Search Results (69)

The global energy transition and digitalization are reshaping traditional production and consumption paradigms. Green hydrogen is emerging as a key element for decarbonizing sectors like industry and transportation, offering a viable alternative to fossil fuels and a pathway toward mitigating climate change. However, implementing green hydrogen supply chains presents challenges related to traceability, operational efficiency, and process certification. This paper explores how blockchain and the Internet of Things can address these challenges and transform the green hydrogen supply chain. Using Morocco as a case study—a country with abundant renewable resources and a strategic focus on green hydrogen—this article proposes innovative technological solutions to support a sustainable energy transition and contribute to a more secure and energy-efficient future. We analyze the current state of research on blockchain, IoT, and green hydrogen, identify key areas for advancement, and present a proposed framework for integrating these technologies. Full article

Texas has abundant forest resources, and the forest sector contributes tremendously to the state economy. However, Texas has the lowest log truck weight limits among the neighboring states, which puts the state at a competitive disadvantage in the forest industry. This study examined the economic and environmental impacts of increasing log truck weight limits from 84,000 to 92,000 pounds across these supply chain sectors: forestry, logging, sawmills, and truck transportation. Economic estimation was conducted using IMPLAN with 2023 data, while the environmental impacts were assessed through a survey. Two scenarios, representing 12 and 13 percent efficiency improvements from the increased log truck weight limits, were analyzed using standard truck tare weights. The 12 percent efficiency improvement generated a total of 864 jobs, USD 56.31 million in labor income, USD 90.90 million in value added, and USD 189.91 million in industry output. While the 13 percent efficiency improvement generated a total of 936 jobs, USD 61.01 million in labor income, USD 98.52 million in value added, and USD 205.73 million in industry output. Additionally, the 12 percent and 13 percent efficiency improvements reduced annual fuel consumption by 4.69 million and 5.53 million liters and lowered carbon dioxide emissions by 12.61 thousand and 14.89 thousand tonnes, respectively. These results offer valuable insights for policymakers aiming to improve efficiency and profitability in the timber industry. Full article

Understanding the asymmetric relationship between manufacturing output and non-renewable energy consumption is critical for formulating sustainable economic policies, particularly in energy-dependent economies like Saudi Arabia (KSA). This study has two aims. First, it examines how the KSA’s manufacturing sector responds to different energy sources, emphasising non-renewable energy—unlike previous studies that primarily examined general economic growth. Second, it investigates the asymmetric impact of non-renewable energy shocks on manufacturing output. Using yearly data from 1990 to 2022, this study finds that positive shocks to non-renewable energy significantly enhance manufacturing output in both the short and long run, driven by the sector’s reliance on cheap fossil fuels. On the contrary, negative shocks disrupt supply chains, increase energy costs, and reduce output over the same periods. In addition, this study reveals that renewable energy negatively affects manufacturing output due to transition costs and operational inefficiencies. However, gross fixed capital accumulation positively affects industrial production. These findings highlight the need for strategic investments in renewable energy infrastructure to mitigate the negative impacts of non-renewable energy disruptions, enhancing Saudi Arabia’s long-term economic stability. This study also underscores the importance of integrating sustainable development goals (SDGs) into policy frameworks to ensure a balanced and sustainable energy transition. Full article

The growing energy demands and increasing environmental concerns in industrial manufacturing necessitate innovative solutions to reduce fuel consumption and lower carbon emissions. This paper presents Sustain AI, a multi-modal deep learning framework that integrates Convolutional Neural Networks (CNNs) for defect detection, Recurrent Neural Networks (RNNs) for predictive energy consumption modeling, and Reinforcement Learning (RL) for dynamic energy optimization to enhance industrial sustainability. The framework employs IoT-based real-time monitoring and AI-driven supply chain optimization to optimize energy use. Experimental results demonstrate that Sustain AI achieves an 18.75% reduction in industrial energy consumption and a 20% decrease in CO₂ emissions through AI-driven processes and scheduling optimizations. Additionally, waste heat recovery efficiency improved by 25%, and smart HVAC systems reduced energy waste by 18%. The CNN-based defect detection model enhanced material efficiency by increasing defect identification accuracy by 42.8%, leading to lower material waste and improved production efficiency. The proposed framework also ensures economic feasibility, with a 17.2% reduction in operational costs. Sustain AI is scalable, adaptable, and fully compatible with Industry 4.0 requirements, making it a viable solution for sustainable industrial practices. Future extensions include enhancing adaptive decision-making with deep RL techniques and incorporating blockchain-based traceability for secure and transparent energy management. These findings indicate that AI-powered industrial ecosystems can achieve carbon neutrality and enhanced energy efficiency through intelligent optimization strategies. Full article

