Environmental Challenges Research Articles

Study on the Resistance of Concrete to High-Concentration Sulfate Attack: A Case Study in Jinyan Bridge

Concrete structures face significant challenges in sulfate-rich environments, where sulfate attack can affect their durability and structural integrity. This study explores innovative approaches to enhancing concrete performance by integrating hydrophobic and densification technologies. It emphasizes the critical role of anti-sulfate erosion inhibitors in mitigating sulfate-induced damage, reducing water absorption, and inhibiting corrosive reactions. This research addresses prevalent issues in Chinese engineering projects where high sulfate concentrations are common, necessitating robust solutions for sulfate resistance. Through rigorous testing, including wet–dry cycling tests with 5% and 10% Na2SO4 solutions following the GB/T 50082-2009 standard, concrete formulations achieved exceptional long-term sulfate resistance, meeting or exceeding KS200-grade requirements. These findings provide valuable insights into optimizing concrete durability in sulfate-rich environments, offering practical strategies to enhance infrastructure resilience and reduce maintenance costs.

Simulation Study on Sea-Rail Intermodal Diversion Operation of Container Terminal in the Beilun Port Area of Ningbo Zhoushan Port

With the continuous development of global trade, the Beilun port area of Ningbo Zhoushan Port, as an important node of international shipping, its efficient and orderly container dredging operation is crucial to ensure the overall operational efficiency of the port and the stability of the regional supply chain. However, the actual operation is faced with multiple constraints such as fluctuating berth utilization rate, complex truck scheduling, tight yard space, and so on, which need to be optimized by scientific means. To achieve more efficient container transport, it is necessary to further optimize and improve sea-rail intermodal transport to improve the efficiency of port container operations. Therefore, this paper is based on the background of the rapid development of sea-rail intermodal transport of port containers, focusing on the problem of dredging operation of container terminals in the Beilun port area of Ningbo Zhoushan Port, through the analysis of the characteristics and influencing factors of container dredging operation, research on the optimization of container dredging scheme and put forward optimization scheme for the problem of dredging in Beilun Port Area of Ningbo Zhoushan Port, which is aimed at improving the efficiency and economy of container dredging operation and the efficiency of container dredging operation in Beilun port area through the advanced modeling and simulation technology. Through advanced modeling and simulation technology, it aims to effectively improve the efficiency and economy of container dredging operations in the Beilun port area, to cope with the increasing throughput pressure and the challenges of a complex logistics environment, and to provide theoretical support and practical guidance for the development of China’s sea-railway intermodal transport.

How Do Nonprofits’ Organizational Characteristics Shape Environmental Philanthropy in Texas? A Network Science Approach

Abstract In efforts to address the far-reaching effects of climate change and associated impacts in communities, research on environmental philanthropy suggests that more resources are being allocated to environmental societal challenges. However, understandings about which environmental nonprofits benefit from these funding flows is limited. This study integrates resource dependency theory with elitism and pluralism perspectives to analyze a network of environmental nonprofits and their funders in Texas. Resource dependency and a network-analytic approaches share underlying relationality principles, and we connect those dots by conceptualizing the funding dynamics in Texas as a network of funder-grantee relations. Drawing on statewide survey data (n = 114), we use a network analysis technique – exponential random graph modeling (ERGM) – to analyze funding allocations in Texas through the organizational attributes of environmental nonprofits, their funder-grantee relations, and their community context. We specifically observe elitism in funding allocations in Texas, which is evident in network effects (preferential attachment) and the focal areas of environmental work. However, we find limited evidence that age or resources of the nonprofit are predictive of funding and the most influential factor determining a funder-grantee relationship is the natural hazard risk of the community served by the nonprofit. Our findings suggest interconnected funding dynamics of pluralism and elitism in the Texas environmental philanthropy landscape, prompting further discussion about the potential synergies of these patterns and the implications for environmental funding practices.

