Search Results (4,121)

According to statistics from the United Nations Environment Program (UNEP), the construction industry accounts for approximately 30% to 40% of global energy consumption and greenhouse gas emissions, making it a major source of carbon emissions. As a critical component of urban construction, residential buildings are characterized by their large scale and significant potential for carbon reduction. Building on this context, this study utilizes diversified geospatial data and applies the life-cycle stage framework for residential buildings alongside the emission factor method to calculate total carbon emissions during the material production, construction, and operation phases. It systematically analyzes the distribution characteristics and spatial evolution trends of life-cycle carbon emissions for urban residential buildings. The findings reveal that 63.06% of the cumulative carbon emissions from residential buildings in Xi’an originate from the operation phase, underscoring the importance of optimizing carbon emissions in this phase as a critical priority for future reductions. Additionally, the spatial distribution of residential building carbon emissions exhibits significant clustering, with an increasingly pronounced expansion pattern. Over time, the direction of expansion has shifted from a northeast–southwest orientation to a northwest–southeast trajectory and continues to extend toward peripheral areas. Economic growth, increased urbanization, and the intensive consumption of specific building materials are identified as significant drivers of residential carbon emissions, while population growth and improvements in material utilization efficiency help mitigate emissions to some extent. This study offers valuable insights to support the green development of China’s construction industry and to advance energy-saving and carbon-reduction strategies. Full article

The automotive industry faces continuing challenges with regard to advancing sustainability and reducing energy consumption and vehicle emissions. South Africa accounts for half of the total CO₂ emissions in Africa and is the world’s 12th-largest CO₂ emitter. In this study, we aimed to develop a model combining autoregressive integrated moving averages (ARIMAs) with long short-term memory (LSTM) to determine the best fit for prediction using the lowest root mean square error configuration and enhance energy consumption in automotive component manufacturing. The ARIMA model dissects time-series data into the components of level, trend, and seasonality, while the automatic ARIMA function refines the model parameters. Simultaneously, utilizing historical data, the LSTM model uses specific algorithms to predict future electricity generation and carbon emissions for the automotive component’s manufacturing sector. According to our results, the predicted variables’ interdependence revealed an enhancement in energy intensity for vehicle body part products equal to 29%, a cumulative energy savings of 7.22%, and an increase in energy efficiency equal to 16.25%. Our model’s predictive fitness holds significant potential for allowing automotive component manufacturers to make informed economic and technical decisions toward the development of low-carbon products. Critically, improved energy efficiency in automotive component manufacturing activities is critical for lowering energy consumption, greenhouse gas emissions, sustainable transportation, and production costs. Full article

The advancement of intelligent packaging technologies has emerged as a pivotal innovation in the food industry, significantly enhancing food safety and preservation. This review explores the latest developments in the fabrication of intelligent packaging, with a focus on applications in food preservation. Intelligent packaging systems, which include sensors, indicators, and RFID technologies, offer the real-time monitoring of food quality and safety by detecting changes in environmental conditions and microbial activity. Innovations in nanotechnology, bio-based materials, and smart polymers have led to the development of eco-friendly and highly responsive packaging solutions. This review underscores the role of active and intelligent packaging components—such as oxygen scavengers, freshness indicators, and antimicrobial agents in extending shelf life and ensuring product integrity. Moreover, it highlights the transformative potential of intelligent packaging in food preservation through the examination of recent case studies. Finally, this review provides a comprehensive overview of current trends, challenges, and potential future directions in this rapidly evolving field. Full article

Background: The poultry industry is one of the most rapidly growing sectors, producing the highest amount of animal-derived protein per unit time while also being the second-largest consumer of antibiotics. The widespread and accelerating spread of antimicrobial resistance (AMR) underscores the necessity of regular monitoring studies. Periodic assessments, especially focusing on commensal strains, can serve as indicators of emerging resistance patterns. Methods: This study assesses the antimicrobial susceptibility profiles of putative commensal Staphylococcus strains (n = 166) isolated from large-scale turkey flocks in Hungary using minimal inhibitory concentration (MIC) determination. The isolated strains were tested against antibiotics of veterinary and public health importance. The results were analyzed using the Kruskal–Wallis test and the Mann–Whitney U test, as well as t-tests. Additionally, correlation analysis and principal component analysis were performed. Results: Our findings revealed the highest resistance rates to tiamulin (90.4%), doxycycline (79.5%), and enrofloxacin (68.7%). Conclusions: These results reflect the extensive antibiotic use in the poultry sector, which contributes to the widespread presence of antimicrobial resistance. As regular monitoring and the identification of trends can aid in mitigating the spread of resistance, these findings should be complemented by data on antibiotic usage at the surveyed farms in further studies. The observed resistance rate of 18.1% to vancomycin is particularly concerning from a public health perspective, given that comparative human data show only a 0.05% resistance rate. Additionally, for multidrug-resistant strains, next-generation sequencing should be utilized to elucidate the genetic mechanisms underlying resistance, particularly in strains exhibiting high levels of resistance to vancomycin, which is of critical importance in human medicine, as well as to the critically important enrofloxacin and the widely used doxycycline and tiamulin. However, the limitations of the study should also be acknowledged, including the relatively small sample size, which is significantly lower than that of available human data, as well as the spatial distribution of the samples. Full article

