bluuebunny/crossref_metadata_2025 huggingface dataset:
Role of Renewables in Energy Storage Economic Viability in the Western Balkans
Authors: Topalović Zejneba , Haas Reinhard
Published: February 2024

Given the growing shares of renewable energy sources in the grids, the interest in energy storage systems has increased. The role of pumped hydro energy storage systems as flexible solutions for managing peak and off-peak prices from nuclear and fossil power plants in previous systems is now revitalized in the liberalized systems, with a volatile generation of wind and solar energy. Thus, understanding of the patterns behind the economics of energy storage is crucial for the further integration of energy storage in the grids. In this paper, the factors that impact the economic viability of energy storage in electricity markets are analyzed. The method of approach used in this study considers the electricity market price distribution, full load hours, the total costs of energy storage, and linear regression analysis. Using revenues from arbitraging a 10-megawatt (MW) pumped hydro storage system in the Western Balkans, resulting from the electricity market price distribution and the analysis of the total costs of storage, an econometric model is created. This model shows the impacting factors of energy storage development in the context of the rising renewables sector. Research shows that the previous hypothesis about the integration of energy storage systems in proportion to the increase in shares of renewables in the grids is incorrect. There is a significant correlation between energy storage revenues, the dependent variable, and the independent variables of hydro, wind, and solar generation. The conducted analysis indicates the future arbitraging opportunities of pumped hydro energy storage systems and provides useful insights for energy storage investors and policymakers. During the transitional period, until the deployment of renewables changes the effects of fossil power plants, energy storage price arbitrage is profitable and desirable for 500, 1000, and 2000 full load hours in the Western Balkan region. Despite the need for flexibility, with more renewables in the grids, large-scale energy storage systems will not be economically viable in the long run because of “revenue cannibalization”.
Low-Wind-Speed Galloping Wind Energy Harvester Based on a W-Shaped Bluff Body
Authors: Zheng Jianfeng , Li Zichang , Zhang Han
Published: February 2024

Galloping-based piezoelectric energy harvesting systems are being used to supply renewable electricity for low-power wireless sensor network nodes. In this paper, a W-shaped bluff body is proposed as the core component of a piezoelectric wind energy harvester. Experiments and simulations have shown that the W-shaped bluff body can improve harvesting efficiency at low wind speeds. For the W-shaped structure, the finite element simulation results indicate that the structure can help improve the aerodynamic performance to obtain high aerodynamic force. The experimental results demonstrate that compared with the traditional bluff bodies, the piezoelectric wind energy harvester with the W-shaped bluff body (WEHW) can generate higher output voltages and has a lower cut-in speed. When the length L is 30 mm and the rear groove angle β is 30°, the W-shaped structure can induce the best harvesting performance. When an external load resistance of 820 KΩ is connected and the wind speed is 5 m/s, the WEHW generates an average output power of 0.28 mW.
Investigating the Effect of Albedo in Simulation-Based Floating Photovoltaic System: 1 MW Bifacial Floating Photovoltaic System Design
Authors: Cosgun Atıl Emre , Demir Hasan
Published: February 2024

Photovoltaic (PV) modules have emerged as a promising technology in the realm of sustainable energy solutions, specifically in the harnessing of solar energy. Photovoltaic modules, which use solar energy to generate electricity, are often used on terrestrial platforms. In recent years, there has been an increasing inclination towards the installation of photovoltaic (PV) modules over water surfaces, including lakes, reservoirs, and even oceans. The novel methodology introduces distinct benefits and complexities, specifically pertaining to the thermal characteristics of the modules. In order to accomplish this objective, a photovoltaic (PV) module system with a capacity of 1 MW was developed as a scenario in the PVsyst Program. The scenario simulation was conducted on the Mamasın Dam, situated in the Gökçe village within the Aksaray province. To conduct the efficiency analysis, a comparative evaluation was conducted between bifacial and monofacial modules, which were installed from above the water at 1 m. The comparison was made considering two different types of modules. Additionally, the albedo effect, water saving amount, and CO2 emissions of the system were also investigated. Albedo measurements were made in summer when the PV power plant will operate most efficiently. As a result of the simulations, it was found that bifacial modules produce 12.4% more energy annually than monofacial modules due to the albedo effect. It is estimated that PV power plant installation will save 19,562.695 and 17,253.475 tons of CO2 emissions in bifacial and monofacial systems, respectively.
The Effectiveness of HEVs Phase-Out by 2035 in Favor of BEVs with Respect to the Production of CO2 Emissions: The Italian Case
Authors: Grimaldi Francesca Maria , Capaldi Pietro
Published: February 2024

