Oxygen (O_2) is essential for physiological activity in humans. On the Qinghai-Tibetan Plateau, with an average altitude of more than 4 km, hypoxia can seriously damage local residents' health, especially the respiratory system. When an organism cannot fully compensate for insufficient physiological function caused by hypoxia, acute and chronic mountain sickness (AMS and CMS) will occur. Previous studies have suggested that the relative oxygen concentration (ROC) in the near-ground air shows no obvious changes at different altitudes. However, during field work in the Qinghai-Tibetan Plateau, we found that, in addition to altitude, surface vegetation coverage and weather conditions may also have an impact on ROC. The results of data analysis showed that altitude and 500 hPa air temperature (500 hPa-T) were negatively correlated with ROC, while vegetation coverage was directly proportional to ROC. Based on principal component analysis (PCA), the results indicated that altitude, vegetation coverage and 500 hPa-T accounted for 65.5% of the total variance in ROC, of which the variance interpretation rate of vegetation coverage was highest (33.1%), followed by 500 hPa-T (28.5%) and altitude (3.9%). Absolute oxygen concentration (AOC) was calculated using the Ideal-Gas Equation. Using this equation, we found that altitude, vegetation coverage and 500 hPa-T accounted for 78.9% of the total variance in AOC, of which the variance interpretation rate of altitude was highest (45.9%), followed by vegetation coverage (18.5%) and 500 hPa-T (14.5%). AOC was negatively correlated with the incidence of CMS, and elevated AOC significantly reduced the incidence of CMS. The science community should pay more attention to this topic as a further decrease in ROC could significantly increase instability and risk in populations at high altitudes. These findings could enhance our understanding of the relationships between oxygen concentration, altitude, vegetation, weather conditions and their interactions. In addition, this research may not only play an important guiding role in human and animal health in high altitude areas, but also significantly deepen our understanding of the risks in high altitude environments under global warming both theoretically and practically. Multi-source data, including in-situ measurement data, remote sensing data, and model reanalysis data, will facilitate further implementations in this direction. Future work can be carried out using more fixed-point observations and by expanding the spatio-temporal extent of relevant data in high altitudes.