Lakes are a crucial component of inland water bodies, and changes in their water levels serve as key indicators of global climate change. Traditional methods of lake water level monitoring rely heavily on hydrological stations, but there are problems such as regional representativeness, data stability, and high maintenance costs. The satellite altimeter is an essential tool in lake research, with the Synthetic Aperture Radar (SAR) altimeter offering a high spatial resolution. This enables precise and quantitative observations of lake water levels on a large scale. In this study, we used Sentinel-3A SAR Radar Altimeter (SRAL) data to establish a more reasonable lake height inversion algorithm for satellite-derived lake heights. Subsequently, using this technology, a systematic analysis study was conducted with Qinghai Lake as the case study area. By employing regional filtering, threshold filtering, and altimeter range filtering techniques, we obtained effective satellite altimeter height measurements of the lake surface height. To enhance the accuracy of the data, we combined these measurements with GPS buoy-based geoid data from Qinghai Lake, normalizing lake surface height data from different periods and locations to a fixed reference point. A dataset based on SAR altimeter data was then constructed to track lake surface height changes in Qinghai Lake. Using data from the Sentinel-3A altimeter’s 067 pass over Qinghai Lake, which has spanned 96 cycles since its launch in 2016, we analyzed over seven years of lake surface height variations. The results show that the lake surface height exhibits distinct seasonal patterns, peaking in September and October and reaching its lowest levels in April and May. From 2016 to 2023, Qinghai Lake showed a general upward trend, with an increase of 2.41 m in lake surface height, corresponding to a rate of 30.0 cm per year. Specifically, from 2016 to 2020, the lake surface height rose at a rate of 47.2 cm per year, while from 2020 to 2022, the height remained relatively stable. Full article

Forest soil organic matter (SOM) is a critical component of forest ecosystems and plays a vital role in the global carbon (C) cycle. Global climate change profoundly affects forest SOM dynamics, particularly its sources and formation processes, which are crucial initial stages of the forest soil C cycle. Therefore, understanding these processes and the impacts of climate change is essential for developing effective forest management strategies and climate policies. In this study, VOSviewer 1.6.18 was used to conduct a bibliometric analysis of research published from 1975 to 2024, retrieved from the Web of Science (WoS) Core Collection database, focusing on the sources and formation processes of forest SOM under climate change. The analysis covers annual publication trends, author co-occurrence networks, publication distributions by country and region, keyword clustering, and evolving keyword trends, integrating both quantitative results and a literature review to provide an understanding of the research progress in the field. The results highlight continuous growth in research publications, which can be categorized into four stages: initial emergence, sustained exploration, rapid development, and deep expansion. A solid theoretical foundation and good research strength have been established, driven by prominent academic groups led by researchers such as Jari Liski, as well as leading countries, including the United States and China. The research progress is divided into four topics: the sources of forest SOM; the formation processes of forest SOM; the impacts of climate change; and measurement methods and model-based analysis techniques, which mainly elaborate upon plant-, microbial-, and soil fauna-derived aspects. Research hotspots have evolved from basic C and nitrogen (N) cycles to in-depth studies involving microbial mechanisms and multiparameter climate change interactive effects. This study provides an overview of the research progress and hotspots in the field, offering basic knowledge and theoretical support for potential future research and climate change mitigation strategies. Full article