The EU has planned the phase-out of new vehicles based on internal combustion engines in favor of high-efficiency battery electric vehicles (BEV) by 2035 (Fit for 55 package). However, many doubts remain about the effectiveness of this choice for each country of the Union in terms of CO2 emissions reduction, as each State is characterized by a different carbon intensity related to the production of electricity needed to manufacture and recharge vehicles. This study seeks to explore the Italian case. To this aim, carbon intensities related to electricity production were calculated considering both the Italian electricity mix production in 2022 and those envisaged in 2035, considering two energy scenarios based on different introductions of renewable energy sources (RES). Afterward, the values obtained were adopted for determining the CO2 emissions related to the whole production process of battery systems in Italy (emissions from mining and refining, scrap materials, and final assembly included) by comparing some of the most up-to-date Life-Cycle Assessment (LCA) analyses related to the manufacturing cycle of the batteries. Finally, the results were adopted to calculate the starting carbon debit for A, B, C, and M car segments for Mild Hybrid, Full Hybrid, and Full Electric powertrains. At the same time, statistical road fuel/electricity consumption data were collected and overall CO2 emissions were calculated for the same vehicles adopting a dynamic approach and plotted for a defined distance, so as to determine break-even points with respect to the cumulative (i.e., from battery and road) carbon emissions. The results showed that advantages related to electric vehicles are significant only if a low carbon intensity related to electricity production is reached by means of a very high introduction of RES, thus keeping the door open for innovative hybrid powertrain technologies, if fed with low carbon fuels.
A Data-Driven Prediction Method for Proton Exchange Membrane Fuel Cell Degradation
Authors: Wang Dan , Min Haitao , Zhao Honghui , Sun Weiyi , Zeng Bin , Ma Qun
Published: February 2024

This paper proposes a long short-term memory (LSTM) network to predict the power degradation of proton exchange membrane fuel cells (PEMFCs), and in order to promote the performance of the LSTM network, the ant colony algorithm (ACO) is introduced to optimize the hyperparameters of the LSTM network. First, the degradation mechanism of PEMFCs is analyzed. Second, the ACO algorithm is used to set the learning rate and dropout probability of the LSTM network combined with partial aging data, which can show the characteristics of the dataset. After that, the aging prediction model is built by using the LSTM and ACO (ACO-LSTM) method. Moreover, the convergence of the method is verified with previous studies. Finally, the fuel cell aging data provided by the Xiangyang Da’an Automotive Testing Center are used for verification. The results show that, compared with the traditional LSTM network, ACO-LSTM can predict the aging process of PEMFCs more accurately, and its prediction accuracy is improved by about 35%, especially when the training data are less. At the same time, the performance of the model trained by ACO-LSTM is also excellent under other operating conditions of the same fuel cell, and it has strong versatility.
Embodied Carbon Transfer in China’s Bilateral Trade with Belt and Road Countries from the Perspective of Global Value Chains
Authors: Zhao Mingyin , Ning Yadong , Bai Shukuan , Zhang Boya
Published: February 2024

In the context of global value chains (GVCs), the impact of the Belt and Road Initiative (BRI) on China’s bilateral trade with Belt and Road countries (BRCs) is controversial. This study constructed a GVC accounting framework based on a multiregional input–output model, aiming to clarify the trends and transfer characteristics of the value added (VA) and the embodied carbon emissions (ECEs) in China–BRCs bilateral trade from 2000 to 2018 at the overall country, Belt and Road region (BRR), and typical country levels. The relevant results are threefold. (1) At the overall country level, the BRCs VA and ECEs imports and exports have shown overall increasing trends. (2) Most BRRs are net ECE exporters to China. Southeast Asia and Northeast Asia are the main ECEs destinations and sources. (3) In China–typical BRCs bilateral trade, China is a net ECEs exporter to most typical BRCs, and the net ECE transfers through route 1 (onefold value chain) are all positive, implying that route 1 can reduce ECEs in BRCs. These findings can help formulate policies and measures to reduce carbon emissions and provide a scientific basis for realizing the coordinated development of carbon emission reduction and economy in China and BRCs.
Application of Proton Ionic Liquid in the Process of Obtaining Bioethanol from Hemp Stalks
Authors: Smuga-Kogut Małgorzata , Walendzik Bartosz , Lewicka-Rataj Katarzyna , Kogut Tomasz , Bychto Leszek , Jachimowicz Piotr , Cydzik-Kwiatkowska Agnieszka
Published: February 2024

In this work, hemp (Cannabis sativa L.) stalks were pretreated with pyrrolidinium acetate [Pyrr][AC] to increase the availability of cellulose for cellulolytic enzymes and thus improve the production of 2G ethanol from reducing sugars. The process was carried out under different temperature and time conditions: The control sample was raw material and deionized water, and the second sample was kept at 21 °C for 24 h. The third sample was kept at 90 °C for 30 min, and the fourth sample was kept at the same temperature for 24 h. For each pretreatment, the extraction of lignin and hemicellulose was determined, as well as the change in biomass composition before and after pretreatment. The stalks of hemp seed contained 41.54% cellulose, 18.08% lignin and 28. 87% hemicellulose. [Pyrr][AC] used to dissolve seed hemp at 90 °C for 24 h was most effective in the extraction of this biopolymer, extracting 3.1% content. After enzymatic hydrolysis, the highest content of reducing sugars was found for samples of hemp stalks that were first pretreated with proton ionic liquid (PIL) and stirred at 90 °C for 24 h. On the other hand, the highest ethanol content (5.6 g/L) after fermentation and yeast viability (56.7%) after 72 h were obtained in samples pretreated at 90 °C and for 24 h.
The Link between Human Development, Foreign Direct Investment, Renewable Energy, and Carbon Dioxide Emissions in G7 Economies
Authors: Leitão Nuno Carlos
Published: February 2024

