<abstract xmlns="http://www.w3.org/1999/xhtml">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.</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.

Analysis of Air Pollution Parameters Using Covariance Function Theory

Ecological Chemistry and Engineering S

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Analysis of Air Pollution Parameters Using Covariance Function Theory"}

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...

Analysis of Air Pollution Parameters Using Covariance Function Theory

Online veröffentlicht: 29. Jan. 2021

Seitenbereich: 555 - 565

DOI: https://doi.org/10.2478/eces-2020-0034

Schlüsselwörter
air pollution, methane, nitrogen dioxide, oxygen, correlation coefficients, covariance functions

© 2020 Ignas Daugela et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Analysis of Air Pollution Parameters Using Covariance Function Theory

Online veröffentlicht: 29. Jan. 2021

Seitenbereich: 555 - 565

DOI: https://doi.org/10.2478/eces-2020-0034

Schlüsselwörterair pollution, methane, nitrogen dioxide, oxygen, correlation coefficients, covariance functions

© 2020 Ignas Daugela et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
air pollution, methane, nitrogen dioxide, oxygen, correlation coefficients, covariance functions