Environmental safety and natural resources

Network and economic component of financial cybersecurity indices

2026-02-05T18:08:01+02:00

The main goal of the study is to develop approaches to using financial (stock exchange) cybersecurity indices to assess cybersecurity and the level of maturity of corporate information assets. The objectives of the study are to analyze existing financial (stock exchange) cybersecurity indices, the methodology for their formation, the application of indices to assess the state of national cybersecurity systems and markets, the development of approaches for modeling the behavior of individual financial cybersecurity indices, and to substantiate their application. The paper examines the methodological foundations of the formation of financial cybersecurity indices depending on network and economic indicators. The methodologies for the formation of existing financial (stock exchange) cybersecurity indices are analyzed, and a model of a generalized financial cybersecurity index is proposed. The application of individual index indicators in the national cybersecurity system is investigated, and their use for collecting and processing cyber statistics data is proposed. The possibility of using game-theoretic resource cooperative models to predict the behavior of individual financial cybersecurity indices is analyzed. To assess cybersecurity and the level of maturity of corporate information assets, an independent use of the cyber insurance index (cyber insurance maturity) is proposed, and the domain structure of the financial cybersecurity indices and the cyber insurance index is compared. The results obtained can be used to assess the state of corporate information resources in order to optimize decision-making.

Synergy of quantum computing and federated learning in information technology detection of hidden target groups

2026-02-05T18:18:42+02:00

The article considers the information technology of detecting hidden target groups in large distributed data sets based on the synergy of quantum computing and federated learning. It is shown that in modern information systems for analyzing big data, traditional methods of machine learning and intelligent analysis demonstrate limited effectiveness in identifying poorly represented or hidden structures, especially under conditions of statistical imbalance of samples, high dimensionality of the feature space and distributed storage of information. The proposed approach combines federated learning as an information technology of distributed model formation without data centralization with quantum algorithms of amplitude amplification, which allows to increase sensitivity to weak signals in subspaces with increased information significance. The paper considers the architecture of a hybrid information technology, which includes classical computing nodes, a level of federated aggregation and a quantum computing module, as well as a structural and algorithmic scheme of interaction of classical and quantum components. The algorithmic aspects of the implementation of the proposed approach are analyzed, taking into account the limitations of modern quantum computing platforms of the NISQ (Noisy Intermediate-Scale Quantum) class, in particular the limited number of qubits and the influence of noise. It is shown that the use of selective quantum processing and iterative interaction between classical and quantum circuits allows to ensure the reproducibility of the results and the possibility of practical implementation of the proposed information technology. The proposed approach is a promising direction in the development of information technologies for analyzing large distributed data and can be used as a theoretical and applied basis for further research in the field of hybrid classical-quantum computing systems.

Ttsunami issues in the Black Sea

2026-02-05T19:54:01+02:00

The coordinating role of the Intergovernmental Oceanographic Commission in the implementation of the Tsunami Research, Development and Implementation Plan within the framework of the UN Decade of Ocean Science for Sustainable Development (2021-2030) is considered. The structural composition of the Intergovernmental Coordination Group on the system of early warning about tsunamis and mitigation of their consequences in the North-East Atlantic, the Mediterranean Sea and adjacent seas is presented. Attention is focused on the potential threats to coastal infrastructure in the Black Sea from the probable movement of explosive objects along with the tsunami in the water areas contaminated by them. It is proposed to develop and approve the relevant provisions on the functional subsystems of early warning about tsunamis as part of the unified state civil protection system.

