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

Cover Page


Cite item

Full Text

Abstract

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.

Full Text

Background

The human body is exposed to various weather and geophysical factors, including temperature, humidity, atmospheric pressure, solar irradiance, magnetic activity, and air composition [1–3]. The intensity of biotropic effect depends on the magnitude of these factors and also their periodic and aperiodic changes over time [4]. Long-term exposure to high temperatures can lead to hyperthermia and related conditions, such as tachycardia, hypertension, hypotension, headaches, convulsions, and electrolyte imbalances [5]. Exposure to low temperatures can result in various functional changes that negatively affect health [6, 7]. For example, 33 types of conditions have been identified where acute exposure to cold can be a causative (etiological) factor for primary dysfunction and a definitive determinant for other pathological processes (pathogenetic factor), which contribute to their progression and poorer outcomes.

High humidity exacerbates the adverse effects of both high and low temperatures. High humidity affects pulmonary ventilation and alveolar–capillary oxygen diffusion [8]. Water vapor is involved in maintaining the partial oxygen density (POD) of inhaled air and in heat transfer processes. Atmospheric pressure significantly impacts many functions of the human body, including gas exchange and circulatory system function [9].

There are growing concerns about changes in the oxygen content of ground-level air [10, 11]. Several weather classification systems use POD as a determinant of human health. These classifications identify four types of weather conditions: hypoxic, spastic, indifferent, and hypotensive, which may or may not require medical supervision [12, 13].

Situations with increased oxygen content are not considered. However, several works have demonstrated that high oxygen levels negatively affect human health and well-being [14], even at high latitudes [15].

Taking into account the combination of periodic and aperiodic components of weather factors, it seems relevant to assess their intra-annual variations in different climatic zones, and determine their contribution to the formation of seasonal POD rhythms.

The study aimed to assess the contribution of weather factors of the subarctic and subtropical climatic zones to the seasonal changes of POD in the atmospheric air.

Materials and methods

The weather undergoes both periodic and aperiodic changes, so wavelet analysis was used for mathematical analysis of weather changes [16]. The wavelet coefficient plane (scale–time–level) was used to evaluate signals [17]. The wavelet transform illustrates over-time changes in the spectral structure of a time series. It can be used to track abrupt weather shifts, such as cyclones with associated atmospheric fronts, and their impact on stable weather rhythms [4].

The following time series parameters were evaluated: mean level (mesor, M ± m), rhythm amplitude (A, arbitrary units), periods of stable and transient (quantized) rhythms (days per month), the coefficient of variation (cv, %), and the coefficient of synchronization (r, arbitrary units). The statistical significance of rhythms was estimated by multiple (5000) random permutations of the levels of the original time series. The reported p-value indicates the percentage of cases in which the energy of the extracted frequency component of the original series exceeded that of the permuted series.

The following parameters were evaluated using daily means to assess weather variations throughout the year: ambient air temperature (T, °C); atmospheric pressure (P, mm Hg); relative humidity (φ, %), and POD (g/m3).

The POD, also defined as the weight oxygen content, is directly proportional to atmospheric pressure minus the partial pressure of water vapor and inversely proportional to air temperature: O2=83×(P–φ)/T. This correlates with the partial oxygen pressure in inhaled and alveolar air, depending on physical characteristics [18, 19].

To minimize the effects of helio-geophysical factors on the weather, 2007 was selected as the reference year. It was the quietest year of Solar Cycle 23, with a minimum monthly mean smoothed sunspot number of 2.2. Table 1 shows the duration of each actual season in the regions that were evaluated.