This study demonstrates that small-scale liquefied natural gas (SS LNG) is a viable and cost-effective alternative to High-Speed Diesel (HSD) for power generation in remote areas of Indonesia. An integrated supply chain model is developed to optimize total costs based on LNG inventory levels. The model minimizes transportation costs from supply depots to demand points and handling costs at receiving terminals, which utilize Floating Storage Regasification Units (FSRUs). LNG distribution is optimized using a Multi-Depot Capacitated Vehicle Routing Problem (MDCVRP), formulated as a Mixed Integer Linear Programming (MILP) problem to reduce fuel consumption, CO₂ emissions, and vessel rental expenses. The novelty of this research lies in its integrated cost optimization, combining transportation and handling within a model specifically adapted to Indonesia’s complex geography and infrastructure. The simulation involves four LNG plant supply nodes and 50 demand locations, serving a total demand of 15,528 m³/day across four clusters. The analysis estimates a total investment of USD 685.3 million, with a plant-gate LNG price of 10.35 to 11.28 USD/MMBTU at a 10 percent discount rate, representing a 55 to 60 percent cost reduction compared to HSD. These findings support the strategic deployment of SS LNG to expand affordable electricity access in remote and underserved regions. Full article

This study presents a Life Cycle Assessment (LCA) of a berry production system using osmotic dehydration and edible coating to extend the shelf life and improve the nutritional value. The goal is to evaluate environmental impacts, identify hotspots, and propose improvements. Osmotic dehydration is the main contributor to environmental impact, particularly due to the energy and resources required by apple juice as the osmotic agent. It contributes up to 0.64 kg CO₂ eq. per kg of blueberries, 1.36 kg CO₂ eq. per kg of raspberries, and 0.66 kg CO₂ eq. per kg of strawberries. The edible coating, however, has minimal environmental impact due to its low energy consumption and biodegradable materials. Packaging has a lower carbon footprint but contributes more to fossil fuel depletion and human toxicity. Raspberries show the highest human health impact (3.5 × 10⁻⁶ DALY/kg) and ecosystem impact (9.5 × 10⁻⁸ species.yr/kg), followed by strawberries (1.78 × 10⁻⁶ DALY/kg, 4.97 × 10⁻⁸ species.yr/kg) and blueberries (1.7 × 10⁻⁶ DALY/kg, 5.1 × 10⁻⁸ species.yr/kg), highlighting the greater environmental and health costs of raspberries. Despite the environmental burden of osmotic dehydration, it offers economic benefits by extending the shelf life, reducing losses, improving supply chain efficiency, and enhancing product quality, which leads to higher prices and profit margins. The study concludes that, while the environmental impacts of osmotic dehydration should be optimized, its economic and logistical benefits make it a promising preservation solution. Further research into eco-friendly practices is recommended to reduce ecological costs while maintaining commercial advantages. Full article

