bluuebunny/crossref_metadata_2025 huggingface dataset:
Climate Risk Assessment Framework in Real Estate: A Focus on Flooding
Authors: Wu Shu-Han , Chiang Chun-Lien , Huang Yu-Hung , Huang Jung , Tsao Jung-Hsuan , Tung Ching-Pin
Published: November 2024

Climate change exacerbates flood hazards, resulting in risks to real estate values that should be considered by long-term investors. Flood risk presents two major financial risks: market risk and credit risk. Market risk refers to potential property value loss, and credit risk increases the likelihood of mortgage defaults. However, methods and comprehensive data for quantifying global real estate flood risks are lacking. To address this problem, this paper proposes two flood risk assessment frameworks: the local-oriented approach (LOA) and global-oriented approach (GOA). Two hazard and three vulnerability assessment methods are also introduced to support these frameworks. The LOA vulnerability estimates of regions with complete records are required to support the GOA. Taiwan was selected as an example for the LOA assessment, and the results were used to estimate vulnerability overseas in GOA assessments. The results of case studies for buildings located in four cities in different countries were compared. The proposed framework enables investors and asset owners to globally quantify climate risks in real estate, even when the available data are incomplete. Users can choose the most appropriate approach on the basis of the available data and their tolerance for uncertainty.
Review of Uncertainty, Carbon Emissions, Greenness Index, and Quality Issues in Green Supply Chains
Authors: Ghayebloo Sima , Venkatadri Uday , Diallo Claver , Samuel Christian N. , Pishvaee Mir Saman
Published: November 2024

The ability of closed-loop supply chains (CLSC) and reverse logistics (RL) to improve the triple bottom line (economic, social and environmental values) has increased the development of design and management models for CLSCs and RL. Consequently, there exists an extensive body of literature dedicated to exploring these supply and logistics issues. This paper reviews recent and relevant literature on CLSC and RL with an emphasis on uncertainty, carbon emissions, greenness index, return product quality and reliability considerations. The selected references are organized, reviewed, and analyzed to establish valuable mapping to highlight major findings. Finally, the outcomes are synthesized, and the primary research gaps are emphasized, pointing toward potential avenues for future investigation. These findings reveal that research efforts must be directed towards the development of multi-criteria greenness indices and multi-objective robust optimization models for uncertain quality and reliability of returns.
Gaps in and Opportunities for Disaster Risk Reduction in Urban Areas Through International Standardization of Smart Community Infrastructure
Authors: Nguyen David N. , Usuda Yuichiro , Imamura Fumihiko
Published: November 2024

Global communities are becoming increasingly vulnerable to natural hazards and climate change, and the rapid pace of urbanization exacerbates these risks. According to the World Bank, approximately 50% of the world’s population lives in areas exposed to natural hazards, making the need to overcome the challenges to sustainable urban development pressing. The increasing frequency of heavy rain, flooding, landslides, and wildfires underscores the urgent need for disaster risk mitigation strategies, aligned with sustainable development goals. Infrastructure plays a crucial role in cultivating resilient cities that can withstand, recover from, and adapt to disasters, while promoting long-term sustainability, by minimizing environmental degradation and encouraging responsible development. International standards for smart community infrastructure provide significant advantages, including cost reductions, technology transfer, and enhanced innovation through improved global competitiveness. This paper investigates how these standards can empower community stakeholders to strengthen both the resilience and sustainability of urban areas, facilitating balanced growth that addresses environmental and social demands.
Economic Analysis of the Impact of Waste on the Production and Consumption of Dates in Saudi Arabia
Authors: Alhamdan Abdullah , Alamri Yosef , Aljuhaim Fahad , Kotb Alaa , Aljohani Emad , Alaagib Sharafeldin , Elamshity Mahmoud
Published: November 2024

The goal of this study was to determine how the loss of dates affected food security in Saudi Arabia from 2000 to 2021. The researchers achieved this by using food security indicators, economic equations to quantify agricultural resource losses, and econometric analyses to develop a partial adjustment model. The results show that dates are considered a self-sufficient crop as well as an export crop, as the state resorts to exporting the surplus instead of storing it for local consumption. During the study period, there was an increase in the period of sufficiency in date production for local consumption and the period of coverage of imports for local consumption. In 2000, the volume of dates lost increased by approximately 131.22%. The total loss of land and water resources reached 31,918.4 hectares and 324.759 million cubic meters, respectively. The value of the partial adjustment coefficient (λ) indicates that about 81.1% of the imbalance in the equilibrium between the actual and equilibrium levels is adjusted within one year. Loss is considered one of the most important factors that determine food security for dates, in addition to the total value of loans financed to date factories, the total population, and the level of technological progress in the marketing and storage of dates. It was found that a change of 10% in these variables leads to a change in food security for dates of (−2.37%), 0.07, (−15.33%), and 0.58%, respectively, and the adjusted coefficient of determination was estimated at 0.93. This study recommends the following: (1) expanding the use of modern technologies for date post-harvest transportation and storage, and (2) increasing support and loans allocated to date factories to increase warehouses for cooling and storage to accommodate the increase in production and surplus consumption.
Power Battery Recycling Model of Closed-Loop Supply Chains Considering Different Power Structures Under Government Subsidies
Authors: Zeng Fei , Lu Zhiping , Lu Chengyu
Published: November 2024

