Promote Energy Efficiency Research Articles

Eco-Sustainable Building Materials in Cameroon: Straw in Contemporary Architecture

The construction industry in Cameroon is facing increasing pressure to adopt more sustainable practices to mitigate environmental degradation and promote energy efficiency. This article explores the potential of straw as an eco-sustainable building material, particularly in the context of contemporary architecture in Garoua- Cameroon. Straw, a renewable resource, offers several benefits, including low embodied energy, excellent thermal insulation, and local availability, making it an ideal material for sustainable construction in the region. This article reviews global examples of straw-based architecture, examines the advantages and challenges of using straw in construction, and proposes practical applications for straw in Cameroon. Finally, it discusses the implications of adopting eco-sustainable practices in the country’s construction industry and highlights the need for updated building regulations and training programs to support the wider use of alternative building materials.

Strategic carbon emission assessment in sludge treatment: A dynamic tool for low-carbon transformation

The carbon–neutral target presents a significant challenge for the sewage sludge treatment and disposal (SSTD) industry, necessitating strategic planning for a low-carbon transition. However, flexible and comprehensive carbon emission analysis tools to support this goal remain lacking. This study presents a carbon emission analysis tool to evaluate the carbon emission characteristics and future mitigation potentials of SSTD. The tool integrates life cycle inventory (LCI) modeling-based analysis, sensitivity analysis, regression analysis, and scenario analysis. Carbon emissions are dynamically calculated based on sludge properties, technological level, and industry external parameters, providing a foundation for adaptable evaluation tailored to local conditions. The framework considers the potential effects of multi-parameter and multi-aspect changes in scene design, both within and outside the industry, to achieve dynamic and comprehensive simulations. A case study conducted in Wuhan, China, demonstrated the usability and application processes of the framework. The results indicated that carbon emissions from SSTD are projected to more than double from 2021 to 2060 without interventions. Among the mitigation measures, energy and chemical savings would yield the largest reduction potential, followed by the technical layout adjustment and the promotion of energy efficiency. Operational optimization in the sludge industry and outside the industry would contribute the least. With all mitigation measures applied, emissions could decrease to –82.91 kt CO2-eq in 2060, equivalent to 13.03% compensation for emissions from the sewage treatment line. Among all the processes, incineration routes are recommended due to their current and future low carbon emissions. The cooperative resource route of anaerobic digestion and land use also shows promise as it progressively demonstrates superior performance with increasing organic matter and nutrient content of sludge. Critical factors, sub-processes, and emission types for different routes were identified and can be optimized accordingly. The developed method demonstrates sufficient flexibility to be applied to other cities and larger-scale regions, thereby offering technical and strategic support for SSTD towards carbon–neutral operation.

Study on steam energy efficiency enhancement, cost management and CO2 emissions in the food industry

Malaysia’s energy intensity per unit GDP has been increasing since the 1990s, leading to the government’s efforts to promote energy efficiency via policies and initiatives such as Energy Performance Contracting (EPC). Additionally, the industrial sector in Malaysia consumed 28% of total final energy in 2018, placing it as the country’s second-largest final energy consumer [1]. This case study focuses on improving energy efficiency in the steam system of an existing plant in the food industry in Malaysia. This work was performed in collaboration with a local Energy Service Company (ESCO) to study the existing steam system, recognize its process requirements and constraints and consequently propose and evaluate retrofit opportunities. These opportunities were evaluated across 3 performance parameters (power output or energy savings, cost savings and CO2 emissions savings). Simulations were performed using the Steam System Modeler Tool (SSMT). The study found that Combined Heat and Power (CHP) was not feasible due to a combination of low steam pressure and flowrate available in the system. However, the study also found that improving condensate recovery coupled with condensate flashing from the high pressure to low pressure header offered the highest increments in overall performance.

