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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 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.

The article considers the task and a new approach to monitoring of soil and groundwater contamination by harmful emissions of nitrogen dioxide from motor vehicles. The approach is based on combination of measurement procedure of the harmful emissions concentrations in the surface atmospheric layer and mathematical modeling of the impact of these emissions on soil and groundwater contamination. The scheme of this harmful emission concentrations measurement using a mobile complex Sniffer4D Hyper-local Air Quality Analyzer is given. Based on these results, a mathematical model of diffusion of this harmful substance in the upper layers of soil and water resources is proposed. As a result of the computations, the distribution of concentrations of soil and water contamination in the neighborhood of separate observation points has been built. Also, the field of nitrogen dioxide concentrations at various depths for observation points has been modeled. For a waterbody, the concentration of nitric acid, which is formed due to the interaction of nitrogen dioxide with water, is higher in water than in the surface layer of the soil. This concentration can be significantly increased during prolonged downpours when acidic solutions drain from surrounding soil areas into the waterbodies. The obtained research results are fully consistent with the practical and theoretical results on the diffusion of gases into soils and water resources. It means that the proposed approach can be used instead of the existing very expensive approach to analysis of soil and groundwater contamination in the laboratory.