Search Results (6,395)

In 2021, the global electricity and heat sector recorded the highest increase in carbon dioxide (CO₂) emissions in comparison with the previous year, highlighting the ongoing challenges in reducing emissions within the sector. Therefore, combined heat and power (CHP) plants running on renewable fuels can play an important role in the energy transition by decarbonising a process, increasing the efficiency and capacity factor. Since 2003, Luxembourgish CHP plants have been transitioning from natural gas to biomass, mainly wood pellets. However, even though wood pellets are a renewable alternative, the market volatility in 2022 highlighted the vulnerability of a system reliant solely on one type of fuel. This study assesses the feasibility of using hydrogen to decarbonise a cogeneration plant powered by a natural gas-fuelled internal combustion engine. Although the technology to use hydrogen as a fuel for such systems already exists, a technical and economic analysis of implementing a hydrogen-ready plant is still lacking. Our results show that, from a technical perspective, retrofitting an existing power plant to operate with hydrogen is feasible, either by adapting or replacing the engine to accommodate hydrogen blends from 0 up to 100%. The costs of making the CHP plant hydrogen-ready vary depending on the scenario, ranging from a 20% increase for retrofitting to a 60% increase for engine replacement in the best-case scenarios. However, these values remain highly variable due to uncertainties associated with the ongoing technology development. From an economic standpoint, as of 2024, running the plant on hydrogen remains more expensive due to significant initial investments and higher fuel costs. Nevertheless, projections indicate that rising climate concerns, CO₂ taxes, geopolitical factors, and the development of the hydrogen framework in the region—through projects such as MosaHYc and HY4Link—could accelerate the competitiveness of hydrogen, making it a more viable alternative to fossil-based solutions in the near future. Full article

Bio-oil energy use in agricultural systems provides sustainable solutions for powering machinery operations and heating and cooling environments in facilities. However, its potential in South Africa is constrained by the limited availability of energy substrate that does not compromise food production, land use, and water resources. This study investigated the physical and chemical properties of six invasive alien plant species (IAPs), three woody species (Acacia mearnsii, Eucalyptus grandis, and Pinus patula), and three nonwoody species (Lantana camara, Chromolaena odorata, and Solanum mauritianum) to assess their suitability for bio-oil production. Key analyses included structural, elemental, proximate, atomic ratio, higher heating value (HHV), and thermogravimetric analysis (TGA) analyses. The results showed that woody IAPs had a significantly higher structural composition (p < 0.05), improving bio-oil yield. The bio-oil can be blended with diesel for agricultural use, while lignin-derived biochar serves as a soil amendment. Higher carbon and hydrogen contents enhanced HHV and combustion, while lower nitrogen and sulfur levels reduced emissions. Despite oxygen hindering pyrolysis, its bioactive properties support crop protection. Compared to South African coal, IAP-derived bio-oil shares similarities with peat coal and could be used for greenhouse heating. This study promotes energy efficiency in agriculture, reduces fossil fuel dependence, and supports environmental sustainability by repurposing IAPs. Additional studies should focus on lignin pretreatment and bio-oil upgrading to reduce oxygenated compounds. Full article

European beech (Fagus sylvatica L.) and Oriental beech (Fagus orientalis Lipsky) are ecologically and economically important tree species in European and western Asian forests, which are currently significantly affected by global climate change. To assess their response to climate variability, tree-ring data from 12 permanent research plots (PRPs) were analyzed in Central Europe and Turkey, covering an elevational gradient from 360 to 1430 m above sea level (a.s.l.). Using 360 tree cores, the relation between air temperature, precipitation, and climate-related stress on radial growth was investigated, alongside production potential and carbon sequestration. The results show that European beech is more sensitive to both air temperature and precipitation than Oriental beech. Carbon sequestration of forest stands ranged from 37 to 361 t·ha⁻¹ depending on the elevational gradient, with European beech storing, on average, 33.1% more carbon than Oriental beech stands. Radial growth was related to both air temperature and precipitation, with the strongest effects observed at mid-elevations (740–950 m a.s.l.). In European beech, both current and previous year temperatures significantly related to growth, whereas in Oriental beech, only the current year was critical. July was the most influential month for tree growth in both species. On PRPs located at lower elevations, radial growth over the past 20 years decreased by 13.1%–19.3% compared to the previous 20-year period, whereas in mountainous areas, it increased by 5.6%–9.8%. Low precipitation during the growing season was the main limiting factor for growth in lowland areas, whereas low temperatures were the primary constraint in mountainous regions, and vice versa. In recent years, the frequency of negative pointer years with extremely low radial growth has been increasing, reflecting a rising occurrence of climate extremes. These findings highlight species-specific climate sensitivities, emphasizing the importance of adaptive forest management strategies for mitigating global climate change impacts and increasing carbon sequestration. Full article