This research evaluates the determinants of pollution emissions, considering the human development index, international trade, renewable energy, and foreign direct investment (FDI) as explanatory variables. This study tests the relationship between trade intensity and FDI on carbon dioxide emissions, considering the arguments of the pollution haven hypothesis (PHH) versus halo pollution (HP). The econometric strategy applies panel data (fixed effects, random effects), a generalised linear model (Gamma), panel cointegration models such as FMOLS and DOLS, the ARDL panel model, and the panel quantile regressions to data from the G7 countries from 1990 to 2019. Before using econometric models, this investigation considers preliminary tests such as the panel unit root test (first and second generation) and the cointegration test. The econometric results show that human development decreased pollution emissions. In addition, renewable energy improves air quality and aims to reduce climate change. The inverted environmental Kuznets curve also supports the results when evaluating the relationship between the human development index and carbon dioxide emissions.
Anomaly Detection on Small Wind Turbine Blades Using Deep Learning Algorithms
Authors: Altice Bridger , Nazario Edwin , Davis Mason , Shekaramiz Mohammad , Moon Todd K. , Masoum Mohammad A. S.
Published: February 2024

Wind turbine blade maintenance is expensive, dangerous, time-consuming, and prone to misdiagnosis. A potential solution to aid preventative maintenance is using deep learning and drones for inspection and early fault detection. In this research, five base deep learning architectures are investigated for anomaly detection on wind turbine blades, including Xception, Resnet-50, AlexNet, and VGG-19, along with a custom convolutional neural network. For further analysis, transfer learning approaches were also proposed and developed, utilizing these architectures as the feature extraction layers. In order to investigate model performance, a new dataset containing 6000 RGB images was created, making use of indoor and outdoor images of a small wind turbine with healthy and damaged blades. Each model was tuned using different layers, image augmentations, and hyperparameter tuning to achieve optimal performance. The results showed that the proposed Transfer Xception outperformed other architectures by attaining 99.92% accuracy on the test data of this dataset. Furthermore, the performance of the investigated models was compared on a dataset containing faulty and healthy images of large-scale wind turbine blades. In this case, our results indicated that the best-performing model was also the proposed Transfer Xception, which achieved 100% accuracy on the test data. These accuracies show promising results in the adoption of machine learning for wind turbine blade fault identification.
Modulation Techniques and Coordinated Voltage Vector Distribution: Effects on Efficiency in Dual-Inverter Topology-Based Electric Drives
Authors: Kucera Jakub , Zakopal Petr , Baum Filip , Lipcak Ondrej
Published: February 2024

The increasing popularity of electric drives employing an isolated dual-inverter (DI) topology is motivated by their superior DC-link voltage and power utilization, fault-tolerant operation, and potential for multilevel operation. These attributes are significant in battery-powered transportation, such as electric vehicles and aviation. Given the considerable freedom in modulation and control of the DI topology, this paper researches the impact of reference voltage vector distribution between the two individual inverters. The study also evaluates the influence of two well-established asynchronous modulation strategies—Space Vector PWM (SVPWM) and Depenbrock’s Discontinuous Modulation (DPWM1). Since simulation tools nowadays play a crucial role in power electronics design and concept verification, the results are based on extensive and detailed models in Matlab/Simulink. Employing the basic field-oriented control of a 12 kW induction motor with precisely parameterized SiC switching devices for accurate loss calculation, this research reveals the possibility of significant energy savings at multiple operating points. Notably, optimal efficiency is achieved when one inverter operates up to half of the nominal speed while the other solely establishes a neutral point for the winding. Moreover, the results highlight DPWM1 as a superior strategy for the DI topology, showcasing reduced converter losses. Overall, it is shown that the system’s losses can be significantly reduced just by the design of the voltage vector distribution in the drive’s operating range and the modulation strategy selection.
A Systematic Review on the Studies of Thermal Comfort in Urban Residential Buildings in China
Authors: Lin Yaolin , Chen Pengju , Yang Wei , Hu Xiancun , Tian Lin
Published: February 2024

