Energy Footprint Research Articles

Comprehensive energy footprint of electrified fleets: School bus fleet case study

This paper proposes a comprehensive framework for estimating the energy footprint and benefits of electrified vehicle fleets prior to their deployment. To support this analysis, it introduces a control-oriented electric bus simulator model that not only captures driving power requirements but also incorporates a thermal model for cabin behavior and a Heating Ventilation and Air Conditioning (HVAC) system for heating and cooling. By analyzing current bus routes and road terrain data, the energy demand and economic effects are estimated, taking into account the current operational characteristics of school buses. As a case study, it examines the potential advantages of electrifying school bus fleets in the Central School District in Ohio, USA, with a focus on energy savings and environmental impact reduction. Our findings suggest that transitioning to electric school buses could achieve up to 76% energy savings compared to gasoline buses and 67% energy savings compared to diesel buses. Economically, when converted to operational costs, this results in a savings of 52%–65% compared to gasoline and 27%–47% compared to diesel under the average price rate. The accuracy of our model is calibrated using actual operational data from school bus fleets. Furthermore, this study provides foundational insights into the charging requirements through the energy footprint analysis. This study contributes to the advancement of sustainable transportation by presenting comprehensive preliminary analysis results for vehicle electrification through a specific case study. It emphasizes the practical implementation of electric school buses and optimized vehicle efficiency, aligning with broader eco-friendly initiatives in the transportation sector.

3D‐printing continuous plant fiber/polylactic acid composites with lightweight and high strength

AbstractContinuous plant yarn‐reinforced polylactic acid (PLA) composites were produced through in situ 3D printing, focusing on how plant fiber attributes influence the crystallization, mechanical, and rheological properties of the printed composites. The aim of this study was to assess the viability of plant fibers as substitutes for synthetic ones in engineering additive manufacturing. Plant fibers promoted the crystallization of PLA due to their shear induction and nucleation agent induction effects. The inherent triangular void defect during printing decreased with increasing plant fiber‐volume fraction. Rheological analysis revealed a transition to more elastic behavior post‐fiber addition, indicating solid‐like properties. The tensile strength of flax fiber‐yarn/PLA composite (volume fraction of 50.79%) was 342.37% higher than that of pure PLA, with a 22.2% lower density than pure PLA. Flax fiber demonstrated a superior reinforcement effect than carbon fiber in compressive strength for 3D printed honeycomb sheets with lower energy consumption and footprint. Optimizing fiber characteristics holds promise for high‐performance 3D‐printed natural fiber composites, particularly in vehicle applications.Highlights Plant fiber/polylactic acid (PLA) composites were in situ printed with a volume fraction of 50.79%. Plant fibers promoted the crystallization of PLA during the printing process. The tensile strength of flax fiber/PLA increased by 342.3% with a 22.2% lower density than PLA. Flax fiber showed a better reinforcement than carbon fiber in a compressive test of printed honeycomb.

Effect of Architecture and Inference Parameters of Artificial Neural Network Models in the Detection Task on Energy Demand

Artificial neural network models for the task of detection are used in many fields and find various applications. Models of this kind require adequate computational resources and thus require adequate energy expenditure. The increase in the number of parameters, the complexity of architectures, and the need to process large data sets significantly increase energy consumption, which is becoming a key sustainability challenge. Optimization of computing and the development of energy-efficient hardware technologies are essential to reduce the energy footprint of these models. This article examines the effect of the type of model, as well as its parameters, on energy consumption during inference. For this purpose, sensors built into the graphics card were used, and software was developed to measure the energy demand of the graphics card for different architectures of YOLO models (v8, v9, v10), as well as for different batch and model sizes. This study showed that the increase in energy demand is not linearly dependent on batch size. After a certain level of batch size, the energy demand begins to decrease. This dependence does not occur only for n/t size models. Optimum utilization of computing power due to the number of processed images for the studied models occurs at the maximum studied batch size. In addition, tests were conducted on an embedded device.