AI (not) against AI

2026-02-05T20:02:05+02:00

The aim of the research is to identify information, technological and methodological approaches to artificial intelligence developing in modern conditions of digital transformation, and in the long term. The objectives of the research are the following questions: a) to conduct a systematic analysis of the main aspects of AI development, in particular by the category of AI security; b) to identify the main time trends in AI improvement and ensuring AI security; c) to assess the current state of AI, development directions in this area and solving problems of ensuring AI security. Given the specifics of the research topic, tools in the form of modern AI means, such as ChatGPT, Claude, Copilot, Gemini, were used to conduct the research. As criteria for assessing the validity of conclusions, it is proposed to rely on the relevance and pertinence of the results of AI means' responses to various prompts. The main topic of inquiries is devoted to key trends that characterize the development of artificial intelligence, how AI will develop in the near future and until 2100, and what consequences this will have for humanity. The main stages of AI development have been identified in accordance with the above predictions. The main results show that the above-mentioned AI means primarily indicate an increase in attention to the ethical and legal aspects of using AI, as well as the growing AI integration into various areas of human activity. At the same time, it was noted that it is important to maintain a balance between using AI to enhance human capabilities and ensuring that people do not lose their intellectual skills. Particular attention is paid to the possible moment of singularity, when AI will begin to develop at an exponential rate, which will lead to radical changes in society and technology, and the consequences of this process are difficult to predict with certainty. Such systematic reviews are suitable for the formation of information meta-resources, which can be used by responsible persons as well as directly by specialists in various fields to support decision-making regarding the formation of AI security tools.

Prediction of hydraulic resistance coefficient using an ensemble neural network algorithm

2026-02-05T20:13:53+02:00

This study presents the development and testing of a computational algorithm based on ensemble learning of artificial neural networks for predicting the empirical hydraulic resistance coefficient known as the Chézy roughness coefficient in open channels. The input data for the model include hydrological and hydro-morphological characteristics of the channel: average flow width and depth, hydraulic radius, discharge or flow velocity, water surface slope, bed roughness, and other parameters influencing flow resistance. The target variable is the Chézy coefficient, which must be determined with high accuracy. Ensemble learning methods are based on the principle of combining the predictions of several individual models to obtain a more reliable and accurate result.
This study introduces an ensemble approach using artificial neural networks for estimating the Chézy roughness coefficient. It expands upon previous research focused on empirical estimation of the Chézy coefficient through neural networks, which involved the review of existing computational methods, refinement of input parameters, and the design of a base model with enhanced architectural complexity. The ensemble was implemented, trained, and evaluated using Python programming tools.
A general ensemble model consisting of three homogeneous fully connected neural networks is proposed. An algorithm for distributing data among ensemble models is proposed. Training subsets for each neural network in the ensemble are formed using the Bagging method (Bootstrap Aggregating). A training algorithm for the ensemble is developed, where each neural network is trained in parallel on its bootstrap sample using the backpropagation method. A forecasting algorithm using the trained ensemble is also proposed. Prediction of the empirical Chezy coefficient for new, unseen data is performed by aggregating forecasts from all neural networks, incorporating an inverse problem approach. The implementation of training and prediction algorithms is presented in Python.
For testing the proposed computational algorithm, field hydrological and hydro-morphological data from specific sections of the mountain rivers Tysa, Teresva, Latorytsia, Opir, Rika, and Chornyi Cheremosh were used. The testing procedure involved comparing observed and predicted flow discharges. Performance metrics such as absolute error and Nash–Sutcliffe efficiency coefficient were used to assess model effectiveness. The proposed ensemble model demonstrated higher accuracy and greater prediction stability compared to individual neural networks, confirming a typical advantage of the Bagging method.

Some results of research on river suspended sediments of the Dnipro and the Danube

2026-02-05T20:31:37+02:00

The aim of the study was to identify the patterns of distribution of the material composition of suspended sediments in the lower sections of the basins of Ukraine’s largest rivers – the Dnipro and the Danube. Determining the qualitative characteristics of suspended sediments, in combination with quantitative indicators from state monitoring data, is a promising approach for developing an information base on their overall condition and distribution. Analysis of the obtained data will contribute to understanding the ecological processes occurring in surface watercourses and their impact on the environment and human activities. Continuity of such research and the formation of long-term data series make it possible to substantiate predictive indicators, assess both short-term and long-term environmental impacts, and provide a reliable foundation for planning and implementing activities aimed at restoring the natural state of river systems and the adjacent marine areas within their zone of influence. The implementation of such comprehensive studies of the qualitative and quantitative characteristics of the substance of water flows, in addition to obtaining new knowledge about natural and man-made factors of river flow formation and creating databases for relevant forecasts, will bring Ukraine closer to the European observation system and will allow for strengthening interstate cooperation in the future.

