Search Results (63)

The paper explores the pressing issue of energy consumption in machine learning (ML) models and their environmental footprint. As ML technologies, especially large-scale models, continue to surge in popularity, their escalating energy demands and corresponding CO₂ emissions are drawing critical attention. The article dives into innovative strategies to curb energy use in ML applications without compromising—and often even enhancing—model performance. Key techniques, such as model compression, pruning, quantization, and cutting-edge hardware design, take center stage in the discussion. Beyond operational energy use, the paper spotlights a pivotal yet often overlooked factor: the substantial emissions tied to the production of ML hardware. In many cases, these emissions eclipse those from operational activities, underscoring the immense potential of optimizing manufacturing processes to drive meaningful environmental impact. The narrative reinforces the urgency of relentless advancements in energy efficiency across the IT sector, with machine learning and data science leading the charge. Furthermore, deploying ML to streamline energy use in other domains like industry and transportation amplifies these benefits, creating a ripple effect of positive environmental outcomes. The paper culminates in a compelling call to action: adopt a dual-pronged strategy that tackles both operational energy efficiency and the carbon intensity of hardware production. By embracing this holistic approach, the artificial intelligence (AI) sector can play a transformative role in global sustainability efforts, slashing its carbon footprint and driving momentum toward a greener future. Full article

Greenhouse gases (GHGs) significantly shape global climate systems by driving temperature rises, disrupting weather patterns, and intensifying environmental imbalances, with direct consequences for human life, including rising sea levels, extreme weather, and threats to food security. Accurate forecasting of GHG concentrations is crucial for crafting effective climate policies, curbing carbon emissions, and fostering sustainable development. However, current models often struggle to capture multi-scale temporal patterns and demand substantial computational resources, limiting their practicality. This study presents MST-GHF (Multi-Scale Temporal Greenhouse Gas Forecasting), an innovative framework that integrates daily and monthly CO₂ data through a multi-encoder architecture to address these challenges. It leverages an Input Attention encoder to manage short-term daily fluctuations, an Autoformer encoder to capture long-term monthly trends, and a Temporal Attention mechanism to ensure stability across scales. Evaluated on a fifty-year NOAA dataset from Mauna Loa, Barrow, American Samoa, and Antarctica, MST-GHF surpasses 14 baseline models, achieving a Test_R² of 0.9627 and a Test_MAPE of 1.47%, with notable stability in long-term forecasting. By providing precise GHG predictions, MST-GHF empowers policymakers with reliable data for crafting targeted climate policies and conducting scenario simulations enabling proactive adjustments to emission reduction strategies and enhancing sustainability by aligning interventions with long-term environmental goals. Its optimized computational efficiency, reducing resource demands compared to Transformer-based models, further strengthens sustainability in climate modeling, making it deployable in resource-limited settings. Ultimately, MST-GHF serves as a robust tool to mitigate GHG impacts on climate and human life, advancing sustainability across environmental and societal domains. Full article

In recent years, the effects of global climate change have become more apparent, and reducing energy-derived CO₂ emissions has become an important issue. The purpose of this study is to evaluate the CO₂ emission reduction effect according to energy conservation scenarios in the residential sector, based on actual data. In this study, we set up energy-saving scenarios assuming the implementation of energy-saving behavior and the replacement of energy-consuming equipment and calculated the CO₂ emission reduction effects of energy conservation for cooling, heating, and hot water using individual data from a large-scale survey of 29,161 samples. Consequently, we could quantify the relationship between the set scenarios and the associated CO₂ reduction effects. Based on the results, we compared countermeasures and considered their respective potentials. However, despite there being an aggressive scenario in which all households implemented energy conservation measures, the calculated savings were limited. Therefore, we also considered the potential of demand response as a rough estimate. The results indicated that, while continued efforts to curb energy demand are necessary, a comprehensive countermeasure approach is important for achieving carbon neutrality. Full article