 

Table 1. Duration of actual seasons of the year in Khanty-Mansiysk (Russia) and Polokwane (South Africa)

Khanty-Mansiysk

August

September

October

November

December

January

February

March

April

May

June

July

Summer

Autumn

Winter

Spring

Summer

Polokwane

August

September

October

November

December

January

February

March

April

May

June

July

Winter

Spring

Summer

Autumn

Winter

Dry season

Wet season

Dry season

 

Khanty-Mansiysk is located at the coordinates 61° N, 69° E. It has a sharply continental climate which is characterized by severe, long winters with strong winds and snowstorms. Cold weather returns in spring, and late spring and early autumn frosts are common. The typical duration of the seasons is as follows: autumn:1 September 5 to October 11 (36 days); winter: October 12 to April 27 (200 days); spring: April 28 to June 9 (42 days); summer: June 10 to September 4 (87 days). Apparent changes in photoperiod occur throughout the year. The shortest daylight duration, 5 hours and 32 minutes, is recorded on December 22. In contrast, during the summer white nights, daylight reaches 19 hours and 17 minutes.

Polokwane is the capital of the Polokwane municipality, the Capricorn District Municipality, the Limpopo province in South Africa. It is located at 23° S, 29° E.

Summer in Limpopo lasts from November to March (~5 months). Most of the annual precipitation falls during this season. Daytime temperatures are 25–40°C or higher. Autumn (April, May) is a transitional season, characterized by moderate temperatures and lower precipitation. Daytime temperatures are 20–30°C, and precipitation is significantly lower. Winter lasts from June to August (~3 months). There is virtually no precipitation. Spring, the transition period from dry to wet season, lasts approximately two months (September and October). The temperature fluctuates between 20°C and 35°C. The province receives abundant sunshine throughout the year, especially in winter. There are minor seasonal variations in photoperiod, with an approximate difference of three hours (10 hours and 39 minutes on June 22 versus 13 hours and 36 minutes on December 22).2

Results

Table 2 shows the average annual values, amplitude of variations, and coefficient of variation for temperature, atmospheric pressure, relative humidity, and POD in Khanty-Mansiysk and Polokwane.

 

Table 2. Average annual values, amplitude of fluctuations and coefficient of variation of temperature, atmospheric pressure, relative humidity, partial oxygen density in the cities of Khanty-Mansiysk and Polokwane

Parameters

M±m

А

cv

Khanty-Mansiysk

Temperature (°C)

0,84±13,86

192,74

1641,15

Atmospheric pressure (mmHg)

1012,34±10,16

1024936,77

1,00

Relative humidity (%)

77,75±10,31

6151,88

13,27

Partial oxygen density (g/m3)

283,24±14,79

80445,13

5,22

Polokwane

Temperature (°C)

17,77±4,36

334,77

24,52

Atmospheric pressure (mmHg)

1021,29±4,24

1043051,72

0,41

Relative humidity (%)

63,28±14,41

4212,23

22,77

Partial oxygen density (g/m3)

274,22±6,55

75237,27

2,39

Note. M — average level; m — standard error; A — oscillation amplitude (conventional units); cv— variation coefficient (%).

 

Although the average annual POD values in Khanty-Mansiysk and Polokwane do not differ significantly (see Table 2), reliable seasonal differences are observed (Fig. 1). The lowest POD values occur in the summer months in both the northern and southern hemispheres. However, POD in Khanty-Mansiysk varies more, with a coefficient of variation of 5.22% (ranging from 260 g/m3 in summer to 330 g/m3 in winter). In contrast, POD in Polokwane varies by only 2.39% throughout the year (ranging from 260 g/m3 in summer to 290 g/m3 in winter).

 

Fig. 1. Dynamics of the partial oxygen density in Khanty-Mansiysk and Polokwane: the abscissa axis is the value of the partial oxygen density (g/m3), the ordinate axis is months and seasons.

 

A wavelet analysis of the POD variations in Khanty-Mansiysk found two transient [20] rhythms, or abrupt weather shifts [21]: 101.1 days/4.65 arbitrary units/0.0013 and 135 days/2.99 arbitrary units/0.001 lasting from January to June (winter/spring). A POD spectrogram was compared with spectrograms of other weather variables, and comparable transient rhythm durations were documented for variations of T (101.1 days), P (75.3 days), and φ (68.3 days). Abrupt shifts in humidity were demonstrated for 19.0 and 17.3 days. A correlation analysis of weather factor variations and the POD in Khanty-Mansiysk indicates strong positive relationships between the POD/T (r=0.924) and moderate positive relationship between POD/P (r=0.318) and POD/φ (r=0.386) ratios.