With the rapid growth of the electric vehicle industry, the recycling of power batteries has attracted significant attention. In light of current circumstances, the question of how the government can incentivize relevant stakeholders to actively engage in recycling and improve its efficiency has become increasingly pressing. In this context, this study analyses and develops four closed-loop supply chain recycling models to investigate how different government subsidy recipients under varying power structures influence recycling efficiency, profitability, and the overall supply chain structures. The following conclusions are derived from numerical simulations: (1) Government subsidies serve to elevate recycling prices, expand profit margins, and consequently boost the volume of recycled batteries, thus incentivizing corporate engagement in recycling initiatives. (2) When the processor assumes the role of the leader in the Stackelberg game framework, it can maximize the overall efficiency and profitability of the supply chain. (3) The sensitivity coefficient and the competition coefficient are closely interrelated, exerting opposing impacts on the recycling decision made by enterprises. (4) The supply chain leader plays a crucial role in ensuring orderly supply chain development, with government subsidies of the supply chain being transmitted to its members through the leader. Consequently, this study offers a theoretical foundation for the government to enhance policy-making and for enterprises to make informed decisions. It also holds significant practical relevance in addressing the challenges associated with power battery recycling.
Kinetic Modeling of Brilliant Blue Discoloration by Ozonation
Authors: Crisciu Adrian Victor , Stoica Ligia , Constantin Carolina , Marcvart Maria (Tiron) , Hanganu Anamaria , Ianos Maria Gratiela (Craioveanu)
Published: November 2024

This paper presents the results of investigations on the kinetic modeling of Brilliant Blue FCF (BB) discoloration reactions in aqueous solutions with different ozone concentrations and pH conditions. Kinetic studies involve knowledge of the structure and properties of dye and ozone, as well as of the experimental conditions. In general, scientists admit that the predominant oxidation pathway is direct (by free oxygen atoms) or indirect (by free hydroxyl radicals); this will depend on influencing factors such as the physicochemical properties of the dye, the pH of the aqueous solution, ozone concentration, reaction time, and the contact mode with/without stirring. In this experimental research, two pathways were chosen following CBB = f(t)—1. a constant dye concentration and different ozone concentrations, in the concentration range of 100–250 mg/L, in three pH media (acidic, neutral, and basic), with and without stirring; 2. a constant concentration of ozone and different dyes in the concentration range of 2.5–10 mg/L, under the conditions of point 1. With the obtained experimental data, the curves CBB = f(t) were drawn and processed according to the integral method of classical kinetics, based on first- and second-order equations. Unfortunately, this simple procedure did not give any results for the pH values studied. The rate constants were negative, and/or the reaction order depended on the initial conditions. Due to its structure, the BB dye has several chromophore groups, and thus multiple attack centers, resulting in several oxidation by-products, which is why the 1H-NMR spectrum was recorded for the discoloration of BB with ozone. Since the stoichiometry of the overall oxidation reaction, as well as the relationship between the rate constant and the reaction conditions mentioned above, is not known, a kinetic model based on mass transfer coupled with a chain reaction in the bulk liquid phase was proposed and successfully tested at pH = 7. This research approach also involves the consolidation of the theoretical bases of the ozonation process through the kinetic study carried out, as well as the proposal of a kinetic model. These systematics lead to results that are applicable to other aqueous systems that are impure with dyes, allowing for generalizations and the development of the field, ensuring the sustainability of the research.
Life Cycle Prediction of Airport Operation Based on System Dynamics
Authors: Wan Lili , Shan Zhanpeng , Jiang Xinyue , Wang Zhan , Lv Yangyang , Xu Shumeng , Huang Jiahui
Published: November 2024

Traditional airport development planning often overlooks an in-depth consideration of the airport operation life cycle, which frequently causes deviations from planned objectives during operation. This paper presents a framework for predicting and segmenting the airport operation life cycle by integrating the dynamic characteristics of the System Dynamics (SD) model with the static properties of Logistic modeling to examine the development trajectory of airport operations. The influencing factors in this model are selected across three levels: airport, city, and macro-environment. A system dynamics model of airport operation is constructed using causal loop diagrams and system flow diagrams. Using Guangzhou Baiyun International Airport (CAN) as a case study, the airport’s operational capacity from 2005 to 2035 is predicted through SD simulation. Subsequently, the airport operation life cycle from 2005 to 2050 is forecasted and segmented using Logistic modeling. The results indicate that, under the standard scenario, CAN’s operational capacity experiences two declines in 2016 and 2020, attributed to airport construction and emergencies. Logistic modeling identifies three distinct life cycle phases in the airport’s operation. Furthermore, by comparing various airport operation scenarios, the analysis reveals that fluctuations in the city economy significantly impact the airport’s operational system without altering its overall development trajectory. In contrast, the occurrence of emergencies can substantially modify the airport operation life cycle.
Transitioning Design-Orienting Scenarios for Food Systems: A Design Contribution to Explore Sustainable Solutions and Steer Action
Authors: Corubolo Marta , Meroni Anna
Published: November 2024