With global climate challenges intensifying, the cement industry, as a major CO₂ emitter, has attracted significant attention regarding its emission reduction potential and strategies. Advanced economies like the European Union use carbon pricing to spur innovation, while emerging countries focus on incremental solutions, such as fuel substitution. Combining LMDI decomposition and the LEAP model, this study examines Jiangsu Province as a test bed for China’s decarbonization strategy, a highly efficient region with carbon intensity 8% lower than the national average. Historical analysis identifies carbon intensity, energy mix, energy intensity, output scale, and economic effects as key drivers of emission changes. Specifically, the reduction in cement production, real estate contraction, lower housing construction, and reduced production capacity are the main factors curbing emissions. Under an integrated technology strategy—including energy efficiency, fuel and clinker substitution, and CCS—CO₂ emissions from Jiangsu’s cement sector are projected to decrease to 17.28 million tons and 10.9 million tons by 2060 under high- and low-demand scenarios, respectively. Clinker substitution is the most significant CO₂ reduction technology, contributing about 60%, while energy efficiency gains contribute only 3.4%. Despite the full deployment of existing reduction methods, Jiangsu’s cement industry is expected to face an emissions gap of approximately 10 million tons to achieve carbon neutrality by 2060, highlighting the need for innovative emission reduction technologies or carbon trading to meet carbon neutrality goals. Full article

There is growing awareness that there is a link between climate change and human influence and that human activities contribute to the warming of the atmosphere. The research identifies two ways to prepare cities to meet the challenges: the first is to optimize the way the urban organism functions by containing CO₂ emissions and consumption of nonrenewable resources by indicating strategies to regenerate the existing city according to an ecosystem approach; the second is to preserve the natural areas of the peri-urban area through graded forms of protection and enhancement by curbing the settlement thrusts of the existing city. The article illustrates two case studies for comparison (Reggio Calabria and Enna) chosen in the context of two Italian regions. Both have urban planning laws that provide for new urban planning instruments sensitive to these aspects. The two case studies were selected because of the similarity of their physical characteristics and the types of agricultural production affecting large areas of land, which has been partially compressed over the years. The respective regional regulations provide solutions to increase protection while allowing for better sustainable use and enhancement. Full article

This study investigates the complex interconnections between renewable energy adoption, carbon dioxide (CO₂) emissions, and economic factors in 50 countries marked by high rates of coronary heart disease (CHD) between 2000 and 2020. Utilizing a sophisticated two-step system generalized method of moments (GMM) estimator and panel data method, our analysis reveals a significant negative impact of renewable energy on greenhouse gas emissions, emphasizing the role of sustainable energy sources in mitigating environmental and quality of life degradation. Additionally, our findings support the existence of the environmental Kuznets curve (EKC), demonstrating an inverted U-shaped relationship between gross domestic product (GDP) per capita and CO₂ emissions. In line with nascent studies, the EKC for CO₂ emissions suggests that as a country’s GDP per capita increases, the CO₂ emissions initially rise but eventually decline after reaching a certain level of economic development, forming an inverted U-shaped relationship. Specifically, nations facing high cardiovascular heart disease mortality rates display an important link between renewable energy integration and improved environmental quality. These insights underscore the urgency for countries to transition rapidly to green energy, advocating for policies that promote renewable technologies through partnerships between the public, private sector, and government entities. Furthermore, the study emphasizes the necessity of innovative structural reforms in developing countries to stimulate economic growth beyond the EKC turning point, ensuring sustainable development while curbing their carbon footprint resulting from economic activities. Future research should explore the broader global contexts, considering variables like social capital and globalization to inform targeted policies aimed at safeguarding public health and the environment. Full article

Methane is a powerful greenhouse gas with a 25 times higher 100-year warming potential than carbon dioxide and is a target for mitigation to achieve climate goals. To control and curb methane emissions, estimates are required from the sources and sectors which are typically generated using bottom-up methods. However, recent studies have shown that national and international bottom-up approaches can significantly underestimate emissions. In this study, we present three bottom-up approaches used to estimate methane emissions from all emission sectors in the Denver-Julesburg basin, CO, USA. Our data show emissions generated from all three methods are lower than historic measurements. A Tier 1/2 approach using IPCC emission factors estimated 2022 methane emissions of 358 Gg (0.8% of produced methane lost by the energy sector), while a Tier 3 EPA-based approach estimated emissions of 269 Gg (0.2%). Using emission factors informed by contemporary and region-specific measurement studies, emissions of 212 Gg (0.2%) were calculated. The largest difference in emissions estimates were a result of using the Mechanistic Air Emissions Simulator (MAES) for the production and transport of oil and gas in the DJ basin. The MAES accounts for changes to regulatory practice in the DJ basin, which include comprehensive requirements for compressors, pneumatics, equipment leaks, and fugitive emissions, which were implemented to reduce emissions starting in 2014. The measurement revealed that normalized gas loss is predicted to have been reduced by a factor of 20 when compared to 10-year-old normalization loss measurements and a factor of 10 less than a nearby oil and production area (Delaware basin, TX); however, we suggest that more measurements should be made to ensure that the long-tail emission distribution has been captured by the modeling. This study suggests that regulations implemented by the Colorado Department of Public Health and Environment could have reduced emissions by a factor of 20, but contemporary regional measurements should be made to ensure these bottom-up calculations are realistic. Full article

