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The purpose of this study is to explore the potential and challenges of biogas utilization as an alternative and sustainable energy source in the Gurage zone of Southern Ethiopia, where traditional energy sources such as firewood and charcoal are widely used.

The study adopts a mixed-methods approach to collect and analyze data from different sources and perspectives. The research collects quantitative data from structured interviews with 200 rural households who use biogas or other energy sources, and qualitative data from key informant interviews and focus group discussions with biogas experts, local authorities and community leaders. Socioeconomic analysis is conducted to assess the importance of biogas in terms of income, expenditure, health and environmental benefits, and a multivariate probit model is used to identify the factors influencing biogas energy adoption among rural households.

The findings indicate that biogas users are more likely to substitute traditional energy sources with biogas for cooking, lighting and heating purposes. The model reveals that age, sex, education level, land size and livestock quantity influence biogas energy adoption, whereas income, distance to market and access to credit do not have a significant effect. The findings also show that biogas users have higher income, lower expenditure, better health and lower greenhouse gas emissions than nonusers.

The study concludes that the socioeconomic impact of biogas varies among households based on location and lifestyle. The study also highlights the need for further research on the technical, institutional and behavioral aspects of biogas utilization in different contexts.

To address the challenges faced by biogas users and their energy choices, such as lack of awareness, maintenance, quality control and affordability, the study suggests exploring biogas energy to meet the diverse needs of cattle owners in different regions. The study also recommends enhancing the capacity of local stakeholders, promoting public–private partnerships, and developing supportive policies and regulations for biogas development in Ethiopia.

The study implies that biogas utilization can contribute to social development by improving the living standards, health status and gender equality of rural households. The study also suggests that biogas utilization can foster social cohesion and empowerment by creating opportunities for collective action, knowledge sharing and income generation among biogas users and their communities.

The study provides a comprehensive and empirical analysis of the socioeconomic landscape of biogas utilization and the determinants of energy choice in the Gurage zone of Southern Ethiopia. The study also offers valuable insights and recommendations for policymakers, practitioners, researchers and other stakeholders involved in biogas development in Ethiopia and other developing countries.

This study aims to explore the diverse sources of electricity generation (coal, natural gas, oil and hydroelectricity) and their respective associations with economic growth and environmental quality.

This study uses static panel data analysis with a random effects model for six selected ASEAN countries (Indonesia, Malaysia, Filipina, Thailand, Vietnam and Myanmar) from 1994 to 2014.

This study reveals that economic growth in six selected ASEAN countries is enhanced by electricity generation from all sources, while the contribution of electricity production from hydroelectricity remains the largest and strongest. There is no environmental impact of electricity production from hydroelectric, whereas fossil fuel-based electricity production emits carbon dioxide, with coal sources being the largest contributor, followed by natural gas and oil.

Based on the results, these six ASEAN countries should invest more in hydropower projects, reduce the coal mix in power generation and promote clean coal technology to improve economic efficiency and environmental sustainability.

To the best of the authors’ knowledge, no research has examined the relationship between electricity production, environmental quality and economic growth in Southeast Asian nations. Therefore, the outcome of this study is expected to provide insightful results to supplement the framing and implementation of national and collective regional strategies for sustainable electricity generation in ASEAN countries.

Energy consumption in transportation accounted for over 29% of total final consumption (TFC) of energy and 65% of global oil usage, and it is highly connected to mobility. Mobility is essential for access to day-to-day activities such as education, leisure, healthcare, business activities, and commercial and industrial operations. This study examines the energy consumption for the transport industry, and the level of renewable energy development in some selected Sub-Saharan African (SSA) nations. This study relied on previous publications of government, reports and articles related to the subject matter. Vehicle ownership is fast increasing, particularly in cities. Still, it begins at a relatively low level because the area is home to countries with the lowest ownership rates worldwide. In its current state, the energy sector faces significant challenges such as inadequate and poorly maintained infrastructure, dealing with increasing traffic congestion in cities, large-scale imports of used vehicles with poor emission standards that affect air quality in cities, a lack of safe and formally operated public transportation systems, and inadequate consideration for women and disabled mobility needs. Motorcycle and tricycle are dominating the rural areas, accounting for a substantial amount of this growth. Aviation is the largest non-road user of energy, and this trend is predicted to continue through 2040 as Gross Domestic Product (GDP) grows and urbanisation expands. This study revealed the energy consumption for the transport industry, and the level of renewable energy development in some selected SSA. Rail and navigation lag behind current global levels. The usage of biofuel and rail transport was recommended.