The slurry collected from the waste water resulting from ceramic tile processing contains significant amounts of quartz, kaolinite, and mullite, along with traces of iron hydroxides as observed using XRD analysis coupled with mineralogical optical microscopy (MOM). Such an admixture would be ideal for the development of ecologic building materials. Microstructural conditioning enhances the binding properties of kaolinite. Therefore, the influence of the vibration compaction of the moistened slurry at 30% humidity on the compressive strength was assessed. The compressive strength of the unvibrated sample is about 0.8 MPa with failure promoted by the microstructural unevenness. Several vibration amplitudes were tested from 20 to 40 mm. The optimal vibration mode was obtained at an amplitude of 25 mm for 10 min, ensuring a compressive strength of 2.37 MPa with a smooth and uniform failure surface involved within the binding layer as observed using SEM microscopy. The samples prepared under optimal conditions were thermally consolidated at 700, 800, and 900 °C below the mullitization temperature to ensure a low carbon footprint. XRD results reveal kaolinite dehydration in all fired samples, inducing its densification, which increases with increasing heating temperature. SEM coupled with EDS elemental investigations reveal that the dehydrated kaolinite better embeds quartz and mullite particles, ensuring a compact microstructure. The binding strength increases with the firing temperature. The mullite particles within the samples fired at 900 °C induce the partial mullitization of the dehydrated kaolinite matrix, increasing their homogeneity. The compression strength of the fired samples is temperature dependent: 4.44 MPa at 700 °C; 5.88 MPa at 800 °C, and 16.87 MPa at 900 °C. SEM fractography shows that failure occurs due to the dehydrated kaolinite matrix cracks and the quartz particles. The failure is rather plastic at low temperatures and becomes brittle at 900 °C. Reducing the firing temperature and treatment time reduces the carbon footprint of the consolidated ceramic parts. Samples fired at 700 °C exhibit a compressive strength comparable to low quality bricks, those fired at 800 °C exhibit a strength comparable to regular bricks, and those fired at 900 °C exhibit a superior strength comparable to high-quality bricks. Full article

Researchers and companies are placing increasing importance on sustainability to fight climate change. This study analyzes the sustainability of hotel installation, photovoltaic (PV) solar panels, and the transition from traditional lighting to light-emitting diode (LED) bulbs. The results show that for the PV system, the NPV (net present value) varied between 3191 and 11,959 kTND/kW and that the installation of PV panels has a positive NPV of 100% in the case of a high market scenario and 79–84% in the case of a scenario with reduced market activity. Regarding energy optimization, the use of LED bulbs generates an NPV of 346 to 713 TND/bulb, depending on self-consumption and the cost of electricity. Ecological studies show that installing PV panels would reduce carbon dioxide emissions by 424 gCO2eq/kWh, or 61 tCO2eq/year. Furthermore, social evaluations have shown the importance of the use of renewable energy from an energy optimization point of view for the ecological transition. In conclusion, green investments improve the sustainability of hotels. However, to fully exploit this potential, a change in consumer attitudes is needed. Hotels must continue to promote their sustainability efforts while making their guests aware of the importance of making eco-friendly choices. Only a combined approach, involving both hoteliers and guests, will achieve a sustainable transition in the hotel sector. The objective of this article is therefore to examine the multidisciplinary interactions between photovoltaic solar energy and sustainable development by highlighting the inherent opportunities of this multidisciplinary approach for their success in the hospitality sector. Our methodological approach therefore combines a theoretical and a numerical study. These studies play a major role in energy transition projects due to their economic, environmental, technical, and technological contributions, which proves the importance of the multidisciplinary approach to address the energy transition in a holistic way. Full article

The electromagnetic properties of 3D-printed carbon–carbonyl iron powder (CIP) composites are studied in the radio (20 Hz–1 MHz) and microwave (26–37 GHz) frequency ranges. Relatively high electrical conductivities (about several hundred S/m), typical for these structures in the radio frequency range, are observed. The temperature dependence of electrical conductivity is described by Arrhenius’ law, with distinct activation energies above and below a critical temperature, attributed to electron transport through various defects. The microwave properties of the investigated structures are particularly noteworthy. For instance, a 2 mm-plate with 20 wt.% magnetic inclusions achieves 52% absorption at 35 GHz. The microwave dielectric properties of the composite structures strongly depend on the concentration of carbonyl iron particles, with the highest values of the imaginary part of complex dielectric permittivity observed in carbon structures containing 20 wt.% CIP. Moreover, carbon composites with the highest CIP concentration exhibited interesting resonance states, demonstrating significant potential for Salisbury screen applications. Full article