This article explores how design, as a disciplinary field, can play a role in conceiving and supporting transition strategies within complex food systems where multiple actors are involved and sustainability is a priority. The work builds on the methodology of Design-Orienting Scenarios (DOS), which are future-oriented narratives motivated, illustrated, and visualized through specific solutions. DOS are applied here to contribute to the ongoing transformation of the Milano Food System, which is at the intersection of dynamics influencing the activities of its various ‘nodes’—pivotal points in the supply chain. A specific scenario is then co-designed with relevant actors, combining two influencing factors: governance and sustainability strategy. The aim of this scenario is to highlight areas of multi-actor collaboration and spark transformative projects while also defining roles, values, and capabilities. This article further introduces the evolution of DOS into Transitioning Design-Orienting Scenarios (T-DOS), designed to facilitate outcome-oriented transitions. Characterized by a multi-actor and relational perspective, T-DOS engage stakeholders through a structured process, leveraging local challenges, resources, and actors to ensure the relevance and applicability of practical futures. The T-DOS methodology is finally discussed as a tool to guide systemic design-oriented conversations within the food system and, more broadly, within complex systems.
Multi-Objective Optimal Power Flow Analysis Incorporating Renewable Energy Sources and FACTS Devices Using Non-Dominated Sorting Kepler Optimization Algorithm
Authors: Abid Mokhtar , Belazzoug Messaoud , Mouassa Souhil , Chanane Abdallah , Jurado Francisco
Published: November 2024

In the rapidly evolving landscape of electrical power systems, optimal power flow (OPF) has become a key factor for efficient energy management, especially with the expanding integration of renewable energy sources (RESs) and Flexible AC Transmission System (FACTS) devices. These elements introduce significant challenges in managing OPF in power grids. Their inherent variability and complexity demand advanced optimization methods to determine the optimal settings that maintain efficient and stable power system operation. This paper introduces a multi-objective version of the Kepler optimization algorithm (KOA) based on the non-dominated sorting (NS) principle referred to as NSKOA to deal with the optimal power flow (OPF) optimization in the IEEE 57-bus power system. The methodology incorporates RES integration alongside multiple types of FACTS devices. The model offers flexibility in determining the size and optimal location of the static var compensator (SVC) and thyristor-controlled series capacitor (TCSC), considering the associated investment costs. Further enhancements were observed when combining the integration of FACTS devices and RESs to the network, achieving a reduction of 6.49% of power production cost and 1.31% from the total cost when considering their investment cost. Moreover, there is a reduction of 9.05% in real power losses (RPLs) and 69.5% in voltage deviations (TVD), while enhancing the voltage stability index (VSI) by approximately 26.80%. In addition to network performance improvement, emissions are reduced by 22.76%. Through extensive simulations and comparative analyses, the findings illustrate that the proposed approach effectively enhances system performance across a variety of operational conditions. The results underscore the significance of employing advanced techniques in modern power systems enhance overall grid resilience and stability.
Charting Success: The Influence of Leadership Styles on Driving Sustainable Employee Performance in the Sierra Leonean Banking Sector
Authors: Kebe Ibrahim Alusine , Kahl Christian , Liu Yingqi
Published: November 2024

Effective leadership sits at the heart of organisational success, especially during periods of change. In the dynamic and highly competitive environment of commercial banks in Sierra Leone, the impact of leadership styles on employee performance is a critical area of investigation. The purpose of this paper is to assess the differential effects of transformational and transactional leadership styles on employee performance during change initiatives within commercial banks in Sierra Leone. The research study utilised a cross-sectional survey design, and data was collected from 903 participants employed in the banking industry. The study used the structural equation model as an investigative instrument to examine the hypotheses. The findings reveal that transformational and transactional leadership styles demonstrate a strong bearing on employee performance, with the latter having a bigger influence. Organisational citizenship behaviour has a mediating effect between leadership styles and employee performance. In contrast, employee commitment does not act as a mediator between transformational leadership and employee performance but does act as a mediator between transactional leadership and employee performance. Commercial banks need to devise training programs that will advance both leadership styles to arouse, energise, or inspire followers to display favourable behaviour and commitment to attain organisational goals. The paper makes an insightful contribution to the existing leadership literature by ascertaining the significance of leadership styles on performance and the role of commitment and organisational citizenship behaviour as mediators of the nexus between leadership styles and performance in the Sierra Leone banking industry.
Driving Safety and Comfort Enhancement in Urban Underground Interchanges via Driving Simulation and Machine Learning
Authors: Liu Qian , Liu Zhen , Cui Bingyan , Zhu Chuanhui
Published: November 2024

