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Commercial buildings have abundant flexible energy resources for demand response (DR). The electricity price for tenants in the commercial building is generally issued by a subcontracting power supplier (SPS), and the tenants cannot directly interact with the energy retailer. Therefore, the incentive for tenants to participate in DR is insufficient, and their potential is not fully explored. To address these issues, this paper proposes a dynamic pricing method based on the Stackelberg game, helping tenants actively participate in DR. Then, with the optimized energy consumption of the tenants, a virtual energy storage model of the commercial building is constructed by aggregating the adjustable capabilities of flexible energy resources such as air-conditioning (AC) and electric vehicles (EVs) in the public area. Finally, simulation tests are conducted based on a real commercial building to demonstrate the effectiveness of the game-theoretic pricing approach and validate the role of virtual energy storage of the building in DR. [ABSTRACT FROM AUTHOR]

With buildings contributing significantly to electricity usage, enabling demand flexibility becomes a challenge, especially when accounting for occupant comfort. This study introduces an innovative co-simulation framework integrating multiple models: heating, ventilation, and air conditioning (HVAC) system, building zone load, indoor airflow, supervisory control, and occupant comfort and behavior. Uniquely, this framework allows for a comprehensive and dynamic analysis of building systems and occupant interactions in demand response events. Using this framework, we conducted a case study using a typical small office building model. Specifically, we focused on three areas: (1) the impact of indoor airflow modeling on energy use, occupant comfort, and behaviors forecasting, (2) the impact of occupant behaviors on demand flexibility, and (3) occupant comfort and behaviors under demand response events. Key performance indicators such as energy use, flexibility factor, durations of occupant discomfort and occupant behaviors were analyzed. Our findings indicated variations in energy usage and occupant comfort within demand flexibility events, marked by uncertainty boundaries, with variability in demand shedding up to 57.9%. We concluded that this framework is suitable for analyzing typical commercial buildings and their HVAC systems in terms of demand flexibility potential under the impact of occupant behaviors. [ABSTRACT FROM AUTHOR]

With the increasing demand for energy in urban areas, there is a pressing need to manage energy consumption more effectively. Buildings, especially commercial and industrial ones, are major consumers of energy. Implementing AI-powered solutions can help monitor, predict, and reduce energy usage, leading to substantial cost savings and more efficient energy use. Integrating Industry 4.0 and the Internet of Things (IoT) into smart buildings presents a significant opportunity for enhancing energy management through advanced technologies. The increasing demand for energy in urban areas necessitates the development of more efficient energy management strategies, particularly within smart buildings, which are significant energy consumers. This study proposes an AI-powered deep learning framework utilizing Convolutional Neural Networks (CNNs) to enhance energy management in smart buildings, leveraging the ASHRAE - Great Energy Predictor III dataset. The proposed framework leverages deep learning techniques to analyze historical energy data, weather conditions, and building characteristics to forecast future energy usage accurately. Additionally, the framework includes anomaly detection mechanisms to identify inefficiencies and faults in the energy management system. By optimizing energy consumption in real-time and implementing demand response strategies, the framework aims to reduce energy costs and enhance the overall efficiency of smart buildings. The proposed CNN-IoT-based energy management framework in smart buildings demonstrates significant advancements over existing methods, achieving an accuracy of 88 %. These performance metrics indicate a substantial improvement in prediction accuracy and efficiency compared to existing approaches such as SVM, ELM, and LSTM. [ABSTRACT FROM AUTHOR]

In recent years, the integration of digital technologies has grown rapidly in the field of thermal comfort and energy efficiency for buildings. The concept of a digital twin, incorporating multiple digital technologies, has gained increasing attention. The literature lacks a review of the digital twin concept in thermal comfort and energy consumption for existing buildings. This paper conducts a review of the current state-of-the-art in digital twin (DT) technology for thermal comfort/ energy consumption in buildings. The review employs a scientometric approach and examines various technologies used in creating DTs and a systematic analysis of the methods, technologies, algorithms, and approaches used in digital twin experiments. The results show a growing number of studies in this area, with a focus on thermal comfort monitoring, visualization, tracking, energy management, prediction, and optimization for existing buildings. Furthermore, the prediction of energy consumption using algorithms such as Artificial Neural Networks (ANN), Artificial Intelligence (AI), deep neural networks, and YOLOv4 have been used in buildings. However, the wider adoption of a DT that can facilitate occupants, and thermal sensations, enhance human-centered solutions, and improve energy prediction levels are necessary. There is a need for further international collaboration to expand the studies on digital twins for thermal comfort and energy efficiency. The review highlights the limitations and areas of improvement, such as the limited adoption of sensors for environmental measures, the need for more focus on the subjective perception of occupants, and the need for more comparative studies of algorithms for predicting energy consumption. Further studies can be conducted in areas such as understanding occupant psychological responses/behaviors to comfort in the digital world. This will enhance a more consolidated and robust validation for building performance. [ABSTRACT FROM AUTHOR]

This article is a final report that presents a national roadmap for improving the building quality of Australian housing stock. The report highlights the prevalence of poor building quality and environmental performance in Australia's housing stock, with 70% of households reporting major building problems. The research analyzes existing data on housing conditions and reviews current policy settings. It identifies the need for a coordinated and comprehensive data infrastructure, as well as a national strategy to improve housing standards. The report recommends mandatory disclosure of performance, minimum standards for the rental sector, and stronger compliance and enforcement regimes. [Extracted from the article]