Most nations are shifting towards renewable energy sources to reduce energy-related emissions and achieve their net zero emissions targets by mid-century. Consequently, many attempts have been made to invest in clean, accessible, inexpensive, sustainable and reliable renewable energy sources while reducing dependency on fossil fuels. Recently, the production of biogas and upgrading it to produce biomethane is considered a sustainable way to reduce emissions from natural gas consumption. However, uncertainties in the biomass supply chain and less attention to decarbonising the natural gas grid have led to fewer investors in biomethane injection projects. Thus, researchers have applied Geographic Information System (GIS) as the best decision-making tool with spatial analytical and optimisation capabilities to address this issue. This study aims to review GIS-based applications on planning and optimising the biomass supply chain. Accordingly, this review covers different GIS-based biomass assessment methods with the evaluation of feedstock types, GIS-based approaches on selecting and optimising bioenergy plant locations and GIS-based applications on facilitating biomethane injection projects. This review identified four major biomass assessment approaches: Administrative division-based, location-based, cluster-based and grid-based. Sustainability criteria involved in site selection were also discussed, along with suitability and optimality techniques. Most of the optimising studies investigated cost optimisation based on a single objective. However, optimising the whole supply chain, including all operational components of the biomass supply chain, is still seldom investigated. Furthermore, it was found that most studies focus on site selection and logistics, neglecting biomethane process optimisation. Full article

Subject to pressures from resource exhaustion and environmental pollution, many countries have aimed to replace fossil fuels with renewable energy as part of their decarbonization strategy. In the post-pandemic era, countries are making efforts to explore a sustainable mode of economic development that features low resource consumption and less environmental pollution. Consumers are increasingly concerned about the environmental friendliness of energy products. In this study, we formulated four solutions for energy-saving optimization and control of the waste heat supply chain to conserve energy and compared the impact of a profit-as-incentive energy efficiency strategy and an energy efficiency incentive strategy on energy efficiency in the waste heat supply chain. Government agencies and enterprises can adopt a suitable strategy with the best current social and economic benefits to manage waste heat recovery. The profit-as-incentive energy efficiency strategy is more favorable for enterprises in the early stage of development. Under dual pressures of social attention to green energy and environmental protection, government agencies may adjust energy conservation policy to encourage enterprises to choose an energy efficiency incentive strategy to increase energy conservation. Full article

This research undertakes a comparative analysis of current and emerging hydrogen (H₂) production technologies, evaluating them based on quantitative and qualitative decision criteria. The quantitative criteria include cost of H₂ production (USD/kg H₂), energy consumption (MJ/kg H₂), global warming potential (kg CO₂-eq/kg H₂), and technology energy efficiency (%). The qualitative criteria encompass technology readiness level (TRL) and availability of supply chain materials (classified as low, medium, or high). To achieve these objectives, an extensive literature review has been conducted, systematically assessing the selected H₂ production technologies against the aforementioned criteria. The insights synthesized from the literature provide a foundation for an informed, science-based evaluation of the potentials and techno-economic challenges that these technologies face in achieving the 1-1-1 goal set by the U.S. Department of Energy (DOE) in 2021. This target aims for a H₂ production cost of USD 1/kg H₂ within one decade (by 2031), including costs associated with production, delivery, and dispensing at H₂ fueling stations (HRSs). Also, the DOE established an interim goal of USD 2/kg H₂ by 2026. This research concludes that among the examined H₂ production technologies, water electrolysis and biomass waste valorization emerge as the most promising near-term solutions to meet the DOE’s goal. Full article

The increasing use of renewable energy sources, such as wind and solar energy, presents challenges to the stability and efficiency of other energy sources due to their intermittent and unpredictable surpluses. The unintended consequence of stabilizing the power supply system is an increase in emissions and external costs from the suboptimal use of coal power plants. The rising number of RES curtailments needs to be addressed by either the adjusting energy supply from fossil fuel or the flexible energy consumption. In Poland’s energy mix, coal-fired power plants are a critical component in ensuring energy security for the foreseeable future. Using domestic lignite to generate a total power of 8.5 GW can stabilize the national power supply, as it is currently done in Germany, where 15 GW of lignite-fueled power units provide the power supply base for the country. The leading Belchatów power plant comprises 10 retrofitted units and one new unit, with a total rating of 5.5 GW. Access to the new coal deposit, Zloczew, is necessary to ensure its longer operation. The other domestic lignite power plants are located in Central Poland at Patnów (0.47 GW from the new unit and 0.6 GW from its three retrofitted counterparts) and located in the Lusatian lignite basin at Turów (operating a brand new unit rated at 0.5 GW and retrofitted units with a total rating of 1.5 GW). The use of this fuel is currently being penalized as a result of increasing carbon costs. However, the continuous surface mining technology that is used in lignite mines is fully electrified, and large amounts of electric energy are required to remove and dump overburden and mining coal and its conveying to power units (the transport of coal from the new lignite mine Zloczew to the Belchatów power plant would be a long-distance operation). A possible solution to this problem is to focus on the lignite fuel supply operations of these power plants, with extensive simulations of the entire supply chain. A modern lignite mine is operated by one control room, and it can balance the dynamic consumption of surplus renewable energy sources (RESs) and reduce the need for reduction. When a lignite supply chain is operated this way, a high-capacity power bank can be created with energy storage in the form of an open brown coal seam. This would enable an almost emission-free supply of cheap and domestic fossil fuel, making it insensitive to changes in the world prices of energy resources for power units operating at the base of the system. Furthermore, extending the life of relatively new and efficient lignite-fired units in Poland would facilitate the decommissioning of older and exhausted hard coal-fired units. Full article

