Jdayil, B.; Mourad, A.H.; Hittini, W.; Hassan, M.; Hameedi, S. Traditional, state-of-the-art and renewable thermal building insulation materials: An overview. Constr. Build. Mater. 2019, 214, 709–735. [Google Scholar] [CrossRef]
  26. Hwang, J.; Kim, Y.; Park, J.; Rie, D. A Study on the Evaluation of Thermal Insulation Performance of Cellulose-Based Silica Aerogel Composite Building Materials. Polymers 2024, 16, 1848. [Google Scholar] [CrossRef] [PubMed]
  27. Dai, H.; Gao, H.; Yang, P.; Mo, J.; Zhang, H.; Lei, S.; Wang, L. Thermal insulation performance of rock wool reinforced kaolinite-based porous geopolymer. Appl. Clay Sci. 2023, 246, 107176. [Google Scholar] [CrossRef]
  28. Hill, C.; Norton, A.; Dibdiakova, J. A comparison of the environmental impacts of different categories of insulation materials. Energy Build. 2018, 162, 12–20. [Google Scholar] [CrossRef]
  29. Song, Z.; Lei, Y.; Ran, W.; Yuan, M.; Shang, S.; Cui, S. Structural properties and barrier performance of low-cost aerogel composites for building insulation. J. Build. Eng. 2024, 90, 109485. [Google Scholar] [CrossRef]
  30. ANSI/ASHRAE Standard 140-2007; Standard Method of Test for the Evaluation of Building Energy Analysis Computer Programs (Addendum C). ASHRAE: Atlanta, GA, USA, 2011.
  31. Kanazawa City Open Data Portal: Housing Construction Methods [Proportion] National Census. Available online: https://portal-data.city.kanazawa.ishikawa.jp/ (accessed on 8 January 2025).
  32. Shimoda, Y.; Sugiyama, M.; Nishimoto, R.; Momonoki, T. Evaluating decarbonization scenarios and energy management requirement for the residential sector in Japan through bottom-up simulations of energy end-use demand in 2050. Appl. Energy 2021, 303, 117510. [Google Scholar] [CrossRef]
  33. Huyen Nguyen, T.; Take, K.; Take, K. Reviewing of the net-zero energy buildings and housings in Japan. In IOP Conference Series: Earth and Environmental Science; Institute of Physics: London, UK, 2024. [Google Scholar]
  34. General Incorporated Association for the Promotion of Wood Utilization in Architecture: FY 2023 (Reiwa 5) Ministry of Land, Infrastructure, Transport and Tourism (MLIT) Subsidy Project: Energy-Saving Design and Construction for Housing [Regions 4-7 Edition] [Revised] Compliance with the 2016 Energy Efficiency Standards. 2024. Available online: https://www.mlit.go.jp/jutakukentiku/house/04.html (accessed on 21 November 2024).
  35. Ministry of Land, Infrastructure, Transport and Tourism. Insulation Renovation of Openings, Criteria for Applicable Construction Works. Available online: https://kosodate-ecohome.mlit.go.jp/material/ (accessed on 17 October 2024).
  36. ANSI/ASHRAE Standard 140-2017; Standard Method of Test for the Evaluation of Building Energy Analysis Computer Programs. ANSI: Washington, DC, USA, 2017.
  37. Vycital, M.; Jarský, C. N automated nD model creation on BIM models. Organ. Technol. Manag. Constr. 2020, 12, 2218–2231. [Google Scholar] [CrossRef]
  38. Muhaxheri, K.; Muhaxheri, B.B. Impact of U-Values in Evaluation of Implemented Energy Efficiency Measures and Energy Savings in Public Buildings in Context of Kosovo Legislation. WSEAS Trans. Environ. Dev. 2023, 19, 11–24. [Google Scholar] [CrossRef]
  39. Bass, B.; Ezell, E.; New, J. Using Measured Building Energy Data to Infer Building Characteristics for Urban Building Energy Modeling. In Proceedings of the 2022 Building Performance Analysis Conference and SimBuild, Chicago, IL, USA, 14–16 September 2022. [Google Scholar]
  40. Otsuka, A. Industrial electricity consumption efficiency and energy policy in Japan. Util. Policy 2023, 81, 101519. [Google Scholar] [CrossRef]
  41. Sustainable Open Innovation Initiative: ZEH Information ZEH (Detached House) Case Study Search Tool Fiscal Year 2024. Available online: https://zehweb.jp/zehinfo/example/ (accessed on 20 January 2025).
  42. Institute for Built Environment and Carbon Neutral for SDGs: LCCM Housing Certification. Available online: https://www.ibecs.or.jp/rating/lccm.html (accessed on 20 January 2025).