Theoretical Analysis of a Novel Rock Wall to Limit Heating Demands in Historical Buildings

In the near future, the building sector will continue to absorb the greatest share of primary energy worldwide. It is necessary to find innovative solutions that promote energy efficiency through renovation measures, especially in historical buildings, for which refurbishment is constrained by several issues. In this study, we propose a novel Trombe Wall configuration that is easily integrable and based on a rock wall made of caged stone to use as a thermal accumulator. The system was investigated preliminarily using a transient Finite Difference Method (FDM) code to analyse the temperature field inside the rock wall. Successively, FDM results were employed as input data in TRNSYS simulations to determine the savings achievable in thermal heating requirements. The results demonstrated that the proposed solution, in the considered climate and on a reference historic building, can produce monthly heating savings varying between 26% and 85%. So, the rock wall results in a reliable solution for buildings in which refurbishment is difficult, allowing for preserving aesthetic features and improving energy efficiency by rationally using solar radiation.

Improved GA-LNS Algorithm for Solving Vehicle Path Problems Considering Carbon Emissions

Logistics, as a significant field for achieving energy-saving and carbon reduction goals, is recognized as a crucial direction for realizing the global “double carbon” objective, while vehicle path optimization is an effective method for promoting energy efficiency and reducing carbon emissions. In this paper, an improved genetic algorithm is proposed for optimizing logistics and distribution paths concerning the carbon emissions of fuel vehicles throughout the logistics and distribution process, and a low-carbon logistics and distribution path model is constructed based on time windows, vehicle loading, and carbon emissions. The INNC method is adopted to initialize the population, and an enhanced genetic algorithm (GA-LNS) is designed to solve the model in conjunction with a large-scale neighborhood vector search algorithm. The results indicate that the initialization of the population using the INNC method produces a higher-quality initial solution. Compared to traditional genetic algorithms and particle swarm optimization, the GA-LNS algorithm exhibits superior robustness, effectively addressing the limitations of traditional genetic algorithms that rely on initial solutions and are prone to local optima. By comparing the computational results of the low-carbon logistics distribution path model constructed in this study with those of traditional optimization objective models, it is demonstrated that this model effectively balances the trade-offs between objectives and benefits, achieving the lowest total logistics distribution cost while promoting sustainable low-carbon logistics. The research findings provide a theoretical foundation for optimizing logistics vehicle paths and formulating energy-saving and carbon reduction implementation plans in China.

Construction 5.0 and Sustainable Neuro-Responsive Habitats: Integrating the Brain–Computer Interface and Building Information Modeling in Smart Residential Spaces

This study takes a unique approach by investigating the integration of Brain–Computer Interfaces (BCIs) and Building Information Modeling (BIM) within residential architecture. It explores their combined potential to foster neuro-responsive, sustainable environments within the framework of Construction 5.0. The methodological approach involves real-time BCI data and subjective evaluations of occupants’ experiences to elucidate cognitive and emotional states. These data inform BIM-driven alterations that facilitate adaptable, customized, and sustainability-oriented architectural solutions. The results highlight the ability of BCI–BIM integration to create dynamic, occupant-responsive environments that enhance well-being, promote energy efficiency, and minimize environmental impact. The primary contribution of this work is the demonstration of the viability of neuro-responsive architecture, wherein cognitive input from Brain–Computer Interfaces enables real-time modifications to architectural designs. This technique enhances built environments’ flexibility and user-centered quality by integrating occupant preferences and mental states into the design process. Furthermore, integrating BCI and BIM technologies has significant implications for advancing sustainability and facilitating the design of energy-efficient and ecologically responsible residential areas. The study offers practical insights for architects, engineers, and construction professionals, providing a method for implementing BCI–BIM systems to enhance user experience and promote sustainable design practices. The research examines ethical issues concerning privacy, data security, and informed permission, ensuring these technologies adhere to moral and legal requirements. The study underscores the transformational potential of BCI–BIM integration while acknowledging challenges related to data interoperability, integrity, and scalability. As a result, ongoing innovation and rigorous ethical supervision are crucial for effectively implementing these technologies. The findings provide practical insights for architects, engineers, and industry professionals, offering a roadmap for developing intelligent and ethically sound design practices.