Urban transportation systems, particularly underground interchanges, present significant challenges for sustainable and resilient urban design due to their complex road geometries and dense traffic signage. These challenges are further compounded by the interaction of diverse road users, which heightens the risk of accidents. To enhance both safety and sustainability, this study integrates advanced driving simulation techniques with machine learning models to improve driving safety and comfort in underground interchanges. By utilizing a driving simulator and 3D modeling, real-world conditions were replicated to design key traffic safety features with an emphasis on sustainability and driver well-being. Critical safety parameters, including speed, acceleration, and pedal use, were analyzed alongside comfort metrics such as lateral acceleration and steering torque. The LightGBM machine learning model was used to classify safety and comfort grades with an accuracy of 97.06%. An important ranking identified entrance signage and deceleration zones as having the greatest impact on safety and comfort, while basic road sections were less influential. These findings underscore the importance of considering visual cues, such as markings and wall color, in creating safer and more comfortable underground road systems. This study’s methodology and results offer valuable insights for urban planners and engineers aiming to design transportation systems that are both safe and aligned with sustainable urban mobility objectives.
Assessment of the Recreational Potential of Flooded Quarries in Slovakia
Authors: Iannaccone Barbora , Domaracká Lucia , Tometzová Dana , Gabániová Ľubomíra
Published: November 2024

This article focuses the assessment of the recreational potential of selected water-filled quarries in Slovakia, specifically the Škrabské, Beňatina, and Kraľovany quarries. Water-filled quarries represent a significant untapped resource that can contribute to the development of various leisure activities while simultaneously supporting local communities and environmental conservation. The main challenge of the study is finding a balance between the recreational use of these sites and the need to maintain ecological sustainability, which requires a detailed evaluation of the natural conditions, infrastructure, and accessibility of the individual quarries. The study focuses on a comprehensive assessment of the recreational potential of selected water-filled quarries in Slovakia, specifically the Škrabské, Beňatina, and Kraľovany quarries, using a methodology based on point evaluation according to criteria such as natural beauty, accessibility, existing infrastructure, and ecological status. The results of this study provide an important foundation for further research and decision-making processes in the transformation of water-filled quarries, aiming to maximize their recreational potential while ensuring long-term environmental sustainability.
Mapping Soil Surface Moisture of an Agrophytocenosis via a Neural Network Based on Synchronized Radar and Multispectral Optoelectronic Data of SENTINEL-1,2—Case Study on Test Sites in the Lower Volga Region
Authors: Zeyliger Anatoly , Muzalevskiy Konstantin , Ermolaeva Olga , Grecheneva Anastasia , Zinchenko Ekaterina , Gerts Jasmina
Published: November 2024

In this article, the authors developed a novel method for the moisture mapping of the soil surface of agrophytocenosis using a neural network based on synchronized radar and multispectral optoelectronic data from Sentinel-1,2. The significance of this research lies in its potential to enhance precision farming practices, which are increasingly vital in addressing global agricultural challenges such as water scarcity and the need for sustainable resource management. To verify the developed method, data from two experimental plots were utilized. These plots were located on irrigated soybean crops, with the first plot situated on the right bank (plot No. 1) and the second on the left bank (plot No. 2) of the lower Volga River. Two experimental soil moisture geodatasets were created through measurements and geo-referencing points using the gravimetric method (for plot No. 1) and the proximal sensing method (for plot No. 2) employing the Soil Moisture Sensor ML3-KIT (THETAKIT, Delta). The soil moisture retrieval algorithm was based on the use of a neural network to predict the reflection coefficient of an electro-magnetic wave from the soil surface, followed by inversion into soil moisture using a dielectric model that takes into account the soil texture. The input parameter of the neural network was the ratio of the microwave radar vegetation index (calculated based on Sentinel-1 data) to the index (calculated based on the data of multispectral optoelectronic channels 8 and 11 of Sentinel-2). The retrieved soil moisture values were compared with in situ measurements, showing a determination coefficient of 0.44–0.65 and a standard deviation of 2.4–4.2% for plot No. 1 and similar metrics for plot No. 2. The conducted research laid the groundwork for developing a new technology for remote sensing of soil moisture content in agrophytocenosis, serving as a crucial component of precision farming systems and agroecology. The integration of this technology promotes sustainable agricultural practices by minimizing water consumption while maximizing crop productivity. This aligns with broader environmental goals of conserving natural resources and reducing agricultural runoff. On a larger scale, data derived from such studies can inform policy decisions related to water resource management, guiding regulations that promote efficient water use in agriculture.
Urban Transportation Data Research Overview: A Bibliometric Analysis Based on CiteSpace
Authors: Liang Yanni , You Jianxin , Wang Ran , Qin Bo , Han Shuo
Published: November 2024

