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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

Artur Rot

Marcin Hernes
doi: 10.3390/su15032163
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.
Environmental effects of industries and plants, atmospheric pollution, interval evaluations, monitoring systems, TJ807-830, TD194-195, mathematical distribution model, Renewable energy sources, Environmental sciences, GE1-350, optimization problem, nitrogen dioxide concentration
Environmental effects of industries and plants, atmospheric pollution, interval evaluations, monitoring systems, TJ807-830, TD194-195, mathematical distribution model, Renewable energy sources, Environmental sciences, GE1-350, optimization problem, nitrogen dioxide concentration
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).17 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