A number of factors will increasingly play a role in the sustainability of wine production in the coming period. The current situation suggests that the analysis of energy consumption and greenhouse gas (GHG) emissions will play a particularly important role. The so-called carbon footprint, expressed in CO₂ equivalents, is used to express the sum of GHG emissions. This study presents an analysis of vine cultivation in a particular Central European region, with the main focus on quantifying the inputs, yield, fuel consumption, and GHG emissions. The emphasis was placed on conventional, integrated, and ecological production systems of growing, evaluated with the help of the developed AGROTEKIS version 5 software. A total of 30 wine-grower entities in the Morava wine-growing region, the subregion Velké Pavlovice, in the Czech Republic weather climate, were included in the input data survey. By analyzing the aggregated values, the real savings in energy and curbing of CO₂ emissions of vineyards could be observed, relating to individual work procedures with lower energy demand used in the vineyard treatment as well as the amounts and doses of agrochemicals used. The average values of the total impacts did not show any statistically significant differences between the conventional (971 ± 78 kg CO₂eq·ha⁻¹·year⁻¹) and integrated production systems (930 ± 62 kg CO₂eq·ha⁻¹·year⁻¹), whereas the values for the ecological production system were significantly higher (1479 ± 40 kg CO₂eq·ha⁻¹·year⁻¹). The results show that growing vines under ecological production conditions generates a higher proportion of the carbon footprint than under conventional production conditions. Overall, the best results can be achieved in an integrated production system. Full article

Approximately 25% of global carbon emissions come from food production. Renewable fuels are crucial for curbing greenhouse gas (GHG) emissions from vehicles, non-road machines, and agricultural machinery. Tractors, key to modern farming, are central to these efforts. As agriculture strives for sustainability, alternative fuels like methanol and hydrotreated vegetable oil (HVO) are arousing interest because they are renewable and offer potential for blending for use in diesel engines. Methanol and HVO have limited solubility in direct mixing, so the addition of a co-solvent is essential. This study addresses the research gap regarding the properties of HVO and methanol blends with co-solvents. It investigated the impact of three co-solvents, 1-dodecanol, 1-octanol, and methyl butyrate, on the miscibility of HVO and methanol. The experimental measurements cross-varied the co-solvent type with different blending ratios (MeOH5 and MeOH10). Investigated parameters include fuel density, kinematic viscosity, distillation properties, and surface tension. The co-solvents enabled the formation of a singular, clear, and homogeneous phase in methanol-HVO blends. The co-solvent 1-dodecanol demonstrated the highest solubilizing capacity for MeOH5 and MeOH10 blends, followed by 1-octanol. Adding co-solvents led to increased fuel density, decreased kinematic viscosity, and small changes in surface tension. These findings contribute to the optimization of methanol–HVO fuel blends for efficient and environmentally friendly use in vehicles, non-road machinery, and agricultural machinery. Full article