Environmental Sustainability: Ecological Footprint Analysis of Ibadan North, Nigeria

The ecological implications of global development have been a primary focus in discussions surrounding sustainability. As urban development expands globally, addressing its many ecological concerns becomes imperative. However, the ecological footprint (EF) analysis of urban sustainability within the sub-Saharan region, particularly Nigeria, remains largely unexplored. Here, we used the EF indices to explore the environmental sustainability of Ibadan City, one of Nigeria's fastest-growing urban centres. We implemented a bottom-up EF approach in the study, employing a cross-sectional design. We used an EF questionnaire to gather monthly household consumption data on food, energy, and water. We analysed these data descriptively and methodologically using EF formulae. Findings indicate environmental sustainability, as reflected in the low EF of 0.43gha/capita, with the energy footprint accounting for the majority (93%) at 0.4gha/capita. In comparison, the food footprint had the lowest share (below 3%) at 0.01gha/capita. Our findings demonstrate the significant impact of energy consumption on the overall EF, reinforcing the need for more sustainable energy solutions in urban planning, thus contributing to urban sustainability by informing urban planning and energy policy in alignment with the global sustainability drive.

Carbon and Energy Footprinting across Archetypes for U.S. Maple Syrup Production.

The production of maple syrup from sap requires extensive processing, which has traditionally led to significant energy inputs and greenhouse gas (GHG) emissions per gallon produced. Technology advancements, e.g., vacuum tubing sap collection systems, reverse osmosis (RO), and electric evaporators have changed the way syrup is produced, resulting in widespread variability in processing equipment and sugar-making operational decisions. This paper evaluates these complex operations through a cradle-to-retail gate carbon footprinting model and by capturing variability in a series of producer archetypes. By isolating energy and emissions impacts, we find that implementing RO has the largest reduction effect on energy (54-77%) and emissions (57-82%), depending on both production size and evaporator fuel (wood, fuel-oil, or electricity). Results also demonstrate the effect of production scale on cumulative energy demand (CED) and emissions per gallon of syrup, with small producers ranging from 333-1,425 MJ/gal and 27-118 kg CO2e/gal (61-90% biogenic on-site) for wood-fired operations and 18-65 kg CO2e/gal for oil-fired operations. Large producers ranged from 90-131 MJ and 3.5-7 kg CO2e/gal (electricity to oil-fired operations). Producers of all scales with the highest rates of electrification in their operations have the lowest GHG emissions and energy use per gallon of syrup produced.

Recycling impacts of renewable energy generation-related rare earth resources: A SWOT-based strategical analysis

As the global energy mix transforms and renewable energy technologies rapidly develop, there has been a significant increase in the demand for rare earth elements, which play a crucial role in renewable energy systems. By recycling rare earth resources from obsolete equipment, the reliance on newly mined rare earth resources can be reduced, thereby reducing the related environmental and energy footprints and increasing the stability of the supply chain. This study aims to systematically and strategically analyze and discuss the recycling impacts of renewable energy generation (REG)-related rare earth resources in terms of environmental, economic, social, and governance aspects. A SWOT strategical analysis framework integrating a management cycle and intelligent text data mining is built to address the above tasks from an ESG (Environment, Society, and Governance) perspective. The SWOT analysis of the rare earth recycling impacts focuses on strengths (e.g., reduced dependence on rare resources, reduced environmental and emission pressure), weaknesses (e.g., high cost, technology and management complexity), opportunities (e.g., policy support, technological innovations, diversification of the global supply chain), and threats (e.g., market volatility, the emergence of alternative materials). This analysis framework reveals textual topic changes and suggests cyclic and strategical improvement pathways to analyze the multi-dimensional recycling impacts. The text data analysis results indicate that the trend of rare earth recycling is gradually transformed from technologies, supply and demand, and secondary resources into resource and environment sustainable development. Beyond overcoming identified challenges, future pathways should focus more on the integration of advanced emerging technologies, life cycle management, and dynamic adjustment of recycling strategies. This study could provide policymakers and industry practitioners with recommendations and outlook on current development status and improvement strategies to promote REG-related rare earth recycling.