Although lignin is a plentiful biomass resource, it continually exists as an underutilized component of biomass material. Elemental sulfur is another abundant yet underutilized commodity produced as a by-product resulting from the refining of fossil fuels. The current study presents a strategy for preparing five durable composites via a simple one-pot synthesis involving the reaction of lignin oil and elemental sulfur. These lignin oil–sulfur composites LOSx@T (where x = wt. % sulfur, ranging from 80 to 90, and T represents the reaction temperature in °C) were prepared via the reaction of elemental sulfur and lignin oil (LO) with elemental sulfur. The resulting composites could be remelted and reshaped several times without the loss of mechanical strength. Mechanical, thermal, and morphological studies showed that LOSx@T possesses properties competitive with some mechanical properties of commercial building materials, exhibiting favorable compressive strengths (22.1–35.9 MPa) and flexural strengths (5.7–6.5 MPa) exceeding the values required for many construction applications of ordinary Portland cement (OPC) and brick formulations. While varying the amount of organic material did not result in a notable difference in mechanical strength, increasing the reaction temperature from 230 to 300 °C resulted in a significant increase in compressive strength. The results reported herein reveal potential applications of both lignin and waste sulfur during the ongoing effort toward developing recyclable and sustainable building materials. [ABSTRACT FROM AUTHOR]

The energy challenges of overcoming climate change and economic and global political crises require not only the increased integration of renewable energies but also an optimisation of energy generation and use and, as a result, a reduction in energy consumption in various sectors. Thermal energy consumption in buildings in particular accounts for a significant proportion of final energy consumption. With respect to commercial buildings, a central problem in optimising the system settings is the lack of or only limited information about the actual room temperatures as well as the comfort requirements and temperature perception of the users in the rooms on the one hand and the operational management and settings specified by the facility management, for example, the heating curves of the heating circuits, on the other. The aim here is to create a bidirectional flow of data and information so that the compromise between the necessary room temperatures and the comfort of the users and the most energy-efficient operational management possible can be achieved. In this context, the paper presents a developed and tested web platform that makes it possible to optimise the operation of the system technology, particularly the heating system in the building, from an energy point of view and to involve the building user (e.g., office employees) and to pass on information to the facility management, thus pursuing a holistic approach. In the associated Living Lab project (called ComfortLab), it was possible to obtain over 6500 votes on temperature perception and combine this with building operation and the parameters relevant to facility management. This made it possible to bridge the gap between user requirements and room temperatures on the one hand and energy consumption and the inlet temperature of the heating system and supply circuits on the other. The use of the platform makes it possible to optimise the setpoint specification, specifically the inlet temperature of individual heating circuits, considering both regular building operation at times of presence and the setting of weekend and night setback times. The results show a diversified picture regarding temperature perception and possible room temperature reductions of several degrees Celsius and energy savings in the double-digit percentage range. [ABSTRACT FROM AUTHOR]

The assessment of earthquake risk at the national scale is crucial for the design and implementation of risk reduction measures. Due to its location in the southwest of the Eurasian plate, Portugal is exposed to moderate to strong seismic events, such as the well-known 1755 Lisbon earthquake. We reviewed existing studies covering exposure, seismic hazard, vulnerability, and risk assessment for Portugal, and performed probabilistic seismic hazard and risk analyses for the country using new model components. These include a new exposure model developed for the residential building stock using the 2021 national Building Census Survey, a recent exposure model for commercial and industrial buildings, updated vulnerability functions for 116 building classes, and the recently released European Probabilistic Seismic Hazard model. The seismic risk results include average annual economic losses, fatalities, buildings with complete damage, and population left homeless. These results allowed the identification of the regions in Portugal with the highest earthquake risk, as well as which building classes contribute the most to the overall impact. [ABSTRACT FROM AUTHOR]

Environmental issues are often neglected in previous studies on site layout evaluation problems. To address this research gap, a comprehensive evaluation model is developed to evaluate construction site layout planning in this paper. The proposed evaluation model includes four aspects: (1) land use; (2) safety; (3) logistics; and (4) sustainability evaluations. To make the results of the evaluation more accurate, the evaluation model includes the subjective factors that need to be scored by the experts and the objective factors that could be gained from the inspections of the projects and the related materials. Then, the entropy weight method-based Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) is chosen to solve the proposed multicriteria evaluation model. In this paper, the construction site layout planning for four different typical and practical cases, which include two commercial mixed buildings, a residential building, and a sewage treatment plant, is studied. The evaluation results proved that the proposed model is suitable to evaluate common types of construction, such as residential and commercial buildings but not specific functional types, such as the sewage treatment plant. [ABSTRACT FROM AUTHOR]

Over the past two decades, extensive research has covered various automated fault detection and diagnostic (AFDD) methods. Nonetheless, there are only limited examples where these tools' usability and adoption are investigated. To address this gap, this review paper investigates two main topics that are relevant to AFDD adoption: (1) the socio-technical challenges faced by facility management (FM) organizations that are the primary target of AFDD tools and (2) user testing and human-computer interaction (HCI) based studies of AFDD and other energy information and management technology. We argue that along with the extensive research on AFDD strategies, these two topics are essential to address the challenges of AFDD adoption and to shape the direction of future AFDD research. The available literature suggests a gap in understanding what design elements of novel AFDD tools and techniques lead to industry use and, ultimately, fault correction. Without further advancements toward understanding the practical requirements for AFDD adoption, this gap leaves researchers and the industry with limited knowledge to improve the design of future AFDD tools. To bridge the gap between theory and adoption, we recommend the expanded use of HCI methods in AFDD development to address the socio-technical challenges faced by FM organizations. [ABSTRACT FROM AUTHOR]

