Mathematical Analysis of Air Pollution on the Territory of Ukraine Using Open Data Sources
DOI:
https://doi.org/10.31649/1997-9266-2021-157-4-20-31Keywords:
air pollution, microparticles, public health, global climate change, statistical data analysisAbstract
In recent decades, the global climate change determined as the increase in average annual air temperature, melting glaciers, increased evaporation of water and salinity of rivers, lakes, ponds, changes in the habitat of aquatic, groundwater and terrestrial animals, and human health and life expectancy, has been accepted as a fact. Because the countries of the world are closely linked by "open borders" of air and water, any local pollution is transferred with the flow of air, surface and groundwater to other countries, lands and continents. Environmental assessment and forecasts for the coming years and decades are based on continuous monitoring data from meteorological, climatic, chemical and biochemical stations, laboratories and research groups. The result of these efforts is an online database with open access, which allows to visualize the monitoring results and process the data with new mathematical methods to obtain reliable indicators of the state of pollution.
The article analyzes the state of air pollution in large cities in Ukraine on the basis of data processing from open sources. Indicators such as concentrations of gases CO, SO2, NO, NO2, chemicals C6H6O, CH2O, NH3, HF, HCl, C, as well as solid particles PM10, PM2.5, which are produced in industrial cycles using imperfect (obsolete) means, energy production, combustion of hydrocarbon fuels in car engines, etc are analyzed. Statistically significant relationships between pairs of the above parameters were obtained both on daily dependencies from open sources (time series) and on averaged data for each month, each city, and the country as a whole. It is shown that at the national level the city has statistically significant relationships between NO2 and NO, CH2O, С and СО.These dependencies differ in different cities and vary depending on the season (i.e. meteorological indicators). Thus, each city has its own dynamic statistical vector of dependencies between the content of measured substances, which indicates the sources of pollution in the form of enterprises, thermal power plants, road traffic and so on. Comparative data of PM2.5 pollution on the territory of Ukraine in comparison with neighboring countries are given. The need to create a common database with a single list of major pollutants, data processing methods, statistical indices and evaluation criteria is discussed.
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