A complex evaluation of antimicrobial activities of microalgae, including those relevant to wastewater treatment (WWT), in light of the integrated biorefinery concept, is performed. An example of this concept is linking a commercial microalgal system to plants, factories, or farms that emit polluted wastewater (WW). The microalgae would not only metabolize the pollutants—such as nitrogen (N) and phosphorus (P)—from the WW, thus fueling their biomass, but they would exert an antibacterial effect against the pathogenic bacteria there. The biomass then could be harvested and used for biofertilizers, biofuels, and bioplastics and might possibly be utilized as animal feed, antimicrobial and other pharmaceutical agents. A large amount of the research on the antimicrobial activity and WWT potential focuses on the families Chlorellaceae and Scenedesmaceae, which are also some of the most commercially used strains of microalgae. For that reason, they are the species chosen for the current review. Furthermore, the increasing antimicrobial resistance necessitates the search for antibiotic alternatives, and the antibacterial and antifungal activity of Chlorellaceae and Scenedesmaceae is very promising. Microalgae are rich in antibacterial compounds like polyunsaturated fatty acids (PUFAs), polysaccharides, carotenoids, proteins, etc., and for that reason, their extracts possess antimicrobial effects. The in vitro antimicrobial activity of Chlorellaceae and Scenedesmaceae families has varied in a broad range from low to strong activity or no effect. Several strains have fulfilled the criteria for outstanding and high activity, especially C. vulgaris and other Chlorellaceae spp., with an effect equal to or better than the control antibiotics. There were several strains with minimum inhibitory concentrations (MIC) below 80 µg/mL and even 10 and 1.5 µg/mL; some species also had inhibition zones (IZ) over 30 mm, even as high as 48 mm. In vivo results are also promising but scarce, and all this warrants further in vivo and in situ studies—from animal models to clinical and environmental trials. Altogether, important data in the light of the circle economy, the urgent necessity to decrease CO₂ emissions to fight climate change, and to curb the harmful influence of future pandemics are presented. This review paves the way for further utilizing the total potential of a microalgal system. Full article

Croatia has both significant CO₂ emissions from the point sources and a history of oil and gas exploration, and this is why the CCS technology surfaced as a viable solution for curbing CO₂ emissions on a national level. Since approximately half of emissions from the stationary industrial sources occur along the Adriatic coastline, the entire offshore area became an exploration target. Regional studies revealed the potential storage plays, one of which is in the aquifer of the Mesozoic carbonate complex with dual porosity extending all along the Croatian offshore area. Three structures were chosen in its central part–Klara, Kate and Perina. For the first two, the models were constructed based on the data from old exploration wells and a regional structural map, while for the Perina structure, a new seismic interpretation was added to better characterise its properties. It came out that the Kate structure appears to be the most prospective in general (45 Mt), with neighbouring Klara as the second (39 Mt), while the initially promising Perina (7 Mt) turned out to be of far lesser importance. The Perina structure case is an example that new seismic interpretation can reduce the capacity estimate if it reveals certain limiting factors, in this case, the limitation of structural closure. Full article

The dairy industry is facing criticism for its role in exacerbating global GHG emissions, as climate change becomes an increasingly pressing issue. These emissions mostly originate from methane (CH₄), nitrous oxide (N₂O), and carbon dioxide (CO₂). An optimal strategy involves the creation of an economical monitoring device to evaluate methane emissions from dairy animals. Livestock production systems encounter difficulties because of escalating food demand and environmental concerns. Enhancing animal productivity via nutrition, feeding management, reproduction, or genetics can result in a decrease in CH₄ emissions per unit of meat or milk. This CH₄ unit approach allows for a more accurate comparison of emissions across different animal production systems, considering variations in productivity. Expressing methane emissions per unit allows for easier comparison between different sources of emissions. Expressing emissions per unit (e.g., per cow) highlights the relative impact of these sources on the environment. By quantifying emissions on a per unit basis, it becomes easier to identify high-emission sources and target mitigation efforts accordingly. Many environmental policies and regulations focus on reducing emissions per unit of activity or output. By focusing on emissions per unit, policymakers and producers can work together to implement practices that lower emissions without sacrificing productivity. Expressing methane emissions in this way aligns with policy goals aimed at curbing overall greenhouse gas emissions. While it is true that total emissions affect the atmosphere globally, breaking down emissions per unit helps to understand the specific contributions of different activities and sectors to overall greenhouse gas emissions. Tackling cattle health issues can increase productivity, reduce GHG emissions, and improve animal welfare. Addressing livestock health issues can also provide favourable impacts on human health by reducing the prevalence of infectious illnesses in livestock, thereby mitigating the likelihood of zoonotic infections transmitting to humans. The progress in animal health offers the potential for a future in which the likelihood of animal diseases is reduced because of improved immunity, more effective preventative techniques, earlier identification, and innovative treatments. The primary objective of veterinary medicine is to eradicate clinical infectious diseases in small groups of animals. However, as the animal population grows, the emphasis shifts towards proactive treatment to tackle subclinical diseases and enhance production. Proactive treatment encompasses the consistent monitoring and implementation of preventive measures, such as vaccination and adherence to appropriate nutrition. Through the implementation of these measures, the livestock industry may enhance both animal well-being and mitigate the release of methane and nitrous oxide, thereby fostering environmental sustainability. In addition, advocating for sustainable farming methods and providing farmers with education on the significance of mitigating GHG emissions can bolster the industry’s endeavours to tackle climate change and infectious illnesses. This will result in a more robust and environmentally sustainable agriculture industry. This review seeks to conduct a thorough examination of the correlation between the health condition of cattle, the composition of milk produced, and the emissions of methane gas. It aims to identify areas where research is lacking and to provide guidance for future scientific investigations, policy making, and industry practices. The goal is to address the difficulties associated with methane emissions in the cattle industry. The primary global health challenge is to identify the causative relationship between climate change and infectious illnesses. Reducing CH₄ and N₂O emissions from digestive fermentation and animal manure can be achieved by improving animal well-being and limiting disease and mortality. Full article