The stereodivergent synthesis of all four stereoisomers of diethyl 4-hydroxyphosphopipecolate from the commercial chiral building block ethyl (R)-4-cyano-3-hydroxybutanoate is described. Key steps in the synthesis of the target compounds involve the triethyl phosphite nucleophilic addition to chiral N -acyliminium ion easily obtained from (R)-4-hydroxypiperidin-2-one, giving diethyl (2 R ,4 R)- and (2 S ,4 R)-4-hydroxyphosphopipecolate diastereoisomers, easily separable by column chromatography followed by the 4-hydroxy epimerization through a sequential oxidation and highly diastereoselective reduction strategy, affording the diethyl (2 R ,4 S)- and (2 S ,4 S)-4-hydroxyphosphopipecolate, respectively, consistent with our recently found results. All synthesized compounds were thoroughly characterized. [ABSTRACT FROM AUTHOR]

The 2006 Turkish Seed Law prohibited the selling of uncertified heirloom seeds, triggering heated debates on and around seeds. This paper examines the construction of discourses on heirloom seeds in Türkiye, focusing on the arguments of the key social actors in the field with a view to understand how knowledge production is taking place on seed. Conducting interviews with key state and non-state actors and analyzing their published documents related to heirloom seed through discourse-historical approach, we examined the argumentative perspectives shaping the discourse on seed. The results revealed a discursive dichotomy constructed between "heirloom seed" and "certified hybrid seeds". In particular, built on commercial and food security concerns, the state discourse frames heirloom seeds as low-yield and unable to feed the nation in comparison to certified hybrid seeds, whereas non-state discourse using the perspectives of agrobiodiversity and farmers' sovereignty construct heirloom seeds with superior features, qualifying them as compatible with biodiversity and the current global and regional economic, environmental and climate problems. The study concludes that different perspectives and interests produced contradictory knowledge about seed (hence food) and caused different realities to exist simultaneously within this knowledge. [ABSTRACT FROM AUTHOR]

As energy demand and electricity costs continue to rise, consumers are increasingly adopting energy-efficient practices and appliances, underscoring the need for detailed metering options like appliance-level load monitoring. Non-intrusive load monitoring (NILM) is particularly favored for its minimal hardware requirements and enhanced customer experience, especially in residential settings. However, commercial power systems present significant challenges due to greater load diversity and imbalance. To address these challenges, we introduce a novel neural network architecture that combines sequence-to-sequence, WaveNet, and ensembling techniques to identify and classify single-phase and three-phase loads using appliance power signatures in commercial power systems. Our approach, validated over four months, achieved an overall accuracy exceeding 93% for nine devices, including six single-phase and four three-phase loads. The study also highlights the importance of incorporating nonlinear loads, such as two different inverter-type air conditioners, within NILM frameworks to ensure accurate energy monitoring. Additionally, we developed a web-based NILM energy dashboard application that enables users to monitor and evaluate load performance, recognize usage patterns, and receive real-time alerts for potential faults. Our findings demonstrate the significant potential of our approach to enhance energy management and conservation efforts in commercial buildings with diverse and complex load profiles, contributing to more efficient energy use and addressing climate change challenges. [ABSTRACT FROM AUTHOR]

With the rise of Internet-of-Things devices, the analysis of sensor-generated energy time series data has become increasingly important. This is especially crucial for detecting rare events like unusual electricity usage or water leakages in residential and commercial buildings, which is essential for optimizing energy efficiency and reducing costs. However, existing detection methods on large-scale data may fail to correctly detect rare events when they do not behave significantly differently from standard events or when their attributes are non-stationary. Additionally, the capacity of computational resources to analyze all time series data generated by an increasing number of sensors becomes a challenge. This situation creates an emergent demand for a workload-bounded strategy. To ensure both effectiveness and efficiency in detecting rare events in massive energy time series, we propose a heuristic-based framework called HALE. This framework utilizes an explore–exploit selection process that is specifically designed to recognize potential features of rare events in energy time series. HALE involves constructing an attribute-aware graph to preserve the attribute information of rare events. A heuristic-based random walk is then derived based on partial labels received at each time period to discover the non-stationarity of rare events. Potential rare event data are selected from the attribute-aware graph, and existing detection models are applied for final confirmation. Our study, which was conducted on three actual energy datasets, demonstrates that the HALE framework is both effective and efficient in its detection capabilities. This underscores its practicality in delivering cost-effective energy monitoring services. [ABSTRACT FROM AUTHOR]

Alun-alun Contong, a historical area in Surabaya, connects popular historical areas via a tram line. Today, it features commercial buildings from the Dutch East Indies era, which is dominated by contemporary style. Therefore, historical appearances have become degraded and disconnected from their surrounding areas. Based on the case study, this research tries to construct specific historical conservation policies on connecting areas that have not been discussed before. The mixed method involves several tactics that involve two phases: assessment of the building facade element and serial vision analysis as an internal and external identification. The results show the visual quality condition and potential of an area between two historical areas as a modality of the Alun-alun Contong conservation policy. The research findings enable conservation policies to use this method at other locations to improve or restore connectivity, strengthen visual quality, and ensure the sustainability of the entire urban heritage area. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Engineering Management / Gongcheng Guanli Xuebao is the property of Journal of Engineering Management Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Engineering Management / Gongcheng Guanli Xuebao is the property of Journal of Engineering Management Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The building sector plays a crucial role in the worldwide shift toward achieving net-zero emissions. Building energy efficiency standards (BEESs) are highly effective policies for reducing carbon emissions. Therefore, exploring the provincial variations in carbon emission efficiency (CEE) in the building sector and identifying the effect of BEESs on CEE is crucial. This study focuses on commercial buildings in China and applies a difference in differences model to evaluate the impact of BEESs on the CEE of commercial buildings. The slacks-based measure–data envelopment analysis model is employed to assess the CEE of commercial buildings in 30 Chinese provinces from 2000 to 2019. Furthermore, heterogeneous tests are used to explore how climate characteristics and economic conditions affect the efficiency of BEESs. The results indicate that BEESs positively influence the CEE of commercial buildings. Specifically, a 1% increase in the intensity of BEESs causes a 0.148 4% increase in the CEE of commercial buildings. Moreover, the impact of BEESs is particularly pronounced in the southern and western provinces. This study provides valuable scientific evidence for governments to enhance BEESs implementation.

Evaluations of nonintrusive load monitoring (NILM) algorithms and technologies have mostly occurred in constrained, artificial environments. However, few field evaluations of NILM products have taken place in actual buildings under normal operating conditions. This paper describes a field evaluation of a state-of-the-art NILM product, tested in eight homes. The match rate metric-a technique recommended by a technical advisory group-was used to measure the NILMs success in identifying specific loads and the accuracy of the energy consumption estimates. A performance assessment protocol was also developed to address common issues with NILM mislabeling and ground-truth comparisons that have not been sufficiently addressed in past evaluations. The NILM products estimates were compared to the submetered consumption of eight major appliances. Overall, the product had good performance in disaggregating the energy consumption of the electric water heaters, which included both electric resistance and heat-pump water heaters, but only a fair accuracy with refrigerators, dryers, and air conditioners. The performance was poor for cooking equipment, furnace fans, clothes washers, and dishwashers. Moreover, the product was often unable to detect major loads in homes. Typically, two or more appliances were not detected in a home. At least two dryers, furnace fans, and air conditioners went undetected across the eight homes. On the other hand, the dishwasher was detected in all homes where available or monitored. The key findings were qualitatively compared to those of past field evaluations. Potential areas for improvement in NILM product performance were determined along with areas where complementary technologies may be able to aid in load-disaggregation applications.

Information on microorganisms in indoor air of various institutional and commercial buildings has significant value in a public health management perspective. However, there is a lack of prior research comparing indoor airborne microbiota across different categories of those buildings. We characterized indoor airborne bacteria in 10 buildings (two for each of five categories: train station, parking garage, mart, public library, and daycare center) during summer and winter. The 16S rRNA gene in the bacterial gDNA extracted from samples was quantified using quantitative real-time polymerase chain reaction and sequenced with the Illumina MiSeq™ platform for characterizing community composition. We collected information on temperature, relative humidity, CO2 concentration, and particulate matter (PM) concentrations by particle size (<1 µm, 1–2.5 µm, 2.5–10 µm) indoors. We performed a multivariate regression analysis to identify factors influencing bacterial quantity and Permutational Multivariate Analysis of Variance (PERMANOVA) to determine factors affecting cluster dissimilarity. We found that bacterial concentration was significantly (p-values < 0.05) associated with season and CO2 concentration. The PERMANOVA analyses showed the significant (p-values < 0.05) associations of bacterial cluster dissimilarity with season, building category, and CO2. Our study indicated that the season, and CO2 concentrations may be important factors associated with the indoor airborne bacterial concentration and composition. Building category and usage appeared to significantly influence the bacterial community composition but not the concentration. Our study may provide basic data on bacterial community composition and their concentration that are needed for properly managing microbial exposures in occupants or customers of the studied institutional and commercial buildings. Copyright © 2024 American Association for Aerosol Research [ABSTRACT FROM AUTHOR]

Commercial Buildings release large volumes of greenhouse gases, expediting global warming. The commercial building industry accounts for 37% of global CO2 emissions. Geothermal energy technologies are an intriguing solution that provides a low-impact, emission-free, and cost-effective thermal fuel source for baseload energy production. Geothermal energy systems offer a potential solution to dramatically halt global warming and facilitate the transition to a carbon-neutral civilization. This study develops a framework for assessing the geothermal power capabilities of innovative house and district heating systems. The energy requirements are first assessed, and then the spatial evaluation of district heating infrastructure is carried out using a Python-based program. Economic comparisons between geothermal energy and fossil fuels are made using LCC analysis. Environmental impacts are measured by Life Cycle Analysis (LCA). This study compares geothermal energy to fossil fuels, and the LCA results show that geothermal energy has a low environmental impact. With a Net Present Value (NPV) of 34.81 USD, it displays economic viability as well as a satisfactory financial return. The study's findings show that geothermal energy has the ability to compete with fossil fuels in commercial heating applications while still being environmentally beneficial.

Numerous studies have demonstrated that commercial activities have significantly reduced during COVID-19, while there are few studies disclosing the consequent impacts on the energy consumption of commercial buildings. This study explores the changes in energy consumption of different types of commercial buildings in Singapore under the impact of the pandemic, using commercial building energy performance data from 2017 to 2020 (n=540). The sampled buildings include 93 hotel buildings, 303 office buildings, 106 retail buildings, and 38 mixed developments. The analysis mainly used linear regression and paired sample t-test. The results showed that relative to 2019, the mean energy use intensity (EUI) of sampled commercial buildings decreased by 56.77 kWh/m² in the pandemic year (2020), a plunge of 19.9%. The extent to which the EUI of each type of commercial building is affected by the pandemic is found as: mixed development>retail>office>hotel. The study also identified the factors that significantly influenced the EUI of commercial buildings before and during the pandemic. The results of the study complement existing knowledge about the factors influencing energy consumption in commercial buildings by considering the impact of the pandemic and furthermore contribute to the improvement of energy management in commercial buildings by providing directions for building energy efficiency approaches.

With the continuous growth of low-carbon economy and people's increasing preference for low-carbon products, the building carbon emission reduction (CER) has been highly concerned by the government. Therefore, in this study, we establish a game model through differential game to analyze the impact of government policies on building's CER. We get: (1) Compared with the carbon tax policy, the government policy combining carbon tax and cost subsidy is more conducive to reducing carbon emissions; (2) For the three government policies, when the cost subsidy rate is lower than a fixed value, the government policy combining carbon tax and cost subsidy is the optimal strategy for building's CER. When the cost subsidy rate is greater than a fixed value, the cost subsidy policy is the best strategy for building's CER. [ABSTRACT FROM AUTHOR]

In recent years, the use of Building Information Modeling (BIM) with Building Energy Modeling (BEM) has become the primary research focus for reducing the energy consumption of buildings in the planning and operational phases. The combination of BIM and BEM offers advantages for the various phases of a construction project. However, there are currently very few studies that can integrate multi-objective optimization algorithms into the BIM-BEM process to achieve automatic optimization and effectively manage many aspects of building development. In this study, an EnergyPlus integrated multi-objective jellyfish search (EP-MOJSO) system was developed, utilizing an optimization algorithm to find the best thermal insulation layers for an Aluminum composite material (ACM) wall. The goal is to reduce the energy consumption and total cost in a BIM-BEM environment. In the case study, the authors successfully applied the system to a real building, resulting in a 10.7% reduction in total cost and a 65 kWh/m2/year reduction in EUI. It is expected that the results of the study will open up new ways of using algorithms for multi-criteria optimization in BIM models to optimize various project factors such as energy and total cost and thus make an important contribution to sustainable building design. [ABSTRACT FROM AUTHOR]

Artificial intelligence has emerged as a technology to enhance productivity and improve life quality. However, its role in building energy efficiency and carbon emission reduction has not been systematically studied. This study evaluated artificial intelligence's potential in the building sector, focusing on medium office buildings in the United States. A methodology was developed to assess and quantify potential emissions reductions. Key areas identified were equipment, occupancy influence, control and operation, and design and construction. Six scenarios were used to estimate energy and emissions savings across representative climate zones. Here we show that artificial intelligence could reduce cost premiums, enhancing high energy efficiency and net zero building penetration. Adopting artificial intelligence could reduce energy consumption and carbon emissions by approximately 8% to 19% in 2050. Combining with energy policy and low-carbon power generation could approximately reduce energy consumption by 40% and carbon emissions by 90% compared to business-as-usual scenarios in 2050. AI reduces building energy and emissions in design/construction, equipment, occupancy, and control/operation. By accelerating high-efficiency and net-zero buildings, AI could cut energy and emissions by 40-90% by 2050 combined with adequate policies. [ABSTRACT FROM AUTHOR]

Translation abstract A supermarket made of infra‐lightweight concrete – Proof of stability for a fire wallInfra‐lightweight concrete (ILC) is a special form of lightweight concrete which, due to its low density, possesses improved thermal insulation properties in comparison to normal concrete. ILC facilitates the construction of monolithic, single‐layer building skins without any added thermal insulation or facade cladding. This way, the building components are effectively simplified in comparison to conventionally insulated concrete members and the recyclability is significantly improved. In addition to that, structural elements made of ILC have a reduced CO2 footprint in comparison to conventional composite elements of the building envelope. After 15 years of research and several completed construction projects in the housing and education sector, a commercial retail building has been realized. For this project, an individual approval for a firewall built out of ILC was obtained based on a fire test in combination with a transfer concept based on calculations. This article demonstrates the transfer concept as well as a simplified structural analysis concept for the proof of stability developed for the special application of a firewall. [ABSTRACT FROM AUTHOR]

This article explores the phenomenon of communities becoming involved in sustaining rural grocery stores in Denmark, and it identifies three kinds of community stores. The paper is mainly based on case studies of eighteen villages where local communities have been involved in saving their local stores. In all cases, the community collected funds to purchase and renovate the store’s premises. Two kinds of stores (A and B) largely resemble the original rural store in terms of products and appearance. For category A stores, the community rents out the renovated store cheaply to a private shopkeeper. In contrast, for category B stores, low rent is not enough to attract storekeepers, and the community has had to take on the store’s management itself. In both cases, stores have engaged with a supermarket chain. A third category (C) consists of an independent store where community members have taken on all activities themselves voluntarily. The type of store reflects the size of the village, its customer base, and also, very importantly, the capacity of the local community. In larger villages, “only financial capital” is needed (for buildings of A stores), whereas in smaller villages, the community has to manage the store (type B and C), which demands more effort and capacity. Thus, closures of rural grocery stores can only be prevented by capable and engaged communities. [ABSTRACT FROM AUTHOR]

This study presents a virtual energy storage system (VESS) scheduling method that strategically integrates fixed and dynamic energy storage (ES) solutions to optimize energy management in commercial buildings. Fixed ES, such as batteries, provides stable flexibility but is expensive and can be inefficiently operated. In contrast, dynamic ES can be utilized as needed but requires validation of their flexibility. By combining fixed ES with dynamic ES utilizing vehicle-to-grid (V2G) capabilities, this approach enhances grid stability and manages energy costs more effectively. Empirical validation using real-world data from Korea demonstrates significant improvements in total net benefits by reducing energy costs, which are crucial for the economic sustainability of commercial energy use. Additionally, the analysis of Pearson's linear correlation coefficient with demand identifies where benefits occur in the scheduling process. The integrated system reduces the need for costly upgrades to the utility grid, suggesting a strategic advantage for large-scale adoption. This study establishes a framework for the broader implementation of such integrated systems, highlighting the potential for substantial improvements in energy efficiency, reduced carbon emissions, and enhanced grid reliability. [ABSTRACT FROM AUTHOR]

