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This study aims to assess carbon emissions in urban aged residential buildings in Qingdao, Shandong Province, constructed prior to 2000, and to evaluate retrofitting and rebuilding strategies for potential carbon reduction.

Field investigations and literature reviews were conducted to identify key factors influencing carbon emissions, such as shape coefficient, window-to-wall ratio and envelope structure. A combination of generalization and mathematical statistical methods was used to classify buildings based on construction year, form, structural type and energy-saving goals. Cluster analysis was employed to extract six typical building models.

Results demonstrate that building form complexity positively correlates with carbon emissions per unit area, while longer lifespans reduce emission intensity. Retrofitting exhibits shorter carbon payback periods (1.62–3.92 years) than rebuilding (18.7–49.94 years), indicating superior environmental performance. Pre-1986 buildings are advised for demolition/rebuilding due to limited retrofit benefits. For 1986–1995 buildings, retrofitting is recommended if structurally viable. Post-1996 buildings favor retrofitting over new construction for its shorter payback and lower emissions, enhancing long-term carbon reduction.

This study contributes to the understanding of carbon emissions in urban aged residential buildings by considering various factors and providing specific recommendations for retrofitting and rebuilding strategies tailored to different construction periods. Additionally, it highlights the importance of building form complexity and remaining lifespan in determining carbon emissions, offering insights for sustainable urban development and carbon reduction initiatives.

Indoor environmental quality (IEQ) in buildings has an impact on people’s health, productivity and comfort. Maintaining the highest possible IEQ level in complex buildings, such as health care, is difficult due to economic and organizational constraints. This study aims to categorize the vicinities in a typical health-care facility in terms of importance and criticality in relation to the various IEQ factors, as well as to develop an IEQ assessment procedure.

A comprehensive literature review, established standards and structured interviews with industrial hygiene professionals in health-care settings were used in this study. To test the applicability of the developed IEQ assessment procedure, a pilot study was conducted in an existing health-care facility.

This study categorized health-care facilities into various vicinities and discovered three respondents group had varying IEQ perceptions (facility managers, environmental health specialists and nurses). According to the findings, indoor air quality is the most important and dominant factor influencing overall IEQ in health-care facilities. The trial application of the framework shows that much work is needed to improve the level of response and readiness of facility management and occupants to allow for the effective use of the developed procedure.

Previous research did not include a detailed categorization of vicinities in health-care buildings based on IEQ requirements. The findings of this study will help to close this knowledge gap and guide facility managers and operators in recognizing the relative importance of different IEQ factors, maintaining functional requirements and identifying priorities when developing maintenance and operational procedures and allocating resources.

This study aimed to design a user-participatory methodology to investigate the post-occupancy sustainability of reused historical buildings and to apply it to a case study.

This study was designed in four stages. In the first stage, the sustainability parameters and sub-parameters were determined in the reused historical buildings based on the literature. The second stage included a field study in which the current situation of the study area was analysed, and the users were reached using the survey technique. In the third stage, the data obtained from the user participation were analysed with importance performance analysis (IPA) and an IPA matrix was created. The fourth stage included an evaluation of the results of the analysis and the development of recommendations.

IPA is a supportive method for ensuring the sustainable use of historic buildings. According to the data obtained from the IPA, it was seen that the functional sustainability of the building was achieved to a great extent. At the same time, there were deficiencies in technical and environmental sustainability. In terms of aesthetic sustainability, it was observed that the importance and performance values given by the users were generally consistent with each other.

The originality of this study is that the performance of the reused historical buildings in the process of use was monitored with appropriate parameters, and a user-participated method was proposed that allows improvement suggestions to be developed in line with the results obtained.

This proposal aims to forecast energy consumption in residential buildings based on the effect of opening and closing windows by the deep architecture approach. In this task, the developed model has three stages: (1) collection of data, (2) feature extraction and (3) prediction. Initially, the data for the closing and opening frequency of the window are taken from the manually collected datasets. After that, the weighted feature extraction is performed in the collected data. The attained weighted feature is fed to predict energy consumption. The prediction uses the efficient hybrid multi-scale convolution networks (EHMSCN), where two deep structured architectures like a deep temporal context network and one-dimensional deep convolutional neural network. Here, the parameter optimization takes place with the hybrid algorithm named jumping rate-based grasshopper lemur optimization (JR-GLO). The core aim of this energy consumption model is to predict the consumption of energy accurately based on the effect of opening and closing windows. Therefore, the offered energy consumption prediction approach is analyzed over various measures and attains an accurate performance rate than the conventional techniques.