How Do Nonprofits’ Organizational Characteristics Shape Environmental Philanthropy in Texas? A Network Science Approach

Abstract In efforts to address the far-reaching effects of climate change and associated impacts in communities, research on environmental philanthropy suggests that more resources are being allocated to environmental societal challenges. However, understandings about which environmental nonprofits benefit from these funding flows is limited. This study integrates resource dependency theory with elitism and pluralism perspectives to analyze a network of environmental nonprofits and their funders in Texas. Resource dependency and a network-analytic approaches share underlying relationality principles, and we connect those dots by conceptualizing the funding dynamics in Texas as a network of funder-grantee relations. Drawing on statewide survey data (n = 114), we use a network analysis technique – exponential random graph modeling (ERGM) – to analyze funding allocations in Texas through the organizational attributes of environmental nonprofits, their funder-grantee relations, and their community context. We specifically observe elitism in funding allocations in Texas, which is evident in network effects (preferential attachment) and the focal areas of environmental work. However, we find limited evidence that age or resources of the nonprofit are predictive of funding and the most influential factor determining a funder-grantee relationship is the natural hazard risk of the community served by the nonprofit. Our findings suggest interconnected funding dynamics of pluralism and elitism in the Texas environmental philanthropy landscape, prompting further discussion about the potential synergies of these patterns and the implications for environmental funding practices.

Towards agri‐food industry sustainability: Addressing agricultural technology adoption challenges through innovation

AbstractAgriculture is a key economic driver but also a significant contributor to environmental challenges. Despite promotion, uptake of agricultural technologies remains low due to various challenges. This study explores challenges and solutions in the adoption of agricultural technology in Thailand, emphasising its positive impact on agri‐food sector sustainability. We developed a conceptual framework based on technology adoption literature review. Employing multiple case studies, our research uncovers challenges not only at the farmer level but also within the agricultural ecosystem level. Addressing these challenges requires comprehensive changes in physical, digital, and legal infrastructure. Solutions include reshaping farmer mindsets and enhancing awareness of technology benefits. Despite limitations to the agri‐food industry in Thailand, the study offers valuable insights for technology providers and policymakers, contributing to the literature on technology adoption by smallholder farmers. Our findings emphasise the need for sustainability strategies in the agri‐food sector through greater technology uptake to enhance environmental sustainability.

Photoassisted Water Purification through an Electrochemically Artificially Adjusted p-Cu2O Light Absorption Layer.

The implementation of photoelectrochemical water purification technology can address prevailing environmental challenges that impede the advancement and prosperity of human society. In this study, Cu, which is abundant on Earth, was fabricated using an electrochemical deposition process, in which the preferential orientation direction and carrier concentration of the Cu-based oxide semiconductor were artificially adjusted by carefully controlling the OH- and applied voltage. In particular, Cu2O grown with a sufficient supply of OH- ions exhibited the (111) preferred orientation, and the (200) surface facet was exposed, independently achieving 90% decomposition efficiency in a methyl orange (MO) solution for 100 min. This specialized method minimizes the recombination loss of electron-hole pairs by increasing the charge separation and transport efficiency of the bulk and surface of the Cu2O multifunctional absorption layer. These discoveries and comprehension not only offer valuable perspectives on mitigating self-photocorrosion in Cu2O absorbing layers but also provide a convenient and expeditious method for the mass production of water purification systems that harness unlimited solar energy. These properties enable significant energy saving and promote high-speed independent removal of organic pollutants (i.e., MO reduction) during the water purification process.

REVIVAL OF THE EVIL EMPIRE AS A THREAT TO HUMANITY

Empires are an extraordinary phenomenon in the history of mankind. The study of empires requires scientific understanding, thoughtful comparison and deep analysis. Such way of studding the comparative approach of the problem has arisen that will help us understand the nature of the emergence and disappearance of imperial formations, find answers to difficult questions: how empires grew, for what reasons some of them were powerful and others weak, why some empires disappeared and others flourished (John Hutchinson, 2017). Is there a connection between the instability of power, coups and the death of empires? And finally, what are the consequences for world development of the disappearance of imperial formations. Among the reasons for the demise of empires, researchers single out political and economic problems, social and cultural issues, and environmental challenges. The author of the article tries to explain how the Moscow Empire was formed and how the Russian Empire manages to survive despite a number of dangerous challenges. In the submitted article prof. L.Chekalenko for the first time revealed the phenomenon of "saving" the empire in historical and political dimensions. The author discovered that Russia was saved by its vassals – conquered peoples. So, the article examines the factors that support and revive imperial formations, and also makes cautious assumptions about the future scenarios of the development of events surrounding the current situation.

