环境科学
温室气体
平流
水文学(农业)
大气科学
对偶(语法数字)
二氧化碳
全球变暖
大气(单位)
地质学
地表水
领域(数学)
温室
海洋学
作者
Fengying Li,Zhibo Shen,Shiheng Tang,Jianan Liu,Chunwei Fu,Airui Wang,Jiasen Zhong,Xin Quan,Yu Han,Ehui Tan,Shuh-Ji Kao
标识
DOI:10.1016/j.wroa.2025.100468
摘要
Intertidal subterranean estuaries (STEs), as a critical component of the Earth's Critical Zone, are biogeochemical hotspots for greenhouse gas (GHGs: N 2 O, CH 4 , and CO 2 ) emissions. Tidal forcing fundamentally controls carbon and nitrogen cycles that driving the production/consumption of GHGs in muddy and sandy intertidal STEs. However, the sediment-dependent source/sink dynamics of GHGs and tidal responses remain poorly constrained. Through high-resolution spatiotemporal observations across sediment types in intertidal STEs, we show that the mudflat acted as a net GHGs source to coastal waters, whereas the sandy beach was a net sink of N 2 O but a source of CH 4 and CO 2 . Both types were net atmospheric GHGs sources, with CO 2 accounting for 79.05–99.88 %. The comparable magnitude of GHGs fluxes between sandy (N 2 O: 0.67±2.36 µmol m -2 h -1 ; CH 4 : 16.64±32.15 µmol m -2 h -1 ; CO 2 : 2722.19±1825.04 µmol m -2 h -1 ) and muddy (N 2 O: 2.12±1.96 µmol m -2 h -1 ; CH 4 : 69.19±163.41 µmol m -2 h -1 ; CO 2 : 4884.07±2680.89 µmol m -2 h -1 ) systems underscores the previously underestimated contribution of low-organic sandy coasts to marine GHGs budgets. Our analyses further identify pronounced tidal modulation of dissolved GHGs storage and transport pathways, including lateral (porewater exchange) and vertical (sediment/water-air interfaces) fluxes, with particularly strong tidal phase dependence in sandy environments. Global extrapolation of these observations estimates intertidal zones emissions at approximately 0.06±0.14 Tg N 2 O, 0.53±1.11 Tg CH 4 , and 191.22 ± 123.69 Tg CO 2 annually. These findings enhance mechanistic understanding of tidal-scale GHGs variability in coastal aquifers, highlighting the necessity to integrate hydrology and biogeochemistry into global GHGs budget to refine climate predictions.
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