Application of the markov model in information technology of the formation of the local socio-economic system

2026-02-05T20:40:55+02:00

The methodology for using Markov models in information technology to support decision-making in the regional and local development management system under conditions of uncertainty is obtained. The organization of cooperation at the local and regional levels is today one of the urgent issues of ensuring national sustainability. After all, in conditions of territorial proximity with the joint use of available resources and infrastructure, forming a single economic environment, the unification of territorial communities (and/or individual cities or villages) into local socio-economic systems allows ensuring effective local development, capacity and sustainability of communities through cooperation, joint use of resources and the resulting synergistic effect from such interaction. Complex dynamic systems are formed, for which it is necessary to ensure the consistency of the interaction of their elements, taking into account competition, increasing load on infrastructure, development of information technologies, changes in the planning of settlements, location of production, etc.
To solve the above problems, the work proposes to use Markov models, models of mass service systems. Based on the fact that most territorial communities have a formed sectoral structure, social sphere facilities, transport highways, etc., the work considers the problem of optimal management of the existing mass transit system. The advantages of using mass transit system models are that their use allows you to take into account the specifics of inter-sectoral interaction at the local and regional levels, to assess the quality of management, having previously found out whether certain influences are available for the system under study. The developed models, methods, algorithms are intended for use in information technology to support decision-making in the system of state and public administration. Its implementation will increase the quality and efficiency of management decisions by optimizing analytical processes.

Using auralization as a promising means of controlling noise on a construction site

2026-02-05T13:22:50+02:00

Noise pollution on construction sites remains one of the most significant and least controlled threats to the health and safety of workers. Constant exposure to noise generated by heavy machinery and technological processes not only leads to irreversible damage to the hearing organs, such as occupational hearing loss, but also significantly increases the psychophysiological load, reduces concentration and, as a result, increases the risk of Occupational Injuries. Traditional noise management methods based on calculated indicators and general recommendations are often not effective enough due to their abstraction and complexity for intuitive understanding by non-specialists. The aim of the work is to substantiate the feasibility of using auralization – the process of creating acoustic renderers based on mathematical modeling – to improve the effectiveness of noise protection measures. The article provides a comprehensive analysis of the problem of noise pollution on construction sites and examines the potential of using auralization technology as a tool for improving acoustic safety. The theoretical foundations of auralization, including its fundamental principles, technical aspects and classification of methods, are considered. Modern approaches to noise control, covering passive, active and organizational methods, as well as innovative personal protective equipment (PPE) of the hearing organs, are analyzed in detail. Based on a systematic review of scientific publications for 2020-2025, key trends, unresolved problems and promising research areas are identified. Practical recommendations for integrating auralization into the processes of design, training and control at construction sites are formulated. The article highlights the key thesis: if the elimination of noise sources is technologically or economically impossible, the priority is to ensure that workers are provided with adequate personal protective equipment (PPE), the effectiveness of which can be tested and demonstrated. The study is based on the analysis of modern scientific publications, international and Ukrainian regulations (State sanitary standards for industrial noise, ultrasound and infrasound, OSHA 1926.52, EU directive 2003/10/EC. It is proved that if it is impossible to completely eliminate noise sources, auralization becomes a key tool for evaluating and selecting optimal PPE, which ensures the implementation of the main thesis of the article: if it is not possible to reduce the noise of machines, then you can at least ensure the safety of workers with proper personal protective equipment.

EU directives on waste management and their implementation in Ukraine within the framework of the association agreement

2026-02-05T09:51:25+02:00

Relevance. The relevance of the study stems from the need to analyze the requirements regarding industrial pollution in the Association Agreement between Ukraine and the EU, particularly concerning the approximation of national legislation to EU environmental law and policy.
Objective. The aim of the study is to summarize the requirements of EU waste management directives and to define the implementation obligations within the framework of the Association Agreement.
Materials and methods. To achieve the stated objective, two key methods were applied: the comparative legal method and the systems approach. These were used to compare the provisions of national legislation with those of EU directives and to identify interrelations among the various normative requirements.
Results. The core of the European Union's legal framework on waste management is the Waste Framework Directive, which establishes fundamental principles such as the five-step waste hierarchy, extended producer responsibility (EPR), and end-of-waste criteria. This framework is complemented by a set of specialized directives and regulations that set ambitious, legally binding targets for specific waste streams, including packaging, WEEE (waste electrical and electronic equipment), batteries, and landfilling. Key challenges for aligning national legislation with EU directives include attracting investment in infrastructure (especially for meeting the requirements of the Landfill Directive), the practical implementation of EPR systems, and the constant need to keep pace with the evolving EU legislative landscape. This necessitates a shift in the mindset of industry and businesses from mere compliance to proactive engagement – developing EPR strategies, investing in cleaner production technologies, and anticipating future EU requirements (such as the new Batteries Regulation) to maintain market access and competitiveness.
Scientific novelty. The scientific contribution lies in summarizing the systemic challenges of implementing national waste management legislation in line with the requirements of EU directives.
Practical value. The study identifies the institutional support needed to transform industrial and production practices toward sustainable development and efficient resource use.