In the subtropical climate zone, the annual POD variations have two transient rhythms: 83.1 days/2.11 arbitrary units/0.002 and 23.2 days/0.69 arbitrary units/0.035. However, unlike in the subarctic climate zone, the high-amplitude rhythm with a period of 83.1 days was observed as two abrupt weather shifts, which occurred during the wet (summer) season (January–March and October–December), and the low-amplitude, but a significant rhythm with a period of 23.2 days was observed during the dry season peak (June–July), respectively (Fig. 1). In contrast to the transient rhythm in the subarctic climate, the air temperature in the subtropical zone was characterized by a stable, low-amplitude, three-month rhythm (101.1 days/1.46 arbitrary units/ 0.003).

Variations in atmospheric pressure are characterized by the stable, high-amplitude (2.46 arbitrary units) rhythm with a period of 101.1 days (0.001), as well as by short-term (transient) rhythms with the periods of 21.0 (0.001), 34.4 (0.001), and 50.9 (0.015) days. These rhythms peaked in the middle of the dry season (May–August). The humidity showed a stable rhythm with the period of 83.1 days (0.001) and the peak during the entire dry season. The relationship between the POD and weather factors in the subtropical climate zone was moderately positive: POD/T (r=0.627), POD/P (r=0.489), and POD/φ (r=0.351).

Discussion

An analysis of the chronobiological features of POD variations has revealed that the annual POD rhythm in the subarctic climate zone is modulated by transient, intra-annual weather patterns. These factors contribute differently to the resulting POD by season. Over time, the transient rhythms of POD, air temperature, and humidity coincide, primarily in the winter. In the summer, however, POD depends more on the short-period transient rhythms of atmospheric pressure. The intra-annual range of the parameters is quite high (cv=5.22% compared with 2.7% in Moscow [15]). An analysis of POD variations throughout the year reveals stable seasonal changes in the subarctic climate zone, such as hyperoxia in winter and hyperthermic hypoxia in summer.

In the subtropical climate zone, a rigid rhythm of POD changes (cv=2.39%) with a low mesor is observed. This suggests an unfavorable, oxygen-based weather type, which can be caused by stable, low-amplitude weather patterns [12]. The higher POD (rhythm with a period of 23.2 days) in May to June of the dry season is caused by short-term variations in atmospheric pressure. The subtropical climate zone is characterized by hypoxia throughout the year, with a slight increase in POD during the dry season.

Transient seasonal rhythms predominate in the north, whereas stable, low-amplitude rhythms predominate in the south throughout the year. This results in rigid subtropical and apparent seasonal subarctic POD rhythms.

From a clinical point of view, a quantitative classification of weather conditions includes three oxygen-based types of weather: positive, with POD of approximately 285±5 g/m3; conditionally negative, with POD of 270–280 g/m3; and negative, with POD of less than 270 g/m3 [19]. A medical weather classification proposed by Grigoryev [12, 18] categorizes weather types as requiring either intensified (POD = 289–260 g/m3) or intensive (POD <260 g/m3) medical monitoring, as opposed to the very positive type (POD >315 g/m3). This classification is based solely on these factors, with no consideration given to the effects of higher POD (hyperoxia), as mentioned by some authors [15].

Oxygen is essential for life. However, like any medicine, it has both positive and toxic biological effects. The pathophysiology of hyperoxia is associated with higher levels of reactive oxygen species (ROS), which can easily react with surrounding biological tissues, affecting lipids, proteins, and nucleic acids. Hyperoxia may impair antioxidant protection. ROS cause oxidative stress. An activated alveolar capillary endothelium is characterized by increased adhesiveness. This leads to the accumulation of cell populations, such as neutrophils, which produce ROS. Higher ROS levels cause hyperpermeability, coagulopathy, collagen deposition, and other irreversible alveolar changes [22].

