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The external/internal sources and sinks of greenhouse gases (CO 2 , CH 4 , N 2 O) in the Pearl River Estuary and adjacent coastal waters in summer.

Bin ChenEhui TanWenbin ZouLi-Li HanLi TianShuh-Ji Kao
Published in: Water research (2023)
Estuary acts as a hotspot of greenhouse gases (GHGs, including CO 2 , CH 4 and N 2 O) to the atmosphere. However, the GHGs budgets, including input/output fluxes through interfaces and biogeochemical source/sink processes in water columns, of the estuarine systems are still not well constrained due to the lacking of comprehensive observational data. Here, we presented the spatial distributions of GHGs of surface/bottom water and sediment porewater along the Pearl River Estuary (PRE) and adjacent region during summertime. The incorporation of the monitoring for the sediment-water interface (SWI) with these of the water-air interface (WAI) allows us to close the budget revealing additional information of internal consumption/production processes of the three GHGs. The oversaturated CO 2 (481-7573 μatm), CH 4 (289-16,990 %) and N 2 O (108-649 %) in surface water suggested PRE is a significant GHGs source to the atmosphere, in which CO 2 is the major contributor accounting for 90 % of total global warming potential (GWP), leaving 2.8 % from CH 4 , and 7.2 % from N 2 O. Addition to the river input, the SWI releases GHGs to the overlying water with fluxes of 3.5 × 10 7 , 10.8 × 10 4 and 0.7 × 10 4  mol d -1 for CO 2 , CH 4 and N 2 O, respectively. Although all three GHGs exhibited emission to the atmosphere, our mass balance calculation showed that 16.9× 10 7  mol d -1 of CO 2 and 1.0 × 10 4  mol d -1 of N 2 O were consumed, respectively, inside the estuary water body, while extra-production (13.8 × 10 4  mol d -1 ) of CH 4 was demanded in the water body to support its output flux. This is the first experiment quantitatively assessing the importance of internal carbon and nitrogen biogeochemical processes in the PRE. Our finding is of guiding significance to constrain the GHGs budget and draw up realistic pathways for modeling works of GHGs prediction.
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