The global rise in population and advancement in civilization have led to a substantial increase in energy demand, particularly in the industrial sector. This sector accounts for a considerable proportion of total energy consumption, with approximately three-quarters of its energy consumption being used for heat processes. To meet the Paris Agreement goals, countries are aligning policies with international agreements, and companies are setting net-zero targets. Upstream emissions of the Scope 3 category refer to activities in the company’s supply chain, being crucial for achieving its net-zero ambitions. This study analyzes heating solutions for the supply chain of certain globally operating companies, contributing to their 2030 carbon-neutral ambition. The objective is to identify current and emerging heating solutions from carbon dioxide equivalent (CO₂e) impact, economic, and technical perspectives, considering regional aspects. The methodology includes qualitative and quantitative surveys to identify heating solutions and gather regional CO₂e emission factors and energy prices. Calculations estimate the CO₂e emissions and energy costs for each technology or fuel, considering each solution’s efficiency. The study focuses on Europe, the United States, Brazil, China, and Saudi Arabia, regions or countries representative of companies’ global supply chain setups. Results indicate that heat pumps are the optimal solution for low temperatures, while biomass is the second most prevalent solution, except in Saudi Arabia where natural gas is more feasible. For medium and high temperatures, natural gas is viable in the short term for Saudi Arabia and China, while biomass and electrification are beneficial for other regions. The proportion of electricity in the energy mix is expected to increase, but achieving decarbonization targets requires cleaner energy mixes or competitive Power Purchase Agreement (PPA) projects. Brazil, with its high proportion of renewable energy sources, offers favorable conditions for using green electricity to reduce emissions. The utilization of biomethane is promising if costs and incentives align with those in the EU. Although not the objective of this study, a comprehensive analysis of CAPEX and lifecycle costs associated with equipment is necessary when migrating technologies. Policies and economic incentives can also make these solutions more or less favorable. Full article

Farm leftovers, particularly crop residues, are a key source of renewable energy in Canada. The nation’s robust agricultural industry provides ample biomass, derived from forestry and agriculture resources, for energy generation. Crop residues, such as straws and husks, play a crucial role in this biomass reservoir, contributing to biofuel production and greenhouse gas mitigation efforts. Focusing on supply chains, waste management, and emission reduction, this study evaluates the sustainability of wheat straw, an agricultural biomass by-product. The environmental issues of various approaches to managing agricultural biomass were explored. Following an evaluation of biomass features, conversion methods, and economic and environmental advantages, the results show anaerobic digestion to be the most sustainable approach. Four metrics were examined in relation to social elements, and numerous aspects were considered as inputs in the evaluation of transportation costs. The use of electric trucks versus fuel-based trucks resulted in an 18% reduction in total operating costs and a 58% reduction in consumption costs. This study examined CO₂ emissions over four different transportation distances. The data indicate that a significant reduction of 36% in kg CO₂ equivalent emissions occurred when the distance was lowered from 100 km to 25 km. These findings offer insights for creating practical plans that should increase the sustainability of agricultural biomass leftovers. Full article