The energy sector faces a pressing need for significant transformation to curb CO₂ emissions. For instance, Czechia and Germany have taken steps to phase out fossil thermal power plants by 2038, opting instead for a greater reliance on variable renewable energy sources like wind and solar power. Nonetheless, thermal power plants will still have roles, too. While the conventional multistage axial turbine design has been predominant in large-scale power plants for the past century, it is unsuitable for small-scale decentralized projects due to complexity and cost. To address this, the study investigates less common turbine types, which were discarded as they demonstrated lower efficiency. One design is the Elektra turbine, characterized by its velocity compounded radial re-entry configuration. The Elektra turbine combines the advantages of volumetric expanders (the low rotational speed requirement) with the advantages of a turbine (no rubbing seals, no lubrication in the working fluid, wear is almost completely avoided). Thus, the research goal of the authors is the implementation of a 10 kW-class ORC turbine driving a cost-effective off-the-shelf 3000 rpm generator. The paper introduces the concept of the Elektra turbine in comparison to other turbines and proposes this approach for an ORC working fluid. In the second part, the 1D design and 3D–CFD optimization of the 7 kW Elektra turbine working with Hexamethyldisiloxane (MM) is performed. Finally, CFD efficiency characteristics of various versions of the Elektra are presented and critically discussed regarding the originally defined design approach. The unsteady CFD calculation of the final Elektra version showed 46% total-to-static isentropic efficiency. Full article

This review focuses on the Just Energy Transition (JET) policies of the BRICS member countries with the aim of finding lessons and possibly adopting some of the key energy policy aspects utilised in other countries as a benchmark for the South African context. We consider the present stage of JET in South Africa while being cognisant of the energy source mix supporting the electricity sector and the lifespan and condition of its power plants. An analysis of the energy mix revealed that all nations are dependent on electricity for energy, which is produced predominantly from fossil-fuelled power plants with high GHG emissions (concentrating on high CO₂ emissions). It was concluded that some of the lessons learnt from the BRICS countries might be incorporated into a South African energy plan for the transition, with options and guidance for the formulation of policies. This study will attract a responsible, environmentally conscious audience that has the commitment and drive to combat global warming and curb climate change. Full article

Installations of decentralised renewable energy systems (RES) are becoming increasing popular as governments introduce ambitious energy policies to curb emissions and slow surging energy costs. This work presents a novel model for optimal sizing for a decentralised renewable generation and hybrid storage system to create a renewable energy community (REC), developed in Python. The model implements photovoltaic (PV) solar and wind turbines combined with a hybrid battery and regenerative hydrogen fuel cell (RHFC). The electrical service demand was derived using real usage data from a rural island case study location. Cost remuneration was managed with an REC virtual trading layer, ensuring fair distribution among actors in accordance with the European RED(III) policy. A multi-objective genetic algorithm (GA) stochastically determines the system capacities such that the inherent trade-off relationship between project cost and decarbonisation can be observed. The optimal design resulted in a levelized cost of electricity (LCOE) of 0.15 EUR/kWh, reducing costs by over 50% compared with typical EU grid power, with a project internal rate of return (IRR) of 10.8%, simple return of 9.6%/year, and return on investment (ROI) of 9 years. The emissions output from grid-only use was reduced by 72% to 69 gCO₂e/kWh. Further research of lifetime economics and additional revenue streams in combination with this work could provide a useful tool for users to quickly design and prototype future decentralised REC systems. Full article