Soil salinization and alkalization are serious global challenges that adversely affect crop growth and yield. In this study, six genotypes of giant reed (Arundo donax) seedlings (LvZhou_No.1, LvZhou_No.3, LvZhou_No.6, LvZhou_No.11, LvZhou_No.12 and LvZhou_Var.) originating from different regions of China and Rwanda were utilized as experimental materials. This study aimed to investigate the physiological and biochemical responses of various genotypes to saline–alkali stress and to identify stress-tolerant resources. A mixture saline–alkali solution with a molar ratio of NaCl: Na₂SO₄: NaHCO₃: Na₂CO₃ = 1:1:1:1 was prepared at three concentrations (75, 150 and 225 millimolar (mM)) for a 7-day pot experiment. Growth and physiological indices were measured at the seedling stage, and salt tolerance was evaluated accordingly. The results indicated the following: the growth indices were significantly reduced across seedlings of all genotypes when the concentration of stress exceeded 150 mM (p < 0.05). There was no significant difference in chlorophyll content (SPAD value) and maximum photochemical efficiency of PS II (F_v/F_m) with increasing saline–alkali stress. However, the photosynthetic rate (P_n), stomatal conductance (G_s) and transpiration rate (T_r) exhibited decreasing trends, reaching their lowest levels at 225 mM. In contrast, the intercellular CO₂ concentration (C_i) value decreased to its lowest at 150 mM but increased at 225 mM. Relative electrical conductivity (REC) and the contents of malondialdehyde (MDA), proline (Pro) and soluble sugar (SS) increased progressively with higher stress concentrations. The activities of superoxide dismutase (SOD), peroxidase (POD) and catalase (CAT) were significantly enhanced at stress concentrations above 150 mM. The saline–alkali tolerance of A. donax seedlings was comprehensively evaluated using principal component analysis and membership function analysis based on 15 parameters. The results indicate that P_n, T_r and G_s are effective physiological indicators for assessing saline–alkali tolerance of A. donax seedlings. The six genotypes were ranked for saline–alkali tolerance as follows: LZ_No.1 > LZ_No.11 > LZ_No.12 > LZ_Var. > LZ_No.3 > LZ_No.6. This indicates that LZ_No.1 shows the highest resistance to saline–alkali stress, whereas LZ_No.6 is the most severely affected, classifying it as a salinity-sensitive genotype. In conclusion, LZ_No.1 exhibits robust saline–alkali tolerance and represents a valuable germplasm resource for improving saline–alkali tolerance in A. donax propagation. The results not only support the development of resilient plants for saline–alkali environments but also offer insights into the mechanisms of salinity tolerance. Full article

Eco-design is an innovative design methodology that focuses on minimizing the environmental footprint of industries, including aviation, right from the conceptual and development stages. However, rising industrial demand calls for a more comprehensive strategy wherein, beyond environmental considerations, competitiveness becomes a critical factor, supported by additional pillars of sustainability such as economic viability, circularity, and social impact. By incorporating sustainability as a primary design driver at the initial design stages, this study suggests a shift from eco-driven to sustainability-driven design approaches for aircraft components. This expanded strategy considers performance and safety goals, environmental impact, costs, social factors, and circular economy considerations. To provide the most sustainable design that balances all objectives, these aspects are rigorously quantified and optimized during the design process. To efficiently prioritize different variables, methods such as multi-criteria decision-making (MCDM) are employed, and a sustainability index is developed in this framework to assess the overall sustainability of each design alternative. The most sustainable design configurations are then identified through an optimization process. A typical aircraft component, namely a hat-stiffened panel, is selected to demonstrate the proposed approach. The study highlights how effectively sustainability considerations can be integrated from the early stages of the design process by exploring diverse material combinations and geometric configurations. The findings indicate that the type of fuel used, and the importance given to the sustainability pillars—which are ultimately determined by the particular requirements and goals of the user—have a significant impact on the sustainability outcome. When equal prioritization is given across the diverse dimensions of sustainability, the most sustainable option appears to be the full thermoplastic component when kerosene is used. Conversely, when hydrogen is considered, the full aluminum component emerges as the most sustainable choice. This trend also holds when environmental impact is prioritized over the other aspects of sustainability. However, when costs are prioritized, the full thermoplastic component is the most sustainable option, whether hydrogen or kerosene is used as the fuel in the use phase. This innovative approach enhances the overall sustainability of aircraft components, emphasizing the importance and benefits of incorporating a broader range of sustainability factors at the conceptual and initial design phases. Full article