Comprehensive emergent assessment of ecosystem services and economic efficiency of urban green structures

2026-02-05T10:19:16+02:00

Rapid urbanisation in recent years has led to the deterioration of urban ecosystems and the emergence of numerous environmental and socio-economic problems. In response to these challenges, the implementation of green structures has gained considerable popularity as a sustainable approach to urban planning. This paper presents a comprehensive assessment of the costs, benefits (ecosystem services) and impacts (ecosystem disservices) associated with the use of green structures in the urban environment, using the emergy accounting approach, which allows for the quantitative assessment of resource costs in biophysical units through the prism of energy transformations. To achieve this goal, a new integrated assessment system is proposed, covering key components: assessment of the costs of implementing and operating green structures, assessment of ecosystem services, determination of environmental costs to compensate for damage to public health and biodiversity, and identification of ecosystem disservices. In particular, the economic efficiency of green walls in reducing noise pollution is investigated using the example of typical urban configurations of apartment buildings. The results show that green roofs provide greater benefits to the ecosystem compared to other types of green structures, but they are accompanied by high initial construction costs and require more intensive maintenance. Green walls demonstrated the highest emergent costs for noise pollution reduction (5.77×10¹² sej/m²·year), indicating their potential effectiveness in improving the city's acoustic environment. Cost-benefit calculations are presented for two simulated architectural configurations, reflecting the impact of green walls on noise reduction and aesthetic benefits for residents; the results show that in both cases the benefits significantly outweigh the costs. The data obtained provides valuable information for urban planners, policymakers and other stakeholders, facilitating informed decisions on the development of sustainable cities to ensure the well-being of current and future generations.

Combustion of pellets from agricultural waste

2026-02-05T12:00:39+02:00

Agricultural waste is a renewable source of energy when it is burned in the form of pallets. When pellets and briquettes are burned, pollutants are released into the environment and waste is generated in the form of ash. Equipping power plants with modern treatment facilities allows reducing atmospheric pollution and reducing the environmental load on the environment. In this work, the processes of formation of pollutants in the process of burning pallets are theoretically considered and the formation of ash and slag waste, which cannot be used as a fertilizer, but needs to be processed or removed in another way, is investigated. Pre-treatment by grinding the slag formed after combustion is an additional technological operation that can be avoided if the correct combustion technology is observed, raw material control, quality control and storage of the components of briquettes and pellets. Studying the composition of the starting raw materials for pellet production is one of the important stages of minimizing slag formation. It should be taken into account that a detailed analysis of the ash composition is an expensive and labor-intensive process that requires expensive equipment. In this case, an important characteristic is the content of silicates in the ash, because it is it that determines the appearance of insoluble slag, which subsequently needs to be dissolved or ground.

Integration of environmental safety into mechanisms for combating energy threats to residential buildings