Investigation of a novel multigeneration system driven by an ammonia-methane Brayton cycle with partial production and utilization of ammonia, methane, and hydrogen: Energy and carbon footprint assessments

In this paper, to address gaps in the development of low-carbon energy systems, an innovative concept of an ammonia-methane Brayton cycle is proposed. This system is interconnected with various subsystems, including the Kalina cycle, high-temperature steam electrolysis, thermoelectric generators, and ammonia and methane synthesis reactors. The primary aim of this system was to reduce dependence on external resources by establishing local sources for water and fuel, thus reducing the environmental impact and enhancing energy sustainability. A thermodynamic model of an energy system was developed via EES codes which leads to a thoughtful perception into the interactions of the proposed system parameters. Also, comprehensive investigations involved the examination of different energy system scenarios. Modeling outputs of the proposed multigeneration system discovered excellent thermal efficiency and power production, with figures of 56.5 % and 17 MW, respectively, while the Brayton system showed the results of 23.7 % and 3.8 MW. This study also highlighted the environmental benefits of the multigeneration system by demonstrating a carbon dioxide emission of 0.058 kg/kWh, representing its significant positive impact on environmental sustainability. Also, the produced ammonia and methane within the system was 0.37 % and 9 %, of fuel in combustion chamber, respectively. Also, the rest of demand fuel was provided from the external resources.

A microporous fluorinated MOF for efficient separation of C2H2 from C2H2/CO2 and C2H2/C2H4 mixtures

Acetylene (C2H2)-adsorbed physisorbents are promising in addressing significant yet challenging industrial separation processes, such as the purification of C2H2 from carbon dioxide (CO2) and ethylene (C2H4) from C2H2. Herein, we report a fluorinated metal–organic framework (MOF), QDU-MOF-1, featuring micropores full of fluorinated anions, which enables preferential C2H2 adsorption over CO2 and C2H4. QDU-MOF-1 exhibits a high C2H2 adsorption capacity of 141.03 cm3/g at 298 K and 1 bar. Dynamic breakthrough experiments demonstrate a C2H2 capture capacity of 127.76 cm3/g for equimolar C2H2/CO2 mixtures. Strong affinity was revealed by density functional theory calculations between C2H2 and SiF62- in pores through hydrogen bonding, contributing to high C2H2 adsorption capacity. QDU-MOF-1 also shows good air stability and recyclability, making it potential for the C2H2/CO2 and C2H2/C2H4 separation applications. This study underscores the strength of discovering advanced physisorbents for challenging gas separations with low energy footprints.

SMAP: Design And Development Of A Sustainable Modular Air Purifier For Energy-Efficient Indoor Air Quality Management

This paper presents the design and development of the Sustainable Modular Air Purifier (SMAP), an innovative solution aimed at improving indoor air quality while minimizing energy consumption. The system features a modular architecture that allows for customizable and targeted air purification based on specific pollutants, including particulate matter, mold spores, and animal dander. Each module is equipped with specialized filters—high-efficiency particulate air, UV-C sterilization, and activated carbon—and operates selectively based on real-time air quality data from advanced sensors. This intelligent activation mechanism is aimed to reduce energy consumption, thus enhancing the system’s sustainability. Its modularity also allows for easy maintenance and adaptability to different indoor environments, making it scalable to a variety of use cases. Through a combination of energy-efficient components and a user-friendly interface, the SMAP ensures high purification efficiency and also contributes to the broader goal of environmental sustainability. The system’s performance, flexibility, and low energy footprint offer a promising solution for maintaining healthy indoor air quality in an environmentally responsible manner

Integrated crop management for long-term sustainability of maize-wheat rotation focusing on productivity, energy and carbon footprints