This paper provides a comprehensive review of the integration of carbon capture, utilization, and storage (CCUS) technologies in waste-to-energy (WtE) plants, specifically focusing on incineration, the most adopted process for managing residual waste fractions that cannot be recycled. The review examines the current CO₂ capture technologies, including the widely used monoethanolamine (MEA) absorption method, and explores emerging alternatives such as molten carbonate fuel cells and oxyfuel combustion. Additionally, the paper discusses the management options for the captured CO₂, exploring both storage (CCS) and utilization (CCU) options, with a focus on current storage projects involving CO₂ from WtE plants and the potential for its use in sectors like chemicals, construction materials, and synthetic fuels. Currently, only four large-scale WtE plants worldwide have successfully implemented carbon capture technologies, with a combined capacity of approximately 78,000 tons of CO₂ per year. However, numerous feasibility studies and pilot-scale projects are ongoing, particularly in northern Europe, with countries such as Norway, the Netherlands, Sweden, the United Kingdom, and Finland leading the way in the development of CO₂ capture, storage, and utilization strategies within the WtE sector. The paper further discusses techno-economic issues for CCUS implementation, including energy demands and associated costs. The use of MEA systems in WtE plants leads to significant energy penalties, reducing plant efficiency by up to 40%. However, alternative technologies, such as advanced amines and calcium looping, could provide more cost-effective solutions by improving energy efficiency and reducing the overall costs. Life cycle assessment studies indicate that CCUS has the potential to significantly reduce CO₂ emissions, but the achievable environmental benefits depend on factors such as energy consumption, process efficiency, and system integration. Overall, while the implementation of CCUS in WtE plants presents CO₂ mitigation potential and may also be exploited to achieve other benefits, energy requirements and economic viability remain challenging. Full article

Maritime transportation is responsible for most global trade and is generally considered more environmentally efficient compared to other modes of transport, particularly for long-distance trade. With increasingly stringent emission regulations, however, accurately quantifying emissions and identifying their key determinants has become essential for effective environmental management. This study introduced a structured and comparative statistical modeling framework for ship-based emission modeling using gross tonnage (GT) as the primary predictor variable, due to its strong correlation with emission levels. Emissions for hydrocarbon (HC), carbon monoxide (CO), particulate matter with an aerodynamic diameter of less than 10 μm (PM10), carbon dioxide (CO₂), sulfur dioxide (SO₂), nitrogen oxides (NO_x), and volatile organic compounds (VOC) were estimated using a bottom-up approach based on emission factors and formulas defined by the U.S. Environmental Protection Agency (EPA), using data from 38,304 vessel movements through the Bosphorus in 2021. These EPA-estimated values served as dependent variables in the modeling process. The modeling framework followed a three-step strategy: (1) outlier detection using Rosner’s test to reduce the influence of outliers on model accuracy, (2) curve fitting with 12 regression models representing four curve types—polynomial (e.g., linear, quadratic), concave/convex (e.g., exponential, logarithmic), sigmoidal (e.g., logistic, Gompertz, Weibull), and spline-based (e.g., cubic spline, natural spline)—to capture diverse functional relationships between GT and emissions, and (3) model comparison using difference performance metrics to ensure a comprehensive assessment of predictive accuracy, consistency, and bias. The findings revealed that nonlinear models outperformed polynomial models, with spline-based models—particularly natural spline and cubic spline—providing superior accuracy for HC, PM₁₀, SO₂, and VOC, and the Weibull model showing strong predictive performance for CO and NO_x. These results underscore the necessity of using pollutant-specific and flexible modeling strategies to capture the intricacies of maritime emission dynamics. By demonstrating the advantages of flexible functional forms over standard regression techniques, this study highlights the need for tailored modeling strategies to better capture the complex relationships in maritime emission data and offers a scalable and transferable framework that can be extended to other vessel types, emission datasets, or maritime regions. Full article

