Analysis of Air Pollution Parameters Using Covariance Function Theory

Abstract

The paper analyses the intensity changes of three pollution parameter vectors in space and time. The RGB raster pollution data of the Lithuanian territory used for the research were prepared according to the digital images of the Sentinel-2 Earth satellites. The numerical vectors of environmental pollution parameters CH4 (methane), NO2 (nitrogen dioxide) and for direct comparison O2 (oxygen gas) were used for the calculations. The covariance function theory was used to perform the analysis of intensity changes in digital vectors. Estimates of the covariance functions of the numerical vectors of pollution parameters and O2 or the auto-covariance functions of single vectors are calculated from random functions consisting of arrays of measurement parameters of all parameters vectors. Correlation between parameters vectors depends on the density of parameters and their structure. Estimates of covariance functions were calculated by changing the quantization interval on a time scale and using a compiled computer program using the Matlab procedure package. The probability dependence between the environmental pollution parameter vectors and trace gas of the territory in Lithuania and their change in time scale was determined.

Evaluation of Total Organic Carbon Quantity and Emissions of CO2 from Soil Into the Atmosphere Near Street

“…Average global temperature is higher by 0.8 °C when compared to pre-industrial levels. In order to avoid the adverse effects of irreversible climate change, global temperature must not rise more than 2 °C [4]. The high amount of carbon dioxide has raised an urgent problem [5].…”