Urban transportation data are crucial for smart city development, enhancing traffic management’s intelligence, accuracy, and efficiency. This paper conducts a comprehensive investigation encompassing policy analysis, a literature review, concept definition, and quantitative analysis using CiteSpace from both domestic and international perspectives. Urban transportation data comprise multiple dimensions, such as infrastructure status, real-time monitoring, policy planning, and environmental assessment, which originate from various sources and stakeholders. Highly influential authors and active institutions, particularly in the USA, China, Canada, and England, contribute significantly to extensive and collaborative research. Key areas include intelligent transportation, traffic flow prediction, data fusion, and deep learning. Domestic research focuses on practical applications, while international studies delve into interdisciplinary research areas. With advancements in intelligent systems and big data technology, research has evolved from basic data collection to sophisticated methodologies, such as deep learning and spatiotemporal analysis, driving substantial progress. This paper concludes by recommending enhanced data integration, improved privacy and security, fostering big data and AI applications, facilitating policy formulation, and exploring innovative transportation modes, thereby underscoring the importance of urban transportation data in shaping the future of smart cities. The findings provide theoretical and practical guidance for the future intelligence, efficiency, and sustainability of urban transportation systems.
A Bibliometric Review of Indoor Environment Quality Research and Its Effects on Occupant Productivity (2011–2023)
Authors: Shetaw Mustafa , Gyoh Louis , Gerges Michael , Dimka Nenpin
Published: November 2024

Over the past decade, there has been a growing recognition of the importance of indoor environmental quality (IEQ) in influencing occupant productivity. Researchers have studied various buildings, including offices, schools, hospitals, and residential settings, to understand the relationship between IEQ and productivity outcomes. Studies have taken a multifactorial approach, considering multiple aspects of IEQ. Evidence from the literature review suggests that the quality of the indoor environment is an essential factor that affects the productivity of building occupants, and it is one of the fundamental issues in the development of societies. This area of research requires the responsible participation of researchers at all levels, as there is significant scope to contribute to knowledge. Therefore, this study aims to conduct a bibliometric analysis of the published literature on indoor environmental quality and its impact on building occupant productivity through the scientific literature available from one of the largest and most famous academic databases, Scopus; the study was determined in 2011 to 2023. The search used differential thresholds for IEQ keywords affecting building occupant productivity. Three discrete queries were performed, resulting in approximately 3861 publications. These were filtered by reducing false positives and excluding publications irrelevant to the research topic. The final results were 72 publications. This study also used Excel and VOS viewer to analyse and create graphs and network visualisation maps to show the growth of publications and their types, active countries and institutions for recovered publications, international collaboration, author keywords, active journals, and citation analysis. This study can significantly advance our understanding of building occupant productivity and enhance quality of life and work. Evaluating the research outputs is essential for highlighting contributions to knowledge and global collaboration in this research area. The potential impact of this study is not just theoretical. It can shape the future of our built environments and the lives of those occupying them.
Cross-Docking Layout Optimization in FlexSim Software Based on Cold Chain 4PL Company
Authors: Lorenc Augustyn
Published: November 2024

The paper highlights the potential of cross-docking to reduce storage time and costs. The study addresses evolving market demands that push logistics providers to adopt new technologies for operational efficiency, emphasizing the often-overlooked importance of optimizing cross-docking layouts. The research, conducted in two phases, first analyzed the current warehouse layout (Variant I) to identify inefficiencies and then designed a new layout (Variant II) that was simulated using FlexSim 2022 software. The results showed significant improvements with the new layout, including a 35% increase in deliveries and a 3.23% reduction in forklift travel distances, leading to lower operational costs. Even minor adjustments in the warehouse design proved to enhance logistics efficiency, particularly during peak demand periods like holidays. The study demonstrates how FlexSim software can be applied in cold chain logistics to optimize warehouse operations, underscoring the benefits of cross-docking for cost-effective logistics management.
Overview of the Special Issue: Embracing the Messiness of Transdisciplinarity
Authors: Crofts Kimberley , Rifkin Will , Espig Martin , Perey Robert , Bray Heather
Published: November 2024

This Special Issue utilizes a transdisciplinary lens to analyse how environment-related problems are being framed and communicated in different settings [...]
Valuing Sustainability Impacts and Food Security Effects of Local Mariculture
Authors: Greenfeld Asael , Angel Dror , Farja Yanay
Published: November 2024