Prioritizing sustainability indicators for Uganda's built environment: Expert perspectives using the Delphi technique

The growing emphasis on energy efficiency within the built environment, driven by global concerns over climate change, has resulted in notable shifts in building energy consumption patterns. Achieving reductions in building energy use and CO₂ emissions through sustainable strategies necessitates the development of country-specific policies. While numerous energy assessment tools are available internationally, they often lack contextual relevance for Uganda and many Sub-Saharan African countries.Therefore, there is a pressing need for a tool tailored to Uganda's distinct climatic conditions. This study aimed to identify key building sustainability indicators to promote energy efficiency in Ugandan buildings. Utilizing the Delphi Technique, experts from academia, construction, energy consulting, and government agencies evaluated 35 building indicators over two assessment rounds. The consensus among experts was validated using the Interrater Agreement, with a significant Kendall's W value exceeding 0.6, rising from 0.655 in the first round to 0.704 in the second. Construction consultants showed the highest W value (0.77) in the second round, followed by energy consultants (0.74), while academicians had the lowest (0.7). The Chi-square test demonstrated strong agreement in ranking indicators across 34 degrees of freedom. The most significant indicators identified include "B20 - Optimization of energy use," "B8 - Advanced design and construction technology," and "B27 - Natural ventilation design," among others. The Delphi Technique was instrumental in achieving expert consensus, while interrater agreement was used to validate and ensure the reliability of the findings. The developed framework provides critical insights for policymakers, practitioners, and researchers seeking to advance energy efficiency and sustainability within Uganda's built environment.

Evaluation of aerial thermography for measuring the thermal transmittance (U-value) of a building façade

In efforts to mitigate greenhouse gas emissions in the construction sector, policies promoting energy efficiency improvements in existing buildings are being implemented. Accurately assessing the impact of energy retrofit strategies requires precise determination of thermal envelope performance through energy audits. Aerial thermography, employing unmanned aerial vehicles (UAVs) equipped with infrared thermal cameras (IRT), is an underused method overcoming limitations in energy audits of large buildings or complexes. This approach offers an elevated perspective, providing an overview of the building’s thermal patterns, aiding in the identification of thermal envelope defects. By measuring temperature distribution, even in inaccessible envelope areas, the severity of identified defects can be estimated. Beyond detecting thermal bridges, air leaks, and moisture, aerial thermography is valid for estimating thermal transmittance (U-value) of enclosures. The aim of this research is to evaluate this method to calculate the U-value of the façade of an university building located in a Subtropical Mediterranean climate, during a typical full day in different seasons of the year. Concurrently with aerial thermography, the thermometric method (THM) was applied to compare results and refine the operational conditions during U-value measurement using different statistical indices and uncertainty analysis. The results demonstrated the validation of airborne thermography as a method for U-value calculation under specific meteorological and operational conditions, overcoming the common physical limitations of traditional building audit methods.

Designing and multi-objective optimization of a novel multigenerational system based on a geothermal energy resource from the perspective of 4E analysis

Over the past few years, a growing emphasis has been placed on providing sustainable energies to reduce carbon emissions and promote energy efficiency. This paper delved into energy, exergy, exergoeconomic, and exergoenvironmental investigation for a system that combines the Kalina cycle, a double-effect absorption chiller with a vapor compression refrigeration system coupled with an air handling unit driven by a geothermal renewable energy resource. This innovative system generated four distinct outputs: electricity, potable water, cooling load, and hot water. Key system performance variables, such as net power output, coefficient of performance, sum unit cost of the product, energy and exergy efficiencies, the temperature of supply air to the cold store, and potable water production in the base mode, are measured at 63.45 kW, 0.83, 56.74 $/GJ, 62.28 %, 45.67 %, 268.7 K and 20.82 lit/h, respectively. This research explored the impact of various parameters on the output variables, the exergy destruction and environmental impact rate of all components, and the net percent value of the proposed system. The multi-objective optimization significantly improved energy and exergy efficiencies by 6.83 % and 1.8 % from its base mode. Exergy and exergoenvironmental analysis revealed that the highest exergy destruction occurs in Re-injection, and the highest environmental impact rate associated with exergy belongs to the HPG component. Moreover, the geothermal section has the largest share of exergy destruction, approximately 58.5 % of the total exergy destruction of the system.