The Paris Agreement is aimed at keeping global warming well below 2 °C while pursuing efforts to limit it below 1.5 °C; however, achieving these goals implies a tight limit on cumulative net carbon emissions, which includes CO₂, CH₄, and NO₂. Moreover, the focus of carbon emission policies should differ from country to country depending on their national circumstances. In this study, based on forecast models, specifically, in 2005, the average annual per-capita CO₂ emissions was recorded as 6.8 tons for Brazil, 4.8 tons for China, 8.4 tons for EU28, 1.2 tons for India, 10.1 tons for Japan, 9.0 tons for Russia, and 18.6 tons for the USA. The carbon intensity is expected to range from 37% to 85% across the studied regions. Based on the AIM, POLES, and IMAGE models, the projected carbon prices for 2050 are estimated at USD 2000, USD 2045, and USD 940 per ton of CO₂, measured in 2005 US dollars, respectively. The forecast data support carbon policy making in major countries. Full article

Sustainable storage and transport of hydrogen are challenges in the transition to renewable energy sources. Hydrogen embrittlement (HE), caused by atomic hydrogen absorption and diffusion into steel, influences the mechanical properties of steel pipelines and reservoirs. This work focuses on the hydrogen diffusion on X60 pipeline steel using electrochemical measurements and X-ray photoelectron spectroscopy (XPS). The hydrogen permeation tests (HPT) were performed to estimate the effective hydrogen diffusion coefficient D_eff and the subsurface hydrogen concentration C₀ in cleaned and mechanically polished X60 steel. XPS analysis confirmed the presence of a 6 nm thick film of Fe (II) oxide, Fe (III) oxide, and Fe (III) oxyhydroxide. Mechanical polishing improved oxide layer uniformity, ensuring reproducible electrochemical behavior. The effective hydrogen diffusion coefficient D_eff was determined for X60 steel using t_lag and t_b methods. It was found in the range from 2.0 (0.4) 10⁻¹⁰ m²/s to 2.9 (0.5) 10⁻¹⁰ m²/s. The subsurface hydrogen concentration, C₀, was found to be 0.7 (0.1) ppm for X60 steel. The hydrogen diffusion in X60 steel depends on its bulk properties; it is unaffected by surface preparation methods, and it is confirmed to be lower than in high-carbon and other high-strength steels. Full article

Lithium is a strategic resource due to its use in rechargeable batteries for electric vehicles and electronic devices, driving high demand for extraction. This study analyzes the lithium supply chain in Mexico, focusing on both the extraction of lithium carbonate for export and the potential for producing lithium–ion batteries and lithium grease, considering their environmental impact. The proposed mixed integer linear programming (MILP) model, solved using the GAMS modeling environment, suggests that lithium extraction in Mexico is viable, with Sonora having the greatest extraction capacity. Three solutions were evaluated: Solution A maximizes profits (USD 317.19 M) but has high greenhouse gas (GHG) emissions (1,119,808 tons), Solution B balances profits (USD 186.98 M) with lower emissions (559,904 tons), and Solution C prioritizes emission reduction (44,792 tons) at the cost of lower profits (USD 48.20 M). Solution C implies a scenario with severe environmental restrictions, which indirectly leads to lower investment costs by avoiding the production of lithium grease and batteries. This study highlights the potential impact of tariffs on U.S. lithium exports, with a 25% tariff making exports economically unviable. This underscores the need for Mexico to diversify its export markets. Decision-makers can use this model to explore alternative strategies, reduce dependence on a single market, and optimize the economic and environmental sustainability of the lithium sector. Full article

Background/Objectives: The development of effective therapies for brain disorders is highly correlated with the ability of drugs or nanosystems to cross the blood–brain barrier (BBB), which has been limited. Recently, carbon dots (CDs) have been receiving attention to be used as BBB-crossing theranostic agents due to their inherent advantages, such as low size, excellent biocompatibility, high quantum yield (QY), tunable fluorescence, high drug loading, and relatively easy synthesis at low cost. The aim of this study was to design CDs with precisely controlled fluorescence properties for advanced bioimaging and an in-depth assessment of BBB permeability. Methods: CDs were synthesized using a microwave-assisted approach, optimized through microwaves’ irradiation time, and employing citric acid, urea, and sodium fluoride as precursors. The optimized sample was labeled as NF-CD. Results: A comprehensive physicochemical, photoluminescence, and biological characterization revealed the ability of NF-CD to diffuse across a neuromimetic-BBB model, mainly due to their small size (average diameter of 4.0 ± 1.1 nm), exhibiting excitation-dependent fluorescence in the blue and green wavelengths, high biocompatibility and QY, and exceptional photostability. Conclusions: Owing to the exceptional fluorescence characteristics and biological compatibility, NF-CD presents promising opportunities in theranostic applications, particularly in brain-targeted bioimaging, nanocarrier-based drug and immunotherapy delivery, early-stage diagnostics, and personalized medicine. NF-CD’s ability to cross the BBB further underscores the relevance of pioneering nanomaterial-based strategies for neurological disorder diagnostics and precision-targeted therapeutic interventions. Overall, this research contributes to the broader field of nanotechnology-driven biomedical advancements, fostering innovations in neurological diagnostics and therapeutic delivery systems. Full article