Global events such as the COVID-19 pandemic and regional events like the wars in Ukraine and in Gaza have affected and still affect global supply chains, including those for food. This has increased awareness of the importance of local food production, including aquaculture and mariculture. In this study, we point out and calculate the economic values of environmental sustainability and food security inherent in local production versus import alternatives. We present a case study involving the environmental effects and food security of supplying sea fish to the Israeli market from local production versus imports. The results show that increasing the consumption of seabream in Israel from imports, rather than local production, causes substantial external costs by increasing environmental damage due to increased transport and increasing potential food insecurity. Decision-makers should take these costs into account when deciding on a policy to support local aquaculture.
Ecological Assessment of Phytoplankton Diversity and Water Quality to Ensure the Sustainability of the Ecosystem in Lake Maybalyk, Astana, Kazakhstan
Authors: Tekebayeva Zhanar , Bazarkhankyzy Aidana , Temirbekova Aliya , Rakhymzhan Zhanar , Kulzhanova Kamshat , Beisenova Raikhan , Kulagin Andrey , Askarova Nurgul , Yevneyeva Dinara , Temirkhanov Aslan , Abzhalelov Akhan
Published: November 2024

Microalgae in planktonic communities are the main producers of biomass in lake ecosystems; however, their stability is influenced by many environmental factors. This study aims to assess the ecological state of Lake Maybalyk, located in Astana (Kazakhstan), based on the study of the taxonomic diversity and structure of phytoplankton, zooplankton, and the physico-chemical properties of the water. From 2019 to 2021, samples were taken for phytoplankton analysis, hydrochemical analysis of the water, zooplankton, and saprobiological analysis of the algocenosis. The study also investigated the main morphometric parameters of the lake, as well as the composition of hydrobionts, such as zooplankton, zoobenthos, and ichthyofauna. The analysis of phytoplankton revealed the presence of 97 species and intraspecific taxa of microalgae, with 71 types of microalgal indicators indicating water saprobity. The planktonic algoflora in Lake Maybalyk is predominantly composed of diatoms (Bacillariophyta) and green algae (Chlorophyta), which play a vital role in oxygen production and the food chain within the reservoir. Based on the Pantle–Buck saprobity index (2.15–2.5), the water quality in Lake Maybalyk is classified as moderately polluted. The assessment of the water quality, considering the number and composition of indicator phytoplankton species, places Lake Maybalyk in class III (β-mesosaprobic). The hydrochemical indicators align with the hydrobiological indicators, confirming the water quality as class III. The trophic status of the reservoir, during the study period, can be described as average. The obtained data on both the hydrobiological and hydrochemical indicators correlate, suggesting satisfactory water quality and the ability of the reservoir to purify itself. This study contributes to the sustainable management of water resources, by providing essential data on the ecological state of Lake Maybalyk. The results underscore the importance of continuous biomonitoring, with microalgae as indicators of water quality, which is crucial for developing effective ecosystem conservation strategies.
Investigation and Simulation Study on the Impact of Vegetation Cover Evolution on Watershed Soil Erosion
Authors: Shen Dandan , Guo Yuangang , Qu Bo , Cao Sisi , Wu Yaer , Bai Yu , Shao Yiting , Qian Jinglin
Published: November 2024

Soil erosion has always been a critical issue confronting watershed environments, impacting the progress of sustainable development. As an increasing number of countries turn their attention to this problem, numerous policies have been enacted to halt the progression of soil erosion. However, policy-driven interventions often lead to significant changes in watershed vegetation coverage, under which circumstances, the original sediment erosion models may fall short in terms of simulation accuracy. Taking the Kuye River watershed as the research subject, this study investigates soil erosion data spanning from 1981 to 2015 and utilizes the Revised Universal Soil Loss Equation (RUSLE) model to simulate soil erosion. It is found that the extensive planting of vegetation after 2000 has led to a rapid reduction in soil erosion within the Kuye River watershed. The original vegetation cover and management factor (C) proves inadequate in predicting the abrupt changes in vegetation coverage. Consequently, this study adopts two improved plant cover and management factor equations. We propose two new methods for calculating the vegetation cover and management factor, one using machine learning techniques and the other employing a segmented calculation approach. The machine learning approach utilizes the Eureqa software (version11.0, Cornell University, New York, American) to search for the relationship between Normalized Difference Vegetation Index (NDVI) and C, ultimately establishing an equation that describes this relationship. On the other hand, the piecewise method determines critical values based on data trends and provides separate formulas for C above and below these critical values. Both methods have achieved superior calculation accuracy. Specifically, the overall data calculation using the machine learning method achieved an determined coefficient (R2) of 0.5959, while the segmented calculation method achieved an R2 of 0.6649. Compared to the R2 calculated by the traditional RULSE method, these two new methods can more accurately predict soil erosion. The findings of this study can provide valuable theoretical reference for water and soil prediction in watersheds.
Analysis of Factors Affecting CO2 Emissions in Türkiye Using Quantile Regression
Authors: Türkyılmaz Serpil , Öztürk Kadriye Nurdanay
Published: November 2024