Modern agriculture, driven by diesel-fed machinery, is both energy and carbon-intensive, primarily due to the improper use of inputs. Designing a production module with lower carbon emissions, greater productivity, and enhanced energy use efficiency is crucial for achieving the environmental sustainability. Conservation agriculture based integrated crop management (ICMs) practices have shown promise in improving the productivity, energy-use, and reducing the carbon emissions. In our extensive long-term field study, we explored the crop yields, energy use, and carbon linkages of a maize-wheat rotation under different ICMs practices. Eight ICMs were evaluated over the course of nine consecutive years, which included ICM1&2: conventional (CT) flat-bed maize and wheat, ICM3&4: CT raised bed maize fb wheat without residues, ICM5&6: conservation agriculture (CA)-based double zero tilled (ZT) maize fb ZT wheat with residues and ICM7&8: CA-based triple ZT maize and wheat with residues and green manures. Our results indicated that the system productivity under CA-based ICMs was 16.5–22.9% greater than that under the CT-based ICM1-4. CA based ICM5-8 (125.2–131.5 × 103 MJ ha−1) needed higher energy input than CT-based ICM1-4 (32.7–39 × 103 MJ ha−1), with 76–80% shared by renewable crop residues. Furthermore, the CA-based ICMs recorded significantly higher levels of specific energy, human energy profitability, non-renewable energy use efficiency, and nutrient energy use efficiencies compared to CT-based. Likewise, the CA-based ICMs produced 12.5% more total output energy than the CT-based ICMs. In contrast, the CT based ICMs demonstrated, energy productivity, higher net energy returns and energy profitability. Compared to conventional ICMs, CA-based ICMs produced a 23–36% reduction in spatial carbon emissions and a 31–44 % reduction in yield-scale emissions. Nevertheless, the CA-based practices recorded the higher C- output, C- sustainability and C- efficiency ratio. Greenhouse gas intensity (GHGI) was 33.3–76.2% greater with the ICM1-4 practices than with the ICM5-8 practises. Thus, the present study proposed that adopting the integrated crop management practices based on the conservation agriculture could prove to be productive, as well as carbon and energy-use efficient approach for the maize-wheat rotation. This approach is envisioned to make substantial contributions to both food security and environmental sustainability.

Ultra-high endurance silicon photonic memory using vanadium dioxide

Silicon photonics arises as a viable solution to address the stringent resource demands of emergent technologies, such as neural networks. Within this framework, photonic memories are fundamental building blocks of photonic integrated circuits that have not yet found a standardized solution due to several trade-offs among different metrics such as energy consumption, speed, footprint, or fabrication complexity, to name a few. In particular, a photonic memory exhibiting ultra-high endurance performance (>106 cycles) has been elusive to date. Here, we report an ultra-high endurance silicon photonic volatile memory using vanadium dioxide (VO2) exhibiting a record cyclability of up to 107 cycles without degradation. Moreover, our memory features an ultra-compact footprint below 5 µm with the potential for nanosecond and picojoule programming performance. Our silicon photonic memory could find application in emerging photonic applications demanding a high number of memory updates, such as photonic neural networks with in situ training.

Towards a Sustainable Future: Examining the Symmetric and Asymmetric Effect of Unstable Macroeconomic Factors on Initial Public Offerings Variability

The research seeks to explore the symmetric and asymmetric effects of renewable energy, technological innovation, and ecological footprint on the variability of initial public offerings in the unique institutional setting of the Pakistani IPO market. The study used yearly data on the Pakistani IPO market and the macroeconomic variables from January 1992 to December 2020. Further, the study employed the linear and Non-Linear ARDL to investigate the symmetric and asymmetric nexus among variables. For that purpose, the stationarity of the variables was predetermined using Augmented Dicker Fuller (ADF) and Phillips Perron (PP) unit root tests. Additionally, the F-bound test verifies that IPO issuance and macroeconomic drivers are co-integrated. The findings show a symmetric and asymmetric relationship between IPO variability and macroeconomic variables under study. Renewable energy and technological innovation have statistically positive effects on IPO variability. On the contrary, the ecological footprint has a significantly negative impact on IPO variability. The weak condition of the Pakistani IPO market could be attributed to the slow adoption of technological innovation, the transition to renewable energy, and a high ecological footprint that attracts stringent regulatory and environmental compliance costs of going public.

