Depletion Of Energy Resources Research Articles

CUTTING-EDGE BIOFUEL TECHNOLOGIES FOR ENVIRONMENTAL MANAGEMENT AND SUSTAINABILITY

Researchers focus on finding Renewable Energy Sources (RES) and green energy for a sustainable future owing to ecological sustainability standards, growing power demands, depletion of traditional energy resources, and ecological damage caused by global warming and climate change. Bioenergy is a very viable option as it may be used for various energy needs via appropriate conversion methods. This analysis focuses on the promise and problems of producing biofuels using different feedstocks and advancements in process technology. The use of biofuels, such as biodiesel, ethanol, bio-oil, syngas, Fischer-Tropsch Hydrogen, and methane (CH4), generated from agricultural crop left-overs, micro- and macroalgae, and other biological waste via thermo-bio-chemical procedures, has been determined to be an environmentally beneficial option for energy production. Developing and implementing biofuels in industry and transportation significantly reduces reliance on petroleum and coal. The literature study indicated that biofuels derived from crops and microalgae have the potential to be the most effective and appealing method. The area of biofuels has made significant advancements via genetic engineering, which has opened up new possibilities for large-scale production for commercial use. However, the process of producing biofuels on a big scale remains difficult. Therefore, it is crucial to address this issue by converting biomass into biofuels using innovative technology to meet present and future energy demands.

CUTTING-EDGE BIOFUEL TECHNOLOGIES FOR ENVIRONMENTAL MANAGEMENT AND SUSTAINABILITY

Researchers focus on finding Renewable Energy Sources (RES) and green energy for a sustainable future owing to ecological sustainability standards, growing power demands, depletion of traditional energy resources, and ecological damage caused by global warming and climate change. Bioenergy is a very viable option as it may be used for various energy needs via appropriate conversion methods. This analysis focuses on the promise and problems of producing biofuels using different feedstocks and advancements in process technology. The use of biofuels, such as biodiesel, ethanol, bio-oil, syngas, Fischer-Tropsch Hydrogen, and methane (CH4), generated from agricultural crop left-overs, micro- and macroalgae, and other biological waste via thermo-bio-chemical procedures, has been determined to be an environmentally beneficial option for energy production. Developing and implementing biofuels in industry and transportation significantly reduces reliance on petroleum and coal. The literature study indicated that biofuels derived from crops and microalgae have the potential to be the most effective and appealing method. The area of biofuels has made significant advancements via genetic engineering, which has opened up new possibilities for large-scale production for commercial use. However, the process of producing biofuels on a big scale remains difficult. Therefore, it is crucial to address this issue by converting biomass into biofuels using innovative technology to meet present and future energy demands.

Global Conditions and Changes in the Level of Renewable Energy Sources

The progressing globalization of the contemporary economy impacts its volatility and unpredictability. The directions of changes in the socioeconomic development of the contemporary global economy are determined by a number of interrelated diverse factors. Factors clearly influencing the development of the modern international economy include innovation, digitization processes, instability of the economy caused by armed conflicts or pandemic outbreaks, the concept of sustainable development, climate policy, as well as issues related to the depletion of energy resources and the necessity of ensuring global energy security. The purpose of the article is to identify the factors of the development of the contemporary economy along with the analysis and evaluation of their impacts on changes in the level of renewable energy sources (RESs) in the EU countries. The time scope of the analysis covers the years 2013 and 2022 (a 10-year perspective). The study used the methods of literature study, literature criticism, statistical data analysis (statistical databases: EUROSTAT and IRENA), and linear ordering methods (TOPSIS and EDAS). The study results indicate that the levels of the RESs have changed in response to the factors diagnosed in the study. In the years studied, the leaders in terms of levels of RES development were France, Spain, and Denmark.

Embodied Energy Coefficient Quantification and Implementation for an Energy-Conservative House in Thailand

Embodied Energy Coefficient Quantification and Implementation for an Energy-Conservative House in Thailand

A Spin-Charge-Regulated Self-Powered Nanogenerator for Simultaneous Pyro-Magneto-Electric Energy Harvesting.