Selective and Controllable Cracking of Polyethylene Waste by Beta Zeolites with Different Mesoporosity and Crystallinity.

Waste plastics bring about increasingly serious environmental challenges, which can be partly addressed by their interconversion into valuable compounds. It is hypothesized that the porosity and acidity of a zeolite-based catalyst will affect the selectivity and effectiveness, enabling a controllable and selective conversion of polyethylene (PE) into gas-diesel or lubricating base oil. A series of embryonic, partial- and well-crystalline zeolites beta with adjustable porosity and acidity are prepared from mesoporous SBA-15. The catalysts and catalytic systems are studied with nuclear magnetic resonance (NMR), X-ray diffraction (XRD), and adsorption kinetics and catalytic reactions. The adjustable porosity and acidity of zeolite-beta-based catalysts achieve a controllable selectivity toward gas-diesel or lubricating base oil for PE cracking. With a catalyst with mesopores and appropriate acid sites, a fast escape and reduced production of cracking of intermediates are observed, leading to a significant fraction (88.7%) of lubricating base oil. With more micropores, a high acid density, and strong acid strength, PE is multiply cracked into low carbon number hydrocarbons. The strong acid center of the zeolite is confirmed to facilitate significantly the activation of hydrogen (H2),and, an in situ ammonia poisoning strategy can significantly inhibit hydrogen transfer and effectively regulate the product distribution.

Resilience in the face of ecological challenges: Strategies for integrating environmental considerations into social policy planning in Africa

AbstractAfrica faces severe ecological crises, such as climate change, resource depletion, and biodiversity loss, undermining sustainable development efforts and exacerbating poverty and hunger. Integrating environmental concerns into social policy planning could help build community resilience and support sustainable development. This study employed policy analysis and stakeholder engagement to identify key environmental issues, policy gaps, and strategies for integrating environmental considerations into social policies across various sectors in Africa. The study found a significant lack of integration of environmental concerns into social policy across areas like disaster management, agriculture, urban planning, healthcare access, and infrastructure development policies. As a percentage of respondents, the top environmental issues were flooding (32%), drought/desertification (13%), and food security/agriculture (11%), with farmers (35.4%) and women (21.7%) being the most vulnerable to climate change. Most community stakeholders (87.5%) emphasized the importance of integrating environmental considerations into social policy, with 56.25% rating it a high priority. They underscored the need for more locally driven planning, ecological monitoring, land restoration, diversified livelihoods, and climate change adaptation support through social policies to enhance environmental sustainability. This study's novelty lies in its comprehensive approach to understanding and addressing the complex interplay between environmental challenges and social policy planning in Africa. The findings emphasize the urgent need for policymakers to develop cross‐sectoral national and local policies that use participatory processes to prioritize environmental sustainability, adaptation, community empowerment, and alignment with sustainable development goals while being responsive to continuing environmental uncertainty and change.

REVIVAL OF THE EVIL EMPIRE AS A THREAT TO HUMANITY

Empires are an extraordinary phenomenon in the history of mankind. The study of empires requires scientific understanding, thoughtful comparison and deep analysis. Such way of studding the comparative approach of the problem has arisen that will help us understand the nature of the emergence and disappearance of imperial formations, find answers to difficult questions: how empires grew, for what reasons some of them were powerful and others weak, why some empires disappeared and others flourished (John Hutchinson, 2017). Is there a connection between the instability of power, coups and the death of empires? And finally, what are the consequences for world development of the disappearance of imperial formations. Among the reasons for the demise of empires, researchers single out political and economic problems, social and cultural issues, and environmental challenges. The author of the article tries to explain how the Moscow Empire was formed and how the Russian Empire manages to survive despite a number of dangerous challenges. In the submitted article prof. L.Chekalenko for the first time revealed the phenomenon of "saving" the empire in historical and political dimensions. The author discovered that Russia was saved by its vassals – conquered peoples. So, the article examines the factors that support and revive imperial formations, and also makes cautious assumptions about the future scenarios of the development of events surrounding the current situation.