Towards green steel-energy and CO2 assessment of low carbon steelmaking via hydrogen based shaft furnace direct reduction process

Under current stringent climate policies, the iron and steel industry, as a major contributor to industrial CO2 emissions, urgently needs the development of low-carbon metallurgical technologies. This work focuses on the hydrogen-based shaft furnace process, which can utilize green energy to significantly reduce CO2 emissions. This work combines the hydrogen-based shaft furnace CFD model, regression equations, and Aspen Plus model to develop a multi-gas source DR (Direct Reduction) plant model. This combination significantly reduces computation time while maintaining predictive accuracy. The transformation from COG (Coke Oven Gas)-DR to H2-DR plant was studied, showing that the top gas circulation process greatly reduces the net carbon input of the entire DR plant. However, the energy consumption of electrolytic hydrogen production limits the transformation of COG-DR plant to H2-DR plant. The process CO2 emissions depend largely on electrical energy footprint. Under traditional electrical energy footprint, the CO2 emissions of H2-DR-EAF (Electric Arc Furnace) route are about four times those of the COG-DR-EAF route. Only when using green source energy does the H2-DR-EAF route achieve the lowest CO2 emissions among all routes, at 344 kg/tls, which is 79 % lower than that of the BF (Blast Furnace)-BOF (Basic Oxygen Furnace) route.

Solar chimney design in rural areas of Anhui, China: CFD simulation, energy and carbon footprint assessment

China is currently undergoing a large-scale renovation of rural buildings. The solar chimney, a passive solar system, emerges as a cost-effective and easily implementable solution, particularly suitable for rural regions. This study designs a solar chimney in the Hui architectural style for renovating residential buildings in rural areas of Anhui province. A selected pilot building serves as the testbed for the solar chimney implementation, with plans to extend the design to other local renovation projects. Computational Fluid Dynamics (CFD) simulations are employed to compare various solar chimney configurations and identify the optimal design for the case study. Results from the CFD simulations highlight the optimal configurations for the pilot building's solar chimney design. Additionally, a comparative analysis of heating and cooling energy consumption is conducted between buildings with and without solar chimneys to assess the energy-saving potential. Furthermore, a life cycle assessment evaluates the environmental impacts of solar chimney construction and the environmental benefits during operation. It is revealed that the solar chimney can reduce building energy consumption. The greenhouse gas emissions associated with solar chimney construction can be offset within one year. The study presents an effect diagram illustrating the renovated building with a solar chimney. This study provides valuable insights into the application of solar chimneys in developing rural areas to enhance indoor comfort and promote energy savings. Additionally, it offers guidance for exploring optimal solar chimney configurations for specific geographical regions areas.

Self-catalysed breakdown of titanate nanotubes by graphitic carbon nitride resulting in enhanced hydrogen production

Efficient design of a photocatalyst is an important step in realizing real world applications. In this work, using in-situ catalysis we have prepared and investigated a titanate nanotube (TiNT)/ graphitic carbon nitride nanocomposite, which after optimization shows excellent hydrogen production efficiency of 2.3 mmolg−1h−1, much improved compared to GCN, which achieved a rate of 0.56 mmolg−1h−1. We can conclude that pyrolysis of urea to carbon nitride also self catalyses the breakdown of TiNT into anatase TiO2 nanoparticles, resulting in a nanocomposite material comprising TiO2 and heterojunctions with GCN. After heating and modification the TiO2 shows a conduction band edge with a more negative potential than the H+/H2 potential, which along with the ideal position of the GCN CB edge facilitates hydrogen production under light irradiation. This novel method can be viewed as a general method for improving catalysis synthesis and design, whilst simultaneously reducing the complexity and energy footprint of active catalyst synthesis.

Understanding Nanoscale Interactions between Minerals and Microbes: Opportunities for Green Remediation of Contaminated Sites.

In situ contaminant degradation and detoxification mediated by microbes and minerals is an important element of green remediation. Improved understanding of microbe-mineral interactions on the nanoscale offers promising opportunities to further minimize the environmental and energy footprints of site remediation. In this Perspective, we describe new methodologies that take advantage of an array of multidisciplinary tools─including multiomics-based analysis, bioinformatics, machine learning, gene editing, real-time spectroscopic and microscopic analysis, and computational simulations─to identify the key microbial drivers in the real environments, and to characterize in situ the dynamic interplay between minerals and microbes with high spatiotemporal resolutions. We then reflect on how the knowledge gained can be exploited to modulate the binding, electron transfer, and metabolic activities at the microbe-mineral interfaces, to develop new in situ contaminant degradation and detoxication technologies with combined merits of high efficacy, material longevity, and low environmental impacts. Two main strategies are proposed to maximize the synergy between minerals and microbes, including using mineral nanoparticles to enhance the versatility of microorganisms (e.g., tolerance to environmental stresses, growth and metabolism, directed migration, selectivity, and electron transfer), and using microbes to synthesize and regenerate highly dispersed nanostructures with desired structural/surface properties and reactivity.