The Russian Federation is one of the world’s largest exporters of fossil-based energy sources such as oil, natural gas and coal. Approximately 90% of the energy production in the Russian Federation consists of oil, natural gas and coal. Renewable energy (RE) in the Russian Federation mainly comprises hydroelectric energy. The purpose of this paper is to identify the factors that influenced the growth of RE resources in the Russian Federation between 1990 and 2020.

The unit root tests augmented Dickey and Fuller and Phillips and Perron, as well as Johansen cointegration and Granger causality approaches, were used. This study was conducted using vector error correction models for the years 1990–2020.

The cointegration method's findings demonstrate that while a rise in non-RE sources has a negative impact on RE development, an increase in income, energy consumption, trade openness and CO₂ emissions has a favorable impact on RE expansion. The vector error correction model Granger causality test also shows a unidirectional relationship between RE and non-RE sources, gross domestic product, energy consumption and CO₂ emissions. Trade openness, on the other hand, has no causal association with RE.

The Russian Federation must consider the practical implications of RE sources. However, there is a greater need for the Russian Federation to frame sound energy policies for RE development.

This paper aims to fill a gap in the literature on Russian RE development. Furthermore, the results of the methodological analysis can be used to guide policymakers in the field of RE development. This paper is also more policy-relevant and is quite useful in the context of sustainable energy development.

Electricity plays an essential role in nations' economic development. However, coal and renewables currently play an important part in electricity production in major world economies. The current study aims to forecast the electricity production from coal and renewables in the USA, China and Japan.

Two intelligent grey forecasting models – optimized discrete grey forecasting model DGM (1,1,α), and optimized even grey forecasting model EGM (1,1,α,θ) – are used to forecast electricity production. Also, the accuracy of the forecasts is measured through the mean absolute percentage error (MAPE).

Coal-powered electricity production is decreasing, while renewable energy production is increasing in the major economies (MEs). China's coal-fired electricity production continues to grow. The forecasts generated by the two grey models are more accurate than that by the classical models EGM (1,1) and DGM (1,1) and the exponential triple smoothing (ETS).

The study confirms the reliability and validity of grey forecasting models to predict electricity production in the MEs.

This paper aims to provide a comprehensive analysis of the state of the art in energy efficiency for autonomous mobile robots (AMRs), focusing on energy sources, consumption models, energy-efficient locomotion, hardware energy consumption, optimization in path planning and scheduling methods, and to suggest future research directions.

The systematic literature review (SLR) identified 244 papers for analysis. Research articles published from 2010 onwards were searched in databases including Google Scholar, ScienceDirect and Scopus using keywords and search criteria related to energy and power management in various robotic systems.

The review highlights the following key findings: batteries are the primary energy source for AMRs, with advances in battery management systems enhancing efficiency; hybrid models offer superior accuracy and robustness; locomotion contributes over 50% of a mobile robot’s total energy consumption, emphasizing the need for optimized control methods; factors such as the center of mass impact AMR energy consumption; path planning algorithms and scheduling methods are essential for energy optimization, with algorithm choice depending on specific requirements and constraints.

The review concentrates on wheeled robots, excluding walking ones. Future work should improve consumption models, explore optimization methods, examine artificial intelligence/machine learning roles and assess energy efficiency trade-offs.

This paper provides a comprehensive analysis of energy efficiency in AMRs, highlighting the key findings from the SLR and suggests future research directions for further advancements in this field.

In the recent wake of environmental sustainability, more attention has been paid to the consumption of specific energy types. However, how the consumption of such energy alternatives influences multiple corporate-level decisions has not yet been well explored in the literature. The current analysis bridges this deficiency in literature by exploring the empirical relationship between energy alternatives and cash holdings.

For empirical analysis, the authors sample the non-financial sector enterprises founded in five BRICS economies and employ the system GMM and fully modified ordinary least square techniques to establish the regression. The selection of econometric techniques is subject to the existence of endogeneity and cointegration.

The estimated coefficients reveal a significant negative effect of renewable energy (REC) while a significant positive impact of non-renewable energy consumption (FFE) on cash holdings. Referring to low pollution emissions, less operational risk and a cheap source of energy, the more consumption of renewable energy reduces the motives of cash holdings. Primarily, the current analysis advocates an important policy regarding the utilization of renewable energy as industrial fuel inputs because it has a material impact on cash holdings and also ensures environmental sustainability.

