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UDC 551.570.04

E. Kiptenko, T. Kozlenko, L. Nadtochii

The method of short-term air pollution forecast based on meteorological conditions for mariupol city

      Analysis of synoptic and meteorological conditions was carried out for Mariupol city, which allowed defining favorable conditions for pollutants accumulation and dispersion. It was found that the closest relation is with wind characteristics and synoptic situation. The study showed that 80% of elevated pollution cases caused by north, northeastern and eastern winds. However, this relation is much stronger during winter season and weaker in summer. Elevated pollution levels are observed in case of wind speed exceed 5m/s, and become the most extreme with the wind speed of 8-9 m/s. The synoptic conditions were classified in this research depend on season. In winter, the highest pollution levels are observed in case of front part of the cyclone and southwestern anticyclone periphery. In summer stationary of anticyclone and its peripheries cause the highest pollution levels. The spatial analysis showed the most polluted areas located close to the industrial zones and cover nearest residential areas.
      Elevated pollution levels also influenced by the duration of high concentrations existance. High correlation between neighboring days was found during the long period with stable pollutants concentrations and precipitation absence. Therefore, inertia play huge role if the synoptic conditions do not change.
      The method of short-term pollution level forecast for Mariupol city there was developed. The method consists of five prediction schemes for five pollutants: dust, sulfur dioxide, carbon monoxide, nitrogen dioxide and formaldehyde. The method of forecast based on multiply nonlinear regression relation. Nonlinearity was taking into account using predictors transformation. In addition to prediction schemes there are a number of prediction features, which must be integrated to the forecast.
      For regular daily usage during the operational forecast phase, it is highly recommended to consider the average atmospheric pollution level during the three- monthly- period of previous year. The month within which the forecast made must be the middle of three monthly period.
      The general accuracy of the short-term forecast is 7382% depending on the pollutant. During the elevated pollution levels, accuracy of prediction is higher and vary from 83 to 100%.
      Key words: air pollution, emissions, contaminants, meteorological conditions, synoptic situation, pollution forecast.

Received at editorial July 11, 2019


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