Zhuravlev [23] hypothesized that physical factors primarily act by influencing free radical processes. The author classified all factors by the process of free radical generation into three main groups: 1) factors initiating free radical oxidation: ionizing radiation, ultraviolet rays, ultrasound, and higher POD (oxygen therapy); 2) factors inhibiting free radical oxidation: peloid therapy, hydrogen sulfide baths, and lower POD; 3) factors indirectly affecting free radical oxidation: various currents, visible and infrared radiation, microwaves, etc. [24].

The increased use of prolonged mechanical ventilation and hyperbaric oxygen therapy in anesthesiology and intensive care has made hyperoxia an urgent clinical concern. Even now, nearly 240 years after the discovery of oxygen, the medically safe upper limits and duration of high-fraction inspired oxygen remain unclear [25, 26].

Recently, hyperoxia has been used in hypoxic/hyperoxic training in sports [27] and clinical [28] practice. The effectiveness of this training is enhanced by alternating short periods of low oxygen with high oxygen pulses (exposure to a gas mixture containing 30% O2 for 2–3 minutes) [29].

However, the dose–effect problem, considered one of the most critical aspects of free radical processes, remains largely unsolved. Levels of ROS and the antioxidant/prooxidant ratio can be used to objectively evaluate the impact of oxygen and other physical factors [30].

Conclusion

In the subarctic climate zone, the POD rhythm throughout the year is modulated by intra-annual transient rhythms of weather patterns, and these effects on POD vary from season to season. Over time, the transient rhythms of POD, air temperature, and humidity coincide, primarily in the winter. In the summer, however, POD depends more on the short-period transient rhythms of atmospheric pressure. The population of Khanty-Mansiysk is exposed to a changed gas environment throughout the year. Hyperoxia is observed for five months: November, December, January, February, and March. Normoxia is observed in April, May, and June (the spring component) and in September and October (the autumn component). Hyperthermic hypoxia is observed in July and August.

In the subtropical climate zone, stable, low-amplitude rhythms of weather patterns largely explain the detection of a rigid POD rhythm with a low mesor (coefficient of variation: 2.3%). The population of the Limpopo province experiences slightly different POD conditions during the dry season (May to September). However, according to the medical weather classification, hypoxia requires intensified medical monitoring during the wet season (November to May).

In the context of mathematical data processing, aperiodic components in weather pattern changes should be considered. To address this necessity, it is crucial to use methodologies that estimate temporal variations in the spectral structure of time series. In addition, it is recommended to use specific terms such as hyperoxic day and hyperoxic weather type to supplement medical weather classifications.

Additional information

Authors’ contribution. O.N. Ragozin — a significant contribution to the concept and design of the study, editing and final approval of the manuscript; I.V. Radysh — editing and final approval of the manuscript; L. Muthelo — data analysis; E.Yu. Shalamova — preparation of the first version of the article; A.B. Gudkov — editing the first version of the article; E.R. Ragozinа — a set of primary material; I.A. Pogonysheva — data analysis. All authors confirm that their authorship meets the international ICMJE criteria (all authors have made a significant contribution to the development of the concept, research and preparation of the article, read and approved the final version before publication).

Ethical expertise. The study was approved by the local ethics committee Khanty-Mansiysk State Medical Academy (conclusion No. 214 dated October 15, 2024).

Funding sources. No funding.

Disclosure of interests. The authors have no relationships, activities or interests for the last three years related with for-profit or not-for-profit third parties whose interests may be affected by the content of the article.

Statement of originality. In creating this work, the authors did not use previously published information (text, illustrations, data).

Data availability statement. The editorial policy regarding data sharing does not apply to this work, and no new data was collected or created.

Generative AI. Generative AI technologies were not used for this article creation.

Provenance and peer-review. This paper was submitted to the journal on an unsolicited basis and reviewed according to the usual procedure. Two external reviewers, a member of the editorial board, and the scientific editor of the publication participated in the review.

