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Concentrations and emissions of dissolved CH4 and N2O in the Yarlung Tsangpo River.

YE Run-cheng1,2, WU Qi-xin1, ZHAO Zhi-qi2, HU Jian2, CUI Li-feng2, DING Hu2,3*   

  1. (1Key Laboratory of Karst Environment and Geohazard, Ministry of Land and Resources, Guizhou University, Guiyang 550025, China; 2State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China; 3University of Glasgow, Glasgow G12 8QQ, Scotland, UK).
  • Online:2019-03-10 Published:2019-03-10

Abstract: Rivers release large quantities of greenhouse gases into the atmosphere, which is an important link in the material cycling and energy flow of terrestrial ecosystems. Mountainous rivers are ‘hotspots’ for greenhouse gas emission, but the release of CH4 and N2O from those rivers has been less documented. To explore the spatiotemporal distributions and related controls of CH4 and N2O in middle-large plateau rivers, the seasonal variations of CH4 and N2O in tributary and main stream of the Yarlung Tsangpo River were examined. The results showed that the ranges of CH4 and N2O concentrations in the Yarlung Tsangpo were 2.3-864.9 and 8.2-23.7 nmol·L-1, respectively. There was no significant difference in CH4 concentrations between low-flow and high-flow periods (P=0.112), but the N2O contents were higher in low-flow months than in high-flow months (P=0.017). River water discharge and water temperature were the major factors controlling the dynamics of CH4 and N2O emission, respectively. The release rates of CH4 and N2O in the Yarlung Tsangpo River ranged 4.3-11.1 mg C·m-2·d-1 and 0.16-0.37 mg N·m-2·d-1, respectively. The emission amounts of CH4 and N2O in Yarlung Tsangpo River system were 1.88-4.59 Gg C·a-1 and 0.07-0.16 Gg N·a-1, accounting for 1.25‰-3.06‰ and 2.17‰-4.96‰ of global river estimations, respectively. The evasion of CH4 and N2O in mountainous rivers need further detailed studies, which may revise the global estimation of greenhouse gas emission.

Key words: Poa pratensis, Cluster analysis, Seed yield, Yielding characteristics