This study aims to show how the impact of factors on carbon dioxide (CO2) emissions differs at the quantile level and to demonstrate the superiority of the quantile regression method over the OLS method by using quantile regression and ordinary least squares (OLS) methods in order to examine the factors affecting CO2 emissions in Türkiye in depth. Covering the period 1990–2021, this study evaluates the relationship between CO2 emissions and GDP per capita growth, population growth, and renewable energy consumption. One of the important findings of the study is that the increase in the population ratio, which is insignificant according to the OLS method, positively affects CO2 emissions at the 0.25 quantile point. According to both OLS and quantile regression methods, GDP growth does not affect CO2 emissions, while renewable energy consumption has a significant and negative effect according to both models. These results demonstrate that economic growth has no discernible impact on CO2 emissions in Türkiye, while investments in renewable energy can significantly lower emissions and open the door for quantile regression to be used more widely in related research. Unlike traditional methods that focus only on the conditional mean, the quantile regression method provides a comprehensive framework for Türkiye’s sustainable development policies by exploring factor effects at different emission levels.
Energy Poverty and Poor Buildings: A Brief Literature Review to Promote New Topics for Future Studies
Authors: Fabbri Kristian
Published: November 2024

The topic of energy poverty is a vast and complex one warranting extensive research. During the XX century, numerous research articles, books, and documents were published with the aim of defining energy poverty, measuring it, and proposing solutions to tackle it. The phenomenon of energy poverty can be studied using a variety of research methods, including the usual economic and econometric analyses, as well as energy policy. Research can also be conducted on the measurement of energy poverty and its social and health impact on disadvantaged communities. This can be explored in depth within specific subject areas, such as engineering, energy, environmental science, and social science. This brief review of literature focuses on energy poverty and poor buildings, thermal comfort, and the phenomenon of cooling poverty. The aim of this brief literature review is to show to a young researcher a previous framework and, through some keywords, that it is useful to drive future research using keywords.
Polycyclic Aromatic Hydrocarbons (PAHs) in Wheat Straw Pyrolysis Products Produced for Energy Purposes
Authors: Półtorak Andrzej , Onopiuk Anna , Kielar Jan , Chojnacki Jerzy , Najser Tomáš , Kukiełka Leon , Najser Jan , Mikeska Marcel , Gaze Błażej , Knutel Bernard , Berner Bogusława
Published: November 2024

Using agricultural waste biomass pyrolysis to produce energy sources and biochar may support local economies in rural areas and enhance sustainability in the agricultural sector, reducing dependence on traditional energy sources and fertilisers. To obtain liquid and gaseous forms of biomass fuel, wheat straw pellets were pyrolysed in a screw reactor at temperatures of 300, 400, 500, 600, and 700 °C. An analysis was conducted to assess the influence of process temperature on the physicochemical composition of the raw material and the resulting biochar, pyrolysis liquid, and synthesis gas. The presence of potentially harmful substances in the biochar, whose addition to soil can improve soil properties, was assessed by quantitatively determining polycyclic aromatic hydrocarbons (PAHs). Similar tests were carried out for pyrolysis fluid. The assessments were based on the standards for the most dangerous PAHs: fluorene, anthracene, fluoranthene, benzo[b]fluorine, benz[a]anthracene, chrysene, benzo[b]fluoranthene, benzo[k]fluoranthene, benzo[a]pyrene, dibenz[a,h]anthracene, benzo[g,h,i]perylene, and indeno[1,2,3-cd]pyrene. The results indicated that the total content of polycyclic aromatic hydrocarbons in the biochar ranged from 346.81 µg·kg−1 at 300 °C to 1660.87 µg·kg−1 (700 °C). In the pyrolytic fluid, the PAH content ranged from 58,240.7 µg·kg−1 (300 °C) to 101,889.0 µg·kg−1 (600 °C). It was found that the increase in PAH content in both the biochar and the liquid progressed with increasing pyrolysis temperature. After finding a correlation between the increase in the PAH content in biochar and the increase in the content of high-energy gases in the synthesis gas, it was concluded that it is difficult to reconcile the production of PAH-free biochar in the pyrolysis of biomass with obtaining high-energy gas and pyrolysis oil.
Analysis and Design of a Recyclable Inductive Power Transfer System for Sustainable Multi-Stage Rocket Microgrid with Multi-Constant Voltage Output Characteristics—Theoretical Considerations
Authors: Gu Peng , Wang Shibo , Zhou Bowen
Published: November 2024