In view of the depletion of natural energy resources, harvesting energy from waste is a revolution to simultaneously capture, unite, and recycle various types of waste energies in flexible devices. Thus, in this work, a spin-charge-regulated pyro-magneto-electric nanogenerator is devised at a well-known ferroelectric P(VDF-TrFE) copolymer. It promptly stores thermal-magnetic energies in a "capacitor" that generates electricity at room temperature. The ferroelectric domains are regulated to slip at the interfaces (also twins) of duly promoting polarization and other properties. An excellent pyroelectric coefficient p ∼ 615 nC·m-2·K-1 is obtained, with duly enhanced stimuli of a thermal sensitivity ∼1.05 V·K-1, a magnetoelectric coefficient αme ∼8.8 mV·cm-1·Oe-1 at 180 Hz (resonance frequency), and a magnetosensitivity ∼473 V/T. It is noteworthy that a strategy of further improving p (up to 41.2 μC·m-2·K-1) and αme (up to 23.6 mV·cm-1·Oe-1) is realized in the electrically poled dipoles. In a model hybrid structure, the spins lead to switch up the electric dipoles parallel at the polymer chains in a cohesive charged layer. It is an innovative approach for efficiently scavenging waste energies from electric vehicles, homes, and industries, where abundant thermal and magnetic energies are accessible. This sustainable strategy could be useful in next-generation self-powered electronics.

Synthesis and Photoreforming Reaction of CdS Prepared from MOF Precursor

The photoreforming reaction, which can produce hydrogen simultaneously with the decomposition of organic waste, is a promising method for resolving longstanding global issues such as the depletion of energy resources and climate change. However, ZnS photocatalysts, one of the most optimal catalysts for such reactions, has an inadequate visible‐light response; thus, the extensibility of the reaction is limited. In this study, CdS photocatalysts are prepared from metal–organic framework (MOF) precursors, that is, Cd‐MOFs. The prepared CdS exhibits high hydrogen production activity in the photoreformation of lignocellulosic biomass under quasi‐sunlight conditions. This activity is approximately 13.4 times that of CdS prepared via conventional hydrothermal synthesis (HT). Further, CdS can utilize light energy in the visible region of sunlight, providing a high quantum yield and demonstrating the potential for the extensibility of the reaction. The results of this study will facilitate the fabrication of novel materials for sustainable and efficient hydrogen production.

Concept development of exercise-to-power: The Green&Healthy power concept

Energy harvesting systems can capture and convert small amounts of energy from various natural sources, contributing to offsetting the growing global energy challenges without incurring the depletion of additional energy resources. Human kinetic energy can be obtained from physical exercise - in indoor cycling, the athlete's metabolic energy converts into heat, enthalpy (to the environment), and work. This study reports on the concept development of the Green&Healthy Power system, an energy harvesting system that collects energy from physical activities. A case study based on an indoor bike generator as a conceptual innovation is presented. The user can select the intensity of effort in which the exercise occurs to produce electricity. Using situations based on literature results, the gains are evaluated by measuring aerobic endurance. The user is informed about the health benefits of the exercise (traditional indices), the energy produced, and the greenhouse gas emissions avoided. This study also reviews some aspects of precedent practices, highlighting the concept's challenging characteristics and setting out the initial formulation of the Green&Healthy Power system. This contribution defines research, development, and demonstration priorities for new ideas and technologies to improve energy efficiency and reduce the final consumption of primary energy. As results of the study case, initial figures indicate that 1000 people performing 20 min of activities on the energy harvesting system three times a week can avoid annual emissions of 180 kg CO2 and produce 800 kWh/year of electricity, resulting in savings of R$ 800/year. Brazil has a population of 200 million inhabitants and if 1 % of the population carried out this activity, electricity generation could reach up to 1.6 TWh/month (= 19.2 TWh/year), representing 3.4 % of electricity flows within the Brazilian electricity matrix.