  43. Khan, S.A.; Alam, T.; Khan, M.S.; Blecich, P.; Kamal, M.A.; Gupta, N.K.; Yadav, A.S. Life Cycle Assessment of Embodied Carbon in Buildings: Background, Approaches and Advancements. Buildings 2022, 12, 1944. [Google Scholar] [CrossRef]
  44. Meng, Q.; Hu, L.; Li, M.; Qi, X. Assessing the environmental impact of building life cycle: A carbon reduction strategy through innovative design, intelligent construction, and secondary utilization. Dev. Built Environ. 2023, 16, 100230. [Google Scholar] [CrossRef]
  45. Seo, M.S.; Kim, T.; Hong, G.; Kim, H. On-Site measurements of CO2 emissions during the construction phase of a building complex. Energies 2016, 9, 599. [Google Scholar] [CrossRef]
  46. Zhan, Z.; Xia, P.; Xia, D. Study on Carbon Emission Measurement and Influencing Factors for Prefabricated Buildings at the Materialization Stage Based on LCA. Sustainability 2023, 15, 13648. [Google Scholar] [CrossRef]
  47. Hertwich, E.G. Increased carbon footprint of materials production driven by rise in investments. Nat. Geosci. 2021, 14, 151–155. [Google Scholar] [CrossRef]
Figure 1. Methodology.
Figure 1. Methodology.
Buildings 15 00570 g001
Figure 2. Case study building model.
Figure 2. Case study building model.
Buildings 15 00570 g002
Figure 3. Step 1 involves drawing the building floor plan in BIM and creating a 3D model of the building.
Figure 3. Step 1 involves drawing the building floor plan in BIM and creating a 3D model of the building.
Buildings 15 00570 g003
Figure 4. Step 2: Set the building zones and add them to the thermal blocks.
Figure 4. Step 2: Set the building zones and add them to the thermal blocks.
Buildings 15 00570 g004
Figure 5. Step 3: Assign the model for energy model review.
Figure 5. Step 3: Assign the model for energy model review.
Buildings 15 00570 g005
Figure 6. Step 4: Define the thermal properties of each building system.
Figure 6. Step 4: Define the thermal properties of each building system.
Buildings 15 00570 g006
Figure 7. Step 5: Set the building operation profile.
Figure 7. Step 5: Set the building operation profile.
Buildings 15 00570 g007
Figure 8. Step 6: Add the climate data for the building location.
Figure 8. Step 6: Add the climate data for the building location.
Buildings 15 00570 g008
Figure 9. Basic wall composite of the simulated wall.
Figure 9. Basic wall composite of the simulated wall.
Buildings 15 00570 g009
Figure 10. The wall scenarios composite.
Figure 10. The wall scenarios composite.
Buildings 15 00570 g010
Figure 11. Simulation results for Scenario 1–Scenario 5.
Figure 11. Simulation results for Scenario 1–Scenario 5.
Buildings 15 00570 g011aBuildings 15 00570 g011b
Figure 12. Cost efficiency and CO2 emission comparison for all scenarios.
Figure 12. Cost efficiency and CO2 emission comparison for all scenarios.
Buildings 15 00570 g012
Figure 13. Heat map of each scenario for three evaluated factors: energy consumption, CO2 emission, and cost.
Figure 13. Heat map of each scenario for three evaluated factors: energy consumption, CO2 emission, and cost.
Buildings 15 00570 g013
Table 1. The category of building materials listed in the Energy-Saving Design and Construction of Housing 2023 guidelines, MLIT [34].
Table 1. The category of building materials listed in the Energy-Saving Design and Construction of Housing 2023 guidelines, MLIT [34].
CategoryDetailsMaterials
By Material
-
Fibrous Insulation Materials: Fine fibers that limit air movement.
Glass Wool, Rock Wool
-
Foam Plastic Insulation Materials: Contain enclosed air bubbles within their structure.
Rigid Urethane Foam, extruded polystyrene foam
By Form and Application
-
Fibrous Insulation Materials: Vary in density.
-
Felt form (low-density)
-
High-density forms are available as boards.
-
Board form (high-density)
-
Suitable for loose-fill applications.
-
Loose-fill form
By Permeability
-
Foam Plastic Insulation Materials: Manufactured as prefabricated boards, panels, or spray-applied forms.
-
Board form, panel form, or spray-applied foam.
-
Moisture Permeability: Indicates the ease with which water vapor can pass through the material. Critical for external insulation designs.
