Introduction. Air pollution modeling is a powerful tool that allows developing scientifically justified solutions to reduce the risks posed by atmospheric emissions of pollutants. Problem Statement. Cloud computing infrastructures provide new opportunities for web-based air pollution forecasting systems. However the implementation of these capabilities requires changes in the architecture of the existing systems. Purpose. The purpose is to adapt the web service of forecasting the atmospheric pollution in Ukraine to operate in the cloud computing platform of the Ukrainian National Grid infrastructure. Materials and Methods. The web client – web server – cloud computing architecture was used. The calculation of the model is performed in the cloud infrastructure, while the client and server parts operate on separate computers. Results. With the developed service the forecast of air pollution is possible for every point at the territory of Ukraine for more than thirty substances, including chlorine, ammonia, hydrogen sulfide and others. The forecast is performed using the data of the WRF-Ukraine numerical weather prediction system and visualized through a web interface. The capabilities of the developed system were demonstrated by the example of simulation of air pollution in part of Kyiv affected by the releases from the Energia incineration plant during pollution episode in September, 2019. The total releases of toluene gas from incineration plant and from the fire on spontaneous waste landfill, which is located a few km from Kyiv, were estimated and analyzed. For the considered period the fire could bring considerable additional amounts of pollutants to the studied region. The confidence interval for the maximum airborne concentration for the considered period is estimated from 0.7 to 2.1 mg·m-3 which is higher than the permissible value (0.6 mg· m-3). Conclusions. The presented system could be used by institutions responsible for response to environmental accidents. Keywords: air pollution, atmospheric dispersion, web-systems, cloud computing. Introduction. Air pollution modeling is a powerful tool that allows developing scientifically justified solutions to reduce the risks posed by atmospheric emissions of pollutants. Problem Statement. Cloud computing infrastructures provide new opportunities for web-based air pollution forecasting systems. However the implementation of these capabilities requires changes in the architecture of the existing systems. Purpose. The purpose is to adapt the web service of forecasting the atmospheric pollution in Ukraine to operate in the cloud computing platform of the Ukrainian National Grid infrastructure. Materials and Methods. The web client – web server – cloud computing architecture was used. The calculation of the model is performed in the cloud infrastructure, while the client and server parts operate on separate computers. Results. With the developed service the forecast of air pollution is possible for every point at the territory of Ukraine for more than thirty substances, including chlorine, ammonia, hydrogen sulfide and others. The forecast is performed using the data of the WRF-Ukraine numerical weather prediction system and visualized through a web interface. The capabilities of the developed system were demonstrated by the example of simulation of air pollution in part of Kyiv affected by the releases from the Energia incineration plant during pollution episode in September, 2019. The total releases of toluene gas from incineration plant and from the fire on spontaneous waste landfill, which is located a few km from Kyiv, were estimated and analyzed. For the considered period the fire could bring considerable additional amounts of pollutants to the studied region. The confidence interval for the maximum airborne concentration for the considered period is estimated from 0.7 to 2.1 mg·m-3 which is higher than the permissible value (0.6 mg· m-3). Conclusions. The presented system could be used by institutions responsible for response to environmental accidents.

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The paper presents the results of the simulation of secondary air pollution scenario in Ukraine due to the wind lift of anthropogenic radionuclides during a dust storm in April 2020. A variant of the Bagnold formula was used to parameterize the intensity of radionuclide resuspension. To set the initial pollution of the territory of Ukraine, the reconstruction of meteorological conditions and fallout of Cs-137 after the disaster at the Chernobyl nuclear power plant was carried out through the use of the RODOS nuclear emergency response system and the WRF meteorological model. For the normalized root-mean-square error of the calculated total fallout in the 50-km zone around the Chernobyl NPP the value NMSE=4,5 was obtained. A decrease in the levels of pollution of the Earth's surface during the time after the accident due to radioactive decay and other environmental processes was estimated. The distribution of contamination of the Earth's surface obtained in this way was used to assess the intensity of wind rise and atmospheric transport of radionuclides during a dust storm on April 16–18, 2020. The calculations were carried out using the CALPUFF model. The input meteorological data were the results of the WRF-Ukraine weather forecasting system. In the calculation of secondary contamination, the effect of fires in the Chernobyl Exclusion Zone (ChEZ) was not taken into account. The calculated average daily concentrations of Cs-137 in the air were maximum for the first day of the dust storm (April 16), when the wind speed was maximum (13 m/s with gusts up to 19 m/s). Average daily concentrations on April 16 ranged from the background values (5,8·10-6 Bq/m3 in Kyiv) to 2,2·10-3 Bq/m3 (ChNPP). The obtained estimates are much less than the permissible concentrations (0.8 Bq/m3). At the same time consideravle exceedance of background values were predicted in a large part of Ukraine – from Rivne NPP (2,2·10-5 Bq/m3) to Kharkiv (1,3·10-5 Bq / m3). In the vicinity of the ChEZ in the cities of Chernihiv and Slavutich, the obtained estimates of daily average concentration were 1,6·10-4 Bq/m3 and 3,2·10-4 Bq/m3 respectively.

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