An EHMSCN-aided energy consumption prediction model is developed to forecast the amount of energy usage during the opening and closing of windows accurately. The emission of CO₂ in indoor spaces is highly reduced.

The MASE measure of the proposed model was 52.55, 43.83, 42.01 and 36.81% higher than ANN, CNN, DTCN and 1DCNN.

The findings of the suggested model in residences were attained high-quality measures with high accuracy, precision and variance.

In this article, the aim is to document the divergences/convergences between the market perceptions of quality and the financial estimations for office buildings relative to the notion of centrality and the distance to the central business district (CBD).

Based on a hierarchical approach that decomposes and estimates the perceived quality of buildings from the stakeholders’ perspectives, we study the geographies of perceived quality measures in the Greater Paris Metropolis and compare them to the financial geography.

The perceived location quality decreases with distance from the CBD whereas judgments on the built structure and the workplace do not, exhibiting a ring-shaped pattern. The gradient of the components of the perceived quality are heterogeneous, having positive, negative or null values. Appraisers tend only to consider the quality of location in their estimations.

This article raises the issue of fair spatial judgments by appraisers and the financial market. Monocentricity is not the rule in the market perceptions of quality. It suggests that financial estimates are strongly biased, with mental representation of centrality as a judgmental heuristic.

To be able to achieve the uptake and usage of green buildings requires various actors within the construction value chain to be engaged. Despite its global uptake, green building construction is still at its nascent stage in Ghana. Most studies in sub-Saharan Africa point to the lack of knowledge as one of the mitigating factors against its development. However, there is a dearth of studies assessing the level of knowledge of stakeholders. The terms “knowledge” and “awareness” of green building construction are often used interchangeably in the Ghanaian Construction Industry (GCI). This study seeks to unearth the level of knowledge of stakeholders on green building construction through a comparative analysis of construction professionals and demand-side operators.

A structured questionnaire was issued to professionals in the various recognised bodies in the construction industry and public and private institutions in Ghana. Frequency, Kolmogorov–Smirnov test, median statistics and Mann–Whitney U-Test were used to rank and analyse the level of knowledge of stakeholders.

Construction professionals were more aware of green building construction than the demand-side operators. It was further identified that only a few of these stakeholders had hands-on experience as the majority of them have gained their awareness through research studies. Based on the findings of the study, it was revealed that the concept of green building construction is more abstract to stakeholders than practical despite their positive attitude towards its adoption.

Contextually, the study has aided in showing the level of knowledge of stakeholders on green building construction. The findings of the study aside from it aiding policymakers have also helped in identifying the perceptions and attitudes of stakeholders, their strengths and weakness in green building construction. It is recommended that due to the differences in socio-political structures and construction methods, a clear definition of green building based on the availability of resources in the GCI will encourage its adoption.

The study used two stakeholder groupings in the GCI as the unit of analysis. This enabled insightful discoveries into the knowledge-attitude gap of Ghanaian stakeholders that are driving the adoption of green building.

As laser scanning technology becomes readily available and affordable, there is an increasing demand of using point cloud data collected from a laser scanner to create as-built building information modeling (BIM) models for quality assessment, schedule control and energy performance within construction projects. To enhance the as-built modeling efficiency, this study explores an integrated system, called Auto-Scan-To-BIM (ASTB), with an aim to automatically generate a complete Industry Foundation Classes (IFC) model consisted of the 3D building elements for the given building based on its point cloud without requiring additional modeling tools.

ASTB has been developed with three function modules. Taking the scanned point data as input, Module 1 is built on the basis of the widely used region segmentation methodology and expanded with enhanced plane boundary line detection methods and corner recalibration algorithms. Then, Module 2 is developed with a domain knowledge-based heuristic method to analyze the features of the recognized planes, to associate them with corresponding building elements and to create BIM models. Based on the spatial relationships between these building elements, Module 3 generates a complete IFC model for the entire project compatible with any BIM software.

A case study validated the ASTB with an application with five common types of building elements (e.g. wall, floor, ceiling, window and door).

First, an integrated system, ASTB, is developed to generate a BIM model from scanned point cloud data without using additional modeling tools. Second, an enhanced plane boundary line detection method and a corner recalibration algorithm are developed in ASTB with high accuracy in obtaining the true surface planes. At last, the research contributes to develop a module, which can automatically convert the identified building elements into an IFC format based on the geometry and spatial relationships of each plan.

