Benzene Source Apportionment Using Bivariate Correlation and Regression Analyses
Benzene Source Apportionment Using Bivariate Correlation and Regression Analyses
Autori:
Izdanje: International Scientific Conference on Information Technology and Data Related Research
DOI: 10.15308/Sinteza-2020-8-13
Oblast: Artificial Intelligence Atlas
Stranice: 8-13
Apstrakt:
The aim of this study was to identify and characterize the individual sources
of benzene in an urban area of Belgrade based on bivariate polar plot concentration,
correlation, and regression analyses. The presented benzene
behavior modeling relied on a weighted Pearson correlation coefficient,
linear regression slope, and Gaussian kernel locally weighted by wind speed
direction surface. The data, including the concentrations of volatile organic
compounds (VOCs), inorganic gaseous pollutants and meteorological
parameters, were obtained from a measurement campaign conducted at the
Singidunum University (Belgrade, Serbia) during and after the heating season
2016. The results indicate the dominance of benzene, toluene, and NO local
emission sources, as well as the significant impact of remote NO2 sources
located in the SW and SE. The strong interrelations between VOCs indicate
the common origin of these compounds. High toluene to benzene ratio (>2)
was almost independent of wind speed and direction, indicating that the
entire area was severely exposed to fresh vehicular emissions. The absence
of relationships between benzene and fossil fuel combustion gaseous pollutants
including NOx and O3 suggests that evaporations from small chemical
industrial complex situated in the S direction from the study site might be the
main benzene and toluene emission source in the area. As regards inorganic
gaseous pollutants, the relationship between benzene and NO in the N and
NE might be related to the intensive anthropogenic activities in the central
urban area of Belgrade and petrochemical industry in Pančevo. As presented
herein, a combination of bivariate polar plot concentration, correlation, and
regression analyses offers unique insight into the individual sources of air
pollutants and their concentration dynamics.
of benzene in an urban area of Belgrade based on bivariate polar plot concentration,
correlation, and regression analyses. The presented benzene
behavior modeling relied on a weighted Pearson correlation coefficient,
linear regression slope, and Gaussian kernel locally weighted by wind speed
direction surface. The data, including the concentrations of volatile organic
compounds (VOCs), inorganic gaseous pollutants and meteorological
parameters, were obtained from a measurement campaign conducted at the
Singidunum University (Belgrade, Serbia) during and after the heating season
2016. The results indicate the dominance of benzene, toluene, and NO local
emission sources, as well as the significant impact of remote NO2 sources
located in the SW and SE. The strong interrelations between VOCs indicate
the common origin of these compounds. High toluene to benzene ratio (>2)
was almost independent of wind speed and direction, indicating that the
entire area was severely exposed to fresh vehicular emissions. The absence
of relationships between benzene and fossil fuel combustion gaseous pollutants
including NOx and O3 suggests that evaporations from small chemical
industrial complex situated in the S direction from the study site might be the
main benzene and toluene emission source in the area. As regards inorganic
gaseous pollutants, the relationship between benzene and NO in the N and
NE might be related to the intensive anthropogenic activities in the central
urban area of Belgrade and petrochemical industry in Pančevo. As presented
herein, a combination of bivariate polar plot concentration, correlation, and
regression analyses offers unique insight into the individual sources of air
pollutants and their concentration dynamics.
Ključne reči: benzene, volatile organic compounds, bivariate polar plot analysis
Priložene datoteke:
- 8-13 ( veličina: 1,03 MB, broj pregleda: 270 )
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BibTeX format
@article{article,
author = {M. Perišić, G. Jovanović, A. Vranić and S. Stanišić},
title = {Benzene Source Apportionment Using Bivariate Correlation and Regression Analyses},
journal = {International Scientific Conference on Information Technology and Data Related Research},
year = 2020,
pages = {8-13},
doi = {10.15308/Sinteza-2020-8-13}
}
RT Conference Proceedings A1 Mirjana Perišić A1 Gordana Jovanović A1 Ana Vranić A1 Svetlana Stanišić T1 Benzene Source Apportionment Using Bivariate Correlation and Regression Analyses AD Univerzitet Singidunum, Beograd, Beograd, Srbija YR 2020 NO doi: 10.15308/Sinteza-2020-8-13
M. Perišić, G. Jovanović, A. Vranić and S. Stanišić, Benzene Source Apportionment Using Bivariate Correlation and Regression Analyses, Univerzitet Singidunum, Beograd, 2020, doi:10.15308/Sinteza-2020-8-13