The Relationship between Mechanical Ventilation, Indoor Air Quality Classes, and Energy Classes in a Romanian Context

Nowadays, indoor air quality (IAQ) and the energy performance of buildings are two main scientific and technical challenges because they are in direct connection with human health and the depletion of energy resources. In this study, we analyzed the influence of an outdoor air flow introduced through a mechanical ventilation system, focusing on the two aforementioned topics. A standardized ventilation rate (25 m3/h/person) led to an increase in the indoor O3 concentration (from 5 μg/m3 to 50 μg/m3) and, simultaneously, to a decrease in the indoor CO2 concentration (from 2000 mg/m3 to 800 mg/m3), a decrease in the PM2.5 concentration (from 300 μg/m3 to 150 μg/m3), and the maintenance of a constant indoor HCHO concentration. In our study, a new, single indoor air quality index, IIAQ, is proposed. This new index presents different implications: on the one hand, it has the ability to simultaneously take into account several pollutant species, and on the other hand, it can prioritize the ventilation strategy that responds to the extreme values of a certain pollutant. Moreover, indoor air quality classes were elaborated, similar to energy classes. The possibility of using this new index simultaneously with energy consumption may lead to ventilation strategies that are adaptative to dynamic outdoor pollutant concentrations.

Harmony in Connectivity: Toward a Sustainable Future with Green Internet

Abstract: The widespread adoption of Internet of Things (IoT) devices has resulted in remarkable progress across various domains, enriching connectivity and automation. However, the growing deployment of IoT presents substantial environmental challenges, raising issues related to energy consumption, electronic waste, and resource depletion. This research paper explores the concept of Green IoT, with a focus on developing and implementing sustainable practices within the IoT ecosystem. The primary goal of this study is to investigate strategies for enhancing the energy efficiency of IoT devices, reducing their carbon footprint, and advocating for environmentally conscious practices throughout their life cycle. We delve into cutting-edge technologies, such as low-power components, energy harvesting mechanisms, and optimization algorithms for communication protocols, aiming to establish a more eco-friendly infrastructure for IoT. Additionally, this paper emphasizes the significance of sustainable materials and design principles in the manufacturing of IoT devices, emphasizing the reduction of electronic waste and the promotion of recycling. We discuss the integration of renewable energy sources like solar and wind power to energize IoT devices, contributing to a cleaner and more sustainable energy supply for the IoT ecosystem.

The Effect of an Educational Intervention Based on an Integrated Social Cognition Model on Waste Recycling at the Source Among Housewives in Lahijan City: A Quasi-Experimental Study

Background: Recycling is proposed as an economic model for saving raw material and energy costs, pollution reduction, reducing waste, resource depletion, and situation improvement in a range of environmental pollution issues. Objectives: The present study aimed to investigate the effect of educational interventions based on an integrated social cognition model (ISCM) on waste recycling at the source among housewives in Lahijan City, Iran. Methods: In this quasi-experimental study, a total of 144 women who sought health care services in Lahijan were selected using a multistage random sampling method. The participants were then evenly divided into intervention and control groups, with each group consisting of 72 women. The study was conducted between 2021 and 2022. Data collection tools included demographic information questionnaires, awareness questions, and ISCM constructs about waste recycling at the source. The total mean scores for the content validity ratio (CVR; 0.84) and content validity index (CVI; 0.83), Cronbach's alpha coefficient (0.85), and internal consistency (0.84) were measured to evaluate the validity and reliability of the questionnaire. Educational content based on ISCM constructs was prepared and carried out in the intervention group in six 60-90-minute sessions virtually via mobile phone using WhatsApp messenger over 6 consecutive weeks. The data were collected before and 1 month after the educational intervention and analyzed using descriptive statistics, Chi-square, independent t-test, paired t-test, and analysis of covariance (ANCOVA) using SPSS version 25. Results: The mean age of the participants was 38.9 ± 12.1 years. Before the study, the 2 groups had no statistically significant difference regarding all demographic variables, awareness, and ISCM constructs (P > 0.05). The 2 groups showed a statistically significant difference in the mean scores of awareness, attitude, subjective norms, perceived behavioral control, self-efficacy, behavioral intention, and action and coping planning after the intervention (P < 0.001). The mean ± SD of the behavior score increased from 17.25 ± 4.96 before the intervention to 25.78 ± 4.95 after the intervention (P < 0.001). Conclusions: The design and implementation of educational interventions based on ISCM have the potential to enhance housewives' performance in waste management and recycling while also increasing their awareness levels.