Дополнительная информация

Вклад авторов. О.Н. Рагозин — существенный вклад в концепцию и дизайн исследования, редактирование и окончательное утверждение рукописи; И.В Радыш — редактирование и окончательное утверждение рукописи; Л. Мутэло — анализ данных; Е.Ю. Шаламова — подготовка первого варианта статьи; А.Б. Гудков — редактирование первого варианта статьи; Э.Р. Рагозина — набор первичного материала; И.А. Погонышева — анализ данных. Все авторы подтверждают соответствие своего авторства международным критериям ICMJE (все авторы внесли существенный вклад в разработку концепции, проведение исследования и подготовку статьи, прочли и одобрили финальную версию перед публикацией).

Этическая экспертиза. Проведение исследования одобрено локальным этическим комитетом Ханты-Мансийской государственной медицинской академии (заключение № 214 от 15 октября 2024 г.).

Источники финансирования. Отсутствуют.

Раскрытие интересов. Авторы заявляют об отсутствии отношений, деятельности и интересов за последние три года, связанных с третьими лицами (коммерческими и некоммерческими), интересы которых могут быть затронуты содержанием статьи.

Оригинальность. При создании настоящей работы авторы не использовали ранее опубликованные сведения (текст, иллюстрации, данные).

Доступ к данным. Редакционная политика в отношении совместного использования данных к настоящей работе не применима, новые данные не собирали и не создавали.

Генеративный искусственный интеллект. При создании настоящей статьи технологии генеративного искусственного интеллекта не использовали.

Рассмотрение и рецензирование. Настоящая работа подана в журнал в инициативном порядке и рассмотрена по обычной процедуре. В рецензировании участвовали два внешних рецензента, член редакционной коллегии и научный редактор издания.

 

1 Khanty-Mansiysk Center for Hydrometeorology and Environmental Monitoring. Available at http://www.ugrameteo.ru Accessed on November 7, 2024.

2 Green Book: Adapting South African Settlements to Climate Change. Available at https://greenbook.co.za Accessed on November 7, 2024.

3 Hereinafter: period / amplitude / significance.

×

About the authors

Oleg N. Ragozin

Khanty-Mansiysk State Medical Academy; Nizhnevartovsk State University

Email: oragozin@mail.ru
ORCID iD: 0000-0002-5318-9623
SPIN-code: 7132-3844

Cand. Sci. (Biology), Associate Professor

Russian Federation, Khanty-Mansiysk; Nizhnevartovsk

Ivan V. Radysh

Peoples' Friendship University of Russia

Email: iradysh@mail.ru
ORCID iD: 0000-0003-0939-6411
SPIN-code: 4780-5985

MD, Dr.Sci. (Medicine), Professor

Russian Federation, Moscow

Livhuwani Muthelo

University of Limpopo

Email: livhuwani.muthelo@ul.ac.za
ResearcherId: AHC-1001-2022

PhD

South Africa, Polokwane

Elena Yu. Shalamova

Khanty-Mansiysk State Medical Academy

Email: selenzik@mail.ru
ORCID iD: 0000-0001-5201-4496
SPIN-code: 8125-9359

Dr. Sci. (Biology), Associate Professor

Russian Federation, Khanty-Mansiysk

Andrey B. Gudkov

Northern State Medical University

Email: gudkovab@nsmu.ru
ORCID iD: 0000-0001-5923-0941
SPIN-code: 4369-3372

MD, Dr. Sci. (Medicine), Professor

Russian Federation, Arkhangelsk

Elina R. Ragozinа

Khanty-Mansiysk State Medical Academy

Email: elinka1000@yandex.ru
ORCID iD: 0000-0003-0199-2948

Postgraduate Student

Russian Federation, Khanty-Mansiysk

Irina А. Pogonysheva

Nizhnevartovsk State University

Author for correspondence.
Email: severina.i@bk.ru
ORCID iD: 0000-0002-5759-0270
SPIN-code: 6095-8392