There have been fruitful publications on thermal comfort of urban residential buildings in China. However, there is a lack of reviews on this topic to perform a comprehensive analysis and find opportunities to meet occupants’ thermal comfort needs while improving building energy efficiencies. This paper addresses this issue by presenting a systematic review on the advancements in research on thermal comfort in urban residential buildings in China. Firstly, two common thermal comfort research approaches, i.e., field studies and laboratory studies, are discussed. Secondly, eleven main thermal comfort evaluation indicators are summarized. Finally, this paper analyzes the thermal comfort survey data from different researchers, discusses the impacts of adaptive behaviors on human thermal comfort, and provides recommendations for future research on urban residential thermal comfort. It was found that people have higher and higher requirements for their indoor thermal environment as time goes by, especially in the winter; the thermoneutral temperature is higher in warmer climate regions in the summer but lower in the winter than in colder climate regions; the thermoneutral temperature tends to increase with the indoor air temperature due to an adaptation to the indoor thermal environment. The outcomes of this paper provide valuable information on thermal comfort behaviors of urban residents in different climate zones in China, which can serve as a resource for the academic community conducting future research on thermal comfort and assist policymakers in enhancing building energy efficiencies without compromising the occupants’ comfort.
Investigating the Impact of Agricultural, Financial, Economic, and Political Factors on Oil Forward Prices and Volatility: A SHAP Analysis
Authors: Kim Hyeon-Seok , Kim Hui-Sang , Choi Sun-Yong
Published: February 2024

Accurately forecasting crude oil prices is crucial due to its vital role in the industrial economy. In this study, we explored the multifaceted impact of various financial, economic, and political factors on the forecasting of crude oil forward prices and volatility. We used various machine learning models to forecast oil forward prices and volatility based on their superior predictive power. Furthermore, we employed the SHAP framework to analyze individual features to identify their contributions in terms of the prediction. According to our findings, factors contributing to oil forward prices and volatility can be summarized into four key focal outcomes. First, it was confirmed that soybean forward pricing overwhelmingly contributes to oil forward pricing predictions. Second, the SSEC is the second-largest contributor to oil forward pricing predictions, surpassing the contributions of the S&P 500 or oil volatility. Third, the contribution of oil forward prices is the highest in predicting oil volatility. Lastly, the contribution of the DXY significantly influences both oil forward price and volatility predictions, with a particularly notable impact on oil volatility predictions. In summary, through the SHAP framework, we identified that soybean forward prices, the SSEC, oil volatility, and the DXY are the primary contributors to oil forward price predictions, while oil forward prices, the S&P 500, and the DXY are the main contributors to oil volatility predictions. These research findings provide valuable insights into the most-influential factors for predicting oil forward prices and oil volatility, laying the foundation for informed investment decisions and robust risk-management strategies.
Beyond Personal Beliefs: The Impact of the Dominant Social Paradigm on Energy Transition Choices
Authors: Platje Johannes , Kurek Katarzyna A. , Berg Petra , van Ophem Johan , Styś Aniela , Jankiewicz Sławomir
Published: February 2024

Energy transition towards a local resilient energy supply is necessary for energy security. Climate change and the threat of economic collapse are reasons to force society to become less dependent on fossil fuel. Small-scale solutions are expected to be more sustainable, as large-scale integrated networks are featured by complexity and difficult-to-notice vulnerabilities, creating system risks. This paper presents the results of empirical research among a sample of Polish business students (N = 205) on the importance of worldviews for the choice of the energy transition scenario (local solutions vs. large-scale solutions). Worldviews are represented here by the Dominant Social Paradigm (defined for the purpose of this study as the belief that liberal democracy, free markets, and technological development are to solve all type of problems). This study addresses two research questions: (1) Is there a difference in preference for the energy transition scenarios? (2) Does adherence to the Dominant Social Paradigm determine the choice of the scenario for energy transition? The results present a preference for non-cooperative solutions (individual household solutions and large-scale solutions), while no significant relation to the worldviews represented by the Dominant Social Paradigm has been found. The results suggest that preferences for individual and large-scale solutions may be influenced more by institutional factors than by personal worldviews. A policy implication is that a change in the socio-political institutions and strengthening local governance may be a prerequisite for a sustainable energy transition.
Experimental Investigation of Non-Premixed Combustion Process in a Swirl Burner with LPG and Hydrogen Mixture
Authors: Dostiyarov Abay Mukhamediyarovich , Umyshev Dias Raybekovich , Kibarin Andrey Anatolievich , Yamanbekova Ayaulym Konusbekovna , Tumanov Musagul Elekenovich , Koldassova Gulzira Ainadinovna , Anuarbekov Maxat Arganatovich
Published: February 2024