-
Low-Permeability Materials: Require a vapor barrier to prevent moisture issues.
-
Specific Note: Rigid Urethane Foam, classified as JIS A 9526 is an A-grade material for moisture resistance.
Rigid Urethane Foam under JIS A 9526
Table 2. Materials chosen for the simulation scenarios [35,36].
Table 2. Materials chosen for the simulation scenarios [35,36].
ScenarioMaterialProperties
Thermal Conductivity (W/mK)Density (kg/m3)Heat Capacity (J/kgK)Embodied Energy (MJ/kg)Embodied Carbon (kgCO2/kg)
Scenario 1Cellulose Fiber0.0450,000250014.71.12
Scenario 2Glass Wool0.04513,000150040.11.6
Scenario 3Urethane Foam 0.02132,0001450102.14.84
Scenario 4Phenolic Board0.02824,0001450102.14.84
Scenario 5Rock Wool0.0460,00084016.80.84
Table 3. Simulation results key values.
Table 3. Simulation results key values.
ScenarioNet Heating Energy (kWh/m2a)Net Cooling Energy (kWh/m2a)Total Energy Consumption (kWh/m2a)Primary Energy (kWh/m2a)Fuel Cost (JPY/m2a)CO2 Emissions (kg/m2a)
Cellulose Fiber64.9214.78103.13119.61134.167.93
Glass Wool65.2714.8103.5119.771135.797.94
Urethane Foam62.814.68100.9118.581124.197.86
Phenolic Board63.7814.73101.94119.061128.817.89
Rock Wool64.9214.78103.13119.61134.167.93
Table 4. ZEH case study of Ishikawa Prefecture with similar insulation type in the study simulation.
Table 4. ZEH case study of Ishikawa Prefecture with similar insulation type in the study simulation.
Web DataBuilding TypeInsulation TypePrimary Energy Reduction RateSimulation Result Performance Ranking
Case Study 12-story buildingGlass Wool21%4
Case Study 22-story buildingGlass Wool26%4
Case Study 32-story buildingPhenolic foam27%2
Case Study 42-story buildingPhenolic foam32%2
Case Study 52-story buildingPhenolic foam38%2
Case Study 62-story buildingRockwool26%3
Case Study 72-story buildingSprayed Rigid Urethane foam26%1
Case Study 82-story buildingSprayed Rigid Urethane foam37%1
Case Study 92-story buildingSprayed Rigid Urethane foam40%1
Table 5. Decision-making selection table.
Table 5. Decision-making selection table.
TypeMaterialFeature
Low CostGlass Wool, Rock Wool, Cellulose FiberBasic performance, affordable initial cost, requires maintenance for moisture control for installment, and considered as a shorter lifespan.
Moderate CostCombination of Fiber-based material and Foam Based materialModerate performance and cost: the use of mixed materials should incorporate the existing building conditions to determine which materials are best suited for specific parts of the building.
High CostUrethane foam and Phenolic boardHigh performance with high initial cost, ideal for prioritizing long-term efficiency with high durability and seamless installation.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Teng, X.; Shen, Z.; Tutuko, D.C.S. Evaluating the Impact of Insulation Materials on Energy Efficiency Using BIM-Based Simulation for Existing Building Retrofits: Case Study of an Apartment Building in Kanazawa, Japan. Buildings 2025, 15, 570. https://doi.org/10.3390/buildings15040570

AMA Style

Teng X, Shen Z, Tutuko DCS. Evaluating the Impact of Insulation Materials on Energy Efficiency Using BIM-Based Simulation for Existing Building Retrofits: Case Study of an Apartment Building in Kanazawa, Japan. Buildings. 2025; 15(4):570. https://doi.org/10.3390/buildings15040570

Chicago/Turabian Style

Teng, Xiao, Zhenjiang Shen, and Dara Citra Saraswati Tutuko. 2025. "Evaluating the Impact of Insulation Materials on Energy Efficiency Using BIM-Based Simulation for Existing Building Retrofits: Case Study of an Apartment Building in Kanazawa, Japan" Buildings 15, no. 4: 570. https://doi.org/10.3390/buildings15040570

APA Style

Teng, X., Shen, Z., & Tutuko, D. C. S. (2025). Evaluating the Impact of Insulation Materials on Energy Efficiency Using BIM-Based Simulation for Existing Building Retrofits: Case Study of an Apartment Building in Kanazawa, Japan. Buildings, 15(4), 570. https://doi.org/10.3390/buildings15040570

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop