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This position paper aims to pave the way for a debate on a few under-explored, at least, perhaps even neglected, challenges we face when trying to improve building overall performance. Specifically, we suggest focusing on how the efforts to increase building energy efficiency, building safety, the home and workplace healthiness, and the comfort perceived by the users can be impaired by budget constraints, especially while operating in critical scenarios. On the one hand, restraints on capital expenditures by property owners and other investors affect the decision-making processes for the construction of new buildings or the renovation of existing ones. More beyond, rapidly developing demographic and other anthropological changes, as well as frequently occurred natural disasters, pose extra burdens on the players in the building industry and the real estate market. It has been a fact that the need to adapt to both budget constraints and challenging situations is seldom fully embedded in the studies focusing on improving building performance. Therefore, we call for attentions in research and publications to advocate for complementing the need. [ABSTRACT FROM AUTHOR]

One-third of all greenhouse gas emissions come from the world's building stock while accounting for 40% of global energy use. There is no way to combat global warming or attain energy independence without addressing the inefficiency of the building sector. This sector is the second consumer of electricity after the industrial sector in Morocco and is ranked third emitter after the energy sector and transportation sector. Using Ifrane as a case study, this paper examines and reviews the city's energy use and the initiatives taken to improve building efficiency. The findings showed that, during the analyzed period, i.e., from 2014 to 2022, Ifrane's annual electricity consumption climbed steadily from 35 to 43 GWh. The government of Morocco has implemented effective laws, guidelines and regulations, as well as publicized ways to reduce energy consumption and increase energy efficiency. However, gathered data and survey results revealed opportunities and challenges for enhancing Ifrane's efficient energy use. The study also evaluates government programs, codes/standards and related actions for the improvement of household energy efficiency. As part of the review, the available literature was analyzed to assess the effectiveness of energy behavior and awareness, the impact of an economical and sustainable building envelope, the impact of building retrofitting programs, the importance of energy-performing devices and appliances, the adoption of smart home energy management systems, the integration of renewable energies for on-site clean energy generation and the role of policies and governance in the building sector in Ifrane. A benchmark evaluation and potential ideas are offered to guide energy policies and improve energy efficiency in Ifrane and other cities within the same climate zone.

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Zero-energy buildings have attracted great attention in China. Limited research about typical high-rise, zero-energy residential buildings in China was found. To figure out the potential of zero-energy buildings in northern China, a techno-economic analysis of a typical residential building adapted to the nearly zero energy building (NZEB) standards in the cold region of China was carried out in detail in this paper. Firstly, the feasibility of different building energy efficiency technologies was figured out in the passive design level. Secondly, the annual energy balance of the nearly zero-energy building model was investigated. Finally, detailed economic and environmental analyses were performed. The results show that the energy consumption of space heating and cooling of a typical high-rise, nearly zero-energy building could decrease to 11.1 kWh/(m2·a) in Beijing. The conclusions could provide a reference and design basis for the development of zero-energy residential buildings in northern China in the near future. [ABSTRACT FROM AUTHOR]

This paper proposes a temperature-adaptive radiative cooling (TARC) coating with simple preparation, cost effectiveness, and large-scale application based on a thermochromic powder. To determine the energy efficiency of the proposed TARC coating, the heat transfer on the surface of the TARC coating was analyzed. Then, a typical two-story residential building with a roof area of 258.43 m2 was modeled using EnergyPlus. Finally, the energy-saving potential and carbon emission reduction resulting from the application of the proposed TARC roof in buildings under different climates in China were discussed. The results showed that the average solar reflectivity under visible light wavelengths (0.38–0.78 μm) decreases from 0.71 to 0.37 when the TARC coating changes from cooling mode to heating mode. Furthermore, energy consumption can be reduced by approximately 17.8–43.0 MJ/m2 and 2.0–32.6 MJ/m2 for buildings with TARC roofs compared to those with asphalt shingle roofs and passive daytime radiative cooling (PDRC) roofs, respectively. This also leads to reductions in carbon emissions of 9.4–38.0 kgCO2/m2 and 1.0–28.9 kgCO2/m2 for the buildings located in the selected cities. To enhance building energy efficiency, TARC roofs and PDRC roofs are more suitable for use on buildings located in zones with high heating demands and high cooling demands, respectively. [ABSTRACT FROM AUTHOR]

With the trend of achieving both energy efficiency in buildings and occupants' comfort, gamification strategies have started to be developed and applied as incentive mechanisms to increase social interaction and facilitate human energy behavior transformation. In this article, 306 published papers are reviewed, and 21 studies are identified to determine the challenges and potential for the development of gamification strategies to improve building energy efficiency. Specifically, this work reviews the implementation techniques of gamification and methods to assess the impact of gamification mechanisms on human energy behavior changes. This analysis demonstrates that, firstly, the choice of an optimal gamification implementation method should be inherently attuned to the distinct characteristics of the building type and its occupants. Secondly, it is imperative to strike a judicious balance between extrinsic and intrinsic motivations, in which customization of gamification design elements are based on users' unique personality traits and preferences, to properly tailor gamification mechanisms. Thirdly, integrating a fusion of quantification of energy savings and qualitative interpretation of user behaviors to improve the energy efficiency in buildings is essential for a more holistic understanding of the impact of gamification on users' energy-related behavior change. The findings indicate that gamification techniques can enable the effective reduction of energy consumption in buildings. [ABSTRACT FROM AUTHOR]

It difficult for buildings in cold regions to reasonably meet ultra-low energy consumption requirements. To explore the influencing factors of building energy consumption in this type of climatic region, this paper takes a typical public building in Zhengzhou, China as a case study to dynamically simulate an entire building. The influence of the window glass, window-to-wall ratio (WWR), thermal insulation material thickness and other factors on building energy consumption is considered. The sensitivity of envelope design factors to energy consumption is analyzed by the orthogonal test. The results indicate that the effect of changing the technical parameters of the external envelope structure on building energy efficiency is significant. Moreover, range analysis is used to determine the primary and secondary factors with regard to their influence on the energy consumption of the building. The WWR, the type of external window glass and the thickness of the external wall insulation layer should be considered first in energy-saving design; the energy-saving potential of the roof insulation thickness is not as significant as these factors. The results of the study can provide a reference for the energy-saving design of public buildings in Central China. [ABSTRACT FROM AUTHOR]

The traditional energy-saving evaluation method for industrial buildings is intended for all industrial buildings; however, substation buildings belong to a special category of industrial buildings, and their energy consumption characteristics are different from those of general industrial buildings. Consequently, it is necessary to establish an energy-saving evaluation system for substation buildings according to the characteristics of their energy consumption. In view of the issue that the energy consumption characteristics of substation buildings are different from those of other industrial buildings, an analytic hierarchy process (AHP) and fuzzy comprehensive evaluation (FCE) are used to establish a more comprehensive energy saving evaluation model that is more applicable to substation buildings. This paper determines 19 quantitative indicators and 13 qualitative indicators through the screening of relevant standards and norms, as well as the literature, and then determines the weight of each indicator by using AHP before finally establishing a secondary evaluation model based on FCE. In this paper, a substation in Shandong, China was selected as a case study to verify the proposed evaluation model, scoring 80.4 points, which falls within the "Good" grade. This method is of great significance for the future establishment of energy-saving evaluation system for substation buildings. [ABSTRACT FROM AUTHOR]

Buildings consume a significant part of the world's resources and energy. The growing environmental awareness and urgent need to reduce energy consumption have highlighted the importance of introducing innovative solutions as nature-based systems in new buildings' construction and retrofitting. In this regard, green façades that integrate vegetation into building envelopes are attractive. This paper presents a bibliographic analysis, based on science mapping, of the available literature on green façades from 1999–2022 with a focus on the thermal effect on the building and on the surroundings. The objective of this study is to reveal the structure and the evolution of the research activity in the field, outlining the main research topics and the future research directions. The analysis was performed on a dataset of 270 documents. The results indicate a growing interest in this topic over the last six years and the multidisciplinary dimension of the studies. The keyword cluster analysis indicates the emergence of three main search topics: thermal behavior and energy modeling; urban design and large-scale effects; sustainable buildings management. A greater future dissemination of green façades could be enabled by further research results based on the application of a multidisciplinary approach and of standardized methods. [ABSTRACT FROM AUTHOR]

The heat exchanger can use shallow geothermal energy to provide regional heating and cooling demand in winter and summer. In this paper, a large-scale public building is taken as the example, and the energy system in the building is taken as the research object. Firstly, through the collection of geothermal drilling geographic information and geothermal data, the geothermal reserves and geothermal recoverable resources are evaluated. Secondly, the cooling and heating demand of the building is calculated by using HVAC simulation software. Then, the heat transfer capacity of a single pile is evaluated and the lay-out scheme of the underground heat exchange pile foundation of the building is given. The actual heating effect of the heat exchange pile foundation system is explored, and the heat transfer characteristics of heat exchange pile foundation under different working conditions are compared and analyzed. Finally, reasonable suggestions for the arrangement of heat exchange pile foundation are given. [ABSTRACT FROM AUTHOR]

Single-side natural ventilation is a commonly used means of ventilation to effectively regulate the thermal environment in building interiors without any fossil energy consumption. To achieve most of the potential for the efficiency of single-side natural ventilation, research needs to be undertaken into the forces that drive single-side natural ventilation. This paper examines the single-side natural ventilation of a single vertical single opening (SSO) and a vertical double opening (SDO) in a freestanding building under wind and thermal pressure. The change in the trajectory of vortex shedding when the building is leeward as well as the frequency of vortex shedding in square buildings was investigated by large eddy simulation (LES), and computational fluid dynamics was used to analyze the difference in the air exchange rate of single-side natural ventilation of SSO and SDO in the windward and leeward conditions of the building. Both of these methods were used in conjunction with one another. According to the findings, the creation of vortices at SSO and SDO in the presence of low wind speeds reduces the ventilation effect of thermal pressure under windward circumstances. Consequently, the influence of thermal stress and wind stress ultimately cancel each other out, and this phenomenon finally disappears as the wind blowing from the outside of the structure increases. The shedding of vortices in the leeward state accomplishes a form of air supply pumping with a particular periodicity of airflow fluctuations in the lateral direction. The Strouhal number computed using the LES simulation acts in a manner consistent with the experimental findings. [ABSTRACT FROM AUTHOR]

PCMs are attractive for the future generation of buildings, where energy efficiency targets and thermal comfort expectations are increasingly prioritized. Experimental analysis of local thermal processes in these dynamic components and whole-building energy consumption predictions are essential for the proper implementation of PCMs in buildings. This paper discusses the experimental analysis of the thermophysical characteristics of both a latent heat storage material (PCM) and a product containing this PCM. The prototype product under investigation is a panelized PCM technology containing inorganic, salt-hydrate-based PCM. The thermal analysis includes studies of melting and freezing temperatures, enthalpy changes during phase change processes, nucleation intensity, sub-cooling effects, and PCM stability. The PCM's stability is also investigated, as is the ability of PCM products to control local temperatures and peak load transmission times. Two inorganic PCM formulations based on calcium chloride hexahydrate (CaCl2.6H2O) were prepared and tested in laboratory conditions. Material-scale testing results were compared with outcomes from the system-scale analysis, using both laboratory test methods as well as field exposure in test huts. This work demonstrates that PCM technologies used in buildings can effectively control both the magnitude of thermal storage capacity as well as the time of the peak thermal load. It was found that commonly used material-scale testing methods may not always be beneficial in assessing the dynamic thermal performance characteristics of building technologies containing PCMs. [ABSTRACT FROM AUTHOR]

The Renovation Wave for Europe highlighted the role of the public building stock for which Directive 2012/27/EU has set an annual renewal rate of 3%, which should rise to reach the goal of decarbonization by 2050. In this paper, the energy retrofit of an educational building—at the academic level—in Southern Italy was investigated. The aim was to evaluate the incentive share, which could accelerate the energy efficiency process, to achieve a cost-effective nZEB. The results show that the highest incentive rate is required for interventions on the opaque building envelope, which are also those that allow the least energy savings. An incentive rate of about 45% for the energy efficiency of the transparent envelope is necessary to reduce the payback time by about 7 years. The efficiency of the plants and the installation of a PV system are energetically and economically convenient even without forms of economic incentive. Finally, if the building is brought to high energy standards—a primary energy saving of 46% and energy class A3—an incentive rate of 40% is required to repay the intervention in about 10 years. [ABSTRACT FROM AUTHOR]

One-third of all greenhouse gas emissions come from the world's building stock while accounting for 40% of global energy use. There is no way to combat global warming or attain energy independence without addressing the inefficiency of the building sector. This sector is the second consumer of electricity after the industrial sector in Morocco and is ranked third emitter after the energy sector and transportation sector. Using Ifrane as a case study, this paper examines and reviews the city's energy use and the initiatives taken to improve building efficiency. The findings showed that, during the analyzed period, i.e., from 2014 to 2022, Ifrane's annual electricity consumption climbed steadily from 35 to 43 GWh. The government of Morocco has implemented effective laws, guidelines and regulations, as well as publicized ways to reduce energy consumption and increase energy efficiency. However, gathered data and survey results revealed opportunities and challenges for enhancing Ifrane's efficient energy use. The study also evaluates government programs, codes/standards and related actions for the improvement of household energy efficiency. As part of the review, the available literature was analyzed to assess the effectiveness of energy behavior and awareness, the impact of an economical and sustainable building envelope, the impact of building retrofitting programs, the importance of energy-performing devices and appliances, the adoption of smart home energy management systems, the integration of renewable energies for on-site clean energy generation and the role of policies and governance in the building sector in Ifrane. A benchmark evaluation and potential ideas are offered to guide energy policies and improve energy efficiency in Ifrane and other cities within the same climate zone. [ABSTRACT FROM AUTHOR]

It has been suggested in the literature that by reducing the incoming voltage at a distribution feeder head or at the supply side of buildings, significant electricity savings can be achieved. This technique is called Conservation Voltage Reduction (CVR). Data-based analysis with and without CVR is primarily used to support such assertions, which does not explain the physics behind reduction in energy consumption with CVR. This paper presents a new approach for evaluating the impact of CVR on cooling equipment. In this approach, a thermal-electric model of the cooling process is developed in MATLAB's SIMSCAPE toolbox that can be used to explain the physics behind energy reduction with CVR. This model includes an accurate model of a compressor coupled to an induction motor whose supply voltage can be varied to simulate CVR. Simulations performed using this model show that the Coefficient of Performance (COP) of cooling equipment improves with a reduction in supply voltage. However, the energy lost in the motor windings may nullify the impact of the improvement in the COP and render the CVR programs ineffective if the range of speed change is small over the allowable voltage change. The simulation results show an increase in energy consumption of 4% at 90% rated voltage compared to the energy consumed at the rated voltage. However, if variable frequency drives-based cooling equipment is appropriately controlled, it is possible to reduce their net energy consumption using CVR. Simulations performed keeping the ratio of the supply voltage and the frequency constant showed a reduction in energy consumption of 2.5% at 90% rated voltage compared to the energy consumed at the rated voltage. Thermal-electric modeling of building cooling equipment is, therefore, vital to accurately evaluating the benefits of CVR as smart, power electronics-based end-use equipment is globally adopted. [ABSTRACT FROM AUTHOR]

Since approximately 75% of Europeans currently live in cities, and this number will rise, urban areas are the most important testbeds for energy transition, climate change adaptation measures, and decarbonisation models, on which studies and efforts for concrete change must focus. The teaching of mitigation and adaptation measures to climate change and decarbonisation models has gradually taken up space within university courses. However, the complexity of the decarbonisation issue is raising awareness on the urgency of an interdisciplinary approach that can be conveyed by spatial planning. Currently, this approach is not widespread in Higher Education Institutions in Europe but is nonetheless necessary to let new professional profiles emerge who are able to coordinate different stakeholders, data, and information sources. The Erasmus+ project CITY MINDED (2020–2022) has worked in this direction, by developing and testing a methodology for the design of a structured ordinary practice for teaching urban decarbonisation to students in Higher Education. This practice (at the same time, interdisciplinary, collaborative, experiential, and place-based) aims to offer students a combination of different approaches and working methods to investigate and improve urban neighbourhoods and districts, resulting in the definition of an operative roadmap for decarbonisation in the medium-to-long-term. The aim of this article is to highlight the learning-by-doing experience developed by the project consortium, with reference to the testing of the methodology conducted within an Intensive Course in the City of Valletta (Malta). In particular, the paper illustrates how this experience succeeded in stimulating students with different academic backgrounds to establish connections across disciplines, in raising their awareness about the complexity of city decarbonisation processes. Overcoming the strict time and budget constraints of an EU-funded project, such an approach can be further developed, replicated on theoretical grounds, and implemented within different degree programmes dealing with urban sustainability. [ABSTRACT FROM AUTHOR]

The architectural form of buildings is determined by many factors, one of the most important is construction technology. It remains in a close and inseparable relationship with architectural design. Contemporary technologies in construction are constantly subject to improvements, streamlining, changes aimed at increasing all kinds of efficiency (cost, thermal efficiency, labor input, etc.). One of today's widely discussed determinants of changes in the way buildings are designed and constructed is environmental issue. An awareness of environmental degradation and climate change and their consequences prompts the search for increasingly sustainable solutions. This paper summarizes the research on prefabricated solutions and their implementation, especially in single-family residential architecture. This article presents pre-design, design, and post-design experiences related to planning and realization of single-family houses with prefabricated wall technology made of light expanded clay concrete. The authors implemented comparative qualitative and quantitative research through case studies, the method also uses experiences from their own research by design practice. The advantages and disadvantages of prefabrication in the selected technology are presented. The authors attempt to answer the question of whether the individual architectural design approach is reflected in the relevant environmental considerations, including, first, those related to the mitigation of climate change and adaptation to its consequences, and to what extent the discussed technology fits into the assumptions of climate and environmentally responsible design. [ABSTRACT FROM AUTHOR]

India's fossil-fuel-based energy dependency is up to 68%, with the commercial and residential sectors contributing to the rise of building energy demand, energy use, and greenhouse gas emissions. Several studies have shown that the increasing building energy demand is associated with increased space-cooling ownership and building footprint. The energy demand is predicted to grow further with the conditions of global warming and the phenomenon of urban heat islands. Building designers have been using state-of-the-art transient simulation tools to evaluate energy-efficient envelopes with present-day weather files that are generated with historical weather datasets for any specific location. Designing buildings with historical climatic conditions makes the buildings vulnerable to the predicted climate change impacts. In this paper, a weather file generator was developed to generate Indian future weather files using a geo-filtering-based spatial technique, as well as the temporal downscaling and machine learning (ML)-based bias correction approach proposed by Belcher et al. The future weather files of the three representative concentration pathways of 2.6, 4.5, and 8.5 could be generated for the years 2030, 2050, 2070, 2090, and 2100. Currently, the outputs of the second-generation Canadian Earth System Model are being used to create future weather files that will aid architects, urban designers, and planners in developing a built environment that is resilient to climate change. The novelty lies in using observed historical data from present-day weather files on the typical meteorological year for testing and training ML models. The typical meteorological weather files are composed of the concatenation of the monthly weather datasets from different years, which are referred to for testing and training ML models for bias correction. [ABSTRACT FROM AUTHOR]

Unlike many previous studies that often focus on optimizing energy efficiency for buildings when detailed design drawings are available, this paper introduces a newly integrated model for energy-efficient building envelope design in the early stages (when detailed design drawings are not yet available). The newly developed model includes three main components: a simulation model, a predictive model, and an optimization model. The simulation model simulates the building's energy performance, considering different values for various envelope parameters. The predictive model employs machine learning algorithms, including RF, ANN, DNN, SVM, GENLIN, and GB (in which GB has been identified as the most suitable algorithm), boasting a very high R 2 (0.994) to assess energy consumption. The optimization model which uses AI optimization algorithms (such as NSGA II, DSE, and MOPSO) integrates the machine learning predictive model into the evaluation function during the evolutionary process, efficiently searching for Pareto-optimal building envelope solutions. Results show simultaneous savings in cost and energy, with savings of 7.52 % in cost and 8.48 % in energy, or 21.17 % in cost and 0.4 % in energy, for a case study in Vietnam. This model establishes a foundation by providing design solutions for stakeholders to assess, and can incorporate additional objectives at later stages. [ABSTRACT FROM AUTHOR]

This paper introduces an innovative method for making cement-based composites from corn straw plants, and investigates the strength, thermal conductivity, and hydration characteristics of the composites. Corn straw is a natural, renewable, and breathable thermal insulation composite that contains cellular sealed pores. Corn straw contains a large amount of soluble cellulosic sugar, which hinders the hydration reaction of Portland cement and affects the use of corn straw as a building material. In this study, a 3 wt.% siliceous solution was used for surface treatment of corn straw particles to prevent cellulosic sugar from affecting the hydration performance of Portland cement. The composition of added cement-based composite materials with treated corn straw at the dosage of 11–20 wt.% was investigated. The test results showed that the corn straw cement-based composite (CSCC) had an optimal thermal conductivity of 0.102–0.112 (W/(m·K)) and a minimum compressive strength of above 1 MPa. The hydration performance of four typical CSCCs was examined using XRD, SEM, and EDS. The experimental results of this study may help to increase the comprehensive utilization of corn straw. The manufacturing method of the composite materials is simple, effective, and convenient for popularization and application, and it provides a new important technical measure to solve the problem of high energy consumption in rural houses. [ABSTRACT FROM AUTHOR]

In this paper, the integral performance indicator for selecting HVAC systems (ACPI) is applied to select the Air Conditioning (AC) system with better results in their life cycle for a typical building in Barranquilla, Colombia. The AC systems under study were: direct expansion system (Split and VRF), air-cooled system (VAC and VAV), and water-cooled system (Chiller). Of the six selection criteria of ACPI, the energy consumption index (EC) and thermal comfort (TC) were calculated through energy simulation of buildings, the regulations were used for IAQ and carbon emissions (CE), and were estimated the investment costs (IC) and operating and maintenance costs (OMC). The best-performance AC system for the building was the air-cooled AC system got the best ACPI values between 25 % and 22.4 %, followed by the water-cooled system with 22.3 %, and finally the direct expansion systems between 16.8 % and 13.5 %, influencing in this level of priority the IAQ and IC criteria. This study contributes to introducing in Colombia a multifactorial analysis to select the more proper AC system technology according to the building and location conditions. [ABSTRACT FROM AUTHOR]

[Display omitted] • The paper reviews 43 articles defining methodologies for climate classification. • The paper provides overview of climate classification and validation methods. • Need of standard methodology or nomenclature for climate classification. • The optimal approach for conducting climate zoning remains a topic of debate. Climate classification simplifies the representation of expected climate conditions by eliminating the need to describe each climatic parameter. Climate classification is frequently used as a basis for recommendations through codes and standards for buildings because a given climate has nearly similar design conditions. Furthermore, building energy efficiency programmes are designed based on the climatic classification to determine appropriate design strategies to eliminate the under-design or over-design of buildings for similar climatic regions. This necessitates the use of realistic and reliable climate classifications. Over the past two decades, numerous research studies have proposed climate classification methods. However, there is a lack of universal acceptance of climate classification methodology to balance complexity and accuracy. This research provides an overview of various climate classification methods and indicators used to assess the significance of climatic conditions. Moreover, this study highlights pressing issues, proposes a feasible climate classification methodology, and offers substantial possibilities for future study. This study organizes and evaluates the various classification and validation methods used by researchers, variables, and the granularity of data used for the classification. The usual criteria for defining a climate are temperature, relative humidity, cooling-degree days, heating-degree days, and solar radiation. About eighty-five percent of the classified climates are using at most three variables. The number and characteristics of climate zones vary with changes in the resolution of climate data, classification methods, and the inclusion of different sets of parameters. Clustering methods are becoming more important for climate classification as these methods can handle multiple variables more accurately. To tackle the complex relationship between climate and building thermal design, it is recommended to use climate variables with cluster analysis and validation based on thermal loads. This paper will give researchers an aerial perspective of the scope and direction of ongoing research in this field. [ABSTRACT FROM AUTHOR]

In this paper, an artificial neural network (ANN) based system-level model predictive control framework is established for a variable air volume (VAV) system to improve its robustness and energy efficiency. The VAV system consists of three processes: the zone temperature process, the damper process and the supply air volume process of the air handling unit connecting the ductwork for all of the boxes. An ANN-based predictive controller is designed for the zone temperature process, and a PI controller is used for the damper process; they operate in a cascaded manner. Another ANN predictive controller tracks the total supply air volume subject to the cooling load constraints from the lower level VAV boxes and minimizes the fan energy consumption. The ANN controllers are optimized online by the Lagrange variational approach (LVA) to minimize the system cost function and implement a feedback receding horizon optimal control. With the LVA based gradient descent training algorithm, the weight convergence of the ANN predictive controllers and stability of the control system is obtained with small computational and storage needs. The modeling methodology, based on ANNs for the above processes, is developed and calibrated with actual data measured from a site. All of the data processing and control strategy implementations are based on extensive measurements collected from a laboratory building located in the campus of Beijing University of Civil Engineering and Architecture , Beijing , China. The experimental results show that an additional 6.12% energy savings is achieved. This is accomplished by introducing the fan control signal into the system cost function as the performance index of energy consumption with a 0.2 penalty coefficient. In the presence of un-modeled disturbances and modeling errors, the framework also reduces the temperature oscillation at least by approximately 60% compared with PI control. • A neural network-based predictive control strategy for VAV systems is designed. • Cascade predictive control is implemented for zone temperature and air flow rate. • The duct air volume process achieves total airflow predictive control with savings in fan energy consumption. • The predictive controller using neural network implementation, easy to achieve nonlinear system optimization. • The control strategy is robust to un-modeled disturbances and modeling errors. [ABSTRACT FROM AUTHOR]

Energy efficiency in the context of building design is a significant concern in Morocco. This paper offers a comprehensive analysis of how various design variables can impact both energy consumption and thermal comfort in the Moroccan context. Rather than isolating individual design variables, we investigate synergistic combinations of these variables. To achieve this, we develop multiple building design scenarios, each employing different combinations of design options, focusing on building orientation, window-to-wall ratio, building envelope construction, and window shading. We use EnergyPlus to conduct energy simulations for all scenarios under the hypothesis of air-conditioned houses and free-running houses with and without natural ventilation. Our results reveal that building design has the potential to significantly enhance energy efficiency and thermal comfort, but not for the same design strategies. In comparison to the most energy-efficient design scenario, the least favorable design scenario can lead to an increase in energy consumption between 237% in Agadir and 130% in Ifrane. Meanwhile, design scenarios favoring comfort can increase the number of comfortable hours by 85% in Agadir and 59% in Ifrane. We identify optimal building design scenarios that simultaneously offer the highest comfort levels with the lowest energy requirements. The findings provide valuable guidance for architects, allowing them to design high-performance buildings in all climate zones in Morocco. [ABSTRACT FROM AUTHOR]

Our work is dedicated to enhancing sustainability through improved energy efficiency in buildings, with a specific focus on heating and cooling control and the optimization of thermal comfort of occupants. With an energy consumption of more than 60% in buildings, HVAC systems are the biggest energy users. By integrating advanced technology, data algorithms, and digital twins, our study aims to optimize energy performance effectively. We have developed a Neural Network-based Model Predictive Control (NNMPC) to achieve this goal. Leveraging technologies such as MQTT communication, Wi-Fi modules, and field-programmable gate arrays will enhance scalability and flexibility. Our findings demonstrate the efficacy of the NNMPC system deployed on the PYNQ board for reducing sensible thermal energy usage for both cooling and heating purposes. Compared to traditional On/Off control systems, the NNMPC achieved an impressive 40.8% reduction in heating energy consumption and a 37.8% decrease in cooling energy consumption in 2006. In comparison to the On/Off technique, the NNMPC demonstrated a 25.6% reduction in annual heating energy consumption and a 28.8% drop in annual cooling energy consumption in the simulated year of 2017. We observed that, across all strategies and platforms, there were no instances where the Predicted Mean Vote (PMV) fell below − 0.5 . However, a significant proportion of PMV values (ranging from 65% to 83%) were observed between − 0.5 and 0.5, signifying a high level of occupant comfort. Additionally, for PMV values between 0.5 and 1.0, percentages ranged from 16% to 33% for both years. Importantly, the NNMPC exhibited notable efficiency in maintaining occupants' comfort within this range, requiring less energy while ensuring highly satisfactory environments. [ABSTRACT FROM AUTHOR]

With the increasing demand for energy worldwide, researchers from different fields have been striving to improve the sustainability and proper utilization of energy resources. Passive radiative cooling, as a natural energy transport method, can achieve cooling without additional external energy input. This review provides a comprehensive examination of passive radiative cooling, including its fundamental theories and latest development. A particular emphasis is placed on the diverse range of fields where passive radiative cooling has been applied, notably including but not limited to construction and architecture. The current state of applications, potential challenges that may arise with wider adaption and promising research directions for each field are thoroughly discussed. This review emphasizes the extensive potential and practical viability of passive radiative cooling in diverse applications and identifies pressing challenges and future research directions aimed at scaling up real-world implementation. [ABSTRACT FROM AUTHOR]

As the building sector acts as an important CO2 emissions source, it is essential to renovate the existing building stock for carbon neutrality in the EU. The study reveals the effects of several novel renovation technologies on building energy consumption and CO2 emissions through building simulations. An English semi-detached house and a Spanish terraced house were chosen as the simulated demo houses. Renovation technologies were divided into passive, ventilation, and generation packages and simulated by packages and final combinations. Insulating breath membrane and bioaerogel thermal insulation are the most appropriate single technology for lowering CO2 emissions for the English and Spanish demo houses, respectively. For generation technologies, solar assisted heat pump is a more recommended CO2 emissions conservation technology than PVT system in both climate conditions. The demo houses' CO2 emissions can be reduced maximally by over 70% after renovating with the final combination including solar assisted heat pump. The current economic feasibility of the novel technologies is limited by various issues, for example, manufacturing costs and energy prices. Nevertheless, considering most of the issues can be solved with time, they will be economically feasible renovation measures in the future. [ABSTRACT FROM AUTHOR]

The objective of energy transition is to convert the worldwide energy sector from using fossil fuels to using sources that do not emit carbon by the end of the current century. In order to achieve sustainability in the construction of energy-positive buildings, it is crucial to employ novel approaches to reduce reliance on fossil fuels. Hence, it is essential to develop buildings with very efficient structures to promote sustainable energy practices and minimize the environmental impact. Our aims were to shed some light on the standards, building modeling strategies, and recent advances regarding the methods of control utilized in the building sector and to pinpoint the areas for improvement in the methods of control in buildings in hopes of giving future scholars a clearer understanding of the issues that need to be addressed. Accordingly, we focused on recent works that handle methods of control in buildings, which we filtered based on their approaches and relevance to the subject at hand. Furthermore, we ran a critical analysis of the reviewed works. Our work proves that model predictive control (MPC) is the most commonly used among other methods in combination with AI. However, it still faces some challenges, especially regarding its complexity. [ABSTRACT FROM AUTHOR]

Buildings remain pivotal in global energy consumption, necessitating a focused approach toward enhancing their energy efficiency to alleviate environmental impacts. Precise energy prediction stands as a linchpin in optimizing efficiency, offering indispensable foresight into future energy demands critical for sustainable environments. However, accurately forecasting energy consumption for individual households and commercial buildings presents multifaceted challenges due to their diverse consumption patterns. Leveraging the emerging landscape of the Internet of Things (IoT) in smart homes, coupled with AI-driven energy solutions, presents promising avenues for overcoming these challenges. This study introduces a pioneering approach that harnesses a hybrid deep learning model for energy consumption prediction, strategically amalgamating convolutional neural networks' features with long short-term memory (LSTM) units. The model harnesses the granularity of IoT-enabled smart meter data, enabling precise energy consumption forecasts in both residential and commercial spaces. In a comparative analysis against established deep learning models, the proposed hybrid model consistently demonstrates superior performance, notably exceling in accurately predicting weekly average energy usage. The study's innovation lies in its novel model architecture, showcasing an unprecedented capability to forecast energy consumption patterns. This capability holds significant promise in guiding tailored energy management strategies, thereby fostering optimized energy consumption practices in buildings. The demonstrated superiority of the hybrid model underscores its potential to serve as a cornerstone in driving sustainable energy utilization, offering invaluable guidance for a more energy-efficient future. [ABSTRACT FROM AUTHOR]

Energy efficiency is currently a hot topic in engineering due to the monetary and environmental benefits it brings. One aspect of energy efficiency in particular, the prediction of thermal loads (specifically heating and cooling), plays a significant role in reducing the costs associated with energy use and in minimising the risks associated with climate change. Recently, data-driven approaches, such as artificial intelligence (AI) and machine learning (ML) techniques, have provided cost-effective and high-quality solutions for solving energy efficiency problems. This research investigates various ML methods for predicting energy efficiency in buildings, with a particular emphasis on heating and cooling loads. The review includes many ML techniques, including ensemble learning, support vector machines (SVM), artificial neural networks (ANN), statistical models, and probabilistic models. Existing studies are analysed and compared in terms of new criteria, including the datasets used, the associated platforms, and, more importantly, the interpretability of the models generated. The results show that, despite the problem under investigation being studied using a range of ML techniques, few have focused on developing interpretable classifiers that can be exploited by stakeholders to support the design of energy-efficient residential buildings for climate impact minimisation. Further research in this area is required. [ABSTRACT FROM AUTHOR]

Life-Cycle Carbon Emission Assessment (LCCO2A) of buildings integrating climate change impact has received increasing attention by researchers as the consequences of climate change become more apparent. It is crucial to integrate the indicator of life cycle carbon equivalent greenhouse gas (GHG) emissions at the early design stage combined with a life cycle assessment, to ensure the elimination of GHG emissions from a building, for its entire life. LCCO2A can provide the necessary information required for reducing carbon emissions of the buildings sector both systematically and comprehensively; however, the lack of a unified assessment framework has prevented the LCCO2A from being utilised as a common daily decision-support tool for sustainable design. This paper will take a retrospective approach when reviewing the methodologies of building LCCO2A in order to facilitate sustainable collective building design which incorporates GHG emission reduction objectives. The paper discusses a wide array of issues concerning LCCO2A and will demonstrate solution methods, as addressed in the extensive existing literature examined in the review and will attempt to establish an effective framework for life cycle carbon assessment. The implication of promoting sustainable designs which incorporate climate change mitigation objectives at the design phase together with the need for climate change policies to facilitate such processes, are also discussed.

Pursuing innovations in sustainable architectural solutions, this study examines the impact of a climate-adaptive building envelope with dynamic photovoltaic integrated shading devices (PVSDs) on building performance. A major challenge in designing PVSDs is the lack of established guidelines for geometry and operations. We delve into the complexities and potential benefits of integrating dynamic PVSD designs into building performance simulations, particularly considering their time-varying geometric and operational aspects. This research assesses a range of similar PVSD design options with differing patterns, emphasizing their effects on solar energy potential, daylighting, and thermal efficiency. We conducted tests on south-oriented PVSDs (featuring two-axis rotation) in Houston, Texas, focusing on variables such as panel count (4 or 36), rotation angle range, and operational patterns (synchronized or individual). Regarding solar potential, the four-panel synchronized PVSD option outperformed static shading by 2.1 times. For daylighting and thermal performance, the 36-panel synchronized option with a wide rotation range and the four-panel individual option proved superior to other PVSD configurations, improving up to an average of 36% (sDA300/50%) and 1.5 °C, respectively. Our findings emphasize the critical role of integrating geometric design and operational patterns in PVSDs for enhanced system effectiveness and highlight PVSD design and application limitations. Our findings emphasize the critical role of integrating geometric design and operational patterns in PVSDs for enhanced system effectiveness. Furthermore, they shed light on the limitations in the PVSD design process and practical applications. [ABSTRACT FROM AUTHOR]

Windows and their control elements, including shading systems, are among the most critical building components affecting both energy consumption and occupant comfort. With the increasing demand for full-glazed facades, designers and researchers are actively devising advanced control strategies to address the challenges posed by excessive sunlight penetration and heat transfer. These strategies aim to harmonize the benefits of natural light with the need for comfortable indoor environments and energy consumption reduction. This study investigates the impact of external shading configurations for an office room in Tehran, categorized as group B in the Köppen climate classification, to reduce total building energy consumption and improve occupant thermal and visual comforts. The shading parameters include shading angle, shading depth, and the number of shading slats. More specifically, this study analyzes and compares two design configurations for the considered office room. The first configuration consists of a single southern window with horizontal shading, whereas the second configuration consists of two windows on the south and west, one being horizontal shading on the southern side and the other being vertical shading on the western side. There are a total of 1330 models investigated from which 20 models are selected as the most suitable solutions. Finally, this paper examines the effect of each design parameter on the overall performance of each configuration in terms of energy efficiency and visual-thermal comfort.

The looming global energy crisis of the 21st century is predicted to worsen as building energy consumption is expected to rise by 50% by 2060. Investing in energy-efficient technologies and reducing carbon emissions is essential to combat this crisis. To this end, this paper delves into the complex issue of energy-efficient building practices in Nigerian households and how they can help curb carbon emissions. Using a statistical method known as the Relative Impor- tance Index (RII), we analyzed nine key factors that influence a building’s energy efficiency. The research revealed that government oversight, support, and financial and technical assis- tance are crucial for achieving household energy efficiency. It also highlights the significance of addressing the energy crisis in Nigeria through the development, implementation, and ad- aptation of energy-efficient building practices.

Unlike many previous studies that often focus on optimizing energy efficiency for buildings when detailed design drawings are available, this paper introduces a newly integrated model for energy-efficient building envelope design in the early stages (when detailed design drawings are not yet available). The newly developed model includes three main components: a simulation model, a predictive model, and an optimization model. The simulation model simulates the building's energy performance, considering different values for various envelope parameters. The predictive model employs machine learning algorithms, including RF, ANN, DNN, SVM, GENLIN, and GB (in which GB has been identified as the most suitable algorithm), boasting a very high R2(0.994) to assess energy consumption. The optimization model which uses AI optimization algorithms (such as NSGA II, DSE, and MOPSO) integrates the machine learning predictive model into the evaluation function during the evolutionary process, efficiently searching for Pareto-optimal building envelope solutions. Results show simultaneous savings in cost and energy, with savings of 7.52 % in cost and 8.48 % in energy, or 21.17 % in cost and 0.4 % in energy, for a case study in Vietnam. This model establishes a foundation by providing design solutions for stakeholders to assess, and can incorporate additional objectives at later stages.

Air-source heat pumps (ASHPs), as an active device, are widely used in building heating and cooling processes. However, in severe cold regions, they face reduced heating efficiency and frosting problems in winter. This paper proposes a new heating solution by coupling an ASHP with passive heating systems. It combines an ASHP with passive sunrooms and heat storage systems for heating. Through software simulations and mathematical modeling, the new scheme is compared and analyzed against traditional ASHP solutions to explore the performance of this scheme in rural houses in severe cold regions of China during winter. According to simulation and calculation analysis, on the coldest day of winter, the coupling scheme can provide approximately 99.41 kWh of heat to the indoors, which exceeds the 86.67 kWh required to maintain an indoor temperature of 20 °C. The system’s power consumption is 36.96 kWh, which is 66.88% lower than that of traditional heat pump heating. The study shows that the coupling system of an ASHP and passive heating has a good heating effect in severe cold regions. For the situation of insufficient solar energy at night, the design of phase-change materials and heat storage media can meet heating needs throughout the day.

This paper proposes a temperature-adaptive radiative cooling (TARC) coating with simple preparation, cost effectiveness, and large-scale application based on a thermochromic powder. To determine the energy efficiency of the proposed TARC coating, the heat transfer on the surface of the TARC coating was analyzed. Then, a typical two-story residential building with a roof area of 258.43 m2 was modeled using EnergyPlus. Finally, the energy-saving potential and carbon emission reduction resulting from the application of the proposed TARC roof in buildings under different climates in China were discussed. The results showed that the average solar reflectivity under visible light wavelengths (0.38–0.78 μm) decreases from 0.71 to 0.37 when the TARC coating changes from cooling mode to heating mode. Furthermore, energy consumption can be reduced by approximately 17.8–43.0 MJ/m2 and 2.0–32.6 MJ/m2 for buildings with TARC roofs compared to those with asphalt shingle roofs and passive daytime radiative cooling (PDRC) roofs, respectively. This also leads to reductions in carbon emissions of 9.4–38.0 kgCO2/m2 and 1.0–28.9 kgCO2/m2 for the buildings located in the selected cities. To enhance building energy efficiency, TARC roofs and PDRC roofs are more suitable for use on buildings located in zones with high heating demands and high cooling demands, respectively.

A large amount of the Iranian energy demand is related to the building sector, mainly due to its obsolescence. In this paper, a second-skin system has been implemented as a retrofit action for an office building, evaluating the effect of a tensile material as second-skin in terms of primary energy saving, carbon dioxide equivalent emissions, and simple payback period. The analysis was carried out through numerical simulations across a whole year and for four Iranian cities (Tabriz, Teheran, Yazd, and Bandar Abbas) in four different climates (cold, temperate, hot-dry, and hot-wet), and with the building aligned at either north-south or east-west. Moreover, an economic analysis was carried out suggesting different incentive policies to promote building energy refurbishment. The simulation results highlighted a favorable orientation for buildings in Iran, suggesting a guideline for new constructions. Indeed, the best results were achieved for an east-west orientation of the building (up to a primary energy saving of 13.6% and reduction of carbon dioxide equivalent emissions of 45.5 MgCO2,eq, in Yazd), with a decrease of the annual specific total (cooling and thermal) energy demand of 37.9 kWh/m2/year. The simple payback period values were also lower in the east-west orientation than the north-south one. [ABSTRACT FROM AUTHOR]

This paper explores the role of international partnerships to facilitate low-energy building design, construction, and operations. We present the strategic approach, joint research and development outcomes, and implementation activities of a unique U.S.-India program on buildings energy efficiency, the Center for Building Energy Research and Development. We discuss the collaboration successes in both countries despite their dissimilar building contexts, implementation challenges and opportunities. We highlight a range of R&D outcomes, such as novel tools and technologies developed and tested by the joint teams, with their technical energy savings potential, as well as results of capacity building and technology demonstrations. A deep-dive into key new scientific methods around building energy monitoring and benchmarking that could have a significant impact on high-performanceof buildings in both countries is also provided. Finally, in addition to joint R&D successes, pathways to deployment, and lessons learned are discussed as key takeaways.

With the trend of achieving both energy efficiency in buildings and occupants’ comfort, gamification strategies have started to be developed and applied as incentive mechanisms to increase social interaction and facilitate human energy behavior transformation. In this article, 306 published papers are reviewed, and 21 studies are identified to determine the challenges and potential for the development of gamification strategies to improve building energy efficiency. Specifically, this work reviews the implementation techniques of gamification and methods to assess the impact of gamification mechanisms on human energy behavior changes. This analysis demonstrates that, firstly, the choice of an optimal gamification implementation method should be inherently attuned to the distinct characteristics of the building type and its occupants. Secondly, it is imperative to strike a judicious balance between extrinsic and intrinsic motivations, in which customization of gamification design elements are based on users’ unique personality traits and preferences, to properly tailor gamification mechanisms. Thirdly, integrating a fusion of quantification of energy savings and qualitative interpretation of user behaviors to improve the energy efficiency in buildings is essential for a more holistic understanding of the impact of gamification on users’ energy-related behavior change. The findings indicate that gamification techniques can enable the effective reduction of energy consumption in buildings.

As building systems account for almost half of the total energy consumed by the building sector to provide space heating, cooling, and ventilation, efficiently designing these systems can be the key to energy conservation in buildings. Dual VAV systems with an effective control strategy can substantially reduce the energy consumption in buildings, providing a significant scope of further research on this system configuration. This paper proposes to utilize the warm air duct of the dual VAV system as a dedicated outdoor air (DOA) unit when no heating is required, which allows the cooling load to be effectively distributed between two ducts. A specific control sequence is proposed with different supply air temperature reset strategies to estimate the heating, cooling loads, and fan power energy consumption of the proposed system. A simple two-zone office building is taken as a preliminary case study to simulate the airflow rates and fan power of a single duct VAV and proposed dual VAV systems to illustrate the concept. Finally, a larger multi-zone office building is simulated to measure the annual heating, cooling loads, and fan power energy and compare the energy savings among the systems. The results show significant fan power reduction ranging from 1.7 to 9% and notable heating energy reduction up to 76.5% with a small amount of cooling load reduction varying from 0.76 to 2.56% depending on the different locations for the proposed dual VAV systems. Further energy savings from different supply air temperature reset strategies demonstrate the opportunity of employing them according to climates and case studies. The proposed dual VAV system proves to have the potential to be adapted in buildings for the purpose of sustainability and energy savings. [ABSTRACT FROM AUTHOR]

Optimizing efficiency in the operation of the HVAC system of existing buildings requires the construction of a thermal dynamic model of the building, which may be challenging because architectural metadata may be missing or obsolete. Based on a suitable set of measured data, this paper presents a novel practical methodology to create and automatically derive thermal models of existing buildings in high-fidelity simulators for energy management. To this end, the philosophy of grey-box strategies is followed to simplify the modeling and avoid the requirement of architectural metadata, facilitating and expediting the process. First, a building model with a highly reduced number of parameters is constructed by exploiting the existing similarities in the materials of the buildings and simplifying their elements to a simple one-layer parameterization. Then, the parameters of the derived model are iteratively updated while minimizing the error between the real temperature evolution and that generated by the model being identified. For this purpose, data of the room air temperature, estimated occupancy, weather conditions, and variables of the HVAC system are assumed to be available in suitable zones of the building to apply the creation and identification processes of the model, allowing that a whole digital twin of the building is constructed. The methodology is presented by its application to a real case study: the Nimbus Research Centre building at Munster Technological University, located in Cork (Ireland). The high-fidelity simulator software TRNSYS is used for the modeling task, together with the GenOpt optimization program. The results demonstrate that the proposed methodology yields a highly accurate model of the building, capable of representing reality with RMSE values consistently below 0.6 C ∘ during open-loop validation periods of up to four days. The findings suggest that this methodology may outperform other modeling techniques reported in the literature. Importantly, the proposed technique is less complex and time-consuming to implement than many of the alternatives. • Thermal modeling of existing buildings avoiding the use of architectural metadata. • Novel integration of grey-box modeling methods with high-fidelity simulators. • The proposed method copes with the drawbacks of the models found in the literature. • Methodology validated with experimental data from the Nimbus Centre (Ireland). • Results show high accuracy of greatly simplified models—RMSE<0.6 °C in 4-day horizons. [ABSTRACT FROM AUTHOR]

High-rise buildings consume more energy and have greater environmental impacts, emphasising the need to adopt best practices during the design stage concerning BIM employment. However, despite strong support from the literature, little is known about the applications of BIM in high-rise buildings at the early design stage. Therefore, this paper aims to provide a holistic understanding of the current applications of BIM in high-rise buildings by analysing 60 studies. The findings identified seven research themes, including studies that used BIM for i) optimising building energy efficiency design; ii) collaborative design and planning; iii) life-cycle assessment; iv) designing net-zero energy buildings; v) integrating BIM with smart technologies for designing high-rise buildings; vi) cost analysis, and vii) structural design of high-rise buildings. Furthermore, this study highlights a number of challenges hindering the widespread application of BIM, alongside providing potential directions for the future development of BIM employment in high-rise buildings. [Display omitted] • A systematic review of BIM applications in high-rise buildings was conducted • Seven domains of BIM applications were identified • Challenges hindering widespread use of BIM in high-rise buildings were highlighted • Directions for future development of this research area were recommended [ABSTRACT FROM AUTHOR]

In this paper, the integral performance indicator for selecting HVAC systems (ACPI) is applied to select the Air Conditioning (AC) system with better results in their life cycle for a typical building in Barranquilla, Colombia. The AC systems under study were: direct expansion system (Split and VRF), air-cooled system (VAC and VAV), and water-cooled system (Chiller). Of the six selection criteria of ACPI, the energy consumption index (EC) and thermal comfort (TC) were calculated through energy simulation of buildings, the regulations were used for IAQ and carbon emissions (CE), and were estimated the investment costs (IC) and operating and maintenance costs (OMC). The best-performance AC system for the building was the air-cooled AC system got the best ACPI values between 25 % and 22.4 %, followed by the water-cooled system with 22.3 %, and finally the direct expansion systems between 16.8 % and 13.5 %, influencing in this level of priority the IAQ and IC criteria. This study contributes to introducing in Colombia a multifactorial analysis to select the more proper AC system technology according to the building and location conditions.

Cooling energy consumption is a major contributor to various sectors in hot climates with a significant number of warm days throughout the year. Buildings account for 40% of total energy consumption, with approximately ∼30–40% of that used for cooling in geographical areas such as Iran. Energy demand for cooling is an important factor in the overall energy efficiency of electric mobility. Electric vehicles (EVs) consume ∼30–50% of energy for the air conditioning (AC) system. Therefore, the efficient management of the cooling demand is essential in implementing energy-saving strategies. Passive radiative cooling is capable of providing subambient cooling without consuming any energy. This article reviews potential applications of passive radiative cooling in reducing cooling energy for buildings. It also provides a rough estimate of the amount of energy saved when applying a radiative cool roof to a model building. It is shown that by using radiative cool materials on roofs, the share of electricity usage for cooling can be reduced to 10%, leading to a reduction in cooling load by 90%. Additionally, the potential use of radiative cool coats of various types for different EV components, such as shell/body, windows, and fabrics, is introduced. Although the prospects of the design and engineering of radiative cooling products appear promising for both buildings and EVs, further investigations are necessary to evaluate scalability, durability, and performance based on factors such as geography and meteorology. [ABSTRACT FROM AUTHOR]

The development of high-performance insulation materials that facilitate the reduction in building energy consumption is of paramount significance. In this study, magnesium–aluminum-layered hydroxide (LDH) was prepared by the classical hydrothermal reaction. By implementing methyl trimethoxy siloxane (MTS), two different MTS-functionalized LDHs were prepared via a one-step in situ hydrothermal synthesis method and a two-step method. Furthermore, using techniques, such as X-ray diffraction, infrared spectroscopy, particle size analysis, and scanning electron microscopy, we evaluated and analyzed the composition, structure, and morphology of the various LDH samples. These LDHs were then employed as inorganic fillers in waterborne coatings, and their thermal-insulation capabilities were tested and compared. It was found that MTS-modified LDH via a one-step in situ hydrothermal synthesis method (M-LDH-2) exhibited the best thermal insulating properties by displaying a thermal-insulation-temperature difference (ΔT) of 25 °C compared with the blank panel. In contrast, the panels coated with unmodified LDH and the MTS-modified LDH via the two-step method exhibited thermal-insulation-temperature difference values of 13.5 °C and 9.5 °C, respectively. Our investigation involved a comprehensive characterization of LDH materials and coating films, unveiling the underlying mechanism of thermal insulation and establishing the correlation between LDH structure and the corresponding insulation performance of the coating. Our findings reveal that the particle size and distribution of LDHs are critical factors in dictating their thermal-insulation capabilities in the coatings. Specifically, we observed that the MTS-modified LDH, prepared via a one-step in situ hydrothermal approach, possessed a larger particle size and wider particle size distribution, resulting in superior thermal-insulation effectiveness. In contrast, the MTS-modified LDH via the two-step method exhibited a smaller particle size and narrow particle size distribution, causing a moderate thermal-insulation effect. This study has significant implications for opening up the potential for LDH-based thermal-insulation coatings. We believe the findings can promote the development of new products and help upgrade industries, while contributing to local economic growth. [ABSTRACT FROM AUTHOR]

An increasing number of U.S. cities require commercial/office properties to publicly disclose their energy performance due to the adoption of energy benchmarking and disclosure policies. This level of transparency provides an additional in-depth assessment of a building's performance beyond a sustainability certification (e.g., Energy Star, LEED) and may lead less energy-efficient buildings to invest in energy retrofits, therefore improving their marketability. However, the research is scarce on assessing the impact of such policies on office building marketability. This study tries to fill this gap by investigating the impact of energy benchmarking policies on the performance of office buildings in four major U.S. cities (New York; Washington, D.C.; San Francisco; and Chicago). We use interrupted time series analysis (ITSA), while accounting for sustainability certification, public policy adoption, and property real estate performance. The results revealed that in some cities, energy-efficient buildings generally perform better than less energy-efficient buildings after the policy implementation, especially if they are Class A. The real estate performances of energy-efficient buildings also exhibited continuously increasing trends after the policy implementation. However, due to potentially confounding factors, further analysis is required to conclude the policy impacts on energy-efficient buildings are more positive than those on less energy-efficient buildings. [ABSTRACT FROM AUTHOR]

Highlights: What are the main findings? What is the implication of the main findings? Proposal of a BIM-based framework for lifecycle carbon prediction and optimisation. Proposal of a standard method with generic formulations to calculate the embodied carbon. Exploration of BIM-enabled parametric modelling for optimising low-carbon alternative design. Exploration of the interoperability between BIM and energy simulation for lifecycle energy analysis. Investigation of low-carbon materials and designs in the lifecycle carbon of residential buildings. Residential building construction is resource-intensive and significantly impacts the environment by embodied and operational carbon emissions. This study has adopted a parametric building information modelling (BIM)-based approach for a residential building to analyse its lifecycle carbon performance and to evaluate the optimisation potential through alternative material use and design. The study looks at a residential development project, applying an automatic calculation and analysis tool of upfront embodied carbon and BIM-based lifecycle energy simulation to predict carbon emissions from operating the built spaces. A parametric BIM model has been established to aid energy simulation and operational carbon assessment across a 50-year building lifetime, considering 1.5 °C Net-Zero World and 3 °C Hot House World climate scenarios. Various improvement opportunities for future residential development projects, from material selection to operational efficiencies, are explored. This includes quantitative analysis on architectural-structure design, low-carbon construction materials (e.g., cement substitutes, steel scraps, and green hydrogen steel), and novel design for construction approaches (such as modular integrated construction), with discussion around their impacts on optimising the building lifecycle carbon performance. This study provides a deeper understanding and insights into the lifecycle performance of residential buildings to facilitate further exploration of achieving a more sustainable and low-carbon built environment. [ABSTRACT FROM AUTHOR]