Exploring the impact of macro-determinant factors on energy resource depletion: Evidence from a worldwide cross-country panel data analysis

The depletion of energy resources stands out as one of humanity's major challenges. Therefore, understanding the determinant factors that could potentially affect the depletion rate of energy resources is emerging as one of the main research interests of academics in this field, and this study intends to contribute by filling this gap. This paper aims to investigate the influence of different factors that can be categorised into six main categories, such as education, governance quality, sustainability, technological advancements, economic development, and health expenditures, on the depletion of energy resources in a large sample of 132 countries clustered according to their income level, for a 14-year period (2007–2020). To this end, we propose six composite indices that we developed to capture each of the six categories of macroeconomic factors. Following the panel data analysis conducted for each cluster of countries, classified based on World Bank income classification, our findings suggest that the most determinant factors for the energy depletion rate are education (for upper-middle income), governance quality (for high-income), technology advancements (for low-income), economic development (for high, upper-middle, and low-income), and health expenditures and diseases (for high, lower-middle, and low-income countries).

Passive sustainability strategies in traditional Gaziantep residences: a critical report on historical development

Abstract In recent years, the increase in the need for energy and the rapid depletion of energy resources have revealed that energy control in buildings is of vital importance. This situation requires energy efficiency not only in new buildings but also in existing building stocks. For this reason, passive strategic measures affecting thermal comfort and energy efficiency in historical buildings built in Gaziantep in the late 18th and early 19th centuries have been evaluated in this study. First, the cultural, technological and natural images of the region that are effective in the development of these strategies were identified. The reflection of these images on architectural design and the parameters affecting energy use as a result were revealed. In order to examine the effect of passive strategy measures in the spaces, a field study was carried out on a selected Gaziantep traditional residential building. For the field study, measurements were taken from the selected building and the street every hour during the day. These measurements have been made under the following conditions: sunny inside the courtyard, sunny outside the courtyard, shade inside the courtyard and shade outside the courtyard. Afterwards, all measurements have been compared. As a result, it is concluded that the courtyard systems that form the cultural, technological and natural image of the region have a great effect on thermal comfort.

Numerical Simulation of the Effect of Particle Size Distribution on Fluidized Bed Gasifier

The rapid development of technology and industrialization has confronted humanity with two important problems: the depletion of fossil energy resources and environmental damage. This study aims to determine the effect of the particle size distribution of the bed on the composition of the produced syngas which has the potential to replace fossil fuels. The particle bed used is silica sand with 4 variations of particle size distribution with a diameter of 600-1000 µm. The results of this study indicate that the larger the particle size distribution of the bed can reduce the temperature distribution and composition of the syngas produced. The highest temperature distribution was found in the 1st particle size distribution variation of 1060.23 K. The highest syngas composition was found in the 3rd particle size distribution variation of 2.21% CH4, 19.68% CO, 6.21% CO2, and 18.51% H2The highest syngas composition was found in the 3rd particle size distribution variation of 2.21% CH4, 19.68% CO, 6.21% CO2, and 18.51% H2. The lowest temperature distribution was obtained in the 3rd particle size distribution variation of 1057.77 K. The lowest syngas composition was found in the 4th particle size distribution 1.99% CH4, 17.71% CO, 5.63% CO2, and 16.66% H2.

A review on the microgrid sizing and performance optimization by metaheuristic algorithms for energy management strategies

A growing concern over climate change and the depletion of conventional energy resources have led to the urgent need for sustainable and resilient energy solutions. The optimization of the size of renewable sources is crucial to maximizing their effectiveness. In contrast to conventional single-objective optimization, the multi-objective technique aims to achieve a trade-off between energy cost and power supply reliability. Due to this need, microgrids (MG) have emerged as a promising paradigm, allowing for localized and decentralized energy generation and distribution. Consequently, the conventional techniques for modelling and optimizing exhibit numerous limitations as the power grid continues to produce substantial volumes of high-dimensional and diverse data types. This review paper examines the use of metaheuristic algorithms in the context of multi-objective energy optimization for hybrid renewable energy-integrated microgrids. A comparative analysis of diverse metaheuristic algorithms for microgrid optimization is provided in this paper, which emulates natural phenomena, such as evolutionary processes and swarm dynamics. Based on the findings of case studies, it can be concluded that trade-offs exist between various objectives, eventually leading to the development of both resilient and efficient microgrid designs. By reviewing sustainable energy solutions, and advocating microgrids as viable alternatives to conventional centralized power systems, the review enhances the advancement of sustainable energy solutions.

The relevance of sustainable laboratory practices.