Smart libraries are the result of the application of smart technologies in the era of digital intelligence. The establishment and improvement of its service evaluation system serve as indicators for evaluating the growth of smart libraries.

This study introduces and improves the capability maturity model (CMM), creatively constructs a service maturity model specifically designed for smart libraries and combines the Delphi method with the analytic hierarchy process (AHP) to establish a service maturity evaluation system for smart libraries while calculating indicator weights. Finally, two representative smart libraries are selected as case studies, and an empirical application is conducted using the fuzzy comprehensive evaluation method.

The empirical study shows that the developed smart libraries service maturity evaluation system holds significant theoretical and practical value in evaluating smart libraries.

Enhances the CMM and creatively constructs a service maturity model for smart libraries. Combines the Delphi method with AHP to establish a service maturity evaluation system while calculating indicator weights. Uses a fuzzy comprehensive evaluation method to evaluate two representative smart libraries. Demonstrates that the smart library services maturity evaluation system holds significant theoretical and practical value.

Determining the suitable material and accurate thickness of the thermal insulation layer used in exterior walls during the design phase of a building can be challenging. This study aims to determine suitable material and optimum thickness for the insulation layer considering both operational and embodied factors by a comprehensive assessment of the energy, economic and environmental (3E) parameters.

First, the energy model of an existing building was created by using Autodesk Revit software according to the as-built floor layout to evaluate the impact of five alternative insulating materials in varying thickness values. Second, using the results derived from the model, a thorough evaluation was conducted to ascertain the optimal insulation material and thickness through individual analysis of 3E factors, followed by a comprehensive analysis considering the three aforementioned factors simultaneously.

The findings indicated that polyurethane with 13 cm thickness, rockwool with 10 cm thickness and EPS with 20 cm thickness were the best states based on energy consumption, cost and environmental footprint, respectively. After completing the 3E investigation, the 15-cm-thick mineral wool insulation was presented as the ideal state.

This study explores how suitable material and thickness of insulating material can be determined in advance during the design phase of a building, which is a lot more accurate and cost-effective than applying insulating materials by assumed thickness in the construction phase.

To the best of the authors’ knowledge, this paper is unique in investigating the advantages of using thermally insulating materials in the context of a mosque structure, taking into account its distinctive attributes that deviate from those of typical buildings. Furthermore, there has been no prior analysis of the cost and sustainability implications of these materials concerning the characteristics of subtropical monsoon climate.

This systematic literature review investigates the contribution of design thinking (DT) as a process and tool to drive innovation in a sustainable built environment (SBE) and develops a new model for sustainability research integrating DT and future thinking approaches toward achieving a unified DT and foresight notion for future research and applications.

This review was based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. Open-access English articles published between 2000 and 2022 identified using the EBSCOhost, Emerald Insight, DOJA, JSTOR, Scopus and Taylor and Francis database searches were reviewed. The review framework deploys a previously proposed modified Ansoff matrix with an integrated innovation matrix to identify and analyze the challenges and opportunities for innovation growth in SBE. Additionally, a citation analysis was conducted to explore the impact of DT for innovation in SBE, and a proposed framework based on design by drawing on foresight theory was developed.

Research on DT for innovation in SBE faces the challenge of unanticipated impacts. According to the average number of citations per document, innovation associated with new solutions within a new context seems to become highly influential. Additionally, research gaps exist in the integration of foresight and DT into sustainability research to identify new contexts and solutions to SBE. A model of foresight design thinking (FDT) is proposed to guide future research and support the practical application of DT in sustainability.

This analysis was limited by the selection criteria as only certain keywords were used and English-only articles were selected. Future research should consider the use of DT for innovation in SBE using various important keywords, which would improve research findings and expand the contribution of DT to SBE.

The FDT model offers a new holistic framework for the iterative process of reframing and reperception, focusing on divergent and convergent thinking with the goal of contributing to SBE practices.

The integrated framework of DT and foresight can contribute to the study and development of sustainable innovation and a strategic shift toward a sustainable society.

The integration of DT, foresight and sustainability can broaden the horizons of sustainability research by systematically addressing future challenges related to SBE, which can be translated into feasible and innovative solutions. Thus, the FDT model complements the application of DT in sustainable innovation in this research field.