This study shows an evaluation of the condition of organic matter against enzymatic activity in soil. Long-term static field experiments with fertilisation with manure (FYM), different minerals, and mineral–manure were used for the research. Assays were obtained of the content of total organic carbon (TOC), dissolved fraction (DOC), susceptibility to oxidation (CL1) and (CL), total nitrogen (TN), dissolved nitrogen fraction (DTNT), and available forms of potassium, phosphorus, and magnesium. The activity of enzymes dehydrogenases, catalase, β-glucosidase, proteases, alkaline, and acid phosphatase was determined. We calculated the enzymatic indices and those evaluating the labile organic carbon management (CMI and CPI) in soil. An increase in TOC, up to 8.85 g kg⁻¹ and 8.56 g kg⁻¹ (FYM, FYM + KN), respectively, as compared with the control (5.67 g kg⁻¹), did not have a significant effect on the content of labile carbon fraction CL for the fertilisation treatments. Only a higher CL content was found in the soil with the FYM + PN and FYM + NPK + Mg treatments (2.07 g kg⁻¹ and 2.05 g kg⁻¹). All the fertilisation treatments under study demonstrated a decrease in the value of the carbon management index (CMI). Similar DOC values (on average, 75.14 mg kg⁻¹) were noted. The average percentage share of the DOC fraction accounted for 1.163% TOC, and it was lower as compared with the control variant (1.33% TOC). The mineral fertilisation treatments decreased soil enzyme activities. Multiparametric enzymatic soil fertility indices differed due to soil properties, depending on the fertilisation applied. Full article

Trees play a critical role in climate regulation, biodiversity, and carbon storage as they cover approximately 30% of the global land area. Nowadays, Machine Learning (ML)is key to automating large-scale tree species classification based on active and passive sensing systems, with a recent trend favoring data fusion approaches for higher accuracy. The use of 3D Deep Learning (DL) models has improved tree species classification by capturing structural and geometric data directly from point clouds. We propose a fully Multimodal Tree Species Classification Network (MMTSCNet) that processes Light Detection and Ranging (LiDAR) point clouds, Full-Waveform (FWF) data, derived features, and bidirectional, color-coded depth images in their native data formats without any modality transformation. We conduct several experiments as well as an ablation study to assess the impact of data fusion. Classification performance on the combination of Airborne Laser Scanning (ALS) data with FWF data scored the highest, achieving an Overall Accuracy (OA) of nearly 97%, a Mean Average F1-score (MAF) of nearly 97%, and a Kappa Coefficient of 0.96. Results for the other data subsets show that the ALS data in combination with or even without FWF data produced the best results, which was closely followed by the UAV-borne Laser Scanning (ULS) data. Additionally, it is evident that the inclusion of FWF data provided significant benefits to the classification performance, resulting in an increase in the MAF of +4.66% for the ALS data, +4.69% for the ULS data under leaf-on conditions, and +2.59% for the ULS data under leaf-off conditions. The proposed model is also compared to a state-of-the-art unimodal 3D-DL model (PointNet++) as well as a feature-based unimodal DL architecture (DSTCN). The MMTSCNet architecture outperformed the other models by several percentage points, depending on the characteristics of the input data. Full article

Illicit or inappropriate inflows into urban drainage systems cause significant operational issues, impacting utilities, communities, and the environment. The continued deterioration of system assets increases these inflows. Groundwater infiltration, rain-derived inflows, and misconnections contribute to reduced system performance, amongst other detrimental inflows. Climate change effects and the revised EU Wastewater Treatment Directive put pressure on utilities to reduce combined sewage and polluted stormwater discharges and overflows while promoting carbon neutrality. The effective management of undue inflows requires identifying cause–effect relationships and quantifying their consequences. This paper proposes a performance-based methodology with metrics and reference values to assess and categorise various undue inflows in wastewater, stormwater, or combined systems. This approach allows the tracking of performance over time, the comparing of systems, and requires data commonly available to utilities. The reliable quantification of inflows depends on the availability and accuracy of flow data from relevant system locations, rainfall data, and pertinent contextual information. This paper uses data from eight utilities and the Portuguese regulator to validate its approach, calculate metrics, refine reference values and enable better-targeted control measures. The results enhance the value of a unified approach to this problem in making better decisions to improve the urban water drainage system’s performance, enhance pollution control, and promote sustainable water management. Full article