The complexity of spatial-temporal air pollutant concentration dynamics
requires innovative modeling investigation approaches. The details of
non-linear nature of pollutant behavior cannot be revealed by conventional
approaches, but fractal and Hurst rescaled analyses allow the quantification
of pollutant dynamics structure via self-similarity and scale invariance. In
this study, we applied multiscale multifractal analysis (MMA) to investigate
the complex time-series of criteria air pollutants (PM10, PM2.5, NOX, SO2, CO
and O3). The results showed that PM10 and PM2.5 concentrations are more
stable compared to gaseous oxides and exhibit less prominent multifractality.
Out of gaseous contaminants, CO is confirmed to be less chemically reactive
than NO, NO2, NOx, SO2 and O3 under the same atmospheric conditions in
urban and semi-urban area. As concluded, the multifractal analysis presented
herein can enhance our understanding of specific pollutant dynamic features
and support relevant sectors to control the pollutant release and distribution.
G. Jovanović, S. Stanišić, M. Perišić, “Multifractal Characteristics of Criteria Air Pollutant Time Series in Urban Areas,” in Sinteza 2020 - International Scientific Conference on Information Technology and Data Related Research, Belgrade, Singidunum University, Serbia, 2020, pp. 29-34. doi:10.15308/Sinteza-2020-29-34
Jovanović, G., Stanišić, S., Perišić, M. (2020). Multifractal Characteristics of Criteria Air Pollutant Time Series in Urban Areas. Paper presented at Sinteza 2020 - International Scientific Conference on Information Technology and Data Related Research. doi:10.15308/Sinteza-2020-29-34