China is one of the world’s largest agricultural producers, and its agricultural carbon footprint (CF) is a major contributor to global warming. However, the long-term annual changes in its agricultural CF and the underlying driving factors remain largely unknown, compromising the scientific basis for effective carbon reduction and sustainable agriculture management. To this end, we used the life cycle assessment (LCA) method and statistical data to calculate long-term annual agricultural CFs in China. We then adopted the linear regression slope and the Moran’s I method to analyze the temporal trends and spatial clustering characteristics and revealed the correlations between the main drivers and agricultural CFs. The results showed that the total (TCF) and farmland-averaged carbon footprint (FCF) of crop production both increased first and then decreased in China from 2000 to 2020, with a turning point in 2015. Overall, the TCF increased by 6.82% (3022.16 × 10⁴ t CO₂ eq), while the FCF slightly decreased by 0.004% (0.01 t CO₂ eq/ha). Both the TCF and the FCF showed spatial heterogeneity, with high values in the east and low values in the west, and the spatial clustering of the TCF and its components has weakened over time. Fertilizer (39.26%) and paddy (27.38%) were the main contributors to TCF. Driver analysis found that grain yield was positively correlated with TCF in most provinces, indicating that the continuous yield increase has brought greater pressure on agricultural carbon emission reduction in China. Agricultural stakeholders should optimize crop planting structures and patterns and improve resource-use efficiencies through technological and management innovation to adapt to these threats and achieve low-carbon agriculture. The findings of our research can aid the scientific research on spatiotemporal estimation and driver analysis of agricultural CFs and provide decision-making support for sustainable agricultural practices. Full article

Polymer-coated controlled-release fertilizers’ (CRFs) unique nutrient release mechanism has the potential to mitigate the leaching of mobile soil nutrients, such as nitrate-nitrogen (NO₃-N). The study aimed to evaluate the capacity of a polymer-coated CRFs to maintain maize (Zea mays L.) crop growth/health indicators and production goals, while reducing NO₃-N leaching risks compared to conventional (CONV) fertilizers in North Florida. Four CRF rates (168, 224, 280, 336 kg N ha⁻¹) were assessed against a no nitrogen (N) application and the current University of Florida Institute for Food and Agricultural Sciences (UF/IFAS) recommended CONV (269 kg N ha⁻¹) fertilizer rate. All CRF treatments, even the lowest CRF rate (168 kg N ha⁻¹), produced yields, leaf tissue N concentrations, plant heights, aboveground biomasses (AGB), and leaf area index (LAI) significantly (p < 0.05) greater than or similar to the CONV fertilizer treatment. Additionally, in 2022, the CONV fertilizer treatment resulted in increases in late-season movement of soil NO₃-N into highly leachable areas of the soil profile (60–120 cm), while none of the CRF treatments did. However, back-to-back leaching rainfall (>76.2 mm over three days) events in the 2023 growing season masked any trends as NO₃-N was likely completely flushed from the system. The results of this two-year study suggest that polymer-coated CRFs can achieve desirable crop growth, crop health, and production goals, while also having the potential to reduce the late-season leaching potential of NO₃-N; however, more research is needed to fully capture and quantify the movement of NO₃-N through the soil profile. Correlation and Principal Component Analysis (PCA) revealed that CRF performance was significantly influenced by environmental factors such as rainfall and temperature. In 2022, temperature-driven nitrogen release aligned with crop uptake, supporting higher yields and minimizing NO₃-N movement. In 2023, however, rainfall-driven variability led to an increase in NO₃-N leaching and masked the benefits of CRF treatments. These analyses provided critical insights into the relationships between environmental factors and CRF performance, emphasizing the importance of adaptive fertilizer management under varying climatic conditions. Full article

Traditional consolidants commonly used for waterlogged wood conservation often present long-term drawbacks, prompting research into new and reliable alternatives. Reducing reliance on fossil-based chemicals that are harmful to people, the environment, and the climate is a growing trend, and sustainable materials are now being explored as alternative consolidants for conserving waterlogged archaeological wood. Among these bio-based products, sodium alginate, a natural polysaccharide, has shown promising potential. This study aimed to evaluate its effectiveness in stabilising dimensions of severely degraded archaeological elm wood during drying. Various treatments were tested, and dimensional stabilisation (ASE), weight percent gain (WPG), and volumetric shrinkage (Vs) were assessed. Fourier transform infrared spectroscopy (FT-IR) and scanning electron microscopy (SEM) were used to evaluate alginate penetration and interactions with residual wood components. Results indicated that the effectiveness of sodium alginate depends on the treatment method, with the soaking approach and slow drying providing the highest WPG and the best stabilisation without altering the natural wood colour. Although the best achieved anti-shrink efficiency of 40% is insufficient from the conservation perspective, sodium alginate has proven to be a promising consolidant for the conservation of waterlogged wood. Further studies will focus on enhancing its penetration and interactions with residual wood components. Full article

