Protection of the atmosphere from pollution in the emission of hazardous substances in railway transport

Purpose. The development of numerical models for the prediction of air pollution in the emission of chemical hazardous substances in rail transport in the case of emergencies. Methodology. To solve this problem developed numerical models based on the use of the equations of mass transfer and potential flow. The equations for potential flow are used to determine the velocity field of the wind flow near the carriages and buildings. For the numerical simulations of mass transfer of the pollutant used implicit change triangle difference schemes. When constructing a difference scheme is carried out physical and geometric splitting of the transport equation in the four steps. For the numerical integration of the equation for potential flow of implicit difference scheme is used conditional approximation. Findings. The numerical models that belong to the class ?operational models?. These numerical models allow to take into account in conducting the computational experiment the basic physical processes that affect dispersion of hazardous chemical substances in the atmosphere taking into account the placement of various types of obstacles near place of emission. These numerical models can be applied in the development of the PLAS, when carried out serial calculations of various scenarios of emergencies in transport. The results of computational experiments to assess the size, shape, concentration of chemical substances in the case of dangerous emissions on the railroad. Originality. The effective numerical models for real-time simulated emergencies, accompanied by the emission of hazardous substances in transport. Practical value. A numerical model of the type of ?operational models? to determine the size and intensity zones of chemical contamination in emergency situations in the case of transport by rail chemically hazardous substances. A numerical model using standard meteorological information and do not require special training of the user.