Cand. Sci. (Biology), Associate Professor

Russian Federation, Nizhnevartovsk

References

  1. Bobrovnitskiy IP, Yakovlev MYu, Fesyun OA, Evseev SM. Main aspects of the influence of meteorological and heliogeophysical factors on the human body. Russian Journal of Rehabilitation Medicine. 2021;(2): 40–46. EDN: OKPRST
  2. Prilipko NS, Bobrovnitskiy IP. Improvement of the regulatory and legal framework in the system of organization and provision of medical care for patients with environmentally caused diseases. Russian Journal of Environmental and Rehabilitation Medicine. 2022;(1):1–30.EDN: SUFXPL
  3. Nagornev SN, Frolkov VK, Khudov VV. The influence of extreme climatogeographical factors of the arctic zone of the russian federation on the functional state of indigenous and newly-arrived population. Russian Journal of Environmental and Rehabilitation Medicine. 2022;(2):53–69. EDN: LEUALA
  4. Vasil'ev DYu, Babkov OK, Kochetkova ES, Semenov VA. Wavelet and cross-wavelet analysis of the sums of atmospheric precipitation and surface air temperature in European Russia. Izvestiya Rossiiskoi Akademii Nauk. Seriya geograficheskaya. 2017;(6):63–77. doi: 10.7868/S0373244417060068 EDN: ZVFRHJ
  5. Aghajanyan NA, Radysh IV. Biorhythms, habitat, health. Moscow: RUDN; 2013. 362 p. (In Russ.)
  6. Gudkov AB, Mosyagin IG, Ivanov VD. Characteristics of the phase structure of the cardiac cycle in recruits of the Navy training center in the North.Military Medical Journal. 2014;335(2):58–59. (In Russ.) EDN: SXFGJN
  7. Chashchin VP, Gudkov AB, Chashchin MV, Popova ON. Predictive assessment of individual human susceptibility to damaging cold exposure. Ekologiya cheloveka (Human Ecology). 2017;24(5):3–13. doi: 10.33396/1728-0869-2017-5-3-13 EDN: YNGENT
  8. Gudkov AB, Popova ON. External human respiration in the European North. Arkhangelsk: Publishing house of the Northern State Medical University; 2012. 251 p. (In Russ.) EDN: QKUPDZ
  9. Kuzmenko NV, Galagudza MM, Fedorenko AA, et al. Seasonal dynamics of cardiovascular events in the Russian Federation. Russian Journal of Cardiology. 2024;29(6):20–30. doi: 10.15829/1560-4071-2024-5773 EDN: KYZRXI
  10. Ginzburg AS, Vinogradova AA, Fedorova EI, et al. Oxygen in the atmosphere of large cities and people breath problems. Geophysical Processes and Biosphere. 2014;13(2):5–19. EDN: SCKXXN
  11. Zamolodchikov DG. The lack of oxygen: myth or reality? Use and Protection of Natural Resources of Russia. 2005;(3):122–132. EDN: REXOLP
  12. Grigoriev II, Paramonov IG, Ten MM. A brief guide to making medical forecasts. Moscow: Hydrometeoizdat; 1974. 14 p. (In Russ.)
  13. Petrov VN. Features of influence of oxygen' partial density gradient in the air on the health status of populations living in the arctic zone of the russian federation. Herald of the Kola Science Centre of RAS. 2015;(3):82–92. EDN: VBAYNZ
  14. Aghajanyan NA, Chizhov AYa. Hypoxic, hypocapnic, hypercapnic conditions. Moscow: Medicine; 2003. 212 p. (In Russ.) EDN: QLEQMZ
  15. Ginzburg AS, Vinogradova AA, Lezina EA, Pomelova MA. Changes in oxygen content in urban air under the influence of natural and anthropogenic factors. Izvestiya. Atmospheric and Oceanic Physics. 2023;59(4):437–449. doi: 10.31857/S0002351523040065EDN: YNGQLA
  16. Ragozin ON, Bochkarev MV, Kosarev AN, et al. Program for the study of biological rhythms by the method of wavelet analysis. Certificate of state registration of a computer program No 2014611398 / 03.02.2014. (In Russ.)