Optimisation of Water-Use in Pulp and Paper Mills: A Streamlined Review of Scientific Journal Publications

The water-, and energy footprints of the processes in the pulp and paper industry are sizable enough to warrant investment of money and commitment of time truncate the same. Besides, there is also a nexus between water and energy here, with optimisation of the use of one of these resoruces enabling that of the other too. This streamlined review focuses on journal publications (originating from different parts of the world, and targeted at researchers and decision-makers in the industry) which train the lens on the optimisation of water use in this particular sector of the (forestry) bioeconomy. The synergies and complementarities which exist among different sustainable development goals (SDGs) , promise positive ripple effects, caused by attending to the truncation of the water footprint. The articles, in general, recommend effective in-plant wastewater treatment in combinaton with recirculating the treated effluent, and looking upon the water streams as carriers or bearers of valorisable substances – organics which can yield a host of bio-products in bio-refineries, including bio-energy. Availing of water-pinch analysis as a tool to uncover possibilities of water use in a cascade (depending upon the requirements imposed on the water, by processes downstream in the cascade), has been shown to aid in the optimisation of both water use and energy demand within the plant. One case study, for example, showed that the demand for steam can be decreased by about 4 GJ per ton of output, by recovering the waste heat in the water streams.

A comprehensive energy, water and carbon footprint analysis of petroleum fuel production in Iran: an allocation approach with uncertainty quantification

A comprehensive energy, water and carbon footprint analysis of petroleum fuel production in Iran: an allocation approach with uncertainty quantification

Transparent metal oxide-based robust, porous, and thin polyurethane coatings for IR, and UV blocking and photocleaning terylene textiles

IR radiations from the sun increases the internal temperature of the buildings when transmitted through glass windows. To reduce this elevated temperature, air conditioning systems are used that consume a large share of total energy expenditure which harms the energy footprints of the ecosystem. To combat this problem IR radiation must be blocked, thereby not affecting visible light transmission. Conductive metal oxides have been found effective in blocking IR radiation. In this work, antimony-doped tin oxide sub-20 nm particles were synthesized by co-precipitation method. The synthesized nanoparticles were homogenously dispersed within polyurethane latex that later encrusted onto polyester textiles for IR-blocking properties. The coated fabrics simultaneously achieve excellent shielding of NIR (90 %) and high transmittance of visible light (80 %), which makes them an ideal material to alleviate the current building energy consumption issues that correspond to a greater than 20 % saving on indoor cooling/heating. These fabrics equally bear other special features such as strength, self-cleaning, and photoactivity required by such furnishing clothes. The developed IR blocking fabric will ensure a sustainable future with a less adverse load on the energy footprints of the ecosystem and thus make human settlements resilient and tackle the impacts of climate change.

Quantifying energy footprint inequalities across different socio-economic segments in Spain

To achieve the ambitious climate targets set for 2050, it is essential to understand the energy footprints resulting from different lifestyles. This research aims to analyse the variation in direct and embedded energy consumption across different Spanish autonomous communities and socio-economic segments. To do so, we combine the Global Multi-Regional Input-Output methodology (GMRIO) with microdata from Household Budget Surveys (HBS). The findings show that income, household size, and nationality significantly affect the energy footprint of individuals. High-income households have an energy footprint of up to 63.3 MWh·cap−1·yr−1, 75.0% higher than national average. Furthermore, individuals living alone show a 41.4% larger consumption than the national average. In contrast, households with foreign nationalities show an energy footprint of 24.7 MWh·cap−1·yr−1, a 31.8% reduction over national average. On the other hand, differences in gender, age, or municipality size do not play a significant role in energy footprint variations. The energy footprint and the Gross Domestic Product are significantly correlated, as wealthier regions have a TPEF of 17.6% above the national average, while poorer regions show a 31.6% decrease in footprint. Altogether, this work suggests ways to reduce energy consumption in lifestyles, providing specific actions in policy-making.