In the modern world, issues related to the use of alternative fuels are becoming increasingly pressing. These fuels offer the potential to achieve significantly improved environmental and technological performance. Currently, among such fuels, biodiesel, ammonia, LPG, and hydrogen are considered the most promising options. LPG and hydrogen exhibit a high Lower Heating Value (LHV) and have a relatively low environmental impact. This article investigates the combustion of hydrogen-LPG mixtures in a diffusion burner. The main parameters under study include the proportion of hydrogen in the fuel, equivalence ratio, and vane angle. The analyzed parameters encompass NOx and CO concentrations. The studies have demonstrated that the addition of hydrogen can reduce greenhouse gas emissions, as the combustion product is clean water. The primary focus of this research is the examination of combustion processes involving flow swirl systems and alternative fuels and their mixtures. The studies indicate that flame stabilization is significantly influenced by several factors. The first factor is the amount of hydrogen added to the fuel mixture. The second factor is the degree of mixing between the fuel and oxidizer, along with hydrogen. Lastly, the equivalence ratio plays a crucial role. As the studies have shown, the maximum stabilization for a speed of 5 m/s is achieved at an angle of 60° and a hydrogen fraction of 40%, resulting in φLBO = 0.9. This represents an 8.0% improvement in stabilization compared to the baseline mode, primarily due to the substantial proportion of hydrogen. An analysis of flame photographs reveals that as the twist angle increases, a recirculation zone becomes more apparent. Increasing the blade angle and incorporating hydrogen leads to a reduction in CO concentrations in the exhaust gases. The analysis indicates that increasing the hydrogen proportion to 50%, compared to the absence of hydrogen, results in a 30% decrease in CO concentration. In our case, for the option φ = 0.3 and blade angles of 60°, the reduction in CO concentration was 28.5%. From the authors’ perspective, the most optimal vane angle is 45°, along with a hydrogen fraction of 30–40%. With these parameters, it was possible to achieve concentrations of NOx = 17–25 ppm, φLBO = 0.66, and CO = 130–122 ppm.
A Methodology to Estimate Single-Event Effects Induced by Low-Energy Protons
Authors: Marques Cleiton , Wrobel Frédéric , Aguiar Ygor , Michez Alain , Boch Jérôme , Saigné Frédéric , García Alía Rubén
Published: February 2024

This work explains that the Coulomb elastic process on the nucleus is a major source of single-event effects (SEE) for protons within the energy range of 1–10 MeV. The infinite range of Coulomb interactions implies an exceptionally high recoil probability. This research seeks to extend the investigations under which the elastic process becomes significant in the energy deposition process by providing a simplified methodology to evaluate the elastic contribution impact on the reliability of electronics. The goal is to derive a method to provide a simple way to calculate and predict the SEE cross-section. At very low energy, we observe a significant increase in the proton differential cross-section. The use of a direct Monte Carlo approach would mainly trigger low energy recoiling ions, and a very long calculation time would be necessary to observe the tail of the spectrum. In this sense, this work provides a simple methodology to calculate the SEE cross-section. The single-event upset (SEU) cross-section results demonstrate a good agreement with the experimental data in terms of shape and order of magnitude for different technological nodes.
Stream Chemistry and Forest Recovery Assessment and Prediction Modeling in Coal-Mine-Affected Watersheds in Kentucky, USA
Authors: Sariyildiz Oguz , Gyawali Buddhi R. , Antonious George F. , Semmens Kenneth , Zourarakis Demetrio , Bhatt Maya P.
Published: February 2024

Kentucky is one of the largest coal-producing states; surface coal mining has led to changes in natural land cover, soil loss, and water quality. This study explored relationships between actively mined and reclaimed areas, vegetation change, and water quality parameters. The study site evaluated 58 watersheds with Landsat-derived variables (reclamation age and percentage of mining, reclaimed forest, and reclaimed woods) as well as topographic variables (such as elevation, slope, drainage density, and infiltration). Water samples were collected in spring (n = 9), summer (n = 14), and fall (n = 58) 2017 to study changes in water quality variables (SO42−, alkalinity, conductivity, Ca2+, Mg2+, Mn2+, Al3+, and Fe2+, Fe3+) in response to changes in land cover. Pearson correlation analyses indicated that conductivity has strong to very strong relationships with water quality variables related to coal mining (except Al3+, Fe2+, Fe3+, Mn2+, elevation, slope, and drainage density) and land cover variables. In addition, separate regression analyses were performed, with conductivity values based on samples collected in the fall. First, conductivity responses to mining percentage, reclamation age and topographic variables were examined (adjusted R2 = 0.818, p < 0.01). Next, vegetation cover change parameters were added to the same model, which yielded slightly improved R2 (adjusted R2 = 0.826, p < 0.01). Finally, reclamation age and mining percentages were used to explain the quantity of reclaimed forested areas as a percentage of watersheds. The model was significant (p < 0.01), with an adjusted R2 value of 0.641. Results suggest that the quantity (area as a percentage) of reclaimed forests may be a predictor of the mining percentage and reclamation age. This study indicated that conductivity is a predictable water quality indicator that is highly associated with Coal-Mine-Related Stream Chemistry in areas where agriculture and urban development are limited. Water quality is not suitable for various purposes due to the presence of contaminants, especially in mined sites. These findings may help the scientific community and key state and federal agencies improve their understanding of water quality attributes in watersheds affected by coal mining, as well as refine land reclamation practices more effectively while such practices are in action.
Addressing Carbon Storage in Forested Landscape Management Planning—An Optimization Approach and Application in Northwest Portugal
Authors: Marques Susete , Rodrigues Ana Raquel , Paulo Joana Amaral , Botequim Brigite , Borges José G.
Published: February 2024