Resilience in the face of ecological challenges: Strategies for integrating environmental considerations into social policy planning in Africa

AbstractAfrica faces severe ecological crises, such as climate change, resource depletion, and biodiversity loss, undermining sustainable development efforts and exacerbating poverty and hunger. Integrating environmental concerns into social policy planning could help build community resilience and support sustainable development. This study employed policy analysis and stakeholder engagement to identify key environmental issues, policy gaps, and strategies for integrating environmental considerations into social policies across various sectors in Africa. The study found a significant lack of integration of environmental concerns into social policy across areas like disaster management, agriculture, urban planning, healthcare access, and infrastructure development policies. As a percentage of respondents, the top environmental issues were flooding (32%), drought/desertification (13%), and food security/agriculture (11%), with farmers (35.4%) and women (21.7%) being the most vulnerable to climate change. Most community stakeholders (87.5%) emphasized the importance of integrating environmental considerations into social policy, with 56.25% rating it a high priority. They underscored the need for more locally driven planning, ecological monitoring, land restoration, diversified livelihoods, and climate change adaptation support through social policies to enhance environmental sustainability. This study's novelty lies in its comprehensive approach to understanding and addressing the complex interplay between environmental challenges and social policy planning in Africa. The findings emphasize the urgent need for policymakers to develop cross‐sectoral national and local policies that use participatory processes to prioritize environmental sustainability, adaptation, community empowerment, and alignment with sustainable development goals while being responsive to continuing environmental uncertainty and change.

Selective and Controllable Cracking of Polyethylene Waste by Beta Zeolites with Different Mesoporosity and Crystallinity.

Waste plastics bring about increasingly serious environmental challenges, which can be partly addressed by their interconversion into valuable compounds. It is hypothesized that the porosity and acidity of a zeolite-based catalyst will affect the selectivity and effectiveness, enabling a controllable and selective conversion of polyethylene (PE) into gas-diesel or lubricating base oil. A series of embryonic, partial- and well-crystalline zeolites beta with adjustable porosity and acidity are prepared from mesoporous SBA-15. The catalysts and catalytic systems are studied with nuclear magnetic resonance (NMR), X-ray diffraction (XRD), and adsorption kinetics and catalytic reactions. The adjustable porosity and acidity of zeolite-beta-based catalysts achieve a controllable selectivity toward gas-diesel or lubricating base oil for PE cracking. With a catalyst with mesopores and appropriate acid sites, a fast escape and reduced production of cracking of intermediates are observed, leading to a significant fraction (88.7%) of lubricating base oil. With more micropores, a high acid density, and strong acid strength, PE is multiply cracked into low carbon number hydrocarbons. The strong acid center of the zeolite is confirmed to facilitate significantly the activation of hydrogen (H2),and, an in situ ammonia poisoning strategy can significantly inhibit hydrogen transfer and effectively regulate the product distribution.

IoT traffic classification and anomaly detection method based on deep autoencoders

This study investigates anomaly detection of IoT device traffic using Convolutional Neural Networks (CNN) and Variational Autoencoders (VAE) to enhance the detection capability of security threats in IoT environments. A series of hardware configurations, software environments, and hyperparameters were utilized to optimize the training and testing processes of the models. The CNN model demonstrates robust classification performance, achieving an accuracy rate of 95.85% on the test dataset, effectively distinguishing between different types of IoT device traffic. Meanwhile, the VAE model exhibits proficient anomaly detection capabilities by effectively capturing abnormal patterns in the data using reconstruction loss and KL divergence. The combined use of CNN and VAE models offers a comprehensive solution to cybersecurity challenges in IoT environments. Future research directions include exploring diverse IoT traffic data, practical deployment for validation, and further optimization of model structures and parameters to improve performance and applicability.

