CONSTRUCTION OF MODELS OF SUBSTANCE CONCENTRATION CHANGING IN THE ATMOSPHERIC AIR
(BY THE EXAMPLE OF STERLITAMAK)

Safarov Ayrat Muratovich, Doctor of engineering sciences, associate professor, sub-department of applied ecology, Ufa State Petroleum Technological University (1 Kosmonavtov street, Ufa, Russia), Kafedra_ecologia@mail.ru
Shaydulina Galina Fatykhovna, Candidate of engineering sciences, associate professor, head of the department of analytical control of natural objects in the technogenic impact zone, Office of State Analytical Control (21 Rossiyskaya street, Ufa, Russia), ugak2004@mail.ru
Afanas'eva Ekaterina Sergeevna, Engineer, department of information technologies, Sterlitamak branch of Bashkir State University (49 Lenina avenue, Sterlitamak, Russia), kulakova87@list.ru

502.3:51-74

DOI

10.21685/2307-9150-2018-1-6

Background. The study of the change in the chemical composition of the atmospheric air of a city with a high level of contamination by petrochemical enterprises is necessary for compliance with its sanitary hygienic composition. The article presents
statistical models of the change in the concentration of substances in the atmospheric air of Sterlitamak. Models of factor regression of the concentration of 1,2-dichloroethane and nitrogen dioxide in the residential zone of Sterlitamak during the period of prevalence of dangerous wind conditions have been developed.
Materials and methods. In the present study, models of a time series of hourly concentrations of carbon monoxide (II), nitrogen oxides, hydrogen sulphide, sulfur dioxide, vinyl chloride, 1,2-dichloroethane, o-xylene, m, p-xylene, phenol, methanol,
ethyl benzene, chloroform, ozone, ethylene in the atmospheric air of the residential zone of Sterlitamak for 2 periods (2010–2012 and 2015–2017); as well as models of factorial regression of hourly concentrations of 1,2-dichloroethane and nitrogen
dioxide at different time intervals.
Results. According to the comparative analysis of ARIMA-models of concentrations of substances for 2010–2012, and 2015–2017. chemical substances were conditionally divided into 2 groups, the distinguishing feature of which is the possibility
of using the time series analysis method for forecasting. The obtained models of factor regression of 1,2-dichloroethane have a high degree of adequacy. The comparability of the experimental and predicted values of nitrogen dioxide obtained by factorial
regression that does not take into account the influence of pollution sources is small.
Conclusions. The use of a change in the concentration of a substance in a residential area of the city together with the results of monitoring industrial emissions allows one to obtain an adequate model for specific components. To predict the content
of common pollutants, the results of monitoring the chemical composition of atmospheric air in a residential area are sufficient. The momentary concentration of 1,2-dichloroethane in air is described with high accuracy by factorial regression,
taking into account the emission concentrations at the pollution source. Changes in the concentration of nitrogen dioxide in the air are regular and constant. To predict the concentration of nitrogen dioxide, it is possible to use time series models.

Key words

ARIMA-model, atmosphere, coefficient of determination, cross-correlation function, factor regression, forecasting, 1,2-dichloroethane, oxides of nitrogen, statistical model, weather conditions

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