This study has equal policy outputs for industry officials, policy regulators and environmental economists. Corporate managers should do more focus on transforming the energy needs from non-renewable to renewable as such transformation can benefit in terms of both, i.e. environmental sustainability and low cash holdings.

Contemporary literature mainly highlights the determinants of energy consumption. However, it is less known how the consumption of specific energy sources affects the firm's cash-holding decisions. Thus, this study enriches both energy economics and financial economics literature by offering cutting-edge evidence on the sustainable role of REC in declining cash holdings.

Privacy preservation is a significant concern in Internet of Things (IoT)-enabled event-driven wireless sensor networks (WSNs). Low energy utilization in the event-driven system is essential if events do not happen. When events occur, IoT-enabled sensor network is required to deal with enormous traffic from the concentration of demand data delivery. This paper aims to explore an effective framework for safeguarding privacy at source in event-driven WSNs.

This paper discusses three algorithms in IoT-enabled event-driven WSNs: source location privacy for event detection (SLP_ED), chessboard alteration pattern (SLP_ED_CBA) and grid-based source location privacy (GB_SLP). Performance evaluation is done using simulation results and security analysis of the proposed scheme.

The sensors observe bound events or sensitive items within the network area in the field of interest. The open wireless channel lets an opponent search traffic designs, trace back and reach the start node or the event-detecting node. SLP_ED and SLP_ED_CBA provide better safety level results than dynamic shortest path scheme and energy-efficient source location privacy protection schemes. This paper discusses security analysis for the GB_SLP. Comparative analysis shows that the proposed scheme is more efficient on safety level than existing techniques.

The authors develop the privacy protection scheme in IoT-enabled event-driven WSNs. There are two categories of occurrences: nominal events and critical events. The choice of the route from source to sink relies on the two types of events: nominal or critical; the privacy level required for an event; and the energy consumption needed for the event. In addition, phantom node selection scheme is designed for source location privacy.

This study aims to examine the links between carbon emissions, electric vehicles, economic growth, energy use, and urbanisation in 15 countries from 2010 to 2020.

This study adopts seminal panel methods of moments quantile regression with fixed effects to trace the distributional aspect of the relationship. The reliability of methods is confirmed via fully modified ordinary least squares coefficients.

This study reveals that fossil fuel use, economic activity, and urbanisation negatively impact environmental quality, whereas renewable energy sources have a significant positive long-term effect on environmental quality in the selected panel of countries.

The main limitation of this study is the generalisability of the findings, as the study is confined to a limited number of countries, and focuses on non-renewable and renewable energy sources.

Finally, this study proposes several policy recommendations for decision-makers and policymakers in the 15 nations to address climate change, boost sales of electric vehicles, and increase the use of renewable energy sources.

This study calls for a comprehensive transition towards green energy in the transportation sector, enhancing economic growth, fostering employment opportunities, and improving environmental quality.

This study aims to examine the impact of socioeconomic factors on electricity usage and assess the feasibility of implementing a mini-grid system in Kasangazi, Malawi. The primary aim is to understand the community’s current and potential utilisation of electrical equipment.

A mixed-methods approach was used to collect quantitative and qualitative data. Information was gathered through structured questionnaires, and energy audits were conducted among 87 randomly selected households from 28 Kasangazi communities. Data analysis relied on descriptive statistics using IBM SPSS version 28.

The study indicates that every household in Kasangazi uses non-renewable energy sources: 60 households use disposable batteries for lighting, 20 for radios and all use firewood, freely sourced from local forests, for cooking and heating water. The study shows that firewood is the community’s preferred energy source, illustrating the challenges faced in the fight against deforestation. Most household income comes from farming, with smaller contributions from businesses, employment and family remittances. Access to higher education is scarce, with only one out of 349 family members receiving tertiary education. Despite the constraints of low education levels and income, there is a demand for larger electrical appliances such as stoves and refrigerators. This underscores the need for mini-grid solutions, even in less technologically advanced, agriculture-dependent communities.

This study underscores that in Sub-Saharan Africa, factors like household size, income and education levels do not significantly influence the electricity demand but should be taken as part of the fundamental human rights. Rural populations express a desire for electricity due to the convenience it offers, particularly for appliances like refrigerators and stoves. Mini-grids emerge as a viable alternative in regions where grid electricity provision is challenging. It is concluded from this paper that the issue of using renewable energy should not only be taken for environmental preservation but also to promote energy access, augmenting efforts in supplying electricity to the remotest parts of the country.