Resonance Acoustic Mixing (RAM) is an efficient mixing technique and holds significant application value in many fields, especially in the mixing of high-viscosity materials. Due to the one-time loading feature, different material structures formed during the feeding process may cause undesired irregularities in the mixing process, which is not conducive to maintaining the mixing consistency between different batches. However, in the analysis of multi-component mixtures, previous studies have often overlooked the impact of the initial material structure. This study delved into the mixing mechanism of RAM in viscous solid–liquid mixtures. By constructing a numerical model based on the Mixture model, simulations of gas–solid–liquid multiphase flows under different initial structures were conducted, and the reliability of the model was verified through experiments. The research results indicate that the mixing processes with different initial structures share similar temporal characteristics of being intense at first and then moderating, but their development trends vary. The mixing time of the structure with the solid on the upper part is shortened by about 10% compared with that of the structure with the solid on the lower part. The double-interface structure exhibits a significantly higher mixing efficiency than the single-interface structure, with the mixing time reduced by up to 41%. This study offers a theoretical basis for optimizing the parameters of resonant acoustic mixing and holds significant reference value for the refined operation of resonant acoustic mixing in the future. Full article

The digitalization of shipbuilding processes has become an important trend in modern naval construction, enabling more efficient design, assembly, and maintenance operations. A key aspect of this digital transformation is traceability, which ensures that every component and step in the shipbuilding process can be accurately tracked and managed. Traceability is critical for quality assurance, safety, and operational efficiency, especially when it comes to identifying and addressing defects that may arise during construction. In this context, defect traceability plays a key role, enabling manufacturers to track the origin, type, and evolution of issues throughout the production process, which are fundamental for maintaining structural integrity and preventing failures. In this paper, we focus on the detection of defects in minor and simple pre-assemblies, which are among the smallest components that form the building blocks of ship assemblies. These components are essential to the larger shipbuilding process, yet their defects can propagate and lead to more significant issues in the overall assembly if left unaddressed. For that reason, we propose an intelligent approach to defect detection in minor and simple pre-assembly pieces by implementing unsupervised learning with convolutional autoencoders (CAEs). Specifically, we evaluate the performance of five different CAEs: BaseLineCAE, InceptionCAE, SkipCAE, ResNetCAE, and MVTecCAE, to detect overshooting defects in these components. Our methodology focuses on automated defect identification, providing a scalable and efficient solution to quality control in the shipbuilding process. Full article

Freshwater zooplankton are a key component of lake food webs and a responsive indicator of changes occurring in an ecosystem’s structure and functioning. A new challenge under climate change is to disentangle the effects of lake warming from changes in lake trophic conditions, and ultimately to relate them to changes in zooplankton and ecosystem functioning. In this study, we examined the zooplankton community of the large deep subalpine Lake Maggiore (Italy) over a period of four decades, spanning changes in both lake trophic conditions and climate warming. Using monthly data from the upper 50 m of water depth, we analyzed long-term trends and investigated the application of zooplankton biomass-based indices in order to provide a better understanding of the changes in the lake ecosystem over time. Examining annual and seasonal patterns of different zooplankton taxa and groups, we observed over time a decreased contribution of Daphnia sp. during the summer and a concurrent increase in microzooplankton, suggesting a change in phytoplankton control in the lake during the recent period. Our study demonstrates that zooplankton communities integrate environmental changes, and underlines the importance of long-term monitoring and the inclusion of seasonality and the entire size range of zooplankton as key components to allow the interpretation of lake ecosystem functioning in response to trophic and climatic changes. Full article

Urban soils are vital components of urban ecosystems, significantly influenced by anthropogenic activities and environmental factors. Despite misconceptions about their quality, urban soils play a pivotal role in carbon (C) cycling and storage, impacting global emissions and sequestration. However, challenges such as soil contamination, land use changes, and urban expansion pose significant threats to soil quality and C storage capacity. Over the last two decades, there has been an increasing interest in the C storage potential of soils as part of climate change mitigation strategies. In this review, a bibliometric analysis covering the last twenty years (2004–2024) was performed to offer insights into global research trends, mainly in urban soils of the Mediterranean region. This paper also identifies research gaps and proposes essential solutions for mitigating the negative impacts of urbanization on soil biodiversity and functions. Key modulators, including plants, microbes, and soil features, are highlighted for their role in C dynamics, emphasizing the importance of effective soil and vegetation management to enhance C sequestration and ecosystem services. Strategies such as reintroducing nature into urban areas and applying organic amendments are promising in improving soil quality and microbial diversity. Further research and awareness are essential to maximize the effectiveness of these strategies, ensuring sustainable urban soil management and climate resilience. Full article