Climate change is driving worldwide efforts to mitigate and reverse the increasing anthropogenic emissions of greenhouse gases. Forests can uptake considerable amounts of carbon from the atmosphere, but management decisions and resultant silvicultural practices can largely influence these ecosystems’ carbon balance. This research presents an approach to help land managers cope with the need to ensure the provision of forest products and services while contributing to mitigating climate change via carbon sequestration. The emphasis is on combining a landscape-level resource capability model with a mathematical programming (LP) optimization method to model and solve a land management problem involving timber production, carbon sequestration, and resistance to wildfire targets. The results of an application on a forested landscape in Northwest Portugal showed that this approach may contribute to analyzing and discussing synergies and trade-offs between these targets. They revealed important trade-offs between carbon sequestration and both timber production and fire resistance.
Production of Chestnut Coppice Biomass in a Framework of Low Mechanization and High Expectations to Combat Climate Change and Other Social Expectations
Authors: Carbone Francesco , Portoghesi Luigi , Romagnoli Manuela , Barbarese Francesco , Grassi Teresa
Published: February 2024

Climate change has become one of the most critical problems facing modern society. Sustainable forest management can be an important solution to counter the increasing concentration of carbon dioxide in the atmosphere. In particular, management of the chestnut forest could prove to be an effective strategy to absorb carbon dioxide as this species is characterized by sustained growth, so it has a high capacity to store carbon, and through the use of wood products, it is possible to sequester it for a considerable period. Chestnut (Castanea sativa Mill.) forests cover an area of about 800,000 ha in Italy, most of which is managed as coppice. It plays a central role in the Latium Region where its productive function is very important, as it provides timber of excellent quality. The purpose of this paper is to verify whether the current management of chestnut is efficient, as well as whether retractable wood products can contribute to the fight against climate change. The chestnut coppice located in the municipality of Tolfa (Lazio region, Italy) produces timber for 352 m3/ha and stores about 390,000 kg of CO2. Wood residues and losses during woodworking, together with emissions for the use of machineries, generate emissions of 368,000 kg of CO2. The chestnut semi-finished products, with long-term use prospects, retain a net volume of 22,000 kg of CO2. Although this is good for combating climate change, the amount of CO2 stored is very low, less than 6% of the CO2 stored by functional unit. Chestnut wood has a high versatility of use, so it could replace several products generated by fossil raw materials. Moreover, the implementation of precision forestry, the adoption of forest management more oriented to favor larger plants, the development of local economies and the reduction in the carbon footprint of the wood supply chain through the use of sustainable technologies would increase the capacity for climate change mitigation and increase the added value of its products.
Forestry Scenario Modelling: Qualitative Analysis of User Needs in Lithuania
Authors: Juknelienė Daiva , Palicinas Michailas , Valčiukienė Jolanta , Mozgeris Gintautas
Published: February 2024

This paper aims to demonstrate the use of qualitative research methods, specifically in-depth interviews, to explore the intangible and often difficult-to-quantify needs for forestry scenario modelling in Lithuania, which are frequently not adequately perceived. The study involved informants representing key actors in forest policy, forest management, research, and education. A total of 21 informants from 11 different institutions, which hold significant power and expertise in forest decision making, were interviewed. The purpose of these interviews was to gather their perspectives on the potential forest decision support system in the country, aiming to address most of their needs. The interview questions explored various aspects, including the requirements for forestry scenario modelling, the desired level of detail and information content for decision making, and both functional and nonfunctional requirements for the scenario modelling system. It is worth noting that the expected functionality of the planned forest DSSs aligns with modern international standards. Nevertheless, the diversity of perspectives, wishes, visions, and intentions of key Lithuanian forestry actors regarding the aims, objectives, and essential functionality of forestry scenario modelling tools were identified. The understanding of the requirements for modern forest DSSs was greatly influenced by the current forestry paradigms in the country and the professional experiences of individual informants. In conclusion, our findings demonstrate that the utilization of qualitative research, particularly through in-depth interviews, has proven to be a highly effective tool for accurately specifying the requirements of a modern forest DSS. It helped mitigate preconceived notions and address gaps in the envisioned product, specifically by developing a framework of core solutions for the national forestry and land-use scenario modelling system.
The Stool Microbiome in African Ruminants: A Comparative Metataxonomic Study Suggests Potential for Biogas Production
Authors: Vogel Felipe Werle , Carlotto Nicolas , Wang Zhongzhong , Garrido Lydia , Chatzi Vasiliki , Herrero Raquel Gonzalez , Benavent-Albarracín Luis , Gimenez Javier Martinez , Carbonell Loles , Porcar Manuel
Published: February 2024