IoT traffic classification and anomaly detection method based on deep autoencoders

This study investigates anomaly detection of IoT device traffic using Convolutional Neural Networks (CNN) and Variational Autoencoders (VAE) to enhance the detection capability of security threats in IoT environments. A series of hardware configurations, software environments, and hyperparameters were utilized to optimize the training and testing processes of the models. The CNN model demonstrates robust classification performance, achieving an accuracy rate of 95.85% on the test dataset, effectively distinguishing between different types of IoT device traffic. Meanwhile, the VAE model exhibits proficient anomaly detection capabilities by effectively capturing abnormal patterns in the data using reconstruction loss and KL divergence. The combined use of CNN and VAE models offers a comprehensive solution to cybersecurity challenges in IoT environments. Future research directions include exploring diverse IoT traffic data, practical deployment for validation, and further optimization of model structures and parameters to improve performance and applicability.

Unlocking Online Insights: LSTM Exploration and Transfer Learning Prospects

AbstractMachine learning algorithms can improve the time series data analysis as compared to the traditional methods such as moving averages or auto-regressive approaches. This advancement has helped to unlock several challenging problems since machine learning not only helps to forecast the overall trend of the data, but it also helps to keep the historical track of changes in factors, influencing this trend. These predictions play a pivotal role in almost all areas of research where the observations are time dependent, such as problems ranging from challenges of finance to public health, environmental and climate change challenges. A key challenge of these domains is the higher number of attributes and predictors since managing and manipulating data from many attributes is itself a significant challenge for future forecasting. Addressing these challenges is possible with Recursive Long Short-Term Memory models. The application of such models is crucial, and their efficacy is further amplified when considering transfer learning. During this research, a detailed and comprehensive description of such models is addressed. Practical application is illustrated through an example, emphasizing that these models, when transferred to complex and large datasets using transfer learning, hold great promise.

The Distribution of the Economic Impacts of Sustainable Regional Transport Policies

In response to current environmental, social and accessibility challenges in the mobility sector, this research focuses on promoting the development of integrated sustainable regional transport policies, supported by a thorough analysis of their distributed economic impacts. This is fulfilled with the development of a new GIS-supported extension of a comprehensive methodology that is currently used for appraising local transport interventions. To illustrate the inputs and outputs of the expanded approach, a regional case study was simulated, highlighting the potential for this methodology to assist in (1) optimising the financial balance between electrification and modal-shift strategies, (2) anticipating and analysing the multiple economic impacts of multimodal transport services (e.g., Mobility as a Service) and (3) understanding how equal the benefits of these policies are across the region. This research will provide novel contributions to the field of transport research and policy development by introducing a comprehensive methodology that quantifies and maps the distributed economic impacts of regional transport policies. This will, consequently, enable the economic outputs of these policies to be easily visualised, analysed and shared with mobility stakeholders, fostering a better understanding of their urban–rural distribution, and promoting the strategic development of sustainable and equitable regional transport systems.

Insights On Liquid Jet Breakup And Spray Formation Of An Air-Assisted Atomizer: Conventional And Alternative Jet Fuel

Presently, it is imperative to address global environmental challenges. The concerns are related to the depletion of non-renewable fossil fuels, greenhouse gases, and pollutant emissions. The transportation sector contributes significantly to these issues. In particular, the aviation industry primarily relies on jet fuel, a fossil fuel responsible for around 2% of anthropogenic CO2 emissions. As a result, to address contemporary society environmental concerns and energy requirements, promising renewable and green energy sources are being intensively investigated, especially in air transportation. Sustainable aviation fuels (SAF), particularly biofuels, have been explored and indicated as a short-term solution to address the energy transition in the aviation sector. Implementing alternative fuels requires a deeper investigation regarding the spray dynamics. Following this, the present study explores conventional (Jet A-1) and alternative jet fuel (HVO) atomization, and the breakup length is explored in a wide range of operating conditions. The normalized mean breakup length was measured, and a correlation was proposed based on the experimental data. Additionally, the droplets released by the jet breakup are compared for both fuels in terms of diameter. Observations reveal the occurrence of jet flapping and bag breakup, affected by the air flowrate. The results also show that regardless of the fuel, increasing the momentum flux leads to a reduction in the normalized mean breakup length. An increase in the air flowrate promotes a shorter breakup length, resulting in a secondary droplet with smaller secondary droplet diameters. An empirical correlation was developed based on the fitting of the experimental data. This correlation indicates that the normalized mean breakup length exhibits a power law relation with M, which is consistent with the literature. This experimental study is essential to research on biofuels and aids in the development of new injectors and the precision of theoretical models integrated into numerical algorithms.