The management of large enterprises influences their efficiency and profitability. One of the important aspects is the appropriate management of electricity consumption used for production and daily operation. The problem becomes more complicated when you need to manage not one but a large complex of buildings with heterogeneous purposes. In the paper, we examine real-time series data of electrical energy consumption in a complex of heterogeneous buildings, including offices and warehouses, using time series analysis methods such as the Holt–Winters model and ARIMA/SARIMA model, and neural networks (Deep Neural Network, Recurrent Neural Network, and Long Short-Term Memory). Experimental research was performed on a dataset obtained from an energy consumption meter placed in the building complex, built in different periods, and equipped with a variety of automation devices. The data were collected over a period of four years 2018–2021 in the form of time series. Results show that classic models are good at predicting energy consumption in the mentioned type of buildings. The ARIMA model gave the best results—for buildings characterized by seasonality and trends the forecasts were almost perfect with actual values. [ABSTRACT FROM AUTHOR]

This study evaluates the use of City Energy Analyst, an urban building energy modelling tool, to design zero-carbon energy communities in low-industry isolated island settings. The research aims to test the effectiveness of the software during the development of sustainable energy systems in isolated microgrids and compares it with the widely used tool EnergyPLAN. The goal of the study focused on making a community self-sustainable, considering the rooftop area available in the populated settlements to install photovoltaic systems and distributed storage capacity. With this purpose in mind, the evaluated tool estimated the energy consumption of each building and the respective total annual consumption of Corvo Island, a location that is naturally isolated and dependent on fossil fuels. The results demonstrated that City Energy Analyst is an innovative tool to estimate energy consumption and potential energy generation of photovoltaic systems in a remote location, providing additional features to a traditional model and motivating further development of the associated plug-in. However, it requires initial time-consuming efforts to build a reliable model. As a complement, EnergyPLAN can be used to enhance the design, with the integration of the local existing and potential generation sources and to confirm the stability of the overall energy system. This tool introduced additional wind capacity and centralized storage into the model, testing the balance of the system. Therefore, the study proposes a framework combining the strengths of both tools to measure island energy systems, as they can complement each other, to build a strong analysis model. [ABSTRACT FROM AUTHOR]

Facing the current sustainability challenges requires reduction in building stock energy usage towards achieving the European Green Deal targets. This can be accomplished by adopting techniques such as fault detection and diagnosis and efficiency optimization. Taking an Estonian school as a case study, an occupancy-based algorithm for scheduling ventilation operations in buildings is here developed starting only from energy use data. The aim is optimizing the system's operation according to occupancy profiles while maintaining a comfortable indoor climate. By relying only on electricity meters without using carbon dioxide or occupancy sensors, we use the historical data of a school to develop a DBSCAN-based clustering algorithm that generates consumption profiles. A novel occupancy estimation algorithm, based on threshold and time-series methods, then creates 12 occupancy schedules that are either based on classical detection with an on-off method or on occupancy estimation for demand-controlled ventilation. We find that the latter replaces the 60% capacity of current on-off schedules by 30% or even 0%, with energy savings ranging from 3.5% to 66.4%. The corresponding costs are reduced from 18.1% up to 62.6%, while still complying with current national regulations for indoor air quality. Remarkably, our method can immediately be extended to other countries, as it relies only on occupancy schedules that ignore weather and other location-specific factors. [ABSTRACT FROM AUTHOR]

This paper investigates the possibilities and challenges of using mass timber as a sustainable alternative for retrofitting existing buildings in Canada. To create the knowledge foundation on which to devise a holistic framework tailored to the specific characteristics of Canada's built environment, a detailed analysis of the types, geographical distribution, structural, and energy features of the local building stock is first presented. Then, previous strategies for enhancing and upgrading existing buildings with engineered timber are reviewed, classified, and evaluated. Finally, to explore economic and environmental implications, a detailed assessment of available life-cycle cost–benefit analysis approaches is conducted alongside their adaptation to Canada's building context. The findings of this paper can inform policymakers, builders, and designers in developing more sustainable building retrofit practices, design, and regulations, in line with Canada's efforts toward net zero emissions. [ABSTRACT FROM AUTHOR]

In October 2019, the largest fire in a commercial building in New Zealand since 1947 burned for over ten days through the roof and upper floor of the 120 m wide × 100 m long New Zealand International Convention Centre, which was under construction and nearing completion at the time. The steel composite and reinforced concrete framed building features five storeys above grade of structural steel framing with composite floors, comprising heavy, intricate steel work that was impacted by the fire. The main steel structure performed very well in response to fire exposure ranging from low to severe, with minimal damage and distortion to the heavy steel roof members in general, considering the severity of the fire. Secondary steel angles, tubular steel, and wide-flange members at the roof elevation were locally more heavily distorted. A very detailed post-fire evaluation of the structure was carried out, comprising mapping of the fire effects, deflections, metallurgical changes, extensive numerical modelling, and full scale in-situ experimental testing. The outcome resulted in retention of over 95% of the total roof steelwork (2500 tonnes). This paper provides an overview of the fire and the key steps involved in the post-fire structural evaluation of this unique fire case history. [ABSTRACT FROM AUTHOR]