Lignocellulosic biomass is a promising substrate for anaerobic digestion (AD) in renewable energy generation but presents a significant challenge during the hydrolysis stage of conventional AD due to the recalcitrant nature of this biomass substrate. Rumen fluid is often employed as a bioaugmentation seed to enhance hydrolysis in the AD of lignocellulosic substrates due to its richness in hydrolytic bacteria. However, using rumen fluid to enhance AD processes presents substantial hurdles, including the procurement difficulties associated with rumen fluid and ethical concerns. In this study, the fecal microbiota of 10 African ruminant species from a large zoological park (Bioparc) in Valencia, Spain, were studied using 16S rRNA gene amplicon sequencing. In this study, the fecal microbiota of 10 African ruminant species from a large zoological park (Bioparc) in Valencia, Spain, were studied using 16S rRNA gene amplicon sequencing. The investigation revealed potential similarities between the fecal microbiota from the African ruminants’ and cows’ rumen fluids, as suggested by theoretical considerations. Although direct comparative analysis with cow rumen fluid was not performed in this study, the theoretical framework and existing literature hint at potential similarities. According to our results, the Impala, Blesbok, Dikdik and Bongo ruminant species stood out as having the greatest potential to be used in bioaugmentation strategies. Key genera such as Fibrobacter, Methanobrevibacter, and Methanosphaera in Impala samples suggested Impala rumen fluid’s involvement in cellulose breakdown and methane production. Blesbok and Dikdik exhibited a high abundance of Bacillus and Atopostipes, potentially contributing to lignin degradation. The richness of Prevotellaceae and Rikenellaceae in the Bongo fecal samples is probably associated with structural carbohydrate degradation. Taken together, our results shed light on the microbial ecology of the gut contents of a whole set of Bovidae ruminants and contribute to the potential application of gut microbiota in AD.
Predicting the Fishery Ground of Jumbo Flying Squid (Dosidicus gigas) off Peru by Extracting Features of the Ocean Environment
Authors: Zhang Tianjiao , Xin Jia , Yu Wei , Yuan Hongchun , Song Liming , Yang Zhuo
Published: February 2024

We introduce a novel method that combines satellite data, advanced clustering techniques, machine learning feature extraction, and statistical models to enhance fishery forecasting accuracy. Focusing on jumbo flying squid in the southeast Pacific Ocean near Peru, we utilize MODIS-Aqua and MODIS-Terra satellite data on sea surface temperature (SST) to construct a deep convolutional embedded clustering (DCEC) model and extract the monthly SST features (FM) based on an optimized number of clusters determined by the Davies–Bouldi index (DBI). We use the extracted FM to construct a series of Generalized Additive Models (GAM) to forecast the catch per unit effort (CPUE) of jumbo flying squid within a spatial resolution of 0.5° × 0.5°. Our results demonstrate the following findings: (1) The SST feature clusters obtained through the DCEC model could capture the SST monthly variations; (2) The GAM models with FM outperform the models with the traditional monthly average SST in terms of predictive accuracy; (3) Using both FM and average SST together can further improve model performance. This study demonstrates the effectiveness of the DCEC combined with DBI in extracting marine environmental features and highlights the ocean environment feature extraction method to enhance the precision and reliability of fishery forecasting models.
Physicochemical and Sensory Properties of Arabica Coffee Beans of Arara cv. Dried Using Different Methods
Authors: Coelho Emerson G. , Bertarini Pedro L. L. , Gomes Matheus S. , Amaral Laurence R. , Zotarelli Marta F. , Santos Líbia D. , Santana Ricardo C.
Published: February 2024

The coffee fruit is preferably harvested at the cherry stage, with high moisture and metabolic activity, and must then undergo a drying process for better preservation of the bean and its sensory attributes. In this context, this study aimed to characterize the final quality of the Arara cultivar Arabica coffee processed using the wet method and subjected to six drying methods: three conducted at the agro-industrial establishment (fixed-bed dryer, rotary drum dryer, and combined drying) and three laboratory-scale methods (convective oven, cast-tape drying, and suspended terrace). Drying was carried out to reduce the coffee’s moisture content from an initial value of 46.2% on a wet basis (w.b.) to a final average value of 11.35% (w.b.). The fruits of in natura demucilaged coffee and the processed dry coffee beans were characterized for moisture, ash content, nitrogen compounds, lipids, total titratable acidity, organic acids, sugars, and the instrumental color of the beans. The sensory profile of the Arabica coffee was evaluated by five coffee specialists using the methodology proposed by the Specialty Coffee Association (SCA), and all the coffees were classified as a specialty.
Studies of Potential Migration of Hazardous Chemicals from Sustainable Food Contact Materials
Authors: Simonetti Giulia , Riccardi Carmela , Pomata Donatella , Acquaviva Luca , Fricano Andrea , Buiarelli Francesca , Senofonte Marta , Di Filippo Patrizia
Published: February 2024