  17. Malla S. Wavelets in signal processing. Moscow: Mir; 2005. 672 p. (In Russ.)
  18. Ovcharova VF, Butyeva IV, Shveinova TG, Alyoshina TP. Specialized weather forecast for medical purposes and prevention of meteopathic reactions. Problems of Balneology, Physiotherapy and Exercise Therapy. 1974;(2):109–19. (In Russ.)
  19. Nikberg II, Revutsky EL, Sakali LI. Human heliometeotropic reactions. Kiev: I'm healthy; 1986. 144 p. (In Russ.)
  20. Ragozin ON, Tatarinzev PB, Pogonysheva IA, et al. Corrections for geographical differences in photoperiod in time-series analysis. Ekologiya cheloveka (Human Ecology). 2023;30(2):139–149. doi: 10.17816/humeco117532 EDN: VVYOJA
  21. Novikov IYa, Stechkin SB. Fundamentals of the theory of bursts. Russian Mathematical Surveys. 1998;53(6):1159–1231. doi: 10.1070/rm1998v053n06ABEH000089 EDN: EJDBAP
  22. Mach WJ, Thimmesch AR, Pierce JT, Pierce JD. Consequences of hyperoxia and the toxicity of oxygen in the lung. Nurs Res Pract. 2011;2011:260482. doi: 10.1155/2011/260482
  23. Zhuravlev AI, Zubkova SM. Antioxidants. Free radical pathology, aging. Moscow: Belye Alvy; 2014. 304 p. (In Russ.)
  24. Zhuravlev AI. Quantum biophysics of animals and humans. Moscow: BINOM; 2011. 398 p. (In Russ.) EDN: QKTOKZ
  25. Dolgikh VT, Govorova NV, OrlovYuP, et al. Pathophysiological aspects of hyperoxia in anesthesiologist-reanimatologist's practice. General Reanimatology. 2017;13(3):83–93. doi: 10.15360/1813-9779-2017-3-83-93 EDN: YYVPHX
  26. Orlov YuP, Govorova NV, Lukach VN, et al. Hyperoxia in the ICU and what has changed in 100 years in the tactics of using oxygen in medicine: a review. Annals of Critical Care. 2022;(2):80–94. doi: 10.21320/1818-474X-2022-2-80-94 EDN: CRDEJI
  27. Glazachev OS, Smolensky AV, Dudnik YeN, et al. Periodic hypoxic-hyperoxic training in the rehabilitation of sportsmen with the chronic hyper-training syndrome (a pilot study).Exercise therapy and Sports Medicine. 2010;(2):19–25. EDN: MUIWDJ
  28. Feofanova TB. The method of interval hypoxic-hyperoxic training as a rehabilitation option for patients after Covid-19. In: Integration of science and society in modern socio-economic conditions. Moscow; 2021. Р. 27–29. (In Russ.) EDN: SLCEFF
  29. Arkhipenko YuV, Sazontova TG. The effect of adaptation to different oxygen levels on physical endurance, free radical oxidation and urgent response proteins. The Russian Conference "Hypoxia: mechanisms, adaptation, correction". Pathogenesis. 2008;(3):44–45. (In Russ.)
  30. Ulashchik VS. Active oxygen species, antioxidants, and the action of therapeutic physical factors. Problems of Balneology, Physiotherapy, and Exercise Therapy. 2013;90(1):60–69. EDN: PYASAR

Supplementary files

Supplementary Files
Action
1. JATS XML
Download
2. Fig. 1. Dynamics of the partial oxygen density in Khanty-Mansiysk and Polokwane: the abscissa axis is the value of the partial oxygen density (g/m3), the ordinate axis is months and seasons.

Download (361KB)
Indexing metadata
3. Fig. 1. Dynamics of the partial oxygen density in Khanty-Mansiysk and Polokwane: the abscissa axis is the value of the partial oxygen density (g/m3), the ordinate axis is months and seasons.

Download (451KB)
Indexing metadata

Copyright (c) 2025 Eco-Vector

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
СМИ зарегистрировано Федеральной службой по надзору в сфере связи, информационных технологий и массовых коммуникаций (Роскомнадзор).
Регистрационный номер и дата принятия решения о регистрации СМИ: серия ПИ № ФС 77 - 78166 от 20.03.2020.