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This paper investigates the feasibility of using the emission intensity of low‐pressure argon and nitrogen gas discharges as the sensing mechanism for a microwave electric field optical sensor probe in microwave resonant cavities. The emission is coupled to a photodiode for detection through an optical fibre due to the difficulty in using conventional optoelectronic devices in close proximity to microwave cavities. The discharge emission intensity is monitored at a range of different input powers to the cavity. The proposed designs for the electric field sensing probe are also included.

The purpose of this study is toward a better understanding of the interplay between the design and the operation under uncertainties of a simple distributed energy system (DES), by analyzing the sensitivity of the operation strategy over the size of the assets.

A two-step framework is developed in this work: first, the equipment sizes are obtained solving an integrated design approach where an operation strategy F^d is embedded in a design loop; then, once the sizes have been fixed, the DES is evaluated with an operation strategy F^a (which can be the same as F^d). The operation strategies F^d and F^a are not necessarily the same, so the objective of the paper is to study the interplay between the design and the operation by varying the optimality level of the operation strategies in both phases.

The results show that the design of DES cannot be approached without considering its close relationship with the operation strategy. Indeed, the design method needs to be chosen according to the performance of the operation policy finally used in real life: no matter if the operation strategies are the same in both phases but they must lead to a similar level of optimality in terms of operating performance.

The originality of this work is to shed light on the importance of the operation strategy in the design procedure as it seems rarely addressed, to the best of the authors’ knowledge, in the literature. Indeed, most of the paper dealing with stochastic design of DES solves single large two-stage problems without discussing the way power flows are finally controlled in real life. The optimal design and operation of DES is rarely addressed conjointly, this study aims at bridging the gap between these two isolated scientific communities.

This paper reviews extant studies on bioclimatic architecture with a view of revealing the focus areas of past studies and mapping out future research directions useful in achieving building energy efficiency.

A mixed-method systematic review that integrates quantitative and qualitative analysis was adopted. The bibliographic data were extracted from the Scopus database, and a scientometric analysis was conducted to analyse the data quantitatively. Qualitative content analysis is then presented, which provided a basis for mapping out trends and gaps in current knowledge.

It is observed that there has been a rise in the number of studies on bioclimatic architecture over the last two decades. Past studies have focused on sustainability, building performance simulation, building climatology and energy use, solar energy applications and passive cooling. Artificial intelligence, algorithm coupling and acoustic comfort were some of the emerging areas discovered in this study.

The study reveals research gaps that researchers can investigate.

The information provided can help the building industry stakeholders in decision-making. It serves as a guideline for maximising the potential benefits of adopting bioclimatic designs in the building industry. Furthermore, it provides references that aid policy formulation for government agencies and corporate organisations.

The study fills the literature gap caused by the need for a holistic literature review that relates bioclimatic architecture and its energy efficiency implications. It is also the first study on bioclimatic architecture that adopts a mix of scientometric and qualitative analysis for analysing past studies on bioclimatic architecture.

The purpose of this paper is to use an index decomposition analysis to investigate the driving forces of China’s CO₂ emissions related to fixed asset investments from 2003 to 2015.

This paper uses an index decomposition analysis to investigate the driving forces of China’s CO₂ emissions related to fixed asset investments from 2003 to 2015. To make policy recommendations, this paper identifies three effects. An approach to calculating energy-relevant CO₂ emissions is also presented.

The results suggest that the amount of CO₂ emissions related to fixed asset investments increased during the entire period. The social and economic effect played a major role in promoting carbon emissions, followed by the fixed asset effect. Therefore, the activity factor was the dominant positive factor, followed by the construction factor. The negative element was the energy effect, in which the energy intensity factor played an important role in reducing emissions, followed by the structural factor. Moreover, the carbon intensity factor might be a potential inhibitory force in reducing carbon emissions.

A steady financial policy, relaxed family planning, sustainable urbanization, strategy of innovation-driven development, reform of scientific and technological structures, development of science and technology and exploration of new energy sources are proposed to mitigate carbon emissions from fixed asset investments. The conclusion also provides a reference for developing countries in similar situations.

This paper uses an index decomposition analysis to investigate the driving forces of China’s CO₂ emissions related to fixed asset investments from 2003 to 2015. To make policy recommendations, this paper identifies three effects. An approach to calculating energy-relevant CO₂ emissions is also presented.

Building energy benchmarking is required for adopting an energy certification scheme, promoting energy efficiency and reducing energy consumption. It demonstrates the current level of energy consumption, the value of potential energy improvement and the prospects for additional savings. This paper aims to create a new data envelopment analysis (DEA) model that overcomes the limitations of existing models for building energy benchmarking.

Data preparation: the findings of the literature search and subject matter experts’ inputs are used to construct the DEA model. Particularly, it is ensured that the included variables would not violate the fundamental assumption of DEA modeling, DEA convexity axiom. New DEA formulation: controllable and non-controllable variables, e.g. weather conditions, are differentiated in the new formulation. A new approach is used to identify outliers to avoid skewing the efficiency scores for the rest of the buildings under consideration. Efficiency analysis: three distinct efficiencies are computed and analyzed in benchmarking building energy: overall, pure technical, and scale efficiency.

The proposed DEA approach is successfully applied to a data set provided by a utility management and energy services company that is active in the multifamily housing industry. Building characteristics and energy consumption of 124 multifamily properties in 15 different states in the USA are found in the data set. Buildings in this data set are benchmarked using the new DEA energy benchmarking formulation. Building energy benchmarking is also conducted in a time series manner showing how a particular building performs across the period of 12 months compared with its peers.

