The contribution of weather factors to seasonal variations in oxygen partial density in different climatic zones

Background: Currently, there is growing concern about changes in the oxygen content in the surface air layer. There are weather classifications where the determining meteotropic effect affecting human health is the value of oxygen partial density, but among these types of weather, hyperoxia situations are not considered, although in a number of studies attention has been drawn to the negative impact on human health of high oxygen content in inhaled air. Taking into account the combination of periodic and aperiodic components of weather factors, it seems relevant to assess their intraannual variations in different climatic zones and determine their contribution to the formation of seasonal rhythms of partial oxygen density.

Aim: To assess the contribution of weather factors of the subarctic and subtropical climatic zones to the seasonal dynamics of the partial oxygen density in the atmospheric air.

Materials and methods: Wavelet analysis was used for mathematical analysis of weather changes. Signal analysis was performed in the plane of wavelet coefficients (scale–time–level). The statistical significance of rhythms was estimated by multiple (5000) random permutations of the levels of the original time series.

Results: In the Subarctic region, the annual rhythm of partial oxygen density is modulated by the insertion intra-annual rhythms of weather factors, in the subtropics, the rhythm of partial oxygen density is determined by constant low-amplitude rhythms of weather factors. The population of the North is exposed to hyperoxia during the five winter months and hypoxia in the summer. In the Limpopo province of South Africa, hypoxia occurs during the wet season (November to May), which, according to the medical weather classification, requires medical supervision.

Conclusion: Considering the presence of aperiodic components in the dynamics of weather factors, mathematical data processing requires the use of methods that evaluate changes in the spectral composition of a time series over time. We recommend supplementing medical weather classifications with such items as "hyperoxic day" and "hyperoxic" weather type.