In recent years, due to modern techniques for the distribution, transport, and retail sale of food, the production of large amounts of non-biodegradable and bioaccumulative packaging waste has become a major environmental issue. To address this issue, new food packaging materials based on renewable biomass have been studied as eco-friendly, biodegradable, and biocompatible alternatives to synthetic materials. However, although these materials are not petrochemical derivatives, the presence of contaminants cannot be excluded. This work aims to extend the knowledge on bio-based packaging materials, researching the presence of contaminants potentially able to migrate to food at concentrations of concern. In this study, we focus on two classes of contaminants, organophosphate esters (OPEs) and perfluoroalkyl substances (PFASs), carrying out migration tests toward different simulants, according to the current European regulation. PFAS analysis was performed using high-resolution liquid chromatography coupled to ion trap-tandem mass spectrometry (QTrap). OPE analyses were performed both by gas chromatography–mass spectrometry (GC-MS) and high-resolution liquid chromatography coupled to triple quadrupole mass spectrometry (TQMS). Preliminary findings demonstrate the release of toxic OPEs and PFASs from bio-based food packaging, highlighting the need to investigate the presence of potentially harmful chemicals in these materials.
Do Mindful Eating and Intuitive Eating Affect Beverage Preferences? A Cross-Sectional Survey
Authors: Kose Gizem , Bas Murat
Published: February 2024

Intuitive eating involves following body signals to guide eating decisions and avoiding restrictive diets. Mindful eating is paying full attention to sensory experiences and fostering nonjudgmental awareness. We aimed to elucidate potential relationships between beverage intake and intuitive and mindful eating scores. This cross-sectional exploratory study (October 2021–December 2022) enrolled adult male and female participants who provided sociodemographic and health-related information and subsequently completed the Beverage Intake Questionnaire, the Mindful Eating Questionnaire (MEQ-30), and the Intuitive Eating Scale (IES-2). Bidirectional relationships were observed between beverage intake and intuitive and mindful eating scores. The total beverage intake of males was double compared with that of females, with the intake being mainly derived from sugar-sweetened beverages (p = 0.000). Increased total water intake was positively correlated with IES-2 and its subscale scores and was negatively correlated with MEQ-30 scores in both sexes (p < 0.05). Alcoholic beverage intake was associated with reductions in IES-2 and MEQ-30 scores, whereas unconditional permission to eat increased by 18.3% in males. In females, the consumption of milk-based beverages decreased the IES-2 scores. Understanding the complex relationships between beverage intake and intuitive and mindful eating may deepen our understanding of individual dietary behaviors and inform dietary interventions.
Comparative Analysis of Characteristic Volatile Compounds in Five Types of Infant Nutrition Powders by HS-GC-IMS and GC-MS
Authors: Yang Zhihua , Li Jinjin , Guo Xiaoming
Published: February 2024

This study employed the headspace-gas chromatography-ion migration spectrum (HS-GC-IMS) in conjunction with the gas chromatography-mass spectrometer (GC-MS) technique for the assessment of the flavor quality of complementary food powder intended for infants and young children. A total of 62 volatile compounds were identified, including aldehydes, esters, alcohols, ketones, pyrazines, and furans, among which aldehydes were the most abundant compounds. Based on the principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) models, infant nutritional powder (YYB) from different manufacturers could be clearly distinguished. Among them, 2-hydroxybenzaldehyde, 1, 2-dimethoxyethane, 2-isobutyl-3-methoxypyrazine, and methyl butyrate were the four most critical differential volatiles. In addition, these differences were also manifested in changes in fatty acids. The reason for this phenomenon can be attributed to the difference in the proportion of raw materials used in nutrition powder, micronutrient content, and the packaging process. In conclusion, this study provides comprehensive information on the flavor quality of YYB, which can be used as a basis for quality control of YYB.
Monitoring the Use of Human Milk, the Ideal Food for Very Low-Birth-Weight Infants—A Narrative Review
Authors: Quitadamo Pasqua Anna , Zambianco Federica , Palumbo Giuseppina , Wagner Xavier , Gentile Maria Assunta , Mondelli Antonio
Published: February 2024

Aware of the utmost importance of feeding premature babies—especially those of lower weight—with human milk, as well as the need to monitor this important element of neonatal care, we focused on four aspects in this review. First of all, we reviewed the beneficial effects of feeding premature infants with breast milk in the short and long term. Secondly, we performed a quantitative evaluation of the rates of breastfeeding and feeding with human milk in Very-Low-Birth-Weight infants (VLBWs) during hospitalization in the Neonatal Intensive Care Unit (NICU) and at discharge. Our aim was to take a snapshot of the current status of human milk-feeding care and track its trends over time. Then we analyzed, on the one hand, factors that have been proven to facilitate the use of maternal milk and, on the other hand, the risk factors of not feeding with breast milk. We also considered the spread of human milk banking so as to assess the availability of donated milk for the most vulnerable category of premature babies. Finally, we proposed a protocol designed as a tool for the systematic monitoring of actions that could be planned and implemented in NICUs in order to achieve the goal of feeding even more VLBWs with human milk.