Statistics indicate that after the COVID-19 pandemic, many individuals have opted to work remotely for at least a few days each week. This study investigates the impact of teleworking on energy consumption and carbon emissions in Canadian homes. Four residential building models, aligned with the 2020 requirements of the National Building Code of Canada (NBC), were investigated across six Canadian climate zones. The findings of this study reveal that the increase in energy consumption and CO2 emissions due to teleworking varies according to the type of building and the number of thermal zones. For the selected single-zone house models, the maximum increase in energy consumption and CO2 emissions were 11% and 10%, respectively occurring in a row house two-story building. For the three-zone house models, the increase was 5%. Also, results indicated that full-time teleworking in a four-storey multi-family building with 12.5%, 50% and 100% teleworking ratios increased the total energy of the building by 1%, 4%, and 10%, respectively. The second phase of this study investigated possible enhancements to building energy codes, focusing on the National Building Code of Canada, to address increasing daytime occupancy resulting from teleworkers, retirees, and other occupants. [ABSTRACT FROM AUTHOR]

As commonly stated, we cannot manage what we do not measure. Understanding the flow of energy and its end-uses within a building is critical for energy management. Therefore, the lack of high resolution energy submetering is a significant barrier to efficient energy management in buildings. Despite this, many buildings still lack adequate submetering for their major end-uses because of the cost and practical restrictions. Energy disaggregation techniques aim at breaking down the bulk meter energy data into primary end-uses to gain insight into consumption patterns. However, high resolution, trustworthy BAS trend data is essential to develop reliable disaggregation techniques and capture unmeasured energy flow accurately. This paper explores a time series decomposition based method to disaggregate the total energy use into three major end uses namely lighting and plug loads, cooling, and heating energy use without BAS trend data. The results were compared with actual submetered data from ten office buildings in Ottawa, Canada for validation purposes. Specific insights into lighting and thermal scheduling, as well as hourly, daily, and monthly operational variations based on the de-composition components were discussed. The promising performance of the proposed method suggests that it could be used for quick and low cost auditing of commercial buildings with access to only the building's total energy use data. [ABSTRACT FROM AUTHOR]

With the continuous increase in building energy consumption, the problem of low energy utilization efficiency, especially concerning windows accounting for approximately 40% of total energy loss, has become increasingly prominent and urgent. Electrochromic (EC) technology emerges as a promising solution capable of effectively regulating the transmittance and absorption of light. Notably, dual‐band EC smart windows (DESWs) offer a unique avenue to address this challenge by independently adjusting sunlight and heat entry, anticipated to significantly reduce energy consumption for internal lighting and temperature regulation in buildings. While the potential benefits of DESWs are substantial, research is still in its early stages, facing important obstacles that hinder progress. This review aims to enhance our comprehension of this technology by providing a detailed introduction to the fundamental features of DESWs, encompassing configuration, operating mechanisms, and parameters for performance evaluation. In particular, we explore potential methods and approaches to achieve independent modulation using single-component materials. Additionally, we analyze performance issues and challenges, pinpoint future development directions, and propose corresponding solutions. The purpose of this review is to expedite the research and development of DESWs, offering robust support for the creation of modern energy-efficient buildings and facilitating the transition of the construction industry towards more sustainable and efficient energy utilization. [Display omitted] • Overview of the emerging technology of dual-band electrochromic smart windows (DESWs) designed for the independent regulation of visible and near-infrared light. • Comprehensive exploration of recent advancements in typical single-component materials for DESWs, with a focus on their unique characteristics and potential applications in green building design. • Evaluation of the challenges encountered in DESWs research and proposed solutions, providing insights into future directions for advancing this technology. [ABSTRACT FROM AUTHOR]

This article explores the promotion of indoor environmental quality (IEQ) principles in building design, specifically focusing on quantity surveying (QS) firms in Nigeria. The study identifies measures to encourage the adoption of IEQ principles, such as financial incentives, educational resources, clear reporting mechanisms, awards and recognition programs, and advocacy campaigns. These measures are categorized into four clusters: education and training, policy and regulation, incentivization and recognition, and collaboration and networking. The article also highlights the importance of smart building technologies and the design of building services and systems in optimizing IEQ. The findings provide valuable insights for policymakers, construction industry professionals, and stakeholders interested in promoting IEQ principles. The EPIC framework outlined in the article offers practical guidance for prioritizing IEQ principles and contributing to sustainable building practices. However, the study acknowledges the need for further research and a larger sample size. Overall, the article emphasizes the importance of incorporating IEQ principles in building design to improve occupant satisfaction and well-being. [Extracted from the article]

The purpose of this study is to determine the effect of leadership style, workload and work discipline on the productivity of Employees at the Building Store of Ahmad Yani Branch, both partially and simultaneously. The population in this study was all employees at the Ahmad Yani branch of RKM building store, with a total of 40 employees. SampWork Environmental Engineering used in this study is a non-probability Work Environmental technique. The method used in this study is Quantitative Method with data collection techniques used is interview and distribute questionnaires to respondents. The data analysis technique used is double linear regression with SPSS program. The results of the study concluded that: (1) the dreaming style has a significant positive effect on productivity. (2) the workload has a significant effect on productivity. (3) the work discipline has a positive and significant effect on productivity. (4) In simultaneous testing of leadership styles, workloads and work discipline have a positive and significant influence on employee productivity in the building store of Ahmad Yani branch. The magnitude of leadership style, workload and Work Discipline is shown by the Adjustable R Field value of 79.9% and the remaining 21.1% are affected by other variables not examined in the study. [ABSTRACT FROM AUTHOR]

