Modeling Based on the Analysis of Interval Data of Atmospheric Air Pollution Processes with Nitrogen Dioxide due to the Spread of Vehicle Exhaust Gases

Mykola Dyvak (), Iryna Spivak, Andriy Melnyk (), Volodymyr Manzhula, Taras Dyvak, Artur Rot and Marcin Hernes
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Mykola Dyvak: Department of Computer Science, West Ukrainian National University, 46000 Ternopil, Ukraine
Iryna Spivak: Department of Computer Science, West Ukrainian National University, 46000 Ternopil, Ukraine
Andriy Melnyk: Department of Computer Science, West Ukrainian National University, 46000 Ternopil, Ukraine
Volodymyr Manzhula: Department of Computer Science, West Ukrainian National University, 46000 Ternopil, Ukraine
Taras Dyvak: Department of Computer Science, West Ukrainian National University, 46000 Ternopil, Ukraine
Artur Rot: Faculty of Management, Wroclaw University of Economics and Business, 53-345 Wroclaw, Poland
Marcin Hernes: Faculty of Management, Wroclaw University of Economics and Business, 53-345 Wroclaw, Poland

Sustainability, 2023, vol. 15, issue 3, 1-17

Abstract: The article deals with the issue of modeling taking into consideration nitrogen dioxide pollution of the atmospheric surface layer caused by vehicle exhaust gases. The interval data analysis methods were suggested. The method of identifying the mathematical model of the distribution of nitrogen dioxide as an atmospheric air pollutant based on the analysis of data with known measurement errors was proposed and grounded for the first time. The obtained mathematical model in the form of a difference equation is characterized by the guaranteed accuracy of forecasting nitrogen dioxide concentrations in a specified area of the city. It also adequately takes into account traffic changes which significantly reduces the costs of environmental control and monitoring. The proposed new model identification method is more effective in terms of computational time complexity compared to the known method and it is based on taking into account measurement errors which in the final case provides predictive properties of the model with guaranteed accuracy.

Keywords: atmospheric pollution; monitoring systems; mathematical distribution model; nitrogen dioxide concentration; optimization problem; interval evaluations (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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