Development of a georeferenced atlas of energy renovation in residential buildings using GIS tool

Abstract This paper presents a method for modelling the energy needs for heating the residential building stock on a macro scale. The method is based on the use of Geographic Information Systems (GIS) tools to manage various existing geolocalised databases and the collection of field data. It combines the calculation of energy demand with the estimation of solar gains received by the building envelope. In order to estimate the heat energy balance, a description of the building geometry is necessary. The geometrical characteristics of the envelope are extracted from the building entities information available in the spatial database. These parameters are then enriched and cross-referenced with other data gathered from the government’s complex taxation files. The TABULA buildings typology was chosen because it is an exhaustive European classification adapted for use in GIS utilities. The objective of this work is to produce a georeferenced atlas that can identify potential energy savings on large zones, such as urban areas. An understanding of energy consumption at this scale is crucial for the effective management of massively scaled energy-saving solutions. The atlas will promote energy efficiency in the residential sector and guide environmental policy measures by identifying priority areas for renovation.

Green fitness tech: A self-powered device for monitoring treadmill metrics

This research presents the development of a self-powered device designed to monitor treadmill metrics, including speed, distance covered, and calories burned, without requiring external power sources. The purpose of this study is to provide a cost-effective and sustainable alternative to conventional treadmill tracking systems that are often expensive and energy-dependent. The device utilizes an Arduino Nano microcontroller, a DC motor functioning as a generator, an TFT display, and an encoder to sense motor speed and position. Experiments demonstrated the system’s ability to accurately capture and display treadmill data in real-time, powered solely by the kinetic energy generated from treadmill operation. Significant findings highlight the system's capacity to reduce power consumption and operational costs while maintaining performance comparable to more expensive integrated tracking systems. The conclusions drawn from this study suggest that the proposed device not only promotes energy efficiency but also offers a practical, low-cost solution for enhancing the fitness experience, making it an attractive alternative for both personal and commercial treadmill applications.

Energy Efficiency and Sustainability in Food Retail Buildings: Introducing a Novel Assessment Framework

One of the primary global objectives is to decrease building energy consumption to promote energy efficiency and environmental sustainability. The large-scale food retail trade sector accounts for over 15% of total primary energy consumption in Europe, posing a significant challenge to the transition towards green energy. This study proposes a simple method for energy efficiency, environmental sustainability, and cost-saving assessment and improvement in large-scale food retail trade buildings. It aims to analyze the energy and environmental performance of building–plant systems, establishing an interactive network to assess intervention potential for the energy transition. The investigation focuses on the proper selection and analysis of the benefits of retrofit solution implementation, emphasizing potential energy savings in current and future climate change scenarios. Dynamic simulation with the Building Energy Model (BEM) was used to evaluate the impacts of building–plant system retrofit solutions, such as high thermal insulation, photovoltaic (PV) panels, Light Emitting Diode (LED) installation, waste heat recovery, and improvement in refrigeration units. The results show a reduction in annual energy consumption for the PV panel installation by up to 29% and lighting systems with high-quality LED to 60%. Additionally, CO2 emissions can be decreased by up to 41% by combining these two strategies.

Thermal performance and Feasibility Study Using a Straw-Based Thermal Insulation in Geothermal systems

Straw is the part of the stem (or stubble) of certain grasses, known as "straw cereals", and is most often a by-product or waste product of cereal production. In northern Algeria, it is produced in all cereal growing regions. It is generally used for animal feed. In this study, straw waste is used as a bio-material for thermal insulation in bioclimatic constructions and especially in geothermal applications, and the thermal insulation needs in a geothermal system is discussed. Furthermore, thermal performance of wheat straw aggregates bio-based material is tested for several thicknesses until stable results are achieved, using conduction heat transfer tests or heating flat plate. This method is based on the temperature difference measuring across the sample (inlet and outlet) and finally, compared it with other commercial geothermal insulation materials. Obtained results give us an idea of the energy gains to be expected from the bio-based materials manufacture to be used in geothermal systems comparing to conventional materials. It is noted that, the optimum thickness of the insulation material based on straw is 2cm, giving a temperature gradient around 9°C versus 16°C for conventional materials. Straw organic waste material is a promising candidate as an alternative insulating material for low-carbon and green buildings targets. Which are in line with the objectives set by the Algerian government as part of the fight against climate change, in particular the development of renewable energies, the promotion of energy efficiency as well as clean technologies and waste recycling.

