The article deals with the issue of modeling taking into consideration nitrogen dioxide pollution of the atmospheric surface layer caused by vehicle exhaust gases. The interval data analysis methods were suggested. The method of identifying the mathematical model of the distribution of nitrogen dioxide as an atmospheric air pollutant based on the analysis of data with known measurement errors was proposed and grounded for the first time. The obtained mathematical model in the form of a difference equation is characterized by the guaranteed accuracy of forecasting nitrogen dioxide concentrations in a specified area of the city. It also adequately takes into account traffic changes which significantly reduces the costs of environmental control and monitoring. The proposed new model identification method is more effective in terms of computational time complexity compared to the known method and it is based on taking into account measurement errors which in the final case provides predictive properties of the model with guaranteed accuracy.

This article considers the task of developing mathematical models and their computer implementation that would establish the dependence of pH (acidity of the environment) on the volume and structure of raw materials for daily loading, as well as on the operating parameters of temperature and humidity based on the interval analysis of experimental data obtained during BGP research of a given type. In the process of research, based on the developed interval models, it was established that this indicator depends on the volume and structure of raw materials, as well as on the temperature and humidity of the substrate in the bioreactor. To build this mathematical model, it is proposed to use the method of interval data analysis and the method of identification of model parameters based on multidimensional optimization. The results of experimental studies for a specific type of biogas plant are given, and interval models with guaranteed prognostic properties that characterize the pH of the environment depending on the specific type of bio-raw material of solid and liquid fractions, temperature, and humidity are obtained. Based on the use of different types of raw materials, the developed models, based on experimental data, describe different configurations of the structure and volumes of raw materials for daily loading. The obtained mathematical models are an algebraic nonlinear equation that can be applied to control the level of pH of the environment in the bioreactor by determining the optimal volumes of raw materials of each type during the loading period depending on the temperature and humidity of the substrate in the bioreactor.

The sustainable implementation of resources and the transition to low-carbon construction is on the world’s daily agenda. This paper describes the development of criteria for the efficient management of material resources in low-carbon construction. Net income, gross profit, balance sheets, and equity are proposed as indicators that serve as criteria for assessing the efficient use of resources. Nonlinear regression models were the methodological basis for the establishment of cause-and-effect relationships of the volume of construction of transport structures. It was established that since construction companies do not purchase materials for storage, the cost of materials for use in low-carbon technological construction work is directly proportional to the cost of construction. The volume of production in the construction industry is determined by construction costs. More efficient use of low-carbon materials reduces cost and construction waste. In this paper, we have established the relationship between the indicator of efficiency for the functioning of the construction enterprises in Ukraine and the use of low-carbon materials for the construction of transport structures. The practical value of the obtained results for low-carbon construction management lies in proving the relationship between the performance indicators of the construction enterprise (net profit, gross profit, output volume, balance sheets, and equity capital) and the use of low-carbon material resources. Our results form the basis for future research into the use of a cost-based model for low-carbon economy transition in municipalities and regions.

Tracking the trend of restricted access to natural fossil energy resources determines the need to search for alternative energy sources, introducing energy-efficient technologies, and optimizing the energy supply system based on intelligent networks. Understanding district heating enterprises’ readiness to work with innovative renewable resources based on climate neutrality plays a unique role. Thus, this article is devoted to the study of the features of providing and determining the district heating enterprises’ capacity to integrate climate management of innovative resources to produce green thermal energy. The research methodology is based on a combination of systemic, process and cybernetic approaches to determining the resource sustainability of district heating enterprises for implementing climate innovations. The scientific novelty of the study lies in a comprehensive assessment of the ability of district heating enterprises to use renewable resources (biomass, waste, hydropower, solar energy, wind energy) for the production of thermal energy according to such indicators as: an indicator of balanced resource use, an indicator of climate neutrality and an indicator of economic feasibility. The results became the basis to apply the set-theoretical approach to calculate the district heating enterprises’ coefficient of resource sustainability, based on the climate management of innovative resources to produce green thermal energy. The innovation of the fuzzy sets method lies in achieving the set goal without the deep formation of a data dynamics series, particularly interval models. The added scientific value of the method to determine the resource sustainability of district heating enterprises is used to justify the feasibility of integrating climate management with the use of innovative resources through the diversification of renewable energy sources for thermal energy production. The prospects for such results are the basis for future research to develop intersectoral clustering enterprises in the green energy production chain based on a closed cycle of renewable energy resources.

This article proposes the concept of an integrated system consisting of two components: a small hydropower plant (SHPP) and a solar power plant (SPP), where the SHPP operates as a pumped-storage hydropower plant, and the SPP supplies energy for lifting water to the upper reservoir. A methodology is proposed for evaluating the joint operation of a solar power plant and a small hydropower plant. The methodology is based on modeling the electricity generation processes of combined solar and small hydropower plants. Additionally, a novel hybrid method is proposed for identifying interval models of small hydropower plants (SHPPs) and solar power plants (SPPs). This method integrates a metaheuristic algorithm for model structure synthesis, inspired by the behavioral model of a bee colony, with gradient-based methods for parameter identification. Using the proposed method, interval models have been developed for both small hydropower plants and the electricity generation of solar power plants. This study confirms the feasibility of using interval models to describe the relationship between electricity generation in a small hydropower plant and factors such as head difference, reactive power, and water level in the reservoir (i.e., available water resources). Furthermore, a mathematical model in the form of a difference equation is used to describe the daily electricity generation of a solar power plant. This model accounts for the characteristics of compressors that pump water from the lower to the upper reservoir. Based on the developed models, an assessment is conducted on the efficiency of the pumped-storage SHPP in ensuring operational stability during peak loads in the power grid and addressing seasonal variations.

Rising carbon emissions from international road freight transport in the EU—increasing from 29.4% in 2023 to 31.4% in 2025 under the With Existing Measures (WEM) Road Transport scenario—necessitate the implementation of additional measures within the framework of the EU Carbon Border Adjustment Mechanism (CBAM). For Ukraine, operating under martial law and pursuing a post-war green recovery of its transport and trade sectors, the adoption of EU experience in distributed generation (DG) from renewable energy sources (RESs) is particularly critical. This study evaluates the synergy between energy-efficient and low-carbon management in logistics chains for road freight transportation in Ukraine, drawing on EU evidence of DG based on RESs. To this end, a decoupling analysis was conducted to identify the factors influencing low-carbon and energy-efficient management of logistics chains in Ukraine’s freight transport sector. Under wartime conditions, the EU practice of utilising electric vehicles (EVs) as an auxiliary source of renewable energy for distributed electricity generation within microgrids—through Grid-to-Vehicle (G2V) and Vehicle-to-Grid (V2G) technologies—was modelled. The results confirm the relevance of RES-based DG and the integration of EVs as a means of enhancing energy resilience in resource-constrained and conflict-affected regions. The scientific novelty of this research lies in identifying the conditions for achieving energy-efficient and low-carbon effects in the design of logistics chains through RES-based distributed generation, grounded in circular and inclusive economic development. The practical significance of the findings lies in formulating a replicable model for diversifying low-carbon fuel sources via the development of distributed generation of electricity based on renewable resources, providing a scalable paradigm for energy-limited and conflict-affected areas. Future research should focus on developing innovative logistics chain models that integrate DG and renewable energy use into Ukraine’s transport system.