After a traditional one-time rocket is launched, most of its parts will fall into the atmosphere and burn or fall into the ocean. The parts cannot be recycled, so the cost is relatively high. Multi-stage rockets can be recovered after launch, which greatly reduces the cost of space launches. Moreover, recycling rockets can reduce the generation of waste and reduce pollution and damage to the environment. With the reduction in rocket launch costs and technological advances, space exploration and development can be carried out more frequently and economically. It provides technical support for the sustainable use of space resources. It not only promotes the sustainable development of the aerospace field but also has a positive impact on global environmental protection, resource utilization, and economic development. In order to adapt to the stage-by-stage separation structure of the rocket, this paper proposes a new multi-stage rocket inductive power transfer (IPT) system to power the rocket microgrid. The planar coil structure is used to form wireless power transfer between each stage of the rocket, reducing the volume of the magnetic coupling structure. The volume of the circuit topology structure is reduced by introducing an auxiliary coil. An equivalent three-stage S/T topology is proposed, and the constant voltage output characteristics of multiple loads are analyzed. A multi-stage coil structure is proposed to supply power to multiple loads simultaneously. In order to eliminate undesired magnetic coupling between coils, ferrite cores are added between coils for effective electromagnetic shielding. The parameters of the magnetic coupling structure are optimized based on the finite element method (FEM). A prototype of the proposed IPT system is built to simulate a multi-stage rocket. A series of experiments are conducted to verify the advantages of the proposed IPT system, and the three-stage rocket system efficiency reached 88.5%. This project is theoretical. Its verification was performed only in the laboratory conditions.
Can Historical Accident Data Improve Sustainable Urban Traffic Safety? A Predictive Modeling Study
Authors: Wang Jing , Zhao Chenhao , Liu Zhixia
Published: November 2024

Traffic safety is a critical factor for the sustainable development of urban transportation systems. This study investigates the impact of historical accident information on the prediction of future traffic accident risks, as well as the interaction between this information and other features, such as driver violations and vehicle attributes. Using a comprehensive dataset of traffic accidents involving passenger vehicles in a western Chinese city, we developed two predictive models: Model 1, which is based on vehicle information and driver violations, and Model 2, which integrates historical accident data. The results indicate that the inclusion of historical accident information significantly enhances the predictive performance of the model, particularly in terms of AUC (Area Under the Curve) and AP (Average Precision) values. Furthermore, through feature importance analysis and SHAP (SHapley Additive exPlanations) value evaluation, this study reveals the interaction effects between historical accident data and other features, and how these interactions influence model decisions. The findings suggest that historical accident data play a positive role in predicting future accident risk, with varying effects on risk mitigation. These insights provide a scientific basis for developing strategies to ensure the sustainable development of urban transportation systems.
Enhancing Tourist Well-Being in Jilin Province: The Roles of Eco-Friendly Engagement and Digital Infrastructure
Authors: Huang Tai , Fang Chongbo , Dukhaykh Suad , Bayram Gül Erkol , Bayram Ali Turan
Published: November 2024

This study fills a research gap by examining how tourist participation, well-being, eco-friendly engagement, and digital infrastructure affect tourism results. We assessed 3692 tourists in Jilin Province, China, using structural equation modeling. We found that tourist participation is directly associated with tourist well-being, and eco-friendly engagement positively mediates tourist participation and tourist well-being. Furthermore, digital infrastructure moderates tourist participation and tourist well-being. Key findings reveal that actively participating in tourism activities considerably increases visitor well-being. Furthermore, eco-friendly behaviors and digital infrastructure may improve tourist well-being and overall experience. These findings may influence many tourist features in the Jilin Province of China. Tourism management should first provide a range of fun and engaging activities to boost tourist well-being. Second, promoting sustainable practices protects the environment and improves visitors’ quality of life. Third, digital infrastructure expenditures support these activities and enhance visitor pleasure. Policymakers should prioritize sustainable tourism. They should employ digital technologies to promote sustainability and improve services. Addressing these concerns may strengthen the country’s economy, sustainable development, and tourism. This study enhances tourist well-being theory by adding eco-friendly interaction, digital infrastructure, and visitor participation. It illuminates the importance of technology, sustainability, and active involvement in producing enjoyable tourist experiences.
Human Adaption to Climate Change: Marine Disaster Risk Reduction in the Era of Intelligence
Authors: Luo Junyao , Yang Aihua
Published: November 2024

With the intensification of global warming and sea level rise, extreme weather and climate events occur frequently, increasing the probability and destructive power of marine disasters. The purpose of this paper is to propose the specific application of artificial intelligence (AI) in marine disaster risk reduction. First, this paper uses computer vision to assess the vulnerability of the target and then uses CNN-LSTM to forecast tropical cyclones. Second, this paper proposes a social media communication mechanism based on deep learning and a psychological crisis intervention mechanism based on AIGC. In addition, the rescue response system based on an intelligent unmanned platform is also the focus of this research. Third, this paper also attempts to discuss disaster loss assessment and reconstruction based on machine learning and smart city concepts. After proposing specific application measures, this paper proposes three policy recommendations. The first one is improving legislation to break the technological trap of AI. The second one is promoting scientific and technological innovation to break through key technologies of AI. The third one is strengthening coordination and cooperation to build a disaster reduction system that integrates man and machine. The purpose of this paper is to reduce the risk of marine disasters by applying AI. Furthermore, we hope to provide scientific references for sustainability and human adaptation to climate change.