Integrating artificial intelligence for optimal thermal comfort: A design approach for electric heating textiles aligned with user preferences

Human thermal comfort, crucial for well-being and productivity, is often improved by personal comfort systems that offer tailored control over environmental conditions while promoting energy efficiency. Previous studies have explored various textile technologies in thermoregulation systems according to user preferences. However, limited research has focused on temperature prediction by artificial intelligence to maximize thermal comfort for varied users. This study proposes a design approach to optimize thermal comfort in electric heating textiles using artificial intelligence, considering user preferences related to age and gender differences. A fuzzy logic model is established as a proof of concept for temperature regulation by varying ambient temperature, followed by developing an artificial neural network model to predict the optimal temperature for maximum comfort. Subsequently, a smart electric heating jacket is fabricated to assess preferred heating temperatures among 50 subjects with varying ages and genders. Results from the artificial neural network model show promising temperature prediction, while subject tests reveal significant differences in skin temperatures based on gender. This emphasizes the need for artificial intelligence-based heating e-textiles to accommodate diverse user needs. The study’s findings are expected to contribute to intelligent temperature regulation in thermal textiles and wearables, benefitting both the industry and consumers through customized heating products.

A Novel Method for Optimising Energy Efficiency in High-Performance Computing Systems

This paper introduces a new method to promote energy efficiency in computing systems. The rapidly growing demand for computational power in high-performance computing (HPC) systems is accompanied by a significant increase in energy consumption. This research investigates the many ways to minimise energy consumption in HPC systems without sacrificing computational performance. Building upon previous research we combined and refined ideas to develop an optimised approach. Our method utilises a tri-modular framework incorporating an Energy-Efficient Hardware Design, Resource Management, and Optimisation, and Server Virtualisation. The first module employs a method of designing smart energy-efficient hardware. This method incorporates leakage reduction techniques such as clock gating and sleep states. The second module uses a technique focused on optimising server software. This method is based on Dynamic Voltage and frequency scaling (DVFS) for power management in data centres. The third module is based on server virtualisation and employs software to create multiple virtual machines on a single physical server allowing for a significant reduction in energy and hardware costs. The methods used in these three modules are systematically integrated to produce a more efficient consumption of electricity. This will allow for the computing system to minimise energy consumption without compromising computational power.

Energy efficiency and greenhouse gas emissions: A panel ARDL model of top five emitters in Africa

The Paris Agreement has mandated drastic decarbonization by developed and developing economies. Many of the top African emitters are now exploring drastic restructuring of the production processes in a way that promotes energy utilization efficiency. This is critical for ensuring an environmentally benign growth process. This study presents a unique addition to the body of existing knowledge by analysing the effect of some indicators of energy efficiency on three indicators of environmental quality among the top five emitters of GHG in Africa. The data were from the World Development Indicators (WDI), covering the 1990–2020 periods for South Africa, Egypt, Nigeria, Algeria, and Libya. The panel Autoregressive Distributed Lag (ARDL) model was used for data analysis. The results showed that all the included series were stationary at first difference. The optimum lag lengths were determined independently in STATA 17 software, and the most frequent lags across the countries were selected. The Hausman test revealed that the pooled mean group (PMG) estimation was preferred to other estimators. The results showed that in the long-run, particulate emission damages, CO2 intensity, and energy use intensity positively impacted GHG emissions, while GDP per capita and renewable energy utilization produced mixed results. In the short run, the error correction mechanism parameters were all significant (p < 0.01) in Libya for all emission indicators, while Algeria showed significance (p < 0.01) in total GHG and CO2 per capita models. The coefficient of particulate emission damages significantly reduced (p < 0.01) total GHG emissions in Libya and Nigeria and renewable energy significantly increased (p < 0.01) GHG emissions in South Africa but reduced them in Nigeria. Also, CO2 emission intensity significantly (p < 0.01) and positively impacted GHG emissions in South Africa, Egypt, Libya, and Nigeria, while electricity power transmission losses increased total emissions and CO2 emissions in Libya and Algeria. It was concluded that initiatives to reduce GHG emissions should focus on developing countries’ sensitivity to emission damages, and promotion of initiatives for using renewable energies. Also, promotion of energy efficiency across industries offers a prospect for ensuring environmental sustainability.

