Multifractal characterisation of particulate matter (PM10) time series in the Caribbean basin using visibility graphs

Background PM10 atmosphere: In the seek of a multifractal characterization using complex networks

“…Consequently, the small noise-like fluctuations are more probable for the low season while large fluctuations are more likely in the high season. These results are consistent with our previous findings (Plocoste et al, 2020c).…”

“…This is explained by the fact that between October and April, the P M 10 concentrations are mainly linked to anthropogenic activity and marine aerosols which composed the background atmosphere (Clergue et al, 2015;Rastelli et al, 2017). Overall, the same trend was observed in our previous study but there are some differences (Plocoste et al, 2020c). This may be attributed to the difference in P M 10 data resolution as the whiskers seem significantly smaller, i.e.…”

“…This may be attributed to the difference in P M 10 data resolution as the whiskers seem significantly smaller, i.e. a more accurate description than in our previous study where daily data is used (Plocoste et al, 2020c).…”

“…To perform a profound analysis of P M 10 time series, multifractal frame is usually used (Ho et al, 2004;Liu et al, 2015b;Gao et al, 2016;Dong et al, 2017;Plocoste et al, 2017Plocoste et al, , 2020c, to mention a few. In all these studies, large fluctuations of P M 10 values are frequently taken into account.…”

Daylight Saving Time transitions and Cardiovascular Disease in Andalusia: Time Series Modeling and Analysis Using Visibility Graphs

“…20 This approach has been successfully applied in fields as diverse as the study of hurricanes 21 and earthquakes, 22 economics, 23 or contaminant dynamics. 24,25 It has also been used in healthcare to analyze psychiatric disorders through the brain activity using functional magnetic resonance imaging (fMRI) data, 26 assess brain dysfunctions through electroencephalographic (EEG) time series, 27 detect epilepsy from EEG signals, 28,29 for early detection of sudden cardiac arrests, 30 for the analysis of multi-omics time series used in precision medicine or for monitoring health events, 31 and for establishing the relation between intracranial pressure (ICP) and heart rate (HR), 32 among others.…”