Skylight is an effective strategy for maximising daylight penetration while minimising electrical lighting energy demand in buildings. However, in tropical climate regions, skylight can be problematic due to the risk of excessive sunlight. This study aimed to optimise skylight design parameters using multi-objective optimisation (MOO) approach through a case study of a low-rise building with office rooms configured to surround a skylight in the tropical climate of Yogyakarta, Indonesia. It was conducted using computational modelling and simulation with RadianceIES tools in IES-VE 2019 software. The parameters examined included skylight shape, opening area, and thickness, while the performance indicators were spatial daylight autonomy (sDA300/50%), average daylight factor (DFave), and annual sunlight exposure (ASE1000,250). The sensitivity analysis showed that skylight opening area significantly influenced daylight performance. Moreover, the optimum design, drawn from the objective function f and Pareto frontiers, was a rounded trapezium skylight with an opening area of 897 m2, achieving sDA300/50%-ASE1000,250 = 35%, DFave = 0.9%, and mean distance to the utopia point of 64.1%. These results could serve as a guide for architects and engineers in designing skylight for typical buildings. [ABSTRACT FROM AUTHOR]

Introduction: This study examines the complex link between regular maintenance procedures and the effectiveness of business-related assets in Australia. Commercial buildings are essential to the country's economy, and the variables affecting their worth must be carefully analysed. Methods: This study evaluates the relationship between asset value and maintenance frequency, examines how maintenance practices affect building performance, and considers industry perspectives on improperly versus correctly maintained assets. Results: The study's findings highlight the significance of renovations, along with adaptive reuse, in raising asset value; however, despite various maintenance techniques available, the Australian commercial building industry has challenges. Budgetary constraints, for instance, pose a significant hurdle, with many companies struggling to allocate sufficient funds for comprehensive maintenance plans. The findings of this research highlight the positive shift towards technology-driven maintenance procedures in business establishments in Australia. The adoption of computerised Maintenance Management Systems (CMMS) and Building Management Systems (BMS) is rising, automating repetitive tasks, improving maintenance procedures, and enabling data-driven decisions. Discussion: This study thoroughly explains the complex processes influencing the value and usefulness of commercial architecture resources in the Australian setting by addressing the differing perspectives within the real estate industry. Future research on this topic should focus on recognising the psychological components of decision-making concerning maintenance practices. Investigating how psychological prejudices, perceptions of danger, and organisational culture affect the choices made by property owners, facility administration, and others can help us better understand why some maintenance methods are preferred over others. [ABSTRACT FROM AUTHOR]

The construction industry and associated processes emit about 40%-50% of greenhouse gasses globally, making buildings' lifelong impact on the environment inevitable. Although research and development stakeholders have directed their focus on various sustainable, recycled, and upcycled building materials, as well as circular designs and construction methods to reduce the adverse effects of environmental challenges, researchers have not yet fully addressed a building's post-use treatment. Considering that the gap still remains in knowledge concerning how to fully achieve net-zero waste and emissions from construction materials, designs, and processes at the end of a building's life, this study contributes a concise definition of the concept of adaptability with a holistic review to understand Design for Adaptability (DfA) and its potential to reduce the need for unnecessary new construction and eliminate potential waste. This review used the PRISMA guidelines approach to gather key insights from various articles on the concept of adaptability that are relevant to the scope of buildings. Moreover, this review identifies potential areas of further research that could boost confidence in the use of adaptable strategies in the future. A total of 50 articles out of 170 articles were chosen through a selection process involving a new set of inclusion and exclusion criteria based on PRISMA guidelines. The findings show that demographical, technological, and economic motivations drive adaptability's functional, environmental, economic, and social benefits. However, the regulatory, technical, economic, and social barriers hinder its implementation in construction processes. The findings also demonstrate that various promising frameworks for assessing adaptability still lack comprehensive guidelines, assessment, and validation methods for the overall implementation of adaptable strategies. Existing frameworks are mostly limited to spatial assessment of the reuse of spaces and do not account for the structural flexibility and performance of load-bearing building elements despite the fact that most assessed papers were from the engineering field. Nevertheless, this paper concludes that adaptability strategies can be implemented early during the construction of new buildings or during the repurposing of existing buildings, with the end goal being to increase the longevity of the use of structures, prevent premature demolition, and minimize unnecessary construction waste. [ABSTRACT FROM AUTHOR]

Commercial Buildings release large volumes of greenhouse gases, expediting global warming. The commercial building industry accounts for 37% of global CO2 emissions. Geothermal energy technologies are an intriguing solution that provides a low-impact, emission-free, and cost-effective thermal fuel source for baseload energy production. Geothermal energy systems offer a potential solution to dramatically halt global warming and facilitate the transition to a carbon-neutral civilization. This study develops a framework for assessing the geothermal power capabilities of innovative house and district heating systems. The energy requirements are first assessed, and then the spatial evaluation of district heating infrastructure is carried out using a Python-based program. Economic comparisons between geothermal energy and fossil fuels are made using LCC analysis. Environmental impacts are measured by Life Cycle Analysis (LCA). This study compares geothermal energy to fossil fuels, and the LCA results show that geothermal energy has a low environmental impact. With a Net Present Value (NPV) of 34.81 USD, it displays economic viability as well as a satisfactory financial return. The study's findings show that geothermal energy has the ability to compete with fossil fuels in commercial heating applications while still being environmentally beneficial. [ABSTRACT FROM AUTHOR]