How digital finance and green finance can synergize to improve urban energy use efficiency? New evidence from China

Accelerating the greening and digital transformation of the energy industry to enhance energy efficiency is pivotal for constructing a new energy system. The high-quality development of the energy sector necessitates the support of emerging financial forces. This study utilizes panel data from 279 prefecture-level cities spanning from 2011 to 2021, employing mediation and moderation models to verify the synergistic impact of digital finance and green finance on energy efficiency. Findings indicate that the synergy between digital finance and green finance enhances energy efficiency. Mechanism analysis reveals that this synergy promotes energy efficiency through advancements in green and digital technology innovations. Climate policy uncertainty positively moderates the process by which digital finance and green finance synergistically improve energy efficiency, enhancing the intermediary effects of digital and green technologies. Environmental regulations similarly exert positive moderation on the joint impact of digital finance and green finance on energy efficiency, yet their effects vary heterogeneously, with market-based environmental regulatory tools demonstrating superior policy outcomes. Moreover, the impact of the synergy between digital finance and green finance on energy efficiency exhibits heterogeneity across geographic regions, development timelines, resource endowments, and policy trial effects.

Consumer perception towards electric cars, an inductive study with specific reference to the Jordanian market

Electric cars are manufactured to address environmental problems, reduce dependence on fossil fuels, and nullify climate change. Their production aligns with sustainability objectives by encouraging cleaner transportation options, promoting energy efficiency, and contributing to a transition towards eco-friendly mobility in an answer to global environmental challenges. In Jordan, similar to any international market, car dealers and traders import electric cars. However, the prevailing perceptions and attitudes of Jordanian consumers need strong consideration. Nevertheless, there is still uncertainty and a need for more trust in electric vehicles among Jordanian consumers. Therefore, this research aims to ascertain whether electric cars have a lasting positive perception among Jordanians through an inductive research approach. Employing thematic qualitative analysis, this research is supported by the diffusion of innovation theory. Notably, the research findings provided robust insights, further leading to reinforcing the idea about the pervasive attitudes of Jordanian consumers. Thus, this research concludes that there still needs to be more confidence regarding electric vehicles among most consumers in Jordan. Furthermore, this research offers practical and theoretical contributions to Jordan’s policymakers and electric vehicle companies.

The nexus between technological innovation, human capital and energy efficiency: Evidence from E7 countries

Enhancing energy efficiency is very effective in supporting environmental sustainability. Financial inclusion, human capital, and technological innovation are newly cited as dominant factors for environmental sustainability in emerging economies. Against this background, this study investigated how financial inclusion and technological innovation affected energy efficiency in E7 countries from 2004 to 2021. The study identifies the diverse effect of variables at different quantiles through a novel Moments Quantile Regression (MM-QR) method to explore the heterogeneous interconnection among the variables. The MMQR outcomes suggest financial inclusion positively affects energy efficiency across all quantiles. Besides, the findings show that human capital positively affects energy efficiency in E7 countries at lower, medium, and higher quantiles. At the same time, estimated outcomes suggest that technological innovation promotes energy efficiency only at lower quantiles. This study recommends appropriate policies for decision-makers in E7 economies based on the study outcomes regarding adequately channelling human capital, financial resources, and technological innovation to promote energy efficiency and achieve sustainable development goals.

Analysis of condensation phenomena according to the type of energy recovery ventilator—Simulation and experiments

Ventilation plays a crucial role in maintaining indoor air quality. Energy recovery ventilators (ERVs) have emerged as a solution to balance ventilation needs and energy consumption in buildings. However, ERVs can encounter condensation issues in extreme outdoor conditions, impacting their performance and indoor air quality. In this study, we investigate occurrence conditions and ratios of condensation in ERVs through dynamic simulations and experimental tests using different heat exchanger types: plastic-based plate, membrane-based plate, and rotary. The simulation results show that condensation ratios vary depending on the heat exchanger type and seasonal conditions, with higher latent effectiveness playing a significant role in reducing condensation. Notably, we demonstrate that rotary ERVs rarely exhibit the generation of condensation. The simulation results are validated through experimental tests, ensuring reliable condensation predictions in ERVs. Our findings underline the importance of selecting appropriate type of ERV to mitigate condensation and enhance indoor comfort while promoting energy efficiency. The proposed simulation methodology will provide valuable insights into estimating condensation ratios in ERVs under diverse climatic conditions.