Recent studies of Cardiovascular-Kidney-Metabolic Syndrome (CKMS) indicate that elevated concentrations of derivatives of phospholipids (ceramide, sphingosine), oxidized LDL, and lipoproteins (a, b) are toxic to kidney and heart function. Energy production for renal proximal tubule resorption of critical fuels and electrolytes is required for homeostasis. Cardiac energy for ventricular contraction/relaxation is preferentially supplied by long chain fatty acids. Metabolism of long chain fatty acids is accomplished within the cardiomyocyte cytoplasm and mitochondria by means of the glycolytic, tricarboxylic acid, and electron transport cycles. Toxic lipids and excessive lipid concentrations may inhibit cardiac function. Cardiac contraction requires calcium movement from the sarcoplasmic reticulum from a high to a low concentration at relatively low energy cost. Cardiac relaxation involves calcium return to the sarcoplasmic reticulum from a lower to a higher concentration and requires more energy consumption. Diastolic cardiac dysfunction occurs when cardiomyocyte energy conversion is inadequate. Diastolic dysfunction from diminished ATP availability occurs in the presence of inadequate blood pressure, glycemia, or lipid control and may lead to heart failure. Similar disruption of renal proximal tubular resorption of fuels/electrolytes has been found to be associated with phospholipid (sphingolipid) accumulation. Elevated concentrations of tissue oxidized low-density lipoprotein cholesterols are associated with loss of filtration efficiency at the level of the renal glomerular podocyte. Macroscopically excessive deposits of epicardial and intra-nephric adipose are associated with vascular pathology, fibrosis, and inhibition of essential functions in both heart and kidney. Chronic triglyceride accumulation is associated with fibrosis of the liver, cardiac and renal structures. Successful liver, kidney, or cardiac allograft of these vital organs does not eliminate the risk of lipid toxicity. Lipid lowering therapy may assist in protecting vital organ function before and after allograft transplantation. Full article

Zero-carbon shipping is the prime goal of the seaborne trade industry at this moment. The utilization of ammonia and liquid hydrogen propulsion in a carbon-free propulsion system is a promising option to achieve net-zero emission in the maritime supply chain. Meanwhile, optimal ship voyage planning is a candidate to reduce carbon emissions immediately without new buildings and retrofits of the alternative fuel-based propulsion system. Due to the voyage options, the precise prediction of fuel consumption and carbon emission via voyage operation profile optimization is a prerequisite for carbon emission reduction. This paper proposes a novel fuel consumption and carbon emission quantity prediction method which is based on the onboard measurement data of a smart ship. The prediction performance of the proposed method was investigated and compared to machine learning and LSTM-model-based fuel consumption and gas emission prediction methods. The results had an accuracy of 81.5% in diesel mode and 91.2% in gas mode. The SHAP (Shapley additive explanations) model, an XAI (Explainable Artificial Intelligence), and a CO₂ consumption model were employed to identify the major factors used in the predictions. The accuracy of the fuel consumption calculated using flow meter data, as opposed to power load data, improved by approximately 21.0%. The operational and flow meter data collected by smart ships significantly contribute to predicting the fuel consumption and carbon emissions of vessels. Full article

The sustainability of large economies is one of the most important challenges in today’s world. As the world strives to create a greener and more efficient future, it becomes necessary to accurately analyze and forecast freight volumes. By developing a reliable freight transportation forecasting model, the authors will be able to gain valuable insights into the trends and patterns that determine the development of economic systems. This will enable informed decisions on resource allocation, infrastructure development, and environmental impact mitigation. Such a model takes into account various factors such as market demand, logistical capabilities, fuel consumption, and emissions. Understanding these dynamics allows us to optimize supply chains, reduce waste, minimize our carbon footprint, and, ultimately, create more sustainable economic systems. The ability to accurately forecast freight volumes not only benefits businesses by enabling better planning and cost optimization but also contributes to the overall sustainable development goals of society. It can identify opportunities to shift to more sustainable modes of transportation, such as rail or water, and reduce dependence on carbon-intensive modes, such as road or air. In conclusion, the development and implementation of a robust freight forecasting model is critical to the sustainability of large-scale economic systems. Thus, by utilizing data and making informed decisions based on these forecasts, it is possible to work toward a more sustainable future for future generations. Full article