Editorial: Air and Water Purification Processes through Photocatalysis—Scale-Up Perspectives, 2nd Edition

In the face of escalating environmental challenges, innovative solutions for purifying air and water are more critical than ever [...]

Sequential Behavior of Broiler Chickens in Enriched Environments under Varying Thermal Conditions Using the Generalized Sequential Pattern Algorithm: A Proof of Concept.

Behavior analysis is a widely used non-invasive tool in the practical production routine, as the animal acts as a biosensor capable of reflecting its degree of adaptation and discomfort to some environmental challenge. Conventional statistics use occurrence data for behavioral evaluation and well-being estimation, disregarding the temporal sequence of events. The Generalized Sequential Pattern (GSP) algorithm is a data mining method that identifies recurrent sequences that exceed a user-specified support threshold, the potential of which has not yet been investigated for broiler chickens in enriched environments. Enrichment aims to increase environmental complexity with promising effects on animal welfare, stimulating priority behaviors and potentially reducing the deleterious effects of heat stress. The objective here was to validate the application of the GSP algorithm to identify temporal correlations between heat stress and the behavior of broiler chickens in enriched environments through a proof of concept. Video image collection was carried out automatically for 48 continuous hours, analyzing a continuous period of seven hours, from 12:00 PM to 6:00 PM, during two consecutive days of tests for chickens housed in enriched and non-enriched environments under comfort and stress temperatures. Chickens at the comfort temperature showed high motivation to perform the behaviors of preening (P), foraging (F), lying down (Ld), eating (E), and walking (W); the sequences <{Ld,P}>; <{Ld,F}>; <{P,F,P}>; <{Ld,P,F}>; and <{E,W,F}> were the only ones observed in both treatments. All other sequential patterns (comfort and stress) were distinct, suggesting that environmental enrichment alters the behavioral pattern of broiler chickens. Heat stress drastically reduced the sequential patterns found at the 20% threshold level in the tested environments. The behavior of lying laterally "Ll" is a strong indicator of heat stress in broilers and was only frequent in the non-enriched environment, which may suggest that environmental enrichment provides the animal with better opportunities to adapt to stress-inducing challenges, such as heat.

Structural and functional assessment of keratin extracted from chicken feathers using microwave-assisted l-cysteine method

Extracting and applying waste feather keratin are important environmental challenges. This study utilized microwave-assisted l-cysteine treatment on chicken feathers, pH adjustments varied reducing capacity of l-cysteine, while modulated microwave power explored synergistic extraction effects on properties of keratin. The highest yield of regenerated keratin was achieved at an l-cysteine concentration of 15 g/L, pH 12, and a microwave power of 400 W. Micromorphological and particle size results revealed that the keratin particle size increased with pH dependency, the highest proportion of particle size values in keratin increasing from 164 nm in L1 (extracted at pH 11) to 220 nm in L5 (extracted at pH 13). Increasing the intensity of both treatments led to a transition of the secondary structure of regenerated keratin from α-helix to β-sheet, but the increasing reducibility of the system resulted in a decrease in the content of tryptophan residues in keratin, whereas the increase in microwave power led to the masking of some fluorescent chromophores within the keratin. The regenerated keratin demonstrated low crystallinity, and it may have undergone refolding and aggregation under microwave-assisted highly reducing extraction conditions. The foaming properties indicated that the highly reducing extraction system significantly decreased foam stability from 95.4% for L1 to 19.8% for L5 (p < 0.05) and improved foaming ability to keratin. Considering the widespread applications of keratin, this study provides a comprehensive characterization of regenerated keratin under different extraction conditions, aiming to offer experimental materials and extraction conditions tailored to specific requirements in the field of biomaterials.