2026-02-05T12:12:26+02:00

This article explores the integration of environmental safety into mechanisms for countering energy threats to residential buildings, a matter of heightened relevance in the context of full-scale warfare. Widespread attacks on critical infrastructure have led to disruptions in energy supply, increased reliance on emergency power sources, intensified environmental pollution, and the accumulation of hazardous waste, including radiological risks. Under such conditions, ensuring energy stability must be accompanied by ecological responsibility and adherence to the principles of sustainable development. Contemporary approaches to energy efficiency are analysed, with emphasis on those that incorporate environmental consequences and contribute to the resilience of residential infrastructure. Strategic planning is foregrounded, encompassing environmental monitoring, damage assessment, scenario modelling for resilience, and social auditing. The application of the Integrated Environmental Assessment (IEA) methodology is substantiated as a key instrument for developing ecologically balanced response strategies to energy threats in the housing sector. IEA enables the synthesis of multidimensional data on the condition of energy infrastructure, environmental risks, and social impacts, facilitating systemic evaluation under crisis scenarios. The importance of energy supply monitoring is highlighted as a dynamic indicator of building resilience, allowing for the timely identification of critical zones and forecasting of supply disruptions. Infrastructure damage analysis is conducted with consideration of building typologies, materials, degrees of deterioration, and potential environmental impacts, thereby informing the prioritisation of recovery measures. The use of digital tools and artificial intelligence methods is emphasised for the rapid analysis of large data sets, risk prediction, and the organisation of effective crisis response. An ecologically balanced response framework is proposed, incorporating integrated energy-environmental audits, contemporary management models, and intelligent systems. These audits serve not only to assess energy efficiency but also to evaluate the ecological compliance of emergency power sources, ventilation systems, and thermal insulation. Scenario modelling for resilience involves multifactorial analysis across technical, environmental, and social dimensions, enabling the adaptation of response strategies to varying threat levels. Social impact assessment considers population vulnerability, access to essential resources, psychological wellbeing, and institutional trust. This approach not only safeguards basic living conditions during wartime but also lays the foundation for Ukraine’s green recovery. The findings may inform the refinement of regulatory frameworks, the development of housing adaptation strategies, and the advancement of environmentally oriented energy policy.

Advanced resource-efficient technologies for Chromium (VI) removal from industrial wastewater: analysis and reuse potential

2026-02-05T12:51:39+02:00

The study addresses a scientific and practical challenge — investigating modern methods for the treatment of wastewater contaminated with hexavalent chromium (Cr(VI)), with a focus on the development of environmentally safe and resource-efficient technologies. The paper analyses key treatment approaches for galvanic wastewater, including chemical precipitation, electrocoagulation and galvanocoagulation, ion exchange, membrane filtration, sorption, and biological methods. The advantages, limitations, efficiency, and economic viability of each method are assessed. Special attention is given to technologies that remove Cr(VI) from wastewater and enable the recovery or reuse of extracted components in industrial processes. The prospects of applying natural and synthetic sorbents, ion-exchange processes for obtaining valuable products, and electrochemical and biological approaches as alternatives to conventional chemical methods are considered. The development of closed-loop technologies is substantiated as a promising direction to minimise the environmental impact of industrial effluents.

Eco-energy potential of exploded quarries and risks of its use

2026-02-05T13:00:12+02:00

Aim of paper to propose a semi-quantitative model for rapidly ranking disturbed industrial lands closed quarries as candidate sites for utility-scale solar plants or renewable «energy parks», explicitly accounting for engineering constraints and environmental–permitting risks. Method the study introduces a pre-feasibility multi-criteria screening framework and an integrated EEP score (0-100) computed from expert-rated components that reflect: solar conditions and terrain shading, geotechnical suitability, grid-connection feasibility, environmental restrictions and permitting effort, and logistics and site-related capital costs. Input evidence is derived from open-access sources and translated into risk-adjusted indicators relevant to eco-engineering decision-making. Findings – the framework was tested on two quarry sites in Ivano-Frankivsk region. The Dubivtsi site achieved EEP≈59 (moderate attractiveness) while a stricter «stop-factor» formulation yielded EEPgeo≈45, indicating barriers requiring mitigation. The Yamnitsa site demonstrated higher feasibility with EEP≈68 and EEPgeo≈46, primarily due to improved geotechnical conditions and less risky grid integration. Theoretical novelty – the paper operationalises the notion of «ecoenergy» renewable potential on degraded land by combining resource availability with infrastructure readiness and risk exposure within a single, transparent scoring construct. Practical implications – the approach supports a 1-2 week desktop screening to prioritise sites, pinpoint dominant constraints (typically grid and geotechnics), and justify targeted field investigations and EIA scoping before full feasibility studies. Originality – the proposed EEP scale and the complementary geometric («hard») aggregation enhance repeatability and penalise critical blockers, improving early-stage comparability of quarry sites. Future research should calibrate weights against realised projects, embed hydrological and slope-stability submodels.