Abstract

The article is devoted to the problem of air pollution and its impact on human health and the environment. The paper considers methods of air pollution analysis based on the use of neural networks, taking into account the variety of data from the Internet. The authors emphasize the different effects of pollutants depending on the type, duration and level of exposure, as well as other factors, including individual risks to human health and the combined effects of different pollutants and stress factors. Special attention is paid to the two most common types of air pollution - smog and soot. The uneven distribution of the negative effects of air pollution, which are most often felt in low-income and colored communities, as well as the Air quality Index (AQI) developed by the Environmental Protection Agency, which informs the population about the current state of atmospheric air and its impact on human health, are considered separately. As a result of the work, the criteria for analyzing air quality, including pollution parameters and weather conditions, are presented, and the structure of future data is developed.

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