The proposed research contributes to the body of knowledge in building energy benchmarking through developing a new outlier detection method to mitigate the impact of super-efficient and super-inefficient buildings on skewing the efficiency scores of the other buildings; avoiding ratio variables in the DEA formulation to adhere to the convexity assumption that existing DEA methods do not follow; and distinguishing between controllable and non-controllable variables in the DEA formulation. This research contributes to the state of practice through providing a new energy benchmarking tool for facility managers and building owners that strive to relatively rank the energy-efficiency of their properties and identify low-performing properties as investment targets to enhance energy efficiency.

An indoor office space should not only provide adequate illuminance on horizontal planes but also cater to the physiological and psychological requirements of the occupants. This paper aims to describe a lighting simulation-based work conducted in Kolkata, India which modeled an indoor office to investigate the effects of variation in room surface reflectance combinations on user perception, mean room surface exitance (MRSE), average horizontal illuminance and overall uniformity of horizontal illuminance.

A fluorescent illumination system–based office space was modeled and retrofitted with tubular LED lamps in DIALux. Simulations were conducted for 16 different room surface reflectance combinations and a five-point Likert scale-type survey questionnaire was formulated to conduct a survey with 32 test subjects to assess the subjective preferability of each resultant light scene.

Simulation results demonstrate that the relationship between average horizontal illuminance and MRSE as well as between average horizontal illuminance and overall uniformity of horizontal illuminance, was statistically significant (p < 0.001). In the conducted survey, the resultant light scene arising out of the reflectance combination of wall:ceiling:floor = 60%:90%:20% was the most well-received one with 187 convinced agreements (“agree” and “strongly agree” responses).

This work found strong linear correlation between average horizontal illuminance and MRSE and between average horizontal illuminance and overall uniformity. A five-point Likert scale-type survey questionnaire with seven questions was formulated and validated with 32 test subjects (Cronbach’s alpha > 0.9295), which showed that the wall:ceiling:floor reflectance combination of 60%:90%:20% was the most favored choice.

Human activities in recent years with the excessive emission of greenhouse gases have had a negative impact on increasing global temperatures. In this regard, one of the best ways to control it is to move toward sustainability with more use of renewable energy. Therefore, this study aims to assess the indicators of sustainable energy, explore benefits of sustainable energy and evaluate strategies to enhance energy sustainability in line with Sustainable Development Goal (SDG) 7.

Quantitative research strategy was adopted. Questionnaires were developed and administered through convenience and snowball sampling techniques to professionals in the energy sector. Data collected was validated by using Cronbach’s alpha coefficient and discriminant validity, whereas objectives were analyzed by using the relative importance index, mean score ranking and Kruskal–Wallis test.

From the findings, the significant indicators of sustainable energy were as follows: reduction in greenhouse gas emissions from energy production, use of renewable energies and policies on proper utilization of energy resources. Furthermore, a reduction in greenhouse gas emissions, less harm caused to the environment and an increase in the economic and social development process were the major benefits of sustainable energy. Finally, the findings of the study revealed that a strong and accounted policy program, adopting sustainable energy indicators and strategic communication are the significant strategies needed to be put in place to enhance energy sustainability.

The study serves as a reminder to policymakers of the crucial role they have to play in enhancing energy sustainability by putting in place suitable policy programs and methods.

The originality of this study is that it is arguably a pioneering study in Ghana and contributes to the body of knowledge on energy sustainability.

The importance of sustainability in architecture currently necessitates the integration of innovative teaching strategies on the subject into architecture programs. This study aims to introduce and examine peer learning pedagogy by peer tutoring to educate architecture students in sustainable design.

Based on class assignments proposed in two different architecture sustainability-focused courses in the second and fourth years of the Bachelor of Science in architecture program, a total of 103 students assessed the proposed peer learning experience and its impact on their sustainability mindsets and education. Subjective surveys for evaluating the peer learning experience were designed and delivered at different stages of the course sequences. A total of 502 survey responses were obtained in the study.

The qualitative and quantitative data analysis confirms that the proposed peer learning by peer tutoring increased students’ knowledge, motivation and commitment to sustainable design. In addition, participants became more confident in applying sustainable design skills and their academic grades improved more than 25% compared to previous courses using traditional teaching methods.

Traditional architecture education has long been criticized for their pedagogical methodologies based primarily on passive learning. Recently, these programs have begun to prepare students to become active learners and communicators in collaborative and multidisciplinary environments. A mixed-method approach of combining pre-/post-experience surveys and analysis of final grades was used to determine the level of success and the quantifiable behavior change delivered by students involved in this peer learning experience.

This paper aims to shed some light on the distribution of population, living in disaster risk areas in Brazil, on the intra-urban scale. The following three aspects are evaluated in this paper: the distribution of exposed population according to municipal size classification; the population density in disaster risk areas; and the municipal human development classification for the municipalities with disaster risk areas.

This research is based on an explorative approach. The main database used is a result of the association of landslide and flood risk areas to demographic census, available for 825 Brazilian municipalities. Additional databases were integrated to characterize disaster risk management and municipal human development.

The results revealed that the population exposed to disaster areas is concentrated within the capitals and small cities in the country. Moreover, disaster risk areas are densely populated even in small cities, suggesting that it is a reality faced not only by the larger cities. Finally, disaster risk areas exist even inside municipalities with a high level of human development.

These findings could contribute to the understanding of the spatialisation of disaster risk in Brazil, a primordial step for the reduction of human losses.

A novel perspective about the Brazilian population exposed to disaster risk was obtained, revealing a current issue faced by the municipalities independent of the size classification and level of human development.