The circular economy in the construction sector in emerging economies is one of the most promising concepts that aims to keep the value of the construction materials and structures as long as possible. The construction industry is rapidly developing in Kazakhstan with a yearly increase in projects. This research paper investigates the construction sector in Kazakhstan in terms of the potential application of circular economy principles by local stakeholders—clients, contractors, designers, and manufacturers. As limited research has been conducted on the circularity within the construction environment, including construction parties, this paper aims to fill this research gap. It seeks to identify the construction trends and perform a barrier and opportunity analysis to develop circular economy principles in the construction sector. As a research method, PEST is used for the study of local construction trends. At the same time, stakeholders are interviewed using semi-structured surveys organized according to the ReSOLVE framework (regenerate, share, optimize, loop, virtualize, and exchange) to identify the barriers and opportunities for circular economy in the construction sector. As an outcome of this study, the most common barriers and opportunities were associated with the economic benefit factor, as this was the main motivation for the stakeholders to save construction materials for reuse or to refuse more eco-friendly technologies. Additionally, policy recommendations for companies involved in the construction ecosystem were provided according to the assessment of found barriers and opportunities in the context of the ReSOLVE framework. This analysis has shown that for most stakeholders of the Kazakhstani construction sector, virtualization is of the highest priority; therefore, opportunities for its development are recommended. Future research could focus on the development of economically feasible solutions for the circular economy in construction with the inclusion of virtualization technologies.

Microbial Fuel Cell (MFC) is a bio-electrochemical system that generates electricity by anaerobic oxidation of substrates. An anode is the most critical component because the primary conversion of wastewater into electrons and protons takes place on the surface of the anode, where a biofilm is formed. This paper describes the essential properties of the anode and classifies its types according to the material used to make it. Anode material is responsible for the flow of electrons generated by the microorganism; hence biocompatibility and conductivity can considered to be the two most important properties. In this paper, the various modification strategies to improve the performance of anodes of MFC are explained through the review of researchers’ published work in this field. The shape and size of the anode turned out to be very significant as the microbial growth depends on the available surface area. The attachment of biofilm on the surface of an anode largely depends on the interfacial surface chemistry. Methods for improving MFC performance by altering the anode material, architecture, biocompatibility, and longevity are discussed with a future perspective giving special importance to the cost.

This review explores recent advancements in hydrogen gas (H₂) safety through the lens of artificial intelligence (AI) techniques. As hydrogen gains prominence as a clean energy source, ensuring its safe handling becomes paramount. The paper critically evaluates the implementation of AI methodologies, including artificial neural networks (ANN), machine learning algorithms, computer vision (CV), and data fusion techniques, in enhancing hydrogen safety measures. By examining the integration of wireless sensor networks and AI for real-time monitoring and leveraging CV for interpreting visual indicators related to hydrogen leakage issues, this review highlights the transformative potential of AI in revolutionizing safety frameworks. Moreover, it addresses key challenges such as the scarcity of standardized datasets, the optimization of AI models for diverse environmental conditions, etc., while also identifying opportunities for further research and development. This review foresees faster response times, reduced false alarms, and overall improved safety for hydrogen-related applications. This paper serves as a valuable resource for researchers, engineers, and practitioners seeking to leverage state-of-the-art AI technologies for enhanced hydrogen safety systems.

The authors compare the energy consumption and CO₂ emissions from vehicles using internal combustion engines (ICE), battery electric vehicles (BEV), fuel cell electric vehicles (FCEV), and two types of hybrid vehicles, BEV-ICE hybrid and BEV-FCEV hybrid. This paper considers several scenarios for four countries’ electricity production from primary energy sources to estimate total CO₂ release. Energy consumption of the vehicle per 100 km, emissions during manufacturing, battery production, and lifecycle of the vehicle are considered in the total amount evaluation of CO₂ released. The results show that with current technologies for battery manufacturing, and a significant proportion of national grid electricity delivered by fossil fuels, BEV is the best choice to reduce carbon emissions for shorter driving ranges. In the case of electricity generation mainly by low-carbon sources, FCEV and BEV-FCEV hybrid vehicles end up with lower carbon dioxide emissions. In contrast, with electricity mainly generated from fossil fuels, electric vehicles do not reduce CO₂ emissions compared to combustion cars.