Scientists are of key importance to the society to advocate awareness of the climate crisis and its underlying scientific evidence and provide solutions for a sustainable future. As much as scientific research has led to great achievements and benefits, traditional laboratory practices come with unintended environmental consequences. Scientists, while providing solutions to climate problems and educating the young innovators of the future, are also part of the problem: excessive energy consumption, (hazardous) waste generation, and resource depletion. Through their own research operations, science, research and laboratories have a significant carbon footprint and contribute to the climate crisis. Climate change requires a rapid response across all sectors of society, modeled by inspiring leaders. A broader scientific community that takes concrete actions would serve as an important step in convincing the general public of similar actions. Over the past years, grassroots movements across the sciences have recognized the overlooked impact of the scientific enterprise, and so-called Green Lab initiatives emerged seeking to address the environmental footprint of research. Driven by the voluntary efforts of researchers and staff, they educate peers, develop sustainability guidelines, write scientific publications and maintain accreditation frameworks. With this perspective we want to advocate for and spark leadership to promote a systemic change in laboratory practices and approach to research. Comprehensive evidence for the environmental impact of laboratories and their root-causes is presented, expanded with data from a current case study of the University of Groningen showcasing annual savings of 398 763 € as well as 477.1 tons of CO2e. This is followed by guidelines for sustainable lab practices and hands-on advice on how to achieve a systemic change at research institutions and industry. How can we expect industry, politics, and society to change, if we as scientists are not changing either? Scientists should lead by example and practice the change they want to see.

Design and Development of an IoT Gateway for Smart Building Applications

Due to the depletion of energy resources and increased energy demand, there is an increased focus on the energy consumption and management in buildings. Many building energy management (BEM) software platforms are commercially available to monitor and control energy consumption. These platforms are hosted on the physical hardware within the building, due to which the hardware specifications limit their performance. To address this limitation, cloud technology emerged which facilitates software to be deployed at a remote location that has scalable hardware resources. Conventional BEM software can leverage such a cloud platform to offer scalable and maintenance-free installation. Once hosted on a remote cloud platform, BEM software lacks direct connectivity to building sensors/controllers, hence requires a device to support remote accessibility. Most devices are bound to a local area network and therefore need an additional functional layer on top of its communication stack to perform Network Address Translation (NAT)-Traversal. This functionality is implemented on a scalable software which connects to the devices in the network and acts as a gateway for cloud-based BEM software to access devices in the local area network. Any message sent to this gateway is translated to a respective device protocol. This paper describes the design and implementation of such an Internet of Things (IoT) gateway for a cloud-based BEM system that requires support for BACnet, Modbus, and HTTP RESTful interface devices.

Renewable Energy Sourcing to Enhance Sustainable Manufacturing by Using Madhab’s EEE Impact Analysis Model

The world's increasing energy demand, coupled with the depletion of finite energy resources, necessitates a shift towards sustainable energy solutions. This research explores the multifaceted benefits of substituting conventional fossil fuel-based energy sources with renewable energy in industrial settings, with a focus on sustainable manufacturing. A case study was conducted at a printing and packaging factory in Bhubaneswar, Odisha, to analyze economic, environmental, health, safety, and efficiency factors associated with various energy options based on the Madhab’s EEE (Environmental, Efficiency, Economic) impact analysis method. The study identified solar power generation as the optimal energy source, boasting the lowest EEE impact index of 1.90. Wind energy ranked second, followed by conventional GRID power and DG (Diesel Generator) power sources, which were found to be less favorable due to their higher EEE impact indices. Feasibility assessments revealed that the factory had ample rooftop and vacant land space for solar power plant installation, making it self-sufficient in power generation. The return on investment (ROI) for the solar power project was calculated to be 5.54 years, making it a viable option from a sustainability perspective. Moreover, the solar system could be integrated with the GRID through a reverse metering system, enabling excess energy to be sold back to the GRID. This research underscores the significance of transitioning to renewable energy sources in industries for environmental sustainability, energy security, and economic benefits. It emphasizes the need for similar studies in diverse industrial settings to identify the most suitable energy sources, considering all relevant factors.

Co-combustion of methane hydrate granules and liquid biofuel

The use of fossil hydrocarbons is accompanied by such problems as the depletion of energy resources and high levels of anthropogenic emissions. One of the options for solving these problems can be the involvement in the fuel sector of composite mixed fuels using gas hydrates and vegetable liquid bio-fuels. In this research we test a hypothesis that gas hydrate with added rapeseed oil will make an energy-efficient and environmentally friendly composite fuel. According to the experimental findings, the co-combustion of gas hydrates and liquid biofuels shows high potential. It shortens the ignition delay by 1.5 times at 700 °C in the combustion chamber and by half at 800 °C compared with the combustion of methane hydrate alone. It also produces 18–32% less carbon monoxide, 12–22% less nitrogen oxides, and 14–33% less sulfur oxides than the direct combustion of rapeseed oil. On the basis of the results obtained, we have developed a predictive mathematical model simulating the heat transfer in a layer of composite fuel. A methane hydrate and rapeseed oil mixing scheme is proposed for combustion chambers. We also provide recommendations on how to use the research findings in a number of energy-related applications.

Re‐estimating the pollution haven–halo hypotheses for Brazil via a machine learning procedure

AbstractIn this study, we re‐examined the pollution haven and halo hypotheses in Brazil for approximately five decades (1970–2019) while controlling for the effects of income, renewable energy and natural resource depletion. For clearer insights, the study employed both the conventional autoregressive distributed lag (ARDL) and the enhanced kernel regularized least squares (KRLS) techniques. Notably, the KRLS is a flexible machine learning nonlinear analytical technique that explains the interactions of the regressand and the regressors both at the average and across a range of quantiles. After ascertaining cointegration through the bounds tests and the Bayer–Hanck procedures, the following empirical outcomes emerged: The ARDL result suggests the acceptance of the pollution haven hypothesis in Brazil in both the short and long runs. However, the KRLS technique reveals that foreign direct investment (FDI) could enhance environmental quality (pollution halo) within the 25th quantile of the distributions of CO2 emissions. However, at the 50th and 70th quantiles, the pollution haven hypothesis is rectified. This suggests the adoption of varying policy options to ensure continuous inflows of FDI without compromising environmental quality. Additionally, among the control variables, a U‐shaped environmental Kuznets curve (EKC) structure is revealed from the influence of gross domestic product (GDP); renewable energy ensures a clean environment at all times, while resource rent ensures a clean environment only at the 25th and 50th quantiles of the distributions. Policies that could lead to clean environments in Brazil have been provided.

Decoding consumer-centric transition to electric mobility based on sentiment, semantic and statistical analysis

Climate change, carbon emissions, and energy resource depletion have become major concerns worldwide. The transportation sector is a primary target in various political and environmental agendas to tackle them. This calls for switching to sustainable transportation, and one of the important steps towards it is vehicle electrification. Understanding public attitudes towards electric vehicles (EVs) is the key to escalating vehicle electrification. By doing so, governments and enterprises can take the necessary action to persuade people to adopt electric mobility. Unlike past studies, which measured public attitudes using user acceptance data at a minuscule level, this paper adopts a macroscopic approach to this problem by mining public opinions from Twitter. Since Twitter provides access to its public tweet database, decoding the opinions of a vast population for extensive periods has become computationally tractable in recent years. The collected tweets have been used to examine the temporal and geographical dimensions of public perception using Natural Language Processing techniques. The substantial shifts in public sentiment have been identified, and the underlying incidents and topics were interpreted. In the pre-pandemic phase, most of the study nations saw an improvement in public sentiment towards EVs in the time period just before the COVID-19 pandemic, which can be attributed to the world-wide race to zero emissions to meet the Paris Agreement's carbon reduction targets. The public optimism further improved during the pandemic period. After the pandemic, the positivity towards EVs has declined in majority of the nations. The interpreted topics of discourse at the sentiment changepoints can be categorised into the following broad themes: (i) users and potential customers discourse, (ii) engineering and technology, (iii) politics, (iv) environment, (v) business and marketing, and (vi) miscellaneous. Most of the topics of discussion were centred around electric automotive firms, signifying the importance of the role of electric vehicle enterprises in electric vehicle adoption. The outcomes of this study can aid policymakers and electric automotive firms in comprehending the evolution of public perception towards electric mobility and thereby adopt and accelerate the human-centric transitions to carbon-neutral transport options.