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Chinese Science Bulletin, Volume 64, Issue 7: 715-724(2019) https://doi.org/10.1360/N972018-00655

Factors contribution to oxygen concentration in Qinghai-Tibetan Plateau

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  • ReceivedJul 1, 2018
  • AcceptedOct 11, 2018
  • PublishedNov 21, 2018

Abstract

Oxygen (O2) 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.


Funded by

国家重点研发计划(2016YFA0602404)

中国科学院战略性先导科技专项(XDA20000000)

国家自然科学基金创新研究群体项目(41621061)


Acknowledgment

在野外观测中, 相关工作得到中国科学院青藏高原研究所姚檀栋院士, 西藏自治区人民政府丁业现先生, 西藏自治区那曲行政公署斯郎江措、罗布扎堆和高鹏先生等的大力支持与帮助, 中国科学院大气物理研究所孔祥慧博士、中国科学院地理科学与资源研究所王红博士及应急管理部国家减灾中心周洪建博士参加了野外采样工作, 北京师范大学龚道溢和周涛教授在数据分析方面提供了帮助, 匿名审稿人为本文提出了建设性修改意见和建议, 在此一并致谢!


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  • Figure 1

    Distribution map of global land altitude. Adapted from Ref. [10], the high altitude area in tan

  • Figure 2

    Location map of study area and sampling sites

  • Figure 3

    Comparison of measured elevations to SRTM data

  • Figure 4

    Schematic diagram of surface vegetation coverage estimation

  • Figure 5

    (Color online) The relationship between multi-factors (S.D. error bar in (a)). (a) Altitude and ROC; (b) vegetation coverage and ROC; (c) 500 hPa-T and ROC; (d) altitude and AOC

  • Figure 6

    Surface air pressure change with altitude change in Qinghai- Tibetan Plateau and Antarctica[20]

  • Figure 7

    The relationships between altitude and oxygen partial pressure (a), between AOC and CMS incidence[25] (b)

  • Table 1   Descriptive statistics for ROC and AOC

    指标

    样本数

    平均值

    最大值

    最小值

    标准差

    氧气相对含量(%)

    65

    21.1

    21.9

    20.8

    0.2

    氧气绝对含量(g/m3)

    153.2

    183.0

    136.1

    9.9

  • Table 2   Vegetation coverages corresponding to LUCC

    编号

    二级分类

    盖度(%)

    编号

    二级分类

    盖度(%)

    12

    旱地

    70

    43

    水库坑塘

    0

    21

    有林地

    65

    51

    城镇用地

    0

    22

    灌木林

    60

    52

    农村居民点

    0

    23

    疏林地

    20

    53

    其他建设用地

    0

    24

    其他林地

    30

    61

    沙地

    2.5

    31

    高覆盖度草地

    75

    62

    戈壁

    2.5

    32

    中覆盖度草地

    35

    64

    沼泽地

    75

    33

    低覆盖度草地

    13.5

    65

    裸土地

    2.5

    41

    河渠

    0

    66

    裸岩石质地

    2.5

    42

    湖泊

    0

    67

    其他未利用地

    20

  • Table 3   The total variances of the interpretation

    成分

    初始特征值

    提取平方和载入

    合计

    方差的百分量(%)

    累积百分量(%)

    合计

    方差的百分量(%)

    累积百分量(%)

    氧气

    相对

    含量

    1

    1.559

    38.982

    38.982

    1.559

    38.982

    38.982

    2

    1.061

    26.519

    65.501

    1.061

    26.519

    65.501

    3

    0.797

    19.931

    85.432

    4

    0.583

    14.568

    100.000

    氧气

    绝对

    含量

    1

    1.973

    49.317

    49.317

    1.973

    49.317

    49.317

    2

    1.183

    29.566

    78.883

    1.183

    29.566

    78.883

    3

    0.814

    20.351

    99.234

    4

    0.031

    0.766

    100.000

  • Table 4   Component matrixes

    氧气相对含量成分

    氧气绝对含量成分

    1

    2

    1

    2

    海拔(m)

    0.458

    0.788

    0.988

    0.089

    植被盖度(%)

    0.540

    0.590

    0.045

    0.777

    500 hPa-T(°C)

    0.643

    0.260

    0.124

    0.754

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