On the issue of predictive assessment of technogenic load on the atmospheric air of urban ecosystems

The development of models of the stability of the ecological situation in urban ecosystems is one of the constructive ways to achieve a balanced interaction of society and nature at the present stage. The most promising method for assessing technogenic actions is a model one using deterministic, probabilistic, mixed and simulation types of models of various processes. The most effective tool in assessing environmental risks are mathematical models described by systems of differential, integral, integral-differential with appropriate limiting and initial conditions. Of great interest are models for estimating the magnitude of the potential of atmospheric pollution in urban landscapes, local Gaussian models, deterministic models describing the process of increasing threats to the environment by a system of differential or integral equations with initial conditions, etc. It is established that the developed models do not allow to fully assess the state of ecosystems exposed to man-made loads when the production infrastructure of the region changes. The development of a new approach to constructing a model of the probabilistic distribution of pollutants and assessing the current state of atmospheric air pollution in urbanized territories based on multispectral satellite imagery data in order to obtain more informative indicators, increase the efficiency and reliability of information about the state of the ecological environment in a megalopolis is very relevant. Monitoring of the risks of atmospheric air pollution of territories using aerospace data will provide for the receipt, accumulation and pre-processing of space and ground-based information, their joint processing using GIS technologies and various software products, computer modeling to predict the direction and intensity of the passage of environmental